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/-
Copyright (c) 2022 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alex J. Best, Riccardo Brasca, Eric Rodriguez
-/
import Mathlib.Data.PNat.Prime
import Mathlib.NumberTheory.Cyclotomic.Basic
import Mathlib.RingTheory.Adjoin.PowerBasis
import Mathlib.RingTheory.Norm.Basic
import Mathlib.RingTheory.Polynomial.Cyclotomic.Eval
import Mathlib.RingTheory.Polynomial.Cyclotomic.Expand
import Mathlib.RingTheory.SimpleModule.Basic
/-!
# Primitive roots in cyclotomic fields
If `IsCyclotomicExtension {n} A B`, we define an element `zeta n A B : B` that is a primitive
`n`th-root of unity in `B` and we study its properties. We also prove related theorems under the
more general assumption of just being a primitive root, for reasons described in the implementation
details section.
## Main definitions
* `IsCyclotomicExtension.zeta n A B`: if `IsCyclotomicExtension {n} A B`, than `zeta n A B`
is a primitive `n`-th root of unity in `B`.
* `IsPrimitiveRoot.powerBasis`: if `K` and `L` are fields such that
`IsCyclotomicExtension {n} K L`, then `IsPrimitiveRoot.powerBasis`
gives a `K`-power basis for `L` given a primitive root `ζ`.
* `IsPrimitiveRoot.embeddingsEquivPrimitiveRoots`: the equivalence between `L →ₐ[K] A`
and `primitiveroots n A` given by the choice of `ζ`.
## Main results
* `IsCyclotomicExtension.zeta_spec`: `zeta n A B` is a primitive `n`-th root of unity.
* `IsCyclotomicExtension.finrank`: if `Irreducible (cyclotomic n K)` (in particular for
`K = ℚ`), then the `finrank` of a cyclotomic extension is `n.totient`.
* `IsPrimitiveRoot.norm_eq_one`: if `Irreducible (cyclotomic n K)` (in particular for `K = ℚ`),
the norm of a primitive root is `1` if `n ≠ 2`.
* `IsPrimitiveRoot.sub_one_norm_eq_eval_cyclotomic`: if `Irreducible (cyclotomic n K)`
(in particular for `K = ℚ`), then the norm of `ζ - 1` is `eval 1 (cyclotomic n ℤ)`, for a
primitive root `ζ`. We also prove the analogous of this result for `zeta`.
* `IsPrimitiveRoot.norm_pow_sub_one_of_prime_pow_ne_two` : if
`Irreducible (cyclotomic (p ^ (k + 1)) K)` (in particular for `K = ℚ`) and `p` is a prime,
then the norm of `ζ ^ (p ^ s) - 1` is `p ^ (p ^ s)` `p ^ (k - s + 1) ≠ 2`. See the following
lemmas for similar results. We also prove the analogous of this result for `zeta`.
* `IsPrimitiveRoot.norm_sub_one_of_prime_ne_two` : if `Irreducible (cyclotomic (p ^ (k + 1)) K)`
(in particular for `K = ℚ`) and `p` is an odd prime, then the norm of `ζ - 1` is `p`. We also
prove the analogous of this result for `zeta`.
* `IsPrimitiveRoot.embeddingsEquivPrimitiveRoots`: the equivalence between `L →ₐ[K] A`
and `primitiveRoots n A` given by the choice of `ζ`.
## Implementation details
`zeta n A B` is defined as any primitive root of unity in `B`, - this must exist, by definition of
`IsCyclotomicExtension`. It is not true in general that it is a root of `cyclotomic n B`,
but this holds if `isDomain B` and `NeZero (↑n : B)`.
`zeta n A B` is defined using `Exists.choose`, which means we cannot control it.
For example, in normal mathematics, we can demand that `(zeta p ℤ ℤ[ζₚ] : ℚ(ζₚ))` is equal to
`zeta p ℚ ℚ(ζₚ)`, as we are just choosing "an arbitrary primitive root" and we can internally
specify that our choices agree. This is not the case here, and it is indeed impossible to prove that
these two are equal. Therefore, whenever possible, we prove our results for any primitive root,
and only at the "final step", when we need to provide an "explicit" primitive root, we use `zeta`.
-/
open Polynomial Algebra Finset Module IsCyclotomicExtension Nat PNat Set
open scoped IntermediateField
universe u v w z
variable {p n : ℕ+} (A : Type w) (B : Type z) (K : Type u) {L : Type v} (C : Type w)
variable [CommRing A] [CommRing B] [Algebra A B] [IsCyclotomicExtension {n} A B]
section Zeta
namespace IsCyclotomicExtension
variable (n)
/-- If `B` is an `n`-th cyclotomic extension of `A`, then `zeta n A B` is a primitive root of
unity in `B`. -/
noncomputable def zeta : B :=
(exists_prim_root A <| Set.mem_singleton n : ∃ r : B, IsPrimitiveRoot r n).choose
/-- `zeta n A B` is a primitive `n`-th root of unity. -/
@[simp]
theorem zeta_spec : IsPrimitiveRoot (zeta n A B) n :=
Classical.choose_spec (exists_prim_root A (Set.mem_singleton n) : ∃ r : B, IsPrimitiveRoot r n)
theorem aeval_zeta [IsDomain B] [NeZero ((n : ℕ) : B)] :
aeval (zeta n A B) (cyclotomic n A) = 0 := by
rw [aeval_def, ← eval_map, ← IsRoot.def, map_cyclotomic, isRoot_cyclotomic_iff]
exact zeta_spec n A B
theorem zeta_isRoot [IsDomain B] [NeZero ((n : ℕ) : B)] : IsRoot (cyclotomic n B) (zeta n A B) := by
convert aeval_zeta n A B using 0
rw [IsRoot.def, aeval_def, eval₂_eq_eval_map, map_cyclotomic]
theorem zeta_pow : zeta n A B ^ (n : ℕ) = 1 :=
(zeta_spec n A B).pow_eq_one
end IsCyclotomicExtension
end Zeta
section NoOrder
variable [Field K] [CommRing L] [IsDomain L] [Algebra K L] [IsCyclotomicExtension {n} K L] {ζ : L}
(hζ : IsPrimitiveRoot ζ n)
namespace IsPrimitiveRoot
variable {C}
/-- The `PowerBasis` given by a primitive root `η`. -/
@[simps!]
protected noncomputable def powerBasis : PowerBasis K L :=
-- this is purely an optimization
letI pb := Algebra.adjoin.powerBasis <| (integral {n} K L).isIntegral ζ
pb.map <| (Subalgebra.equivOfEq _ _ (IsCyclotomicExtension.adjoin_primitive_root_eq_top hζ)).trans
Subalgebra.topEquiv
theorem powerBasis_gen_mem_adjoin_zeta_sub_one :
(hζ.powerBasis K).gen ∈ adjoin K ({ζ - 1} : Set L) := by
rw [powerBasis_gen, adjoin_singleton_eq_range_aeval, AlgHom.mem_range]
exact ⟨X + 1, by simp⟩
/-- The `PowerBasis` given by `η - 1`. -/
@[simps!]
noncomputable def subOnePowerBasis : PowerBasis K L :=
(hζ.powerBasis K).ofGenMemAdjoin
(((integral {n} K L).isIntegral ζ).sub isIntegral_one)
(hζ.powerBasis_gen_mem_adjoin_zeta_sub_one _)
variable {K} (C)
-- We are not using @[simps] to avoid a timeout.
/-- The equivalence between `L →ₐ[K] C` and `primitiveRoots n C` given by a primitive root `ζ`. -/
noncomputable def embeddingsEquivPrimitiveRoots (C : Type*) [CommRing C] [IsDomain C] [Algebra K C]
(hirr : Irreducible (cyclotomic n K)) : (L →ₐ[K] C) ≃ primitiveRoots n C :=
(hζ.powerBasis K).liftEquiv.trans
{ toFun := fun x => by
haveI := IsCyclotomicExtension.neZero' n K L
haveI hn := NeZero.of_faithfulSMul K C n
refine ⟨x.1, ?_⟩
cases x
rwa [mem_primitiveRoots n.pos, ← isRoot_cyclotomic_iff, IsRoot.def,
← map_cyclotomic _ (algebraMap K C), hζ.minpoly_eq_cyclotomic_of_irreducible hirr,
← eval₂_eq_eval_map, ← aeval_def]
invFun := fun x => by
haveI := IsCyclotomicExtension.neZero' n K L
haveI hn := NeZero.of_faithfulSMul K C n
refine ⟨x.1, ?_⟩
cases x
rwa [aeval_def, eval₂_eq_eval_map, hζ.powerBasis_gen K, ←
hζ.minpoly_eq_cyclotomic_of_irreducible hirr, map_cyclotomic, ← IsRoot.def,
isRoot_cyclotomic_iff, ← mem_primitiveRoots n.pos]
left_inv := fun _ => Subtype.ext rfl
right_inv := fun _ => Subtype.ext rfl }
-- Porting note: renamed argument `φ`: "expected '_' or identifier"
@[simp]
theorem embeddingsEquivPrimitiveRoots_apply_coe (C : Type*) [CommRing C] [IsDomain C] [Algebra K C]
(hirr : Irreducible (cyclotomic n K)) (φ' : L →ₐ[K] C) :
(hζ.embeddingsEquivPrimitiveRoots C hirr φ' : C) = φ' ζ :=
rfl
end IsPrimitiveRoot
namespace IsCyclotomicExtension
variable {K} (L)
/-- If `Irreducible (cyclotomic n K)` (in particular for `K = ℚ`), then the `finrank` of a
cyclotomic extension is `n.totient`. -/
theorem finrank (hirr : Irreducible (cyclotomic n K)) : finrank K L = (n : ℕ).totient := by
haveI := IsCyclotomicExtension.neZero' n K L
rw [((zeta_spec n K L).powerBasis K).finrank, IsPrimitiveRoot.powerBasis_dim, ←
(zeta_spec n K L).minpoly_eq_cyclotomic_of_irreducible hirr, natDegree_cyclotomic]
variable {L} in
/-- If `L` contains both a primitive `p`-th root of unity and `q`-th root of unity, and
`Irreducible (cyclotomic (lcm p q) K)` (in particular for `K = ℚ`), then the `finrank K L` is at
least `(lcm p q).totient`. -/
theorem _root_.IsPrimitiveRoot.lcm_totient_le_finrank [FiniteDimensional K L] {p q : ℕ} {x y : L}
(hx : IsPrimitiveRoot x p) (hy : IsPrimitiveRoot y q)
(hirr : Irreducible (cyclotomic (Nat.lcm p q) K)) :
(Nat.lcm p q).totient ≤ Module.finrank K L := by
rcases Nat.eq_zero_or_pos p with (rfl | hppos)
· simp
rcases Nat.eq_zero_or_pos q with (rfl | hqpos)
· simp
let z := x ^ (p / factorizationLCMLeft p q) * y ^ (q / factorizationLCMRight p q)
let k := PNat.lcm ⟨p, hppos⟩ ⟨q, hqpos⟩
have : IsPrimitiveRoot z k := hx.pow_mul_pow_lcm hy hppos.ne' hqpos.ne'
haveI := IsPrimitiveRoot.adjoin_isCyclotomicExtension K this
convert Submodule.finrank_le (Subalgebra.toSubmodule (adjoin K {z}))
rw [show Nat.lcm p q = (k : ℕ) from rfl] at hirr
simpa using (IsCyclotomicExtension.finrank (Algebra.adjoin K {z}) hirr).symm
end IsCyclotomicExtension
end NoOrder
section Norm
namespace IsPrimitiveRoot
section Field
variable {K} [Field K] [NumberField K]
variable (n) in
/-- If a `n`-th cyclotomic extension of `ℚ` contains a primitive `l`-th root of unity, then
`l ∣ 2 * n`. -/
theorem dvd_of_isCyclotomicExtension [IsCyclotomicExtension {n} ℚ K] {ζ : K}
{l : ℕ} (hζ : IsPrimitiveRoot ζ l) (hl : l ≠ 0) : l ∣ 2 * n := by
have hl : NeZero l := ⟨hl⟩
have hroot := IsCyclotomicExtension.zeta_spec n ℚ K
have key := IsPrimitiveRoot.lcm_totient_le_finrank hζ hroot
(cyclotomic.irreducible_rat <| Nat.lcm_pos (Nat.pos_of_ne_zero hl.1) n.2)
rw [IsCyclotomicExtension.finrank K (cyclotomic.irreducible_rat n.2)] at key
rcases _root_.dvd_lcm_right l n with ⟨r, hr⟩
have ineq := Nat.totient_super_multiplicative n r
rw [← hr] at ineq
replace key := (mul_le_iff_le_one_right (Nat.totient_pos.2 n.2)).mp (le_trans ineq key)
have rpos : 0 < r := by
refine Nat.pos_of_ne_zero (fun h ↦ ?_)
simp only [h, mul_zero, _root_.lcm_eq_zero_iff, PNat.ne_zero, or_false] at hr
exact hl.1 hr
replace key := (Nat.dvd_prime Nat.prime_two).1 (Nat.dvd_two_of_totient_le_one rpos key)
rcases key with (key | key)
· rw [key, mul_one] at hr
rw [← hr]
exact dvd_mul_of_dvd_right (_root_.dvd_lcm_left l ↑n) 2
· rw [key, mul_comm] at hr
simpa [← hr] using _root_.dvd_lcm_left _ _
/-- If `x` is a root of unity (spelled as `IsOfFinOrder x`) in an `n`-th cyclotomic extension of
`ℚ`, where `n` is odd, and `ζ` is a primitive `n`-th root of unity, then there exist `r`
such that `x = (-ζ)^r`. -/
theorem exists_neg_pow_of_isOfFinOrder [IsCyclotomicExtension {n} ℚ K]
(hno : Odd (n : ℕ)) {ζ x : K} (hζ : IsPrimitiveRoot ζ n) (hx : IsOfFinOrder x) :
∃ r : ℕ, x = (-ζ) ^ r := by
have hnegζ : IsPrimitiveRoot (-ζ) (2 * n) := by
convert IsPrimitiveRoot.orderOf (-ζ)
rw [neg_eq_neg_one_mul, (Commute.all _ _).orderOf_mul_eq_mul_orderOf_of_coprime]
· simp [hζ.eq_orderOf]
· simp [← hζ.eq_orderOf, hno]
obtain ⟨k, hkpos, hkn⟩ := isOfFinOrder_iff_pow_eq_one.1 hx
obtain ⟨l, hl, hlroot⟩ := (isRoot_of_unity_iff hkpos _).1 hkn
have hlzero : NeZero l := ⟨fun h ↦ by simp [h] at hl⟩
have : NeZero (l : K) := ⟨NeZero.natCast_ne l K⟩
rw [isRoot_cyclotomic_iff] at hlroot
obtain ⟨a, ha⟩ := hlroot.dvd_of_isCyclotomicExtension n hlzero.1
replace hlroot : x ^ (2 * (n : ℕ)) = 1 := by rw [ha, pow_mul, hlroot.pow_eq_one, one_pow]
obtain ⟨s, -, hs⟩ := hnegζ.eq_pow_of_pow_eq_one hlroot
exact ⟨s, hs.symm⟩
/-- If `x` is a root of unity (spelled as `IsOfFinOrder x`) in an `n`-th cyclotomic extension of
`ℚ`, where `n` is odd, and `ζ` is a primitive `n`-th root of unity, then there exists `r < n`
such that `x = ζ^r` or `x = -ζ^r`. -/
theorem exists_pow_or_neg_mul_pow_of_isOfFinOrder [IsCyclotomicExtension {n} ℚ K]
(hno : Odd (n : ℕ)) {ζ x : K} (hζ : IsPrimitiveRoot ζ n) (hx : IsOfFinOrder x) :
∃ r : ℕ, r < n ∧ (x = ζ ^ r ∨ x = -ζ ^ r) := by
obtain ⟨r, hr⟩ := hζ.exists_neg_pow_of_isOfFinOrder hno hx
refine ⟨r % n, Nat.mod_lt _ n.2, ?_⟩
rw [show ζ ^ (r % ↑n) = ζ ^ r from (IsPrimitiveRoot.eq_orderOf hζ).symm ▸ pow_mod_orderOf .., hr]
rcases Nat.even_or_odd r with (h | h) <;> simp [neg_pow, h.neg_one_pow]
end Field
section CommRing
variable [CommRing L] {ζ : L}
variable {K} [Field K] [Algebra K L]
/-- This mathematically trivial result is complementary to `norm_eq_one` below. -/
theorem norm_eq_neg_one_pow (hζ : IsPrimitiveRoot ζ 2) [IsDomain L] :
norm K ζ = (-1 : K) ^ finrank K L := by
rw [hζ.eq_neg_one_of_two_right, show -1 = algebraMap K L (-1) by simp, Algebra.norm_algebraMap]
variable (hζ : IsPrimitiveRoot ζ n)
include hζ
/-- If `Irreducible (cyclotomic n K)` (in particular for `K = ℚ`), the norm of a primitive root is
`1` if `n ≠ 2`. -/
theorem norm_eq_one [IsDomain L] [IsCyclotomicExtension {n} K L] (hn : n ≠ 2)
(hirr : Irreducible (cyclotomic n K)) : norm K ζ = 1 := by
haveI := IsCyclotomicExtension.neZero' n K L
by_cases h1 : n = 1
· rw [h1, one_coe, one_right_iff] at hζ
rw [hζ, show 1 = algebraMap K L 1 by simp, Algebra.norm_algebraMap, one_pow]
· replace h1 : 2 ≤ n := by
by_contra! h
exact h1 (PNat.eq_one_of_lt_two h)
-- Porting note: specifying the type of `cyclotomic_coeff_zero K h1` was not needed.
| rw [← hζ.powerBasis_gen K, PowerBasis.norm_gen_eq_coeff_zero_minpoly, hζ.powerBasis_gen K, ←
hζ.minpoly_eq_cyclotomic_of_irreducible hirr,
(cyclotomic_coeff_zero K h1 : coeff (cyclotomic n K) 0 = 1), mul_one,
hζ.powerBasis_dim K, ← hζ.minpoly_eq_cyclotomic_of_irreducible hirr, natDegree_cyclotomic]
exact (totient_even <| h1.lt_of_ne hn.symm).neg_one_pow
/-- If `K` is linearly ordered, the norm of a primitive root is `1` if `n` is odd. -/
theorem norm_eq_one_of_linearly_ordered {K : Type*}
[Field K] [LinearOrder K] [IsStrictOrderedRing K] [Algebra K L]
(hodd : Odd (n : ℕ)) : norm K ζ = 1 := by
have hz := congr_arg (norm K) ((IsPrimitiveRoot.iff_def _ n).1 hζ).1
rw [← (algebraMap K L).map_one, Algebra.norm_algebraMap, one_pow, map_pow, ← one_pow ↑n] at hz
exact StrictMono.injective hodd.strictMono_pow hz
theorem norm_of_cyclotomic_irreducible [IsDomain L] [IsCyclotomicExtension {n} K L]
| Mathlib/NumberTheory/Cyclotomic/PrimitiveRoots.lean | 296 | 310 |
/-
Copyright (c) 2022 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Topology.MetricSpace.HausdorffDistance
/-!
# Topological study of spaces `Π (n : ℕ), E n`
When `E n` are topological spaces, the space `Π (n : ℕ), E n` is naturally a topological space
(with the product topology). When `E n` are uniform spaces, it also inherits a uniform structure.
However, it does not inherit a canonical metric space structure of the `E n`. Nevertheless, one
can put a noncanonical metric space structure (or rather, several of them). This is done in this
file.
## Main definitions and results
One can define a combinatorial distance on `Π (n : ℕ), E n`, as follows:
* `PiNat.cylinder x n` is the set of points `y` with `x i = y i` for `i < n`.
* `PiNat.firstDiff x y` is the first index at which `x i ≠ y i`.
* `PiNat.dist x y` is equal to `(1/2) ^ (firstDiff x y)`. It defines a distance
on `Π (n : ℕ), E n`, compatible with the topology when the `E n` have the discrete topology.
* `PiNat.metricSpace`: the metric space structure, given by this distance. Not registered as an
instance. This space is a complete metric space.
* `PiNat.metricSpaceOfDiscreteUniformity`: the same metric space structure, but adjusting the
uniformity defeqness when the `E n` already have the discrete uniformity. Not registered as an
instance
* `PiNat.metricSpaceNatNat`: the particular case of `ℕ → ℕ`, not registered as an instance.
These results are used to construct continuous functions on `Π n, E n`:
* `PiNat.exists_retraction_of_isClosed`: given a nonempty closed subset `s` of `Π (n : ℕ), E n`,
there exists a retraction onto `s`, i.e., a continuous map from the whole space to `s`
restricting to the identity on `s`.
* `exists_nat_nat_continuous_surjective_of_completeSpace`: given any nonempty complete metric
space with second-countable topology, there exists a continuous surjection from `ℕ → ℕ` onto
this space.
One can also put distances on `Π (i : ι), E i` when the spaces `E i` are metric spaces (not discrete
in general), and `ι` is countable.
* `PiCountable.dist` is the distance on `Π i, E i` given by
`dist x y = ∑' i, min (1/2)^(encode i) (dist (x i) (y i))`.
* `PiCountable.metricSpace` is the corresponding metric space structure, adjusted so that
the uniformity is definitionally the product uniformity. Not registered as an instance.
-/
noncomputable section
open Topology TopologicalSpace Set Metric Filter Function
attribute [local simp] pow_le_pow_iff_right₀ one_lt_two inv_le_inv₀ zero_le_two zero_lt_two
variable {E : ℕ → Type*}
namespace PiNat
/-! ### The firstDiff function -/
open Classical in
/-- In a product space `Π n, E n`, then `firstDiff x y` is the first index at which `x` and `y`
differ. If `x = y`, then by convention we set `firstDiff x x = 0`. -/
irreducible_def firstDiff (x y : ∀ n, E n) : ℕ :=
if h : x ≠ y then Nat.find (ne_iff.1 h) else 0
theorem apply_firstDiff_ne {x y : ∀ n, E n} (h : x ≠ y) :
x (firstDiff x y) ≠ y (firstDiff x y) := by
rw [firstDiff_def, dif_pos h]
classical
exact Nat.find_spec (ne_iff.1 h)
theorem apply_eq_of_lt_firstDiff {x y : ∀ n, E n} {n : ℕ} (hn : n < firstDiff x y) : x n = y n := by
rw [firstDiff_def] at hn
split_ifs at hn with h
· convert Nat.find_min (ne_iff.1 h) hn
simp
· exact (not_lt_zero' hn).elim
theorem firstDiff_comm (x y : ∀ n, E n) : firstDiff x y = firstDiff y x := by
classical
simp only [firstDiff_def, ne_comm]
theorem min_firstDiff_le (x y z : ∀ n, E n) (h : x ≠ z) :
min (firstDiff x y) (firstDiff y z) ≤ firstDiff x z := by
by_contra! H
rw [lt_min_iff] at H
refine apply_firstDiff_ne h ?_
calc
x (firstDiff x z) = y (firstDiff x z) := apply_eq_of_lt_firstDiff H.1
_ = z (firstDiff x z) := apply_eq_of_lt_firstDiff H.2
/-! ### Cylinders -/
/-- In a product space `Π n, E n`, the cylinder set of length `n` around `x`, denoted
`cylinder x n`, is the set of sequences `y` that coincide with `x` on the first `n` symbols, i.e.,
such that `y i = x i` for all `i < n`.
-/
def cylinder (x : ∀ n, E n) (n : ℕ) : Set (∀ n, E n) :=
{ y | ∀ i, i < n → y i = x i }
theorem cylinder_eq_pi (x : ∀ n, E n) (n : ℕ) :
cylinder x n = Set.pi (Finset.range n : Set ℕ) fun i : ℕ => {x i} := by
ext y
simp [cylinder]
@[simp]
theorem cylinder_zero (x : ∀ n, E n) : cylinder x 0 = univ := by simp [cylinder_eq_pi]
theorem cylinder_anti (x : ∀ n, E n) {m n : ℕ} (h : m ≤ n) : cylinder x n ⊆ cylinder x m :=
fun _y hy i hi => hy i (hi.trans_le h)
@[simp]
theorem mem_cylinder_iff {x y : ∀ n, E n} {n : ℕ} : y ∈ cylinder x n ↔ ∀ i < n, y i = x i :=
Iff.rfl
theorem self_mem_cylinder (x : ∀ n, E n) (n : ℕ) : x ∈ cylinder x n := by simp
theorem mem_cylinder_iff_eq {x y : ∀ n, E n} {n : ℕ} :
y ∈ cylinder x n ↔ cylinder y n = cylinder x n := by
constructor
· intro hy
apply Subset.antisymm
· intro z hz i hi
rw [← hy i hi]
exact hz i hi
· intro z hz i hi
rw [hy i hi]
exact hz i hi
· intro h
rw [← h]
exact self_mem_cylinder _ _
theorem mem_cylinder_comm (x y : ∀ n, E n) (n : ℕ) : y ∈ cylinder x n ↔ x ∈ cylinder y n := by
simp [mem_cylinder_iff_eq, eq_comm]
theorem mem_cylinder_iff_le_firstDiff {x y : ∀ n, E n} (hne : x ≠ y) (i : ℕ) :
x ∈ cylinder y i ↔ i ≤ firstDiff x y := by
constructor
· intro h
by_contra!
exact apply_firstDiff_ne hne (h _ this)
· intro hi j hj
exact apply_eq_of_lt_firstDiff (hj.trans_le hi)
theorem mem_cylinder_firstDiff (x y : ∀ n, E n) : x ∈ cylinder y (firstDiff x y) := fun _i hi =>
apply_eq_of_lt_firstDiff hi
theorem cylinder_eq_cylinder_of_le_firstDiff (x y : ∀ n, E n) {n : ℕ} (hn : n ≤ firstDiff x y) :
cylinder x n = cylinder y n := by
rw [← mem_cylinder_iff_eq]
intro i hi
exact apply_eq_of_lt_firstDiff (hi.trans_le hn)
theorem iUnion_cylinder_update (x : ∀ n, E n) (n : ℕ) :
⋃ k, cylinder (update x n k) (n + 1) = cylinder x n := by
ext y
simp only [mem_cylinder_iff, mem_iUnion]
constructor
· rintro ⟨k, hk⟩ i hi
simpa [hi.ne] using hk i (Nat.lt_succ_of_lt hi)
· intro H
refine ⟨y n, fun i hi => ?_⟩
rcases Nat.lt_succ_iff_lt_or_eq.1 hi with (h'i | rfl)
· simp [H i h'i, h'i.ne]
· simp
theorem update_mem_cylinder (x : ∀ n, E n) (n : ℕ) (y : E n) : update x n y ∈ cylinder x n :=
mem_cylinder_iff.2 fun i hi => by simp [hi.ne]
section Res
variable {α : Type*}
open List
/-- In the case where `E` has constant value `α`,
the cylinder `cylinder x n` can be identified with the element of `List α`
consisting of the first `n` entries of `x`. See `cylinder_eq_res`.
We call this list `res x n`, the restriction of `x` to `n`. -/
def res (x : ℕ → α) : ℕ → List α
| 0 => nil
| Nat.succ n => x n :: res x n
@[simp]
theorem res_zero (x : ℕ → α) : res x 0 = @nil α :=
rfl
@[simp]
theorem res_succ (x : ℕ → α) (n : ℕ) : res x n.succ = x n :: res x n :=
rfl
@[simp]
theorem res_length (x : ℕ → α) (n : ℕ) : (res x n).length = n := by induction n <;> simp [*]
/-- The restrictions of `x` and `y` to `n` are equal if and only if `x m = y m` for all `m < n`. -/
theorem res_eq_res {x y : ℕ → α} {n : ℕ} :
res x n = res y n ↔ ∀ ⦃m⦄, m < n → x m = y m := by
constructor <;> intro h
· induction n with
| zero => simp
| succ n ih =>
intro m hm
rw [Nat.lt_succ_iff_lt_or_eq] at hm
simp only [res_succ, cons.injEq] at h
rcases hm with hm | hm
· exact ih h.2 hm
rw [hm]
exact h.1
· induction n with
| zero => simp
| succ n ih =>
simp only [res_succ, cons.injEq]
refine ⟨h (Nat.lt_succ_self _), ih fun m hm => ?_⟩
exact h (hm.trans (Nat.lt_succ_self _))
theorem res_injective : Injective (@res α) := by
intro x y h
ext n
apply res_eq_res.mp _ (Nat.lt_succ_self _)
rw [h]
/-- `cylinder x n` is equal to the set of sequences `y` with the same restriction to `n` as `x`. -/
theorem cylinder_eq_res (x : ℕ → α) (n : ℕ) :
cylinder x n = { y | res y n = res x n } := by
ext y
dsimp [cylinder]
rw [res_eq_res]
end Res
/-!
### A distance function on `Π n, E n`
We define a distance function on `Π n, E n`, given by `dist x y = (1/2)^n` where `n` is the first
index at which `x` and `y` differ. When each `E n` has the discrete topology, this distance will
define the right topology on the product space. We do not record a global `Dist` instance nor
a `MetricSpace` instance, as other distances may be used on these spaces, but we register them as
local instances in this section.
-/
open Classical in
/-- The distance function on a product space `Π n, E n`, given by `dist x y = (1/2)^n` where `n` is
the first index at which `x` and `y` differ. -/
protected def dist : Dist (∀ n, E n) :=
⟨fun x y => if x ≠ y then (1 / 2 : ℝ) ^ firstDiff x y else 0⟩
attribute [local instance] PiNat.dist
theorem dist_eq_of_ne {x y : ∀ n, E n} (h : x ≠ y) : dist x y = (1 / 2 : ℝ) ^ firstDiff x y := by
simp [dist, h]
protected theorem dist_self (x : ∀ n, E n) : dist x x = 0 := by simp [dist]
protected theorem dist_comm (x y : ∀ n, E n) : dist x y = dist y x := by
classical
simp [dist, @eq_comm _ x y, firstDiff_comm]
protected theorem dist_nonneg (x y : ∀ n, E n) : 0 ≤ dist x y := by
rcases eq_or_ne x y with (rfl | h)
· simp [dist]
· simp [dist, h, zero_le_two]
theorem dist_triangle_nonarch (x y z : ∀ n, E n) : dist x z ≤ max (dist x y) (dist y z) := by
rcases eq_or_ne x z with (rfl | hxz)
· simp [PiNat.dist_self x, PiNat.dist_nonneg]
rcases eq_or_ne x y with (rfl | hxy)
· simp
rcases eq_or_ne y z with (rfl | hyz)
· simp
simp only [dist_eq_of_ne, hxz, hxy, hyz, inv_le_inv₀, one_div, inv_pow, zero_lt_two, Ne,
not_false_iff, le_max_iff, pow_le_pow_iff_right₀, one_lt_two, pow_pos,
min_le_iff.1 (min_firstDiff_le x y z hxz)]
protected theorem dist_triangle (x y z : ∀ n, E n) : dist x z ≤ dist x y + dist y z :=
calc
dist x z ≤ max (dist x y) (dist y z) := dist_triangle_nonarch x y z
_ ≤ dist x y + dist y z := max_le_add_of_nonneg (PiNat.dist_nonneg _ _) (PiNat.dist_nonneg _ _)
protected theorem eq_of_dist_eq_zero (x y : ∀ n, E n) (hxy : dist x y = 0) : x = y := by
rcases eq_or_ne x y with (rfl | h); · rfl
simp [dist_eq_of_ne h] at hxy
theorem mem_cylinder_iff_dist_le {x y : ∀ n, E n} {n : ℕ} :
y ∈ cylinder x n ↔ dist y x ≤ (1 / 2) ^ n := by
rcases eq_or_ne y x with (rfl | hne)
· simp [PiNat.dist_self]
suffices (∀ i : ℕ, i < n → y i = x i) ↔ n ≤ firstDiff y x by simpa [dist_eq_of_ne hne]
constructor
· intro hy
by_contra! H
exact apply_firstDiff_ne hne (hy _ H)
· intro h i hi
exact apply_eq_of_lt_firstDiff (hi.trans_le h)
theorem apply_eq_of_dist_lt {x y : ∀ n, E n} {n : ℕ} (h : dist x y < (1 / 2) ^ n) {i : ℕ}
(hi : i ≤ n) : x i = y i := by
rcases eq_or_ne x y with (rfl | hne)
· rfl
have : n < firstDiff x y := by
simpa [dist_eq_of_ne hne, inv_lt_inv₀, pow_lt_pow_iff_right₀, one_lt_two] using h
exact apply_eq_of_lt_firstDiff (hi.trans_lt this)
/-- A function to a pseudo-metric-space is `1`-Lipschitz if and only if points in the same cylinder
of length `n` are sent to points within distance `(1/2)^n`.
Not expressed using `LipschitzWith` as we don't have a metric space structure -/
theorem lipschitz_with_one_iff_forall_dist_image_le_of_mem_cylinder {α : Type*}
| [PseudoMetricSpace α] {f : (∀ n, E n) → α} :
(∀ x y : ∀ n, E n, dist (f x) (f y) ≤ dist x y) ↔
∀ x y n, y ∈ cylinder x n → dist (f x) (f y) ≤ (1 / 2) ^ n := by
| Mathlib/Topology/MetricSpace/PiNat.lean | 309 | 311 |
/-
Copyright (c) 2022 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.MeasureTheory.Integral.IntegrableOn
/-!
# Locally integrable functions
A function is called *locally integrable* (`MeasureTheory.LocallyIntegrable`) if it is integrable
on a neighborhood of every point. More generally, it is *locally integrable on `s`* if it is
locally integrable on a neighbourhood within `s` of any point of `s`.
This file contains properties of locally integrable functions, and integrability results
on compact sets.
## Main statements
* `Continuous.locallyIntegrable`: A continuous function is locally integrable.
* `ContinuousOn.locallyIntegrableOn`: A function which is continuous on `s` is locally
integrable on `s`.
-/
open MeasureTheory MeasureTheory.Measure Set Function TopologicalSpace Bornology
open scoped Topology Interval ENNReal
variable {X Y E F R : Type*} [MeasurableSpace X] [TopologicalSpace X]
variable [MeasurableSpace Y] [TopologicalSpace Y]
variable [NormedAddCommGroup E] [NormedAddCommGroup F] {f g : X → E} {μ : Measure X} {s : Set X}
namespace MeasureTheory
section LocallyIntegrableOn
/-- A function `f : X → E` is *locally integrable on s*, for `s ⊆ X`, if for every `x ∈ s` there is
a neighbourhood of `x` within `s` on which `f` is integrable. (Note this is, in general, strictly
weaker than local integrability with respect to `μ.restrict s`.) -/
def LocallyIntegrableOn (f : X → E) (s : Set X) (μ : Measure X := by volume_tac) : Prop :=
∀ x : X, x ∈ s → IntegrableAtFilter f (𝓝[s] x) μ
theorem LocallyIntegrableOn.mono_set (hf : LocallyIntegrableOn f s μ) {t : Set X}
(hst : t ⊆ s) : LocallyIntegrableOn f t μ := fun x hx =>
(hf x <| hst hx).filter_mono (nhdsWithin_mono x hst)
theorem LocallyIntegrableOn.norm (hf : LocallyIntegrableOn f s μ) :
LocallyIntegrableOn (fun x => ‖f x‖) s μ := fun t ht =>
let ⟨U, hU_nhd, hU_int⟩ := hf t ht
⟨U, hU_nhd, hU_int.norm⟩
theorem LocallyIntegrableOn.mono (hf : LocallyIntegrableOn f s μ) {g : X → F}
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ x ∂μ, ‖g x‖ ≤ ‖f x‖) :
LocallyIntegrableOn g s μ := by
intro x hx
rcases hf x hx with ⟨t, t_mem, ht⟩
exact ⟨t, t_mem, Integrable.mono ht hg.restrict (ae_restrict_of_ae h)⟩
theorem IntegrableOn.locallyIntegrableOn (hf : IntegrableOn f s μ) : LocallyIntegrableOn f s μ :=
fun _ _ => ⟨s, self_mem_nhdsWithin, hf⟩
/-- If a function is locally integrable on a compact set, then it is integrable on that set. -/
theorem LocallyIntegrableOn.integrableOn_isCompact (hf : LocallyIntegrableOn f s μ)
(hs : IsCompact s) : IntegrableOn f s μ :=
IsCompact.induction_on hs integrableOn_empty (fun _u _v huv hv => hv.mono_set huv)
(fun _u _v hu hv => integrableOn_union.mpr ⟨hu, hv⟩) hf
theorem LocallyIntegrableOn.integrableOn_compact_subset (hf : LocallyIntegrableOn f s μ) {t : Set X}
(hst : t ⊆ s) (ht : IsCompact t) : IntegrableOn f t μ :=
(hf.mono_set hst).integrableOn_isCompact ht
/-- If a function `f` is locally integrable on a set `s` in a second countable topological space,
then there exist countably many open sets `u` covering `s` such that `f` is integrable on each
set `u ∩ s`. -/
theorem LocallyIntegrableOn.exists_countable_integrableOn [SecondCountableTopology X]
(hf : LocallyIntegrableOn f s μ) : ∃ T : Set (Set X), T.Countable ∧
(∀ u ∈ T, IsOpen u) ∧ (s ⊆ ⋃ u ∈ T, u) ∧ (∀ u ∈ T, IntegrableOn f (u ∩ s) μ) := by
have : ∀ x : s, ∃ u, IsOpen u ∧ x.1 ∈ u ∧ IntegrableOn f (u ∩ s) μ := by
rintro ⟨x, hx⟩
rcases hf x hx with ⟨t, ht, h't⟩
rcases mem_nhdsWithin.1 ht with ⟨u, u_open, x_mem, u_sub⟩
exact ⟨u, u_open, x_mem, h't.mono_set u_sub⟩
choose u u_open xu hu using this
obtain ⟨T, T_count, hT⟩ : ∃ T : Set s, T.Countable ∧ s ⊆ ⋃ i ∈ T, u i := by
have : s ⊆ ⋃ x : s, u x := fun y hy => mem_iUnion_of_mem ⟨y, hy⟩ (xu ⟨y, hy⟩)
obtain ⟨T, hT_count, hT_un⟩ := isOpen_iUnion_countable u u_open
exact ⟨T, hT_count, by rwa [hT_un]⟩
refine ⟨u '' T, T_count.image _, ?_, by rwa [biUnion_image], ?_⟩
· rintro v ⟨w, -, rfl⟩
exact u_open _
· rintro v ⟨w, -, rfl⟩
exact hu _
/-- If a function `f` is locally integrable on a set `s` in a second countable topological space,
then there exists a sequence of open sets `u n` covering `s` such that `f` is integrable on each
set `u n ∩ s`. -/
theorem LocallyIntegrableOn.exists_nat_integrableOn [SecondCountableTopology X]
(hf : LocallyIntegrableOn f s μ) : ∃ u : ℕ → Set X,
(∀ n, IsOpen (u n)) ∧ (s ⊆ ⋃ n, u n) ∧ (∀ n, IntegrableOn f (u n ∩ s) μ) := by
rcases hf.exists_countable_integrableOn with ⟨T, T_count, T_open, sT, hT⟩
let T' : Set (Set X) := insert ∅ T
have T'_count : T'.Countable := Countable.insert ∅ T_count
have T'_ne : T'.Nonempty := by simp only [T', insert_nonempty]
rcases T'_count.exists_eq_range T'_ne with ⟨u, hu⟩
refine ⟨u, ?_, ?_, ?_⟩
· intro n
have : u n ∈ T' := by rw [hu]; exact mem_range_self n
rcases mem_insert_iff.1 this with h|h
· rw [h]
exact isOpen_empty
· exact T_open _ h
· intro x hx
obtain ⟨v, hv, h'v⟩ : ∃ v, v ∈ T ∧ x ∈ v := by simpa only [mem_iUnion, exists_prop] using sT hx
have : v ∈ range u := by rw [← hu]; exact subset_insert ∅ T hv
obtain ⟨n, rfl⟩ : ∃ n, u n = v := by simpa only [mem_range] using this
exact mem_iUnion_of_mem _ h'v
· intro n
have : u n ∈ T' := by rw [hu]; exact mem_range_self n
rcases mem_insert_iff.1 this with h|h
· simp only [h, empty_inter, integrableOn_empty]
· exact hT _ h
theorem LocallyIntegrableOn.aestronglyMeasurable [SecondCountableTopology X]
(hf : LocallyIntegrableOn f s μ) : AEStronglyMeasurable f (μ.restrict s) := by
rcases hf.exists_nat_integrableOn with ⟨u, -, su, hu⟩
have : s = ⋃ n, u n ∩ s := by rw [← iUnion_inter]; exact (inter_eq_right.mpr su).symm
rw [this, aestronglyMeasurable_iUnion_iff]
exact fun i : ℕ => (hu i).aestronglyMeasurable
/-- If `s` is locally closed (e.g. open or closed), then `f` is locally integrable on `s` iff it is
integrable on every compact subset contained in `s`. -/
theorem locallyIntegrableOn_iff [LocallyCompactSpace X] (hs : IsLocallyClosed s) :
LocallyIntegrableOn f s μ ↔ ∀ (k : Set X), k ⊆ s → IsCompact k → IntegrableOn f k μ := by
refine ⟨fun hf k hk ↦ hf.integrableOn_compact_subset hk, fun hf x hx ↦ ?_⟩
rcases hs with ⟨U, Z, hU, hZ, rfl⟩
rcases exists_compact_subset hU hx.1 with ⟨K, hK, hxK, hKU⟩
rw [nhdsWithin_inter_of_mem (nhdsWithin_le_nhds <| hU.mem_nhds hx.1)]
refine ⟨Z ∩ K, inter_mem_nhdsWithin _ (mem_interior_iff_mem_nhds.1 hxK), ?_⟩
exact hf (Z ∩ K) (fun y hy ↦ ⟨hKU hy.2, hy.1⟩) (.inter_left hK hZ)
protected theorem LocallyIntegrableOn.add
(hf : LocallyIntegrableOn f s μ) (hg : LocallyIntegrableOn g s μ) :
LocallyIntegrableOn (f + g) s μ := fun x hx ↦ (hf x hx).add (hg x hx)
protected theorem LocallyIntegrableOn.sub
(hf : LocallyIntegrableOn f s μ) (hg : LocallyIntegrableOn g s μ) :
LocallyIntegrableOn (f - g) s μ := fun x hx ↦ (hf x hx).sub (hg x hx)
protected theorem LocallyIntegrableOn.neg (hf : LocallyIntegrableOn f s μ) :
LocallyIntegrableOn (-f) s μ := fun x hx ↦ (hf x hx).neg
end LocallyIntegrableOn
/-- A function `f : X → E` is *locally integrable* if it is integrable on a neighborhood of every
point. In particular, it is integrable on all compact sets,
see `LocallyIntegrable.integrableOn_isCompact`. -/
def LocallyIntegrable (f : X → E) (μ : Measure X := by volume_tac) : Prop :=
∀ x : X, IntegrableAtFilter f (𝓝 x) μ
theorem locallyIntegrable_comap (hs : MeasurableSet s) :
LocallyIntegrable (fun x : s ↦ f x) (μ.comap Subtype.val) ↔ LocallyIntegrableOn f s μ := by
simp_rw [LocallyIntegrableOn, Subtype.forall', ← map_nhds_subtype_val]
exact forall_congr' fun _ ↦ (MeasurableEmbedding.subtype_coe hs).integrableAtFilter_iff_comap.symm
theorem locallyIntegrableOn_univ : LocallyIntegrableOn f univ μ ↔ LocallyIntegrable f μ := by
simp only [LocallyIntegrableOn, nhdsWithin_univ, mem_univ, true_imp_iff]; rfl
theorem LocallyIntegrable.locallyIntegrableOn (hf : LocallyIntegrable f μ) (s : Set X) :
LocallyIntegrableOn f s μ := fun x _ => (hf x).filter_mono nhdsWithin_le_nhds
theorem Integrable.locallyIntegrable (hf : Integrable f μ) : LocallyIntegrable f μ := fun _ =>
hf.integrableAtFilter _
theorem LocallyIntegrable.mono (hf : LocallyIntegrable f μ) {g : X → F}
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ x ∂μ, ‖g x‖ ≤ ‖f x‖) :
LocallyIntegrable g μ := by
rw [← locallyIntegrableOn_univ] at hf ⊢
exact hf.mono hg h
/-- If `f` is locally integrable with respect to `μ.restrict s`, it is locally integrable on `s`.
(See `locallyIntegrableOn_iff_locallyIntegrable_restrict` for an iff statement when `s` is
closed.) -/
theorem locallyIntegrableOn_of_locallyIntegrable_restrict [OpensMeasurableSpace X]
(hf : LocallyIntegrable f (μ.restrict s)) : LocallyIntegrableOn f s μ := by
intro x _
obtain ⟨t, ht_mem, ht_int⟩ := hf x
obtain ⟨u, hu_sub, hu_o, hu_mem⟩ := mem_nhds_iff.mp ht_mem
refine ⟨_, inter_mem_nhdsWithin s (hu_o.mem_nhds hu_mem), ?_⟩
simpa only [IntegrableOn, Measure.restrict_restrict hu_o.measurableSet, inter_comm] using
ht_int.mono_set hu_sub
/-- If `s` is closed, being locally integrable on `s` wrt `μ` is equivalent to being locally
integrable with respect to `μ.restrict s`. For the one-way implication without assuming `s` closed,
see `locallyIntegrableOn_of_locallyIntegrable_restrict`. -/
theorem locallyIntegrableOn_iff_locallyIntegrable_restrict [OpensMeasurableSpace X]
(hs : IsClosed s) : LocallyIntegrableOn f s μ ↔ LocallyIntegrable f (μ.restrict s) := by
refine ⟨fun hf x => ?_, locallyIntegrableOn_of_locallyIntegrable_restrict⟩
by_cases h : x ∈ s
· obtain ⟨t, ht_nhds, ht_int⟩ := hf x h
obtain ⟨u, hu_o, hu_x, hu_sub⟩ := mem_nhdsWithin.mp ht_nhds
refine ⟨u, hu_o.mem_nhds hu_x, ?_⟩
rw [IntegrableOn, restrict_restrict hu_o.measurableSet]
exact ht_int.mono_set hu_sub
· rw [← isOpen_compl_iff] at hs
refine ⟨sᶜ, hs.mem_nhds h, ?_⟩
rw [IntegrableOn, restrict_restrict, inter_comm, inter_compl_self, ← IntegrableOn]
exacts [integrableOn_empty, hs.measurableSet]
/-- If a function is locally integrable, then it is integrable on any compact set. -/
theorem LocallyIntegrable.integrableOn_isCompact {k : Set X} (hf : LocallyIntegrable f μ)
(hk : IsCompact k) : IntegrableOn f k μ :=
(hf.locallyIntegrableOn k).integrableOn_isCompact hk
/-- If a function is locally integrable, then it is integrable on an open neighborhood of any
compact set. -/
theorem LocallyIntegrable.integrableOn_nhds_isCompact (hf : LocallyIntegrable f μ) {k : Set X}
(hk : IsCompact k) : ∃ u, IsOpen u ∧ k ⊆ u ∧ IntegrableOn f u μ := by
refine IsCompact.induction_on hk ?_ ?_ ?_ ?_
· refine ⟨∅, isOpen_empty, Subset.rfl, integrableOn_empty⟩
· rintro s t hst ⟨u, u_open, tu, hu⟩
exact ⟨u, u_open, hst.trans tu, hu⟩
· rintro s t ⟨u, u_open, su, hu⟩ ⟨v, v_open, tv, hv⟩
exact ⟨u ∪ v, u_open.union v_open, union_subset_union su tv, hu.union hv⟩
· intro x _
rcases hf x with ⟨u, ux, hu⟩
rcases mem_nhds_iff.1 ux with ⟨v, vu, v_open, xv⟩
exact ⟨v, nhdsWithin_le_nhds (v_open.mem_nhds xv), v, v_open, Subset.rfl, hu.mono_set vu⟩
theorem locallyIntegrable_iff [LocallyCompactSpace X] :
LocallyIntegrable f μ ↔ ∀ k : Set X, IsCompact k → IntegrableOn f k μ :=
⟨fun hf _k hk => hf.integrableOn_isCompact hk, fun hf x =>
let ⟨K, hK, h2K⟩ := exists_compact_mem_nhds x
⟨K, h2K, hf K hK⟩⟩
theorem LocallyIntegrable.aestronglyMeasurable [SecondCountableTopology X]
(hf : LocallyIntegrable f μ) : AEStronglyMeasurable f μ := by
simpa only [restrict_univ] using (locallyIntegrableOn_univ.mpr hf).aestronglyMeasurable
/-- If a function is locally integrable in a second countable topological space,
then there exists a sequence of open sets covering the space on which it is integrable. -/
theorem LocallyIntegrable.exists_nat_integrableOn [SecondCountableTopology X]
(hf : LocallyIntegrable f μ) : ∃ u : ℕ → Set X,
(∀ n, IsOpen (u n)) ∧ ((⋃ n, u n) = univ) ∧ (∀ n, IntegrableOn f (u n) μ) := by
rcases (hf.locallyIntegrableOn univ).exists_nat_integrableOn with ⟨u, u_open, u_union, hu⟩
refine ⟨u, u_open, eq_univ_of_univ_subset u_union, fun n ↦ ?_⟩
simpa only [inter_univ] using hu n
theorem MemLp.locallyIntegrable [IsLocallyFiniteMeasure μ] {f : X → E} {p : ℝ≥0∞}
(hf : MemLp f p μ) (hp : 1 ≤ p) : LocallyIntegrable f μ := by
intro x
rcases μ.finiteAt_nhds x with ⟨U, hU, h'U⟩
have : Fact (μ U < ⊤) := ⟨h'U⟩
refine ⟨U, hU, ?_⟩
rw [IntegrableOn, ← memLp_one_iff_integrable]
apply (hf.restrict U).mono_exponent hp
@[deprecated (since := "2025-02-21")]
alias Memℒp.locallyIntegrable := MemLp.locallyIntegrable
theorem locallyIntegrable_const [IsLocallyFiniteMeasure μ] (c : E) :
LocallyIntegrable (fun _ => c) μ :=
(memLp_top_const c).locallyIntegrable le_top
theorem locallyIntegrableOn_const [IsLocallyFiniteMeasure μ] (c : E) :
LocallyIntegrableOn (fun _ => c) s μ :=
(locallyIntegrable_const c).locallyIntegrableOn s
theorem locallyIntegrable_zero : LocallyIntegrable (fun _ ↦ (0 : E)) μ :=
(integrable_zero X E μ).locallyIntegrable
theorem locallyIntegrableOn_zero : LocallyIntegrableOn (fun _ ↦ (0 : E)) s μ :=
locallyIntegrable_zero.locallyIntegrableOn s
theorem LocallyIntegrable.indicator (hf : LocallyIntegrable f μ) {s : Set X}
(hs : MeasurableSet s) : LocallyIntegrable (s.indicator f) μ := by
intro x
rcases hf x with ⟨U, hU, h'U⟩
exact ⟨U, hU, h'U.indicator hs⟩
theorem locallyIntegrable_map_homeomorph [BorelSpace X] [BorelSpace Y] (e : X ≃ₜ Y) {f : Y → E}
{μ : Measure X} : LocallyIntegrable f (Measure.map e μ) ↔ LocallyIntegrable (f ∘ e) μ := by
refine ⟨fun h x => ?_, fun h x => ?_⟩
· rcases h (e x) with ⟨U, hU, h'U⟩
refine ⟨e ⁻¹' U, e.continuous.continuousAt.preimage_mem_nhds hU, ?_⟩
exact (integrableOn_map_equiv e.toMeasurableEquiv).1 h'U
· rcases h (e.symm x) with ⟨U, hU, h'U⟩
refine ⟨e.symm ⁻¹' U, e.symm.continuous.continuousAt.preimage_mem_nhds hU, ?_⟩
apply (integrableOn_map_equiv e.toMeasurableEquiv).2
simp only [Homeomorph.toMeasurableEquiv_coe]
convert h'U
ext x
simp only [mem_preimage, Homeomorph.symm_apply_apply]
protected theorem LocallyIntegrable.add (hf : LocallyIntegrable f μ) (hg : LocallyIntegrable g μ) :
LocallyIntegrable (f + g) μ := fun x ↦ (hf x).add (hg x)
protected theorem LocallyIntegrable.sub (hf : LocallyIntegrable f μ) (hg : LocallyIntegrable g μ) :
LocallyIntegrable (f - g) μ := fun x ↦ (hf x).sub (hg x)
protected theorem LocallyIntegrable.neg (hf : LocallyIntegrable f μ) :
LocallyIntegrable (-f) μ := fun x ↦ (hf x).neg
protected theorem LocallyIntegrable.smul {𝕜 : Type*} [NormedAddCommGroup 𝕜] [SMulZeroClass 𝕜 E]
[IsBoundedSMul 𝕜 E] (hf : LocallyIntegrable f μ) (c : 𝕜) :
LocallyIntegrable (c • f) μ := fun x ↦ (hf x).smul c
theorem locallyIntegrable_finset_sum' {ι} (s : Finset ι) {f : ι → X → E}
(hf : ∀ i ∈ s, LocallyIntegrable (f i) μ) : LocallyIntegrable (∑ i ∈ s, f i) μ :=
Finset.sum_induction f (fun g => LocallyIntegrable g μ) (fun _ _ => LocallyIntegrable.add)
locallyIntegrable_zero hf
theorem locallyIntegrable_finset_sum {ι} (s : Finset ι) {f : ι → X → E}
(hf : ∀ i ∈ s, LocallyIntegrable (f i) μ) : LocallyIntegrable (fun a ↦ ∑ i ∈ s, f i a) μ := by
simpa only [← Finset.sum_apply] using locallyIntegrable_finset_sum' s hf
/-- If `f` is locally integrable and `g` is continuous with compact support,
then `g • f` is integrable. -/
theorem LocallyIntegrable.integrable_smul_left_of_hasCompactSupport
[NormedSpace ℝ E] [OpensMeasurableSpace X] [T2Space X]
(hf : LocallyIntegrable f μ) {g : X → ℝ} (hg : Continuous g) (h'g : HasCompactSupport g) :
Integrable (fun x ↦ g x • f x) μ := by
let K := tsupport g
have hK : IsCompact K := h'g
have : K.indicator (fun x ↦ g x • f x) = (fun x ↦ g x • f x) := by
apply indicator_eq_self.2
apply support_subset_iff'.2
intros x hx
simp [image_eq_zero_of_nmem_tsupport hx]
rw [← this, indicator_smul]
apply Integrable.smul_of_top_right
· rw [integrable_indicator_iff hK.measurableSet]
exact hf.integrableOn_isCompact hK
· exact hg.memLp_top_of_hasCompactSupport h'g μ
/-- If `f` is locally integrable and `g` is continuous with compact support,
then `f • g` is integrable. -/
theorem LocallyIntegrable.integrable_smul_right_of_hasCompactSupport
[NormedSpace ℝ E] [OpensMeasurableSpace X] [T2Space X] {f : X → ℝ} (hf : LocallyIntegrable f μ)
{g : X → E} (hg : Continuous g) (h'g : HasCompactSupport g) :
Integrable (fun x ↦ f x • g x) μ := by
let K := tsupport g
have hK : IsCompact K := h'g
have : K.indicator (fun x ↦ f x • g x) = (fun x ↦ f x • g x) := by
apply indicator_eq_self.2
apply support_subset_iff'.2
intros x hx
simp [image_eq_zero_of_nmem_tsupport hx]
rw [← this, indicator_smul_left]
apply Integrable.smul_of_top_left
· rw [integrable_indicator_iff hK.measurableSet]
exact hf.integrableOn_isCompact hK
· exact hg.memLp_top_of_hasCompactSupport h'g μ
open Filter
theorem integrable_iff_integrableAtFilter_cocompact :
Integrable f μ ↔ (IntegrableAtFilter f (cocompact X) μ ∧ LocallyIntegrable f μ) := by
refine ⟨fun hf ↦ ⟨hf.integrableAtFilter _, hf.locallyIntegrable⟩, fun ⟨⟨s, hsc, hs⟩, hloc⟩ ↦ ?_⟩
obtain ⟨t, htc, ht⟩ := mem_cocompact'.mp hsc
rewrite [← integrableOn_univ, ← compl_union_self s, integrableOn_union]
exact ⟨(hloc.integrableOn_isCompact htc).mono ht le_rfl, hs⟩
theorem integrable_iff_integrableAtFilter_atBot_atTop [LinearOrder X] [CompactIccSpace X] :
Integrable f μ ↔
(IntegrableAtFilter f atBot μ ∧ IntegrableAtFilter f atTop μ) ∧ LocallyIntegrable f μ := by
constructor
· exact fun hf ↦ ⟨⟨hf.integrableAtFilter _, hf.integrableAtFilter _⟩, hf.locallyIntegrable⟩
· refine fun h ↦ integrable_iff_integrableAtFilter_cocompact.mpr ⟨?_, h.2⟩
exact (IntegrableAtFilter.sup_iff.mpr h.1).filter_mono cocompact_le_atBot_atTop
theorem integrable_iff_integrableAtFilter_atBot [LinearOrder X] [OrderTop X] [CompactIccSpace X] :
Integrable f μ ↔ IntegrableAtFilter f atBot μ ∧ LocallyIntegrable f μ := by
constructor
· exact fun hf ↦ ⟨hf.integrableAtFilter _, hf.locallyIntegrable⟩
· refine fun h ↦ integrable_iff_integrableAtFilter_cocompact.mpr ⟨?_, h.2⟩
exact h.1.filter_mono cocompact_le_atBot
theorem integrable_iff_integrableAtFilter_atTop [LinearOrder X] [OrderBot X] [CompactIccSpace X] :
Integrable f μ ↔ IntegrableAtFilter f atTop μ ∧ LocallyIntegrable f μ :=
integrable_iff_integrableAtFilter_atBot (X := Xᵒᵈ)
variable {a : X}
theorem integrableOn_Iic_iff_integrableAtFilter_atBot [LinearOrder X] [CompactIccSpace X] :
| IntegrableOn f (Iic a) μ ↔ IntegrableAtFilter f atBot μ ∧ LocallyIntegrableOn f (Iic a) μ := by
refine ⟨fun h ↦ ⟨⟨Iic a, Iic_mem_atBot a, h⟩, h.locallyIntegrableOn⟩, fun ⟨⟨s, hsl, hs⟩, h⟩ ↦ ?_⟩
haveI : Nonempty X := Nonempty.intro a
obtain ⟨a', ha'⟩ := mem_atBot_sets.mp hsl
refine (integrableOn_union.mpr ⟨hs.mono ha' le_rfl, ?_⟩).mono Iic_subset_Iic_union_Icc le_rfl
exact h.integrableOn_compact_subset Icc_subset_Iic_self isCompact_Icc
| Mathlib/MeasureTheory/Function/LocallyIntegrable.lean | 385 | 390 |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Yury Kudryashov
-/
import Mathlib.Data.ENNReal.Operations
/-!
# Results about division in extended non-negative reals
This file establishes basic properties related to the inversion and division operations on `ℝ≥0∞`.
For instance, as a consequence of being a `DivInvOneMonoid`, `ℝ≥0∞` inherits a power operation
with integer exponent.
## Main results
A few order isomorphisms are worthy of mention:
- `OrderIso.invENNReal : ℝ≥0∞ ≃o ℝ≥0∞ᵒᵈ`: The map `x ↦ x⁻¹` as an order isomorphism to the dual.
- `orderIsoIicOneBirational : ℝ≥0∞ ≃o Iic (1 : ℝ≥0∞)`: The birational order isomorphism between
`ℝ≥0∞` and the unit interval `Set.Iic (1 : ℝ≥0∞)` given by `x ↦ (x⁻¹ + 1)⁻¹` with inverse
`x ↦ (x⁻¹ - 1)⁻¹`
- `orderIsoIicCoe (a : ℝ≥0) : Iic (a : ℝ≥0∞) ≃o Iic a`: Order isomorphism between an initial
interval in `ℝ≥0∞` and an initial interval in `ℝ≥0` given by the identity map.
- `orderIsoUnitIntervalBirational : ℝ≥0∞ ≃o Icc (0 : ℝ) 1`: An order isomorphism between
the extended nonnegative real numbers and the unit interval. This is `orderIsoIicOneBirational`
composed with the identity order isomorphism between `Iic (1 : ℝ≥0∞)` and `Icc (0 : ℝ) 1`.
-/
assert_not_exists Finset
open Set NNReal
namespace ENNReal
noncomputable section Inv
variable {a b c d : ℝ≥0∞} {r p q : ℝ≥0}
protected theorem div_eq_inv_mul : a / b = b⁻¹ * a := by rw [div_eq_mul_inv, mul_comm]
@[simp] theorem inv_zero : (0 : ℝ≥0∞)⁻¹ = ∞ :=
show sInf { b : ℝ≥0∞ | 1 ≤ 0 * b } = ∞ by simp
@[simp] theorem inv_top : ∞⁻¹ = 0 :=
bot_unique <| le_of_forall_gt_imp_ge_of_dense fun a (h : 0 < a) => sInf_le <| by
simp [*, h.ne', top_mul]
theorem coe_inv_le : (↑r⁻¹ : ℝ≥0∞) ≤ (↑r)⁻¹ :=
le_sInf fun b (hb : 1 ≤ ↑r * b) =>
coe_le_iff.2 <| by
rintro b rfl
apply NNReal.inv_le_of_le_mul
rwa [← coe_mul, ← coe_one, coe_le_coe] at hb
@[simp, norm_cast]
theorem coe_inv (hr : r ≠ 0) : (↑r⁻¹ : ℝ≥0∞) = (↑r)⁻¹ :=
coe_inv_le.antisymm <| sInf_le <| mem_setOf.2 <| by rw [← coe_mul, mul_inv_cancel₀ hr, coe_one]
@[norm_cast]
theorem coe_inv_two : ((2⁻¹ : ℝ≥0) : ℝ≥0∞) = 2⁻¹ := by rw [coe_inv _root_.two_ne_zero, coe_two]
@[simp, norm_cast]
theorem coe_div (hr : r ≠ 0) : (↑(p / r) : ℝ≥0∞) = p / r := by
rw [div_eq_mul_inv, div_eq_mul_inv, coe_mul, coe_inv hr]
lemma coe_div_le : ↑(p / r) ≤ (p / r : ℝ≥0∞) := by
simpa only [div_eq_mul_inv, coe_mul] using mul_le_mul_left' coe_inv_le _
theorem div_zero (h : a ≠ 0) : a / 0 = ∞ := by simp [div_eq_mul_inv, h]
instance : DivInvOneMonoid ℝ≥0∞ :=
{ inferInstanceAs (DivInvMonoid ℝ≥0∞) with
inv_one := by simpa only [coe_inv one_ne_zero, coe_one] using coe_inj.2 inv_one }
protected theorem inv_pow : ∀ {a : ℝ≥0∞} {n : ℕ}, (a ^ n)⁻¹ = a⁻¹ ^ n
| _, 0 => by simp only [pow_zero, inv_one]
| ⊤, n + 1 => by simp [top_pow]
| (a : ℝ≥0), n + 1 => by
rcases eq_or_ne a 0 with (rfl | ha)
· simp [top_pow]
· have := pow_ne_zero (n + 1) ha
norm_cast
rw [inv_pow]
protected theorem mul_inv_cancel (h0 : a ≠ 0) (ht : a ≠ ∞) : a * a⁻¹ = 1 := by
lift a to ℝ≥0 using ht
norm_cast at h0; norm_cast
exact mul_inv_cancel₀ h0
protected theorem inv_mul_cancel (h0 : a ≠ 0) (ht : a ≠ ∞) : a⁻¹ * a = 1 :=
mul_comm a a⁻¹ ▸ ENNReal.mul_inv_cancel h0 ht
/-- See `ENNReal.inv_mul_cancel_left` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma inv_mul_cancel_left' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) :
a⁻¹ * (a * b) = b := by
obtain rfl | ha₀ := eq_or_ne a 0
· simp_all
obtain rfl | ha := eq_or_ne a ⊤
· simp_all
· simp [← mul_assoc, ENNReal.inv_mul_cancel, *]
/-- See `ENNReal.inv_mul_cancel_left'` for a stronger version. -/
protected lemma inv_mul_cancel_left (ha₀ : a ≠ 0) (ha : a ≠ ∞) : a⁻¹ * (a * b) = b :=
ENNReal.inv_mul_cancel_left' (by simp [ha₀]) (by simp [ha])
/-- See `ENNReal.mul_inv_cancel_left` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma mul_inv_cancel_left' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) :
a * (a⁻¹ * b) = b := by
obtain rfl | ha₀ := eq_or_ne a 0
· simp_all
obtain rfl | ha := eq_or_ne a ⊤
· simp_all
· simp [← mul_assoc, ENNReal.mul_inv_cancel, *]
/-- See `ENNReal.mul_inv_cancel_left'` for a stronger version. -/
protected lemma mul_inv_cancel_left (ha₀ : a ≠ 0) (ha : a ≠ ∞) : a * (a⁻¹ * b) = b :=
ENNReal.mul_inv_cancel_left' (by simp [ha₀]) (by simp [ha])
/-- See `ENNReal.mul_inv_cancel_right` for a simpler version assuming `b ≠ 0`, `b ≠ ∞`. -/
protected lemma mul_inv_cancel_right' (hb₀ : b = 0 → a = 0) (hb : b = ∞ → a = 0) :
a * b * b⁻¹ = a := by
obtain rfl | hb₀ := eq_or_ne b 0
· simp_all
obtain rfl | hb := eq_or_ne b ⊤
· simp_all
· simp [mul_assoc, ENNReal.mul_inv_cancel, *]
/-- See `ENNReal.mul_inv_cancel_right'` for a stronger version. -/
protected lemma mul_inv_cancel_right (hb₀ : b ≠ 0) (hb : b ≠ ∞) : a * b * b⁻¹ = a :=
ENNReal.mul_inv_cancel_right' (by simp [hb₀]) (by simp [hb])
/-- See `ENNReal.inv_mul_cancel_right` for a simpler version assuming `b ≠ 0`, `b ≠ ∞`. -/
protected lemma inv_mul_cancel_right' (hb₀ : b = 0 → a = 0) (hb : b = ∞ → a = 0) :
a * b⁻¹ * b = a := by
obtain rfl | hb₀ := eq_or_ne b 0
· simp_all
obtain rfl | hb := eq_or_ne b ⊤
· simp_all
· simp [mul_assoc, ENNReal.inv_mul_cancel, *]
/-- See `ENNReal.inv_mul_cancel_right'` for a stronger version. -/
protected lemma inv_mul_cancel_right (hb₀ : b ≠ 0) (hb : b ≠ ∞) : a * b⁻¹ * b = a :=
ENNReal.inv_mul_cancel_right' (by simp [hb₀]) (by simp [hb])
/-- See `ENNReal.mul_div_cancel_right` for a simpler version assuming `b ≠ 0`, `b ≠ ∞`. -/
protected lemma mul_div_cancel_right' (hb₀ : b = 0 → a = 0) (hb : b = ∞ → a = 0) :
a * b / b = a := ENNReal.mul_inv_cancel_right' hb₀ hb
/-- See `ENNReal.mul_div_cancel_right'` for a stronger version. -/
protected lemma mul_div_cancel_right (hb₀ : b ≠ 0) (hb : b ≠ ∞) : a * b / b = a :=
ENNReal.mul_div_cancel_right' (by simp [hb₀]) (by simp [hb])
/-- See `ENNReal.div_mul_cancel` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma div_mul_cancel' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) : b / a * a = b :=
ENNReal.inv_mul_cancel_right' ha₀ ha
/-- See `ENNReal.div_mul_cancel'` for a stronger version. -/
protected lemma div_mul_cancel (ha₀ : a ≠ 0) (ha : a ≠ ∞) : b / a * a = b :=
ENNReal.div_mul_cancel' (by simp [ha₀]) (by simp [ha])
/-- See `ENNReal.mul_div_cancel` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma mul_div_cancel' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) : a * (b / a) = b := by
rw [mul_comm, ENNReal.div_mul_cancel' ha₀ ha]
/-- See `ENNReal.mul_div_cancel'` for a stronger version. -/
protected lemma mul_div_cancel (ha₀ : a ≠ 0) (ha : a ≠ ∞) : a * (b / a) = b :=
ENNReal.mul_div_cancel' (by simp [ha₀]) (by simp [ha])
protected theorem mul_comm_div : a / b * c = a * (c / b) := by
simp only [div_eq_mul_inv, mul_left_comm, mul_comm, mul_assoc]
protected theorem mul_div_right_comm : a * b / c = a / c * b := by
simp only [div_eq_mul_inv, mul_right_comm]
instance : InvolutiveInv ℝ≥0∞ where
inv_inv a := by
by_cases a = 0 <;> cases a <;> simp_all [none_eq_top, some_eq_coe, -coe_inv, (coe_inv _).symm]
@[simp] protected lemma inv_eq_one : a⁻¹ = 1 ↔ a = 1 := by rw [← inv_inj, inv_inv, inv_one]
@[simp] theorem inv_eq_top : a⁻¹ = ∞ ↔ a = 0 := inv_zero ▸ inv_inj
theorem inv_ne_top : a⁻¹ ≠ ∞ ↔ a ≠ 0 := by simp
@[aesop (rule_sets := [finiteness]) safe apply]
protected alias ⟨_, Finiteness.inv_ne_top⟩ := ENNReal.inv_ne_top
| @[simp]
theorem inv_lt_top {x : ℝ≥0∞} : x⁻¹ < ∞ ↔ 0 < x := by
simp only [lt_top_iff_ne_top, inv_ne_top, pos_iff_ne_zero]
| Mathlib/Data/ENNReal/Inv.lean | 192 | 195 |
/-
Copyright (c) 2021 Kalle Kytölä. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kalle Kytölä
-/
import Mathlib.MeasureTheory.Integral.Bochner.ContinuousLinearMap
import Mathlib.MeasureTheory.Measure.HasOuterApproxClosed
import Mathlib.MeasureTheory.Measure.Prod
import Mathlib.Topology.Algebra.Module.WeakDual
/-!
# Finite measures
This file defines the type of finite measures on a given measurable space. When the underlying
space has a topology and the measurable space structure (sigma algebra) is finer than the Borel
sigma algebra, then the type of finite measures is equipped with the topology of weak convergence
of measures. The topology of weak convergence is the coarsest topology w.r.t. which
for every bounded continuous `ℝ≥0`-valued function `f`, the integration of `f` against the
measure is continuous.
## Main definitions
The main definitions are
* `MeasureTheory.FiniteMeasure Ω`: The type of finite measures on `Ω` with the topology of weak
convergence of measures.
* `MeasureTheory.FiniteMeasure.toWeakDualBCNN : FiniteMeasure Ω → (WeakDual ℝ≥0 (Ω →ᵇ ℝ≥0))`:
Interpret a finite measure as a continuous linear functional on the space of
bounded continuous nonnegative functions on `Ω`. This is used for the definition of the
topology of weak convergence.
* `MeasureTheory.FiniteMeasure.map`: The push-forward `f* μ` of a finite measure `μ` on `Ω`
along a measurable function `f : Ω → Ω'`.
* `MeasureTheory.FiniteMeasure.mapCLM`: The push-forward along a given continuous `f : Ω → Ω'`
as a continuous linear map `f* : FiniteMeasure Ω →L[ℝ≥0] FiniteMeasure Ω'`.
## Main results
* Finite measures `μ` on `Ω` give rise to continuous linear functionals on the space of
bounded continuous nonnegative functions on `Ω` via integration:
`MeasureTheory.FiniteMeasure.toWeakDualBCNN : FiniteMeasure Ω → (WeakDual ℝ≥0 (Ω →ᵇ ℝ≥0))`
* `MeasureTheory.FiniteMeasure.tendsto_iff_forall_integral_tendsto`: Convergence of finite
measures is characterized by the convergence of integrals of all bounded continuous functions.
This shows that the chosen definition of topology coincides with the common textbook definition
of weak convergence of measures. A similar characterization by the convergence of integrals (in
the `MeasureTheory.lintegral` sense) of all bounded continuous nonnegative functions is
`MeasureTheory.FiniteMeasure.tendsto_iff_forall_lintegral_tendsto`.
* `MeasureTheory.FiniteMeasure.continuous_map`: For a continuous function `f : Ω → Ω'`, the
push-forward of finite measures `f* : FiniteMeasure Ω → FiniteMeasure Ω'` is continuous.
* `MeasureTheory.FiniteMeasure.t2Space`: The topology of weak convergence of finite Borel measures
is Hausdorff on spaces where indicators of closed sets have continuous decreasing approximating
sequences (in particular on any pseudo-metrizable spaces).
## Implementation notes
The topology of weak convergence of finite Borel measures is defined using a mapping from
`MeasureTheory.FiniteMeasure Ω` to `WeakDual ℝ≥0 (Ω →ᵇ ℝ≥0)`, inheriting the topology from the
latter.
The implementation of `MeasureTheory.FiniteMeasure Ω` and is directly as a subtype of
`MeasureTheory.Measure Ω`, and the coercion to a function is the composition `ENNReal.toNNReal`
and the coercion to function of `MeasureTheory.Measure Ω`. Another alternative would have been to
use a bijection with `MeasureTheory.VectorMeasure Ω ℝ≥0` as an intermediate step. Some
considerations:
* Potential advantages of using the `NNReal`-valued vector measure alternative:
* The coercion to function would avoid need to compose with `ENNReal.toNNReal`, the
`NNReal`-valued API could be more directly available.
* Potential drawbacks of the vector measure alternative:
* The coercion to function would lose monotonicity, as non-measurable sets would be defined to
have measure 0.
* No integration theory directly. E.g., the topology definition requires
`MeasureTheory.lintegral` w.r.t. a coercion to `MeasureTheory.Measure Ω` in any case.
## References
* [Billingsley, *Convergence of probability measures*][billingsley1999]
## Tags
weak convergence of measures, finite measure
-/
noncomputable section
open BoundedContinuousFunction Filter MeasureTheory Set Topology
open scoped ENNReal NNReal
namespace MeasureTheory
namespace FiniteMeasure
section FiniteMeasure
/-! ### Finite measures
In this section we define the `Type` of `MeasureTheory.FiniteMeasure Ω`, when `Ω` is a measurable
space. Finite measures on `Ω` are a module over `ℝ≥0`.
If `Ω` is moreover a topological space and the sigma algebra on `Ω` is finer than the Borel sigma
algebra (i.e. `[OpensMeasurableSpace Ω]`), then `MeasureTheory.FiniteMeasure Ω` is equipped with
the topology of weak convergence of measures. This is implemented by defining a pairing of finite
measures `μ` on `Ω` with continuous bounded nonnegative functions `f : Ω →ᵇ ℝ≥0` via integration,
and using the associated weak topology (essentially the weak-star topology on the dual of
`Ω →ᵇ ℝ≥0`).
-/
variable {Ω : Type*} [MeasurableSpace Ω]
/-- Finite measures are defined as the subtype of measures that have the property of being finite
measures (i.e., their total mass is finite). -/
def _root_.MeasureTheory.FiniteMeasure (Ω : Type*) [MeasurableSpace Ω] : Type _ :=
{ μ : Measure Ω // IsFiniteMeasure μ }
/-- Coercion from `MeasureTheory.FiniteMeasure Ω` to `MeasureTheory.Measure Ω`. -/
@[coe]
def toMeasure : FiniteMeasure Ω → Measure Ω := Subtype.val
/-- A finite measure can be interpreted as a measure. -/
instance instCoe : Coe (FiniteMeasure Ω) (MeasureTheory.Measure Ω) := { coe := toMeasure }
instance isFiniteMeasure (μ : FiniteMeasure Ω) : IsFiniteMeasure (μ : Measure Ω) := μ.prop
@[simp]
theorem val_eq_toMeasure (ν : FiniteMeasure Ω) : ν.val = (ν : Measure Ω) := rfl
theorem toMeasure_injective : Function.Injective ((↑) : FiniteMeasure Ω → Measure Ω) :=
Subtype.coe_injective
instance instFunLike : FunLike (FiniteMeasure Ω) (Set Ω) ℝ≥0 where
coe μ s := ((μ : Measure Ω) s).toNNReal
coe_injective' μ ν h := toMeasure_injective <| Measure.ext fun s _ ↦ by
simpa [ENNReal.toNNReal_eq_toNNReal_iff, measure_ne_top] using congr_fun h s
lemma coeFn_def (μ : FiniteMeasure Ω) : μ = fun s ↦ ((μ : Measure Ω) s).toNNReal := rfl
lemma coeFn_mk (μ : Measure Ω) (hμ) :
DFunLike.coe (F := FiniteMeasure Ω) ⟨μ, hμ⟩ = fun s ↦ (μ s).toNNReal := rfl
@[simp, norm_cast]
lemma mk_apply (μ : Measure Ω) (hμ) (s : Set Ω) :
DFunLike.coe (F := FiniteMeasure Ω) ⟨μ, hμ⟩ s = (μ s).toNNReal := rfl
@[simp]
theorem ennreal_coeFn_eq_coeFn_toMeasure (ν : FiniteMeasure Ω) (s : Set Ω) :
(ν s : ℝ≥0∞) = (ν : Measure Ω) s :=
ENNReal.coe_toNNReal (measure_lt_top (↑ν) s).ne
@[simp]
theorem null_iff_toMeasure_null (ν : FiniteMeasure Ω) (s : Set Ω) :
ν s = 0 ↔ (ν : Measure Ω) s = 0 :=
⟨fun h ↦ by rw [← ennreal_coeFn_eq_coeFn_toMeasure, h, ENNReal.coe_zero],
fun h ↦ congrArg ENNReal.toNNReal h⟩
theorem apply_mono (μ : FiniteMeasure Ω) {s₁ s₂ : Set Ω} (h : s₁ ⊆ s₂) : μ s₁ ≤ μ s₂ :=
ENNReal.toNNReal_mono (measure_ne_top _ s₂) ((μ : Measure Ω).mono h)
/-- Continuity from below: the measure of the union of a sequence of (not necessarily measurable)
sets is the limit of the measures of the partial unions. -/
protected lemma tendsto_measure_iUnion_accumulate {ι : Type*} [Preorder ι]
[IsCountablyGenerated (atTop : Filter ι)] {μ : FiniteMeasure Ω} {f : ι → Set Ω} :
Tendsto (fun i ↦ μ (Accumulate f i)) atTop (𝓝 (μ (⋃ i, f i))) := by
simpa [← ennreal_coeFn_eq_coeFn_toMeasure]
using tendsto_measure_iUnion_accumulate (μ := μ.toMeasure) (ι := ι)
/-- The (total) mass of a finite measure `μ` is `μ univ`, i.e., the cast to `NNReal` of
`(μ : measure Ω) univ`. -/
def mass (μ : FiniteMeasure Ω) : ℝ≥0 := μ univ
@[simp] theorem apply_le_mass (μ : FiniteMeasure Ω) (s : Set Ω) : μ s ≤ μ.mass := by
simpa using apply_mono μ (subset_univ s)
@[simp]
theorem ennreal_mass {μ : FiniteMeasure Ω} : (μ.mass : ℝ≥0∞) = (μ : Measure Ω) univ :=
ennreal_coeFn_eq_coeFn_toMeasure μ Set.univ
instance instZero : Zero (FiniteMeasure Ω) where zero := ⟨0, MeasureTheory.isFiniteMeasureZero⟩
@[simp, norm_cast] lemma coeFn_zero : ⇑(0 : FiniteMeasure Ω) = 0 := rfl
@[simp]
theorem zero_mass : (0 : FiniteMeasure Ω).mass = 0 := rfl
@[simp]
theorem mass_zero_iff (μ : FiniteMeasure Ω) : μ.mass = 0 ↔ μ = 0 := by
refine ⟨fun μ_mass => ?_, fun hμ => by simp only [hμ, zero_mass]⟩
apply toMeasure_injective
apply Measure.measure_univ_eq_zero.mp
rwa [← ennreal_mass, ENNReal.coe_eq_zero]
theorem mass_nonzero_iff (μ : FiniteMeasure Ω) : μ.mass ≠ 0 ↔ μ ≠ 0 :=
not_iff_not.mpr <| FiniteMeasure.mass_zero_iff μ
@[ext]
theorem eq_of_forall_toMeasure_apply_eq (μ ν : FiniteMeasure Ω)
(h : ∀ s : Set Ω, MeasurableSet s → (μ : Measure Ω) s = (ν : Measure Ω) s) : μ = ν := by
apply Subtype.ext
ext1 s s_mble
exact h s s_mble
theorem eq_of_forall_apply_eq (μ ν : FiniteMeasure Ω)
(h : ∀ s : Set Ω, MeasurableSet s → μ s = ν s) : μ = ν := by
ext1 s s_mble
simpa [ennreal_coeFn_eq_coeFn_toMeasure] using congr_arg ((↑) : ℝ≥0 → ℝ≥0∞) (h s s_mble)
instance instInhabited : Inhabited (FiniteMeasure Ω) := ⟨0⟩
instance instAdd : Add (FiniteMeasure Ω) where add μ ν := ⟨μ + ν, MeasureTheory.isFiniteMeasureAdd⟩
variable {R : Type*} [SMul R ℝ≥0] [SMul R ℝ≥0∞] [IsScalarTower R ℝ≥0 ℝ≥0∞]
[IsScalarTower R ℝ≥0∞ ℝ≥0∞]
instance instSMul : SMul R (FiniteMeasure Ω) where
smul (c : R) μ := ⟨c • (μ : Measure Ω), MeasureTheory.isFiniteMeasureSMulOfNNRealTower⟩
@[simp, norm_cast]
theorem toMeasure_zero : ((↑) : FiniteMeasure Ω → Measure Ω) 0 = 0 := rfl
@[norm_cast]
theorem toMeasure_add (μ ν : FiniteMeasure Ω) : ↑(μ + ν) = (↑μ + ↑ν : Measure Ω) := rfl
@[simp, norm_cast]
theorem toMeasure_smul (c : R) (μ : FiniteMeasure Ω) : ↑(c • μ) = c • (μ : Measure Ω) :=
rfl
@[simp, norm_cast]
theorem coeFn_add (μ ν : FiniteMeasure Ω) : (⇑(μ + ν) : Set Ω → ℝ≥0) = (⇑μ + ⇑ν : Set Ω → ℝ≥0) := by
funext
simp only [Pi.add_apply, ← ENNReal.coe_inj, ne_eq, ennreal_coeFn_eq_coeFn_toMeasure,
ENNReal.coe_add]
norm_cast
@[simp, norm_cast]
theorem coeFn_smul [IsScalarTower R ℝ≥0 ℝ≥0] (c : R) (μ : FiniteMeasure Ω) :
(⇑(c • μ) : Set Ω → ℝ≥0) = c • (⇑μ : Set Ω → ℝ≥0) := by
funext; simp [← ENNReal.coe_inj, ENNReal.coe_smul]
instance instAddCommMonoid : AddCommMonoid (FiniteMeasure Ω) :=
toMeasure_injective.addCommMonoid _ toMeasure_zero toMeasure_add fun _ _ ↦ toMeasure_smul _ _
/-- Coercion is an `AddMonoidHom`. -/
@[simps]
def toMeasureAddMonoidHom : FiniteMeasure Ω →+ Measure Ω where
toFun := (↑)
map_zero' := toMeasure_zero
map_add' := toMeasure_add
instance {Ω : Type*} [MeasurableSpace Ω] : Module ℝ≥0 (FiniteMeasure Ω) :=
Function.Injective.module _ toMeasureAddMonoidHom toMeasure_injective toMeasure_smul
@[simp]
theorem smul_apply [IsScalarTower R ℝ≥0 ℝ≥0] (c : R) (μ : FiniteMeasure Ω) (s : Set Ω) :
(c • μ) s = c • μ s := by
rw [coeFn_smul, Pi.smul_apply]
/-- Restrict a finite measure μ to a set A. -/
def restrict (μ : FiniteMeasure Ω) (A : Set Ω) : FiniteMeasure Ω where
val := (μ : Measure Ω).restrict A
property := MeasureTheory.isFiniteMeasureRestrict (μ : Measure Ω) A
theorem restrict_measure_eq (μ : FiniteMeasure Ω) (A : Set Ω) :
(μ.restrict A : Measure Ω) = (μ : Measure Ω).restrict A := rfl
theorem restrict_apply_measure (μ : FiniteMeasure Ω) (A : Set Ω) {s : Set Ω}
(s_mble : MeasurableSet s) : (μ.restrict A : Measure Ω) s = (μ : Measure Ω) (s ∩ A) :=
Measure.restrict_apply s_mble
theorem restrict_apply (μ : FiniteMeasure Ω) (A : Set Ω) {s : Set Ω} (s_mble : MeasurableSet s) :
(μ.restrict A) s = μ (s ∩ A) := by
apply congr_arg ENNReal.toNNReal
exact Measure.restrict_apply s_mble
theorem restrict_mass (μ : FiniteMeasure Ω) (A : Set Ω) : (μ.restrict A).mass = μ A := by
simp only [mass, restrict_apply μ A MeasurableSet.univ, univ_inter]
theorem restrict_eq_zero_iff (μ : FiniteMeasure Ω) (A : Set Ω) : μ.restrict A = 0 ↔ μ A = 0 := by
rw [← mass_zero_iff, restrict_mass]
theorem restrict_nonzero_iff (μ : FiniteMeasure Ω) (A : Set Ω) : μ.restrict A ≠ 0 ↔ μ A ≠ 0 := by
rw [← mass_nonzero_iff, restrict_mass]
/-- The type of finite measures is a measurable space when equipped with the Giry monad. -/
instance : MeasurableSpace (FiniteMeasure Ω) := Subtype.instMeasurableSpace
/-- The set of all finite measures is a measurable set in the Giry monad. -/
lemma measurableSet_isFiniteMeasure : MeasurableSet { μ : Measure Ω | IsFiniteMeasure μ } := by
suffices { μ : Measure Ω | IsFiniteMeasure μ } = (fun μ => μ univ) ⁻¹' (Set.Ico 0 ∞) by
rw [this]
exact Measure.measurable_coe MeasurableSet.univ measurableSet_Ico
ext μ
simp only [mem_setOf_eq, mem_iUnion, mem_preimage, mem_Ico, zero_le, true_and, exists_const]
exact isFiniteMeasure_iff μ
/-- The monoidal product is a measurabule function from the product of finite measures over
`α` and `β` into the type of finite measures over `α × β`. -/
theorem measurable_prod {α β : Type*} [MeasurableSpace α] [MeasurableSpace β] :
Measurable (fun (μ : FiniteMeasure α × FiniteMeasure β)
↦ μ.1.toMeasure.prod μ.2.toMeasure) := by
have Heval {u v} (Hu : MeasurableSet u) (Hv : MeasurableSet v):
Measurable fun a : (FiniteMeasure α × FiniteMeasure β) ↦
a.1.toMeasure u * a.2.toMeasure v :=
Measurable.mul
((Measure.measurable_coe Hu).comp (measurable_subtype_coe.comp measurable_fst))
((Measure.measurable_coe Hv).comp (measurable_subtype_coe.comp measurable_snd))
apply Measurable.measure_of_isPiSystem generateFrom_prod.symm isPiSystem_prod _
· simp_rw [← Set.univ_prod_univ, Measure.prod_prod, Heval MeasurableSet.univ MeasurableSet.univ]
simp only [mem_image2, mem_setOf_eq, forall_exists_index, and_imp]
intros _ _ Hu _ Hv Heq
simp_rw [← Heq, Measure.prod_prod, Heval Hu Hv]
variable [TopologicalSpace Ω]
| /-- Two finite Borel measures are equal if the integrals of all non-negative bounded continuous
functions with respect to both agree. -/
| Mathlib/MeasureTheory/Measure/FiniteMeasure.lean | 313 | 314 |
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Analysis.NormedSpace.Multilinear.Basic
import Mathlib.LinearAlgebra.Multilinear.Curry
/-!
# Currying and uncurrying continuous multilinear maps
We associate to a continuous multilinear map in `n+1` variables (i.e., based on `Fin n.succ`) two
curried functions, named `f.curryLeft` (which is a continuous linear map on `E 0` taking values
in continuous multilinear maps in `n` variables) and `f.curryRight` (which is a continuous
multilinear map in `n` variables taking values in continuous linear maps on `E (last n)`).
The inverse operations are called `uncurryLeft` and `uncurryRight`.
We also register continuous linear equiv versions of these correspondences, in
`continuousMultilinearCurryLeftEquiv` and `continuousMultilinearCurryRightEquiv`.
## Main results
* `ContinuousMultilinearMap.curryLeft`, `ContinuousLinearMap.uncurryLeft` and
`continuousMultilinearCurryLeftEquiv`
* `ContinuousMultilinearMap.curryRight`, `ContinuousMultilinearMap.uncurryRight` and
`continuousMultilinearCurryRightEquiv`.
-/
suppress_compilation
noncomputable section
open NNReal Finset Metric ContinuousMultilinearMap Fin Function
/-!
### Type variables
We use the following type variables in this file:
* `𝕜` : a `NontriviallyNormedField`;
* `ι`, `ι'` : finite index types with decidable equality;
* `E`, `E₁` : families of normed vector spaces over `𝕜` indexed by `i : ι`;
* `E'` : a family of normed vector spaces over `𝕜` indexed by `i' : ι'`;
* `Ei` : a family of normed vector spaces over `𝕜` indexed by `i : Fin (Nat.succ n)`;
* `G`, `G'` : normed vector spaces over `𝕜`.
-/
universe u v v' wE wE₁ wE' wEi wG wG'
variable {𝕜 : Type u} {ι : Type v} {ι' : Type v'} {n : ℕ} {E : ι → Type wE}
{Ei : Fin n.succ → Type wEi} {G : Type wG} {G' : Type wG'} [Fintype ι]
[Fintype ι'] [NontriviallyNormedField 𝕜] [∀ i, NormedAddCommGroup (E i)]
[∀ i, NormedSpace 𝕜 (E i)] [∀ i, NormedAddCommGroup (Ei i)] [∀ i, NormedSpace 𝕜 (Ei i)]
[NormedAddCommGroup G] [NormedSpace 𝕜 G] [NormedAddCommGroup G'] [NormedSpace 𝕜 G']
theorem ContinuousLinearMap.norm_map_tail_le
(f : Ei 0 →L[𝕜] ContinuousMultilinearMap 𝕜 (fun i : Fin n => Ei i.succ) G) (m : ∀ i, Ei i) :
‖f (m 0) (tail m)‖ ≤ ‖f‖ * ∏ i, ‖m i‖ :=
calc
‖f (m 0) (tail m)‖ ≤ ‖f (m 0)‖ * ∏ i, ‖(tail m) i‖ := (f (m 0)).le_opNorm _
_ ≤ ‖f‖ * ‖m 0‖ * ∏ i, ‖tail m i‖ := mul_le_mul_of_nonneg_right (f.le_opNorm _) <| by positivity
_ = ‖f‖ * (‖m 0‖ * ∏ i, ‖(tail m) i‖) := by ring
_ = ‖f‖ * ∏ i, ‖m i‖ := by
rw [prod_univ_succ]
rfl
theorem ContinuousMultilinearMap.norm_map_init_le
(f : ContinuousMultilinearMap 𝕜 (fun i : Fin n => Ei <| castSucc i) (Ei (last n) →L[𝕜] G))
(m : ∀ i, Ei i) : ‖f (init m) (m (last n))‖ ≤ ‖f‖ * ∏ i, ‖m i‖ :=
calc
| ‖f (init m) (m (last n))‖ ≤ ‖f (init m)‖ * ‖m (last n)‖ := (f (init m)).le_opNorm _
_ ≤ (‖f‖ * ∏ i, ‖(init m) i‖) * ‖m (last n)‖ :=
(mul_le_mul_of_nonneg_right (f.le_opNorm _) (norm_nonneg _))
_ = ‖f‖ * ((∏ i, ‖(init m) i‖) * ‖m (last n)‖) := mul_assoc _ _ _
_ = ‖f‖ * ∏ i, ‖m i‖ := by
rw [prod_univ_castSucc]
rfl
theorem ContinuousMultilinearMap.norm_map_cons_le (f : ContinuousMultilinearMap 𝕜 Ei G) (x : Ei 0)
(m : ∀ i : Fin n, Ei i.succ) : ‖f (cons x m)‖ ≤ ‖f‖ * ‖x‖ * ∏ i, ‖m i‖ :=
calc
| Mathlib/Analysis/NormedSpace/Multilinear/Curry.lean | 73 | 83 |
/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Data.Finset.Sort
import Mathlib.Data.Fin.VecNotation
import Mathlib.Data.Sign
import Mathlib.LinearAlgebra.AffineSpace.Combination
import Mathlib.LinearAlgebra.AffineSpace.AffineEquiv
import Mathlib.LinearAlgebra.Basis.VectorSpace
/-!
# Affine independence
This file defines affinely independent families of points.
## Main definitions
* `AffineIndependent` defines affinely independent families of points
as those where no nontrivial weighted subtraction is `0`. This is
proved equivalent to two other formulations: linear independence of
the results of subtracting a base point in the family from the other
points in the family, or any equal affine combinations having the
same weights. A bundled type `Simplex` is provided for finite
affinely independent families of points, with an abbreviation
`Triangle` for the case of three points.
## References
* https://en.wikipedia.org/wiki/Affine_space
-/
noncomputable section
open Finset Function
open scoped Affine
section AffineIndependent
variable (k : Type*) {V : Type*} {P : Type*} [Ring k] [AddCommGroup V] [Module k V]
variable [AffineSpace V P] {ι : Type*}
/-- An indexed family is said to be affinely independent if no
nontrivial weighted subtractions (where the sum of weights is 0) are
0. -/
def AffineIndependent (p : ι → P) : Prop :=
∀ (s : Finset ι) (w : ι → k),
∑ i ∈ s, w i = 0 → s.weightedVSub p w = (0 : V) → ∀ i ∈ s, w i = 0
/-- The definition of `AffineIndependent`. -/
theorem affineIndependent_def (p : ι → P) :
AffineIndependent k p ↔
∀ (s : Finset ι) (w : ι → k),
∑ i ∈ s, w i = 0 → s.weightedVSub p w = (0 : V) → ∀ i ∈ s, w i = 0 :=
Iff.rfl
/-- A family with at most one point is affinely independent. -/
theorem affineIndependent_of_subsingleton [Subsingleton ι] (p : ι → P) : AffineIndependent k p :=
fun _ _ h _ i hi => Fintype.eq_of_subsingleton_of_sum_eq h i hi
/-- A family indexed by a `Fintype` is affinely independent if and
only if no nontrivial weighted subtractions over `Finset.univ` (where
the sum of the weights is 0) are 0. -/
theorem affineIndependent_iff_of_fintype [Fintype ι] (p : ι → P) :
AffineIndependent k p ↔
∀ w : ι → k, ∑ i, w i = 0 → Finset.univ.weightedVSub p w = (0 : V) → ∀ i, w i = 0 := by
constructor
· exact fun h w hw hs i => h Finset.univ w hw hs i (Finset.mem_univ _)
· intro h s w hw hs i hi
rw [Finset.weightedVSub_indicator_subset _ _ (Finset.subset_univ s)] at hs
rw [← Finset.sum_indicator_subset _ (Finset.subset_univ s)] at hw
replace h := h ((↑s : Set ι).indicator w) hw hs i
simpa [hi] using h
@[simp] lemma affineIndependent_vadd {p : ι → P} {v : V} :
AffineIndependent k (v +ᵥ p) ↔ AffineIndependent k p := by
simp +contextual [AffineIndependent, weightedVSub_vadd]
protected alias ⟨AffineIndependent.of_vadd, AffineIndependent.vadd⟩ := affineIndependent_vadd
@[simp] lemma affineIndependent_smul {G : Type*} [Group G] [DistribMulAction G V]
[SMulCommClass G k V] {p : ι → V} {a : G} :
AffineIndependent k (a • p) ↔ AffineIndependent k p := by
simp +contextual [AffineIndependent, weightedVSub_smul,
← smul_comm (α := V) a, ← smul_sum, smul_eq_zero_iff_eq]
protected alias ⟨AffineIndependent.of_smul, AffineIndependent.smul⟩ := affineIndependent_smul
/-- A family is affinely independent if and only if the differences
from a base point in that family are linearly independent. -/
theorem affineIndependent_iff_linearIndependent_vsub (p : ι → P) (i1 : ι) :
AffineIndependent k p ↔ LinearIndependent k fun i : { x // x ≠ i1 } => (p i -ᵥ p i1 : V) := by
classical
constructor
· intro h
rw [linearIndependent_iff']
intro s g hg i hi
set f : ι → k := fun x => if hx : x = i1 then -∑ y ∈ s, g y else g ⟨x, hx⟩ with hfdef
let s2 : Finset ι := insert i1 (s.map (Embedding.subtype _))
have hfg : ∀ x : { x // x ≠ i1 }, g x = f x := by
intro x
rw [hfdef]
dsimp only
rw [dif_neg x.property, Subtype.coe_eta]
rw [hfg]
have hf : ∑ ι ∈ s2, f ι = 0 := by
rw [Finset.sum_insert
(Finset.not_mem_map_subtype_of_not_property s (Classical.not_not.2 rfl)),
Finset.sum_subtype_map_embedding fun x _ => (hfg x).symm]
rw [hfdef]
dsimp only
rw [dif_pos rfl]
exact neg_add_cancel _
have hs2 : s2.weightedVSub p f = (0 : V) := by
set f2 : ι → V := fun x => f x • (p x -ᵥ p i1) with hf2def
set g2 : { x // x ≠ i1 } → V := fun x => g x • (p x -ᵥ p i1)
have hf2g2 : ∀ x : { x // x ≠ i1 }, f2 x = g2 x := by
simp only [g2, hf2def]
refine fun x => ?_
rw [hfg]
rw [Finset.weightedVSub_eq_weightedVSubOfPoint_of_sum_eq_zero s2 f p hf (p i1),
Finset.weightedVSubOfPoint_insert, Finset.weightedVSubOfPoint_apply,
Finset.sum_subtype_map_embedding fun x _ => hf2g2 x]
exact hg
exact h s2 f hf hs2 i (Finset.mem_insert_of_mem (Finset.mem_map.2 ⟨i, hi, rfl⟩))
· intro h
rw [linearIndependent_iff'] at h
intro s w hw hs i hi
rw [Finset.weightedVSub_eq_weightedVSubOfPoint_of_sum_eq_zero s w p hw (p i1), ←
s.weightedVSubOfPoint_erase w p i1, Finset.weightedVSubOfPoint_apply] at hs
let f : ι → V := fun i => w i • (p i -ᵥ p i1)
have hs2 : (∑ i ∈ (s.erase i1).subtype fun i => i ≠ i1, f i) = 0 := by
rw [← hs]
convert Finset.sum_subtype_of_mem f fun x => Finset.ne_of_mem_erase
have h2 := h ((s.erase i1).subtype fun i => i ≠ i1) (fun x => w x) hs2
simp_rw [Finset.mem_subtype] at h2
have h2b : ∀ i ∈ s, i ≠ i1 → w i = 0 := fun i his hi =>
h2 ⟨i, hi⟩ (Finset.mem_erase_of_ne_of_mem hi his)
exact Finset.eq_zero_of_sum_eq_zero hw h2b i hi
/-- A set is affinely independent if and only if the differences from
a base point in that set are linearly independent. -/
theorem affineIndependent_set_iff_linearIndependent_vsub {s : Set P} {p₁ : P} (hp₁ : p₁ ∈ s) :
AffineIndependent k (fun p => p : s → P) ↔
LinearIndependent k (fun v => v : (fun p => (p -ᵥ p₁ : V)) '' (s \ {p₁}) → V) := by
rw [affineIndependent_iff_linearIndependent_vsub k (fun p => p : s → P) ⟨p₁, hp₁⟩]
constructor
· intro h
have hv : ∀ v : (fun p => (p -ᵥ p₁ : V)) '' (s \ {p₁}), (v : V) +ᵥ p₁ ∈ s \ {p₁} := fun v =>
(vsub_left_injective p₁).mem_set_image.1 ((vadd_vsub (v : V) p₁).symm ▸ v.property)
let f : (fun p : P => (p -ᵥ p₁ : V)) '' (s \ {p₁}) → { x : s // x ≠ ⟨p₁, hp₁⟩ } := fun x =>
⟨⟨(x : V) +ᵥ p₁, Set.mem_of_mem_diff (hv x)⟩, fun hx =>
Set.not_mem_of_mem_diff (hv x) (Subtype.ext_iff.1 hx)⟩
convert h.comp f fun x1 x2 hx =>
Subtype.ext (vadd_right_cancel p₁ (Subtype.ext_iff.1 (Subtype.ext_iff.1 hx)))
ext v
exact (vadd_vsub (v : V) p₁).symm
· intro h
let f : { x : s // x ≠ ⟨p₁, hp₁⟩ } → (fun p : P => (p -ᵥ p₁ : V)) '' (s \ {p₁}) := fun x =>
⟨((x : s) : P) -ᵥ p₁, ⟨x, ⟨⟨(x : s).property, fun hx => x.property (Subtype.ext hx)⟩, rfl⟩⟩⟩
convert h.comp f fun x1 x2 hx =>
Subtype.ext (Subtype.ext (vsub_left_cancel (Subtype.ext_iff.1 hx)))
/-- A set of nonzero vectors is linearly independent if and only if,
given a point `p₁`, the vectors added to `p₁` and `p₁` itself are
affinely independent. -/
theorem linearIndependent_set_iff_affineIndependent_vadd_union_singleton {s : Set V}
(hs : ∀ v ∈ s, v ≠ (0 : V)) (p₁ : P) : LinearIndependent k (fun v => v : s → V) ↔
AffineIndependent k (fun p => p : ({p₁} ∪ (fun v => v +ᵥ p₁) '' s : Set P) → P) := by
rw [affineIndependent_set_iff_linearIndependent_vsub k
(Set.mem_union_left _ (Set.mem_singleton p₁))]
have h : (fun p => (p -ᵥ p₁ : V)) '' (({p₁} ∪ (fun v => v +ᵥ p₁) '' s) \ {p₁}) = s := by
simp_rw [Set.union_diff_left, Set.image_diff (vsub_left_injective p₁), Set.image_image,
Set.image_singleton, vsub_self, vadd_vsub, Set.image_id']
exact Set.diff_singleton_eq_self fun h => hs 0 h rfl
rw [h]
/-- A family is affinely independent if and only if any affine
combinations (with sum of weights 1) that evaluate to the same point
have equal `Set.indicator`. -/
theorem affineIndependent_iff_indicator_eq_of_affineCombination_eq (p : ι → P) :
AffineIndependent k p ↔
∀ (s1 s2 : Finset ι) (w1 w2 : ι → k),
∑ i ∈ s1, w1 i = 1 →
∑ i ∈ s2, w2 i = 1 →
s1.affineCombination k p w1 = s2.affineCombination k p w2 →
Set.indicator (↑s1) w1 = Set.indicator (↑s2) w2 := by
classical
constructor
· intro ha s1 s2 w1 w2 hw1 hw2 heq
ext i
by_cases hi : i ∈ s1 ∪ s2
· rw [← sub_eq_zero]
rw [← Finset.sum_indicator_subset w1 (s1.subset_union_left (s₂ := s2))] at hw1
rw [← Finset.sum_indicator_subset w2 (s1.subset_union_right)] at hw2
have hws : (∑ i ∈ s1 ∪ s2, (Set.indicator (↑s1) w1 - Set.indicator (↑s2) w2) i) = 0 := by
simp [hw1, hw2]
rw [Finset.affineCombination_indicator_subset w1 p (s1.subset_union_left (s₂ := s2)),
Finset.affineCombination_indicator_subset w2 p s1.subset_union_right,
← @vsub_eq_zero_iff_eq V, Finset.affineCombination_vsub] at heq
exact ha (s1 ∪ s2) (Set.indicator (↑s1) w1 - Set.indicator (↑s2) w2) hws heq i hi
· rw [← Finset.mem_coe, Finset.coe_union] at hi
have h₁ : Set.indicator (↑s1) w1 i = 0 := by
simp only [Set.indicator, Finset.mem_coe, ite_eq_right_iff]
intro h
by_contra
exact (mt (@Set.mem_union_left _ i ↑s1 ↑s2) hi) h
have h₂ : Set.indicator (↑s2) w2 i = 0 := by
simp only [Set.indicator, Finset.mem_coe, ite_eq_right_iff]
intro h
by_contra
exact (mt (@Set.mem_union_right _ i ↑s2 ↑s1) hi) h
simp [h₁, h₂]
· intro ha s w hw hs i0 hi0
let w1 : ι → k := Function.update (Function.const ι 0) i0 1
have hw1 : ∑ i ∈ s, w1 i = 1 := by
rw [Finset.sum_update_of_mem hi0]
simp only [Finset.sum_const_zero, add_zero, const_apply]
have hw1s : s.affineCombination k p w1 = p i0 :=
s.affineCombination_of_eq_one_of_eq_zero w1 p hi0 (Function.update_self ..)
fun _ _ hne => Function.update_of_ne hne ..
let w2 := w + w1
have hw2 : ∑ i ∈ s, w2 i = 1 := by
simp_all only [w2, Pi.add_apply, Finset.sum_add_distrib, zero_add]
have hw2s : s.affineCombination k p w2 = p i0 := by
simp_all only [w2, ← Finset.weightedVSub_vadd_affineCombination, zero_vadd]
replace ha := ha s s w2 w1 hw2 hw1 (hw1s.symm ▸ hw2s)
have hws : w2 i0 - w1 i0 = 0 := by
rw [← Finset.mem_coe] at hi0
rw [← Set.indicator_of_mem hi0 w2, ← Set.indicator_of_mem hi0 w1, ha, sub_self]
simpa [w2] using hws
/-- A finite family is affinely independent if and only if any affine
combinations (with sum of weights 1) that evaluate to the same point are equal. -/
theorem affineIndependent_iff_eq_of_fintype_affineCombination_eq [Fintype ι] (p : ι → P) :
AffineIndependent k p ↔ ∀ w1 w2 : ι → k, ∑ i, w1 i = 1 → ∑ i, w2 i = 1 →
Finset.univ.affineCombination k p w1 = Finset.univ.affineCombination k p w2 → w1 = w2 := by
rw [affineIndependent_iff_indicator_eq_of_affineCombination_eq]
constructor
· intro h w1 w2 hw1 hw2 hweq
simpa only [Set.indicator_univ, Finset.coe_univ] using h _ _ w1 w2 hw1 hw2 hweq
· intro h s1 s2 w1 w2 hw1 hw2 hweq
have hw1' : (∑ i, (s1 : Set ι).indicator w1 i) = 1 := by
rwa [Finset.sum_indicator_subset _ (Finset.subset_univ s1)]
have hw2' : (∑ i, (s2 : Set ι).indicator w2 i) = 1 := by
rwa [Finset.sum_indicator_subset _ (Finset.subset_univ s2)]
rw [Finset.affineCombination_indicator_subset w1 p (Finset.subset_univ s1),
Finset.affineCombination_indicator_subset w2 p (Finset.subset_univ s2)] at hweq
exact h _ _ hw1' hw2' hweq
variable {k}
/-- If we single out one member of an affine-independent family of points and affinely transport
all others along the line joining them to this member, the resulting new family of points is affine-
independent.
This is the affine version of `LinearIndependent.units_smul`. -/
theorem AffineIndependent.units_lineMap {p : ι → P} (hp : AffineIndependent k p) (j : ι)
(w : ι → Units k) : AffineIndependent k fun i => AffineMap.lineMap (p j) (p i) (w i : k) := by
rw [affineIndependent_iff_linearIndependent_vsub k _ j] at hp ⊢
simp only [AffineMap.lineMap_vsub_left, AffineMap.coe_const, AffineMap.lineMap_same, const_apply]
exact hp.units_smul fun i => w i
theorem AffineIndependent.indicator_eq_of_affineCombination_eq {p : ι → P}
(ha : AffineIndependent k p) (s₁ s₂ : Finset ι) (w₁ w₂ : ι → k) (hw₁ : ∑ i ∈ s₁, w₁ i = 1)
(hw₂ : ∑ i ∈ s₂, w₂ i = 1) (h : s₁.affineCombination k p w₁ = s₂.affineCombination k p w₂) :
Set.indicator (↑s₁) w₁ = Set.indicator (↑s₂) w₂ :=
(affineIndependent_iff_indicator_eq_of_affineCombination_eq k p).1 ha s₁ s₂ w₁ w₂ hw₁ hw₂ h
/-- An affinely independent family is injective, if the underlying
ring is nontrivial. -/
protected theorem AffineIndependent.injective [Nontrivial k] {p : ι → P}
(ha : AffineIndependent k p) : Function.Injective p := by
intro i j hij
rw [affineIndependent_iff_linearIndependent_vsub _ _ j] at ha
by_contra hij'
refine ha.ne_zero ⟨i, hij'⟩ (vsub_eq_zero_iff_eq.mpr ?_)
simp_all only [ne_eq]
/-- If a family is affinely independent, so is any subfamily given by
composition of an embedding into index type with the original
family. -/
theorem AffineIndependent.comp_embedding {ι2 : Type*} (f : ι2 ↪ ι) {p : ι → P}
(ha : AffineIndependent k p) : AffineIndependent k (p ∘ f) := by
classical
intro fs w hw hs i0 hi0
let fs' := fs.map f
let w' i := if h : ∃ i2, f i2 = i then w h.choose else 0
have hw' : ∀ i2 : ι2, w' (f i2) = w i2 := by
intro i2
have h : ∃ i : ι2, f i = f i2 := ⟨i2, rfl⟩
have hs : h.choose = i2 := f.injective h.choose_spec
simp_rw [w', dif_pos h, hs]
have hw's : ∑ i ∈ fs', w' i = 0 := by
rw [← hw, Finset.sum_map]
simp [hw']
have hs' : fs'.weightedVSub p w' = (0 : V) := by
rw [← hs, Finset.weightedVSub_map]
congr with i
simp_all only [comp_apply, EmbeddingLike.apply_eq_iff_eq, exists_eq, dite_true]
rw [← ha fs' w' hw's hs' (f i0) ((Finset.mem_map' _).2 hi0), hw']
/-- If a family is affinely independent, so is any subfamily indexed
by a subtype of the index type. -/
protected theorem AffineIndependent.subtype {p : ι → P} (ha : AffineIndependent k p) (s : Set ι) :
AffineIndependent k fun i : s => p i :=
ha.comp_embedding (Embedding.subtype _)
/-- If an indexed family of points is affinely independent, so is the
corresponding set of points. -/
protected theorem AffineIndependent.range {p : ι → P} (ha : AffineIndependent k p) :
AffineIndependent k (fun x => x : Set.range p → P) := by
let f : Set.range p → ι := fun x => x.property.choose
have hf : ∀ x, p (f x) = x := fun x => x.property.choose_spec
let fe : Set.range p ↪ ι := ⟨f, fun x₁ x₂ he => Subtype.ext (hf x₁ ▸ hf x₂ ▸ he ▸ rfl)⟩
convert ha.comp_embedding fe
ext
simp [fe, hf]
theorem affineIndependent_equiv {ι' : Type*} (e : ι ≃ ι') {p : ι' → P} :
AffineIndependent k (p ∘ e) ↔ AffineIndependent k p := by
refine ⟨?_, AffineIndependent.comp_embedding e.toEmbedding⟩
intro h
have : p = p ∘ e ∘ e.symm.toEmbedding := by
ext
simp
rw [this]
exact h.comp_embedding e.symm.toEmbedding
/-- If a set of points is affinely independent, so is any subset. -/
protected theorem AffineIndependent.mono {s t : Set P}
(ha : AffineIndependent k (fun x => x : t → P)) (hs : s ⊆ t) :
AffineIndependent k (fun x => x : s → P) :=
ha.comp_embedding (s.embeddingOfSubset t hs)
/-- If the range of an injective indexed family of points is affinely
independent, so is that family. -/
theorem AffineIndependent.of_set_of_injective {p : ι → P}
(ha : AffineIndependent k (fun x => x : Set.range p → P)) (hi : Function.Injective p) :
AffineIndependent k p :=
ha.comp_embedding
(⟨fun i => ⟨p i, Set.mem_range_self _⟩, fun _ _ h => hi (Subtype.mk_eq_mk.1 h)⟩ :
ι ↪ Set.range p)
section Composition
variable {V₂ P₂ : Type*} [AddCommGroup V₂] [Module k V₂] [AffineSpace V₂ P₂]
/-- If the image of a family of points in affine space under an affine transformation is affine-
independent, then the original family of points is also affine-independent. -/
theorem AffineIndependent.of_comp {p : ι → P} (f : P →ᵃ[k] P₂) (hai : AffineIndependent k (f ∘ p)) :
AffineIndependent k p := by
rcases isEmpty_or_nonempty ι with h | h
· haveI := h
apply affineIndependent_of_subsingleton
obtain ⟨i⟩ := h
rw [affineIndependent_iff_linearIndependent_vsub k p i]
simp_rw [affineIndependent_iff_linearIndependent_vsub k (f ∘ p) i, Function.comp_apply, ←
f.linearMap_vsub] at hai
exact LinearIndependent.of_comp f.linear hai
/-- The image of a family of points in affine space, under an injective affine transformation, is
affine-independent. -/
theorem AffineIndependent.map' {p : ι → P} (hai : AffineIndependent k p) (f : P →ᵃ[k] P₂)
(hf : Function.Injective f) : AffineIndependent k (f ∘ p) := by
rcases isEmpty_or_nonempty ι with h | h
· haveI := h
apply affineIndependent_of_subsingleton
obtain ⟨i⟩ := h
rw [affineIndependent_iff_linearIndependent_vsub k p i] at hai
simp_rw [affineIndependent_iff_linearIndependent_vsub k (f ∘ p) i, Function.comp_apply, ←
f.linearMap_vsub]
have hf' : LinearMap.ker f.linear = ⊥ := by rwa [LinearMap.ker_eq_bot, f.linear_injective_iff]
exact LinearIndependent.map' hai f.linear hf'
/-- Injective affine maps preserve affine independence. -/
theorem AffineMap.affineIndependent_iff {p : ι → P} (f : P →ᵃ[k] P₂) (hf : Function.Injective f) :
AffineIndependent k (f ∘ p) ↔ AffineIndependent k p :=
⟨AffineIndependent.of_comp f, fun hai => AffineIndependent.map' hai f hf⟩
/-- Affine equivalences preserve affine independence of families of points. -/
theorem AffineEquiv.affineIndependent_iff {p : ι → P} (e : P ≃ᵃ[k] P₂) :
AffineIndependent k (e ∘ p) ↔ AffineIndependent k p :=
e.toAffineMap.affineIndependent_iff e.toEquiv.injective
/-- Affine equivalences preserve affine independence of subsets. -/
theorem AffineEquiv.affineIndependent_set_of_eq_iff {s : Set P} (e : P ≃ᵃ[k] P₂) :
AffineIndependent k ((↑) : e '' s → P₂) ↔ AffineIndependent k ((↑) : s → P) := by
have : e ∘ ((↑) : s → P) = ((↑) : e '' s → P₂) ∘ (e : P ≃ P₂).image s := rfl
-- This used to be `rw`, but we need `erw` after https://github.com/leanprover/lean4/pull/2644
erw [← e.affineIndependent_iff, this, affineIndependent_equiv]
end Composition
/-- If a family is affinely independent, and the spans of points
indexed by two subsets of the index type have a point in common, those
subsets of the index type have an element in common, if the underlying
ring is nontrivial. -/
theorem AffineIndependent.exists_mem_inter_of_exists_mem_inter_affineSpan [Nontrivial k] {p : ι → P}
(ha : AffineIndependent k p) {s1 s2 : Set ι} {p0 : P} (hp0s1 : p0 ∈ affineSpan k (p '' s1))
(hp0s2 : p0 ∈ affineSpan k (p '' s2)) : ∃ i : ι, i ∈ s1 ∩ s2 := by
rw [Set.image_eq_range] at hp0s1 hp0s2
rw [mem_affineSpan_iff_eq_affineCombination, ←
Finset.eq_affineCombination_subset_iff_eq_affineCombination_subtype] at hp0s1 hp0s2
rcases hp0s1 with ⟨fs1, hfs1, w1, hw1, hp0s1⟩
rcases hp0s2 with ⟨fs2, hfs2, w2, hw2, hp0s2⟩
rw [affineIndependent_iff_indicator_eq_of_affineCombination_eq] at ha
replace ha := ha fs1 fs2 w1 w2 hw1 hw2 (hp0s1 ▸ hp0s2)
have hnz : ∑ i ∈ fs1, w1 i ≠ 0 := hw1.symm ▸ one_ne_zero
rcases Finset.exists_ne_zero_of_sum_ne_zero hnz with ⟨i, hifs1, hinz⟩
simp_rw [← Set.indicator_of_mem (Finset.mem_coe.2 hifs1) w1, ha] at hinz
use i, hfs1 hifs1
exact hfs2 (Set.mem_of_indicator_ne_zero hinz)
/-- If a family is affinely independent, the spans of points indexed
by disjoint subsets of the index type are disjoint, if the underlying
ring is nontrivial. -/
theorem AffineIndependent.affineSpan_disjoint_of_disjoint [Nontrivial k] {p : ι → P}
(ha : AffineIndependent k p) {s1 s2 : Set ι} (hd : Disjoint s1 s2) :
Disjoint (affineSpan k (p '' s1) : Set P) (affineSpan k (p '' s2)) := by
refine Set.disjoint_left.2 fun p0 hp0s1 hp0s2 => ?_
obtain ⟨i, hi⟩ := ha.exists_mem_inter_of_exists_mem_inter_affineSpan hp0s1 hp0s2
exact Set.disjoint_iff.1 hd hi
/-- If a family is affinely independent, a point in the family is in
the span of some of the points given by a subset of the index type if
and only if that point's index is in the subset, if the underlying
ring is nontrivial. -/
@[simp]
protected theorem AffineIndependent.mem_affineSpan_iff [Nontrivial k] {p : ι → P}
(ha : AffineIndependent k p) (i : ι) (s : Set ι) : p i ∈ affineSpan k (p '' s) ↔ i ∈ s := by
constructor
· intro hs
have h :=
AffineIndependent.exists_mem_inter_of_exists_mem_inter_affineSpan ha hs
(mem_affineSpan k (Set.mem_image_of_mem _ (Set.mem_singleton _)))
rwa [← Set.nonempty_def, Set.inter_singleton_nonempty] at h
· exact fun h => mem_affineSpan k (Set.mem_image_of_mem p h)
/-- If a family is affinely independent, a point in the family is not
in the affine span of the other points, if the underlying ring is
nontrivial. -/
theorem AffineIndependent.not_mem_affineSpan_diff [Nontrivial k] {p : ι → P}
(ha : AffineIndependent k p) (i : ι) (s : Set ι) : p i ∉ affineSpan k (p '' (s \ {i})) := by
simp [ha]
theorem exists_nontrivial_relation_sum_zero_of_not_affine_ind {t : Finset V}
(h : ¬AffineIndependent k ((↑) : t → V)) :
∃ f : V → k, ∑ e ∈ t, f e • e = 0 ∧ ∑ e ∈ t, f e = 0 ∧ ∃ x ∈ t, f x ≠ 0 := by
classical
rw [affineIndependent_iff_of_fintype] at h
simp only [exists_prop, not_forall] at h
obtain ⟨w, hw, hwt, i, hi⟩ := h
simp only [Finset.weightedVSub_eq_weightedVSubOfPoint_of_sum_eq_zero _ w ((↑) : t → V) hw 0,
vsub_eq_sub, Finset.weightedVSubOfPoint_apply, sub_zero] at hwt
let f : ∀ x : V, x ∈ t → k := fun x hx => w ⟨x, hx⟩
refine ⟨fun x => if hx : x ∈ t then f x hx else (0 : k), ?_, ?_, by use i; simp [f, hi]⟩
on_goal 1 =>
suffices (∑ e ∈ t, dite (e ∈ t) (fun hx => f e hx • e) fun _ => 0) = 0 by
convert this
rename V => x
by_cases hx : x ∈ t <;> simp [hx]
all_goals
simp only [f, Finset.sum_dite_of_true fun _ h => h, Finset.mk_coe, hwt, hw]
variable {s : Finset ι} {w w₁ w₂ : ι → k} {p : ι → V}
/-- Viewing a module as an affine space modelled on itself, we can characterise affine independence
in terms of linear combinations. -/
theorem affineIndependent_iff {ι} {p : ι → V} :
AffineIndependent k p ↔
∀ (s : Finset ι) (w : ι → k), s.sum w = 0 → ∑ e ∈ s, w e • p e = 0 → ∀ e ∈ s, w e = 0 :=
forall₃_congr fun s w hw => by simp [s.weightedVSub_eq_linear_combination hw]
lemma AffineIndependent.eq_zero_of_sum_eq_zero (hp : AffineIndependent k p)
(hw₀ : ∑ i ∈ s, w i = 0) (hw₁ : ∑ i ∈ s, w i • p i = 0) : ∀ i ∈ s, w i = 0 :=
affineIndependent_iff.1 hp _ _ hw₀ hw₁
lemma AffineIndependent.eq_of_sum_eq_sum (hp : AffineIndependent k p)
(hw : ∑ i ∈ s, w₁ i = ∑ i ∈ s, w₂ i) (hwp : ∑ i ∈ s, w₁ i • p i = ∑ i ∈ s, w₂ i • p i) :
∀ i ∈ s, w₁ i = w₂ i := by
refine fun i hi ↦ sub_eq_zero.1 (hp.eq_zero_of_sum_eq_zero (w := w₁ - w₂) ?_ ?_ _ hi) <;>
simpa [sub_mul, sub_smul, sub_eq_zero]
lemma AffineIndependent.eq_zero_of_sum_eq_zero_subtype {s : Finset V}
(hp : AffineIndependent k ((↑) : s → V)) {w : V → k} (hw₀ : ∑ x ∈ s, w x = 0)
(hw₁ : ∑ x ∈ s, w x • x = 0) : ∀ x ∈ s, w x = 0 := by
rw [← sum_attach] at hw₀ hw₁
exact fun x hx ↦ hp.eq_zero_of_sum_eq_zero hw₀ hw₁ ⟨x, hx⟩ (mem_univ _)
lemma AffineIndependent.eq_of_sum_eq_sum_subtype {s : Finset V}
(hp : AffineIndependent k ((↑) : s → V)) {w₁ w₂ : V → k} (hw : ∑ i ∈ s, w₁ i = ∑ i ∈ s, w₂ i)
(hwp : ∑ i ∈ s, w₁ i • i = ∑ i ∈ s, w₂ i • i) : ∀ i ∈ s, w₁ i = w₂ i := by
refine fun i hi => sub_eq_zero.1 (hp.eq_zero_of_sum_eq_zero_subtype (w := w₁ - w₂) ?_ ?_ _ hi) <;>
simpa [sub_mul, sub_smul, sub_eq_zero]
/-- Given an affinely independent family of points, a weighted subtraction lies in the
`vectorSpan` of two points given as affine combinations if and only if it is a weighted
subtraction with weights a multiple of the difference between the weights of the two points. -/
theorem weightedVSub_mem_vectorSpan_pair {p : ι → P} (h : AffineIndependent k p) {w w₁ w₂ : ι → k}
{s : Finset ι} (hw : ∑ i ∈ s, w i = 0) (hw₁ : ∑ i ∈ s, w₁ i = 1)
(hw₂ : ∑ i ∈ s, w₂ i = 1) :
s.weightedVSub p w ∈
vectorSpan k ({s.affineCombination k p w₁, s.affineCombination k p w₂} : Set P) ↔
∃ r : k, ∀ i ∈ s, w i = r * (w₁ i - w₂ i) := by
rw [mem_vectorSpan_pair]
refine ⟨fun h => ?_, fun h => ?_⟩
· rcases h with ⟨r, hr⟩
refine ⟨r, fun i hi => ?_⟩
rw [s.affineCombination_vsub, ← s.weightedVSub_const_smul, ← sub_eq_zero, ← map_sub] at hr
have hw' : (∑ j ∈ s, (r • (w₁ - w₂) - w) j) = 0 := by
simp_rw [Pi.sub_apply, Pi.smul_apply, Pi.sub_apply, smul_sub, Finset.sum_sub_distrib, ←
Finset.smul_sum, hw, hw₁, hw₂, sub_self]
have hr' := h s _ hw' hr i hi
rw [eq_comm, ← sub_eq_zero, ← smul_eq_mul]
exact hr'
· rcases h with ⟨r, hr⟩
refine ⟨r, ?_⟩
let w' i := r * (w₁ i - w₂ i)
change ∀ i ∈ s, w i = w' i at hr
rw [s.weightedVSub_congr hr fun _ _ => rfl, s.affineCombination_vsub, ←
s.weightedVSub_const_smul]
congr
/-- Given an affinely independent family of points, an affine combination lies in the
span of two points given as affine combinations if and only if it is an affine combination
with weights those of one point plus a multiple of the difference between the weights of the
two points. -/
theorem affineCombination_mem_affineSpan_pair {p : ι → P} (h : AffineIndependent k p)
{w w₁ w₂ : ι → k} {s : Finset ι} (_ : ∑ i ∈ s, w i = 1) (hw₁ : ∑ i ∈ s, w₁ i = 1)
(hw₂ : ∑ i ∈ s, w₂ i = 1) :
s.affineCombination k p w ∈ line[k, s.affineCombination k p w₁, s.affineCombination k p w₂] ↔
∃ r : k, ∀ i ∈ s, w i = r * (w₂ i - w₁ i) + w₁ i := by
rw [← vsub_vadd (s.affineCombination k p w) (s.affineCombination k p w₁),
AffineSubspace.vadd_mem_iff_mem_direction _ (left_mem_affineSpan_pair _ _ _),
direction_affineSpan, s.affineCombination_vsub, Set.pair_comm,
weightedVSub_mem_vectorSpan_pair h _ hw₂ hw₁]
· simp only [Pi.sub_apply, sub_eq_iff_eq_add]
· simp_all only [Pi.sub_apply, Finset.sum_sub_distrib, sub_self]
end AffineIndependent
section DivisionRing
variable {k : Type*} {V : Type*} {P : Type*} [DivisionRing k] [AddCommGroup V] [Module k V]
variable [AffineSpace V P] {ι : Type*}
/-- An affinely independent set of points can be extended to such a
set that spans the whole space. -/
theorem exists_subset_affineIndependent_affineSpan_eq_top {s : Set P}
(h : AffineIndependent k (fun p => p : s → P)) :
∃ t : Set P, s ⊆ t ∧ AffineIndependent k (fun p => p : t → P) ∧ affineSpan k t = ⊤ := by
rcases s.eq_empty_or_nonempty with (rfl | ⟨p₁, hp₁⟩)
· have p₁ : P := AddTorsor.nonempty.some
let hsv := Basis.ofVectorSpace k V
have hsvi := hsv.linearIndependent
have hsvt := hsv.span_eq
rw [Basis.coe_ofVectorSpace] at hsvi hsvt
have h0 : ∀ v : V, v ∈ Basis.ofVectorSpaceIndex k V → v ≠ 0 := by
intro v hv
simpa [hsv] using hsv.ne_zero ⟨v, hv⟩
rw [linearIndependent_set_iff_affineIndependent_vadd_union_singleton k h0 p₁] at hsvi
exact
⟨{p₁} ∪ (fun v => v +ᵥ p₁) '' _, Set.empty_subset _, hsvi,
affineSpan_singleton_union_vadd_eq_top_of_span_eq_top p₁ hsvt⟩
· rw [affineIndependent_set_iff_linearIndependent_vsub k hp₁] at h
let bsv := Basis.extend h
have hsvi := bsv.linearIndependent
have hsvt := bsv.span_eq
rw [Basis.coe_extend] at hsvi hsvt
rw [linearIndependent_subtype_iff] at hsvi h
have hsv := h.subset_extend (Set.subset_univ _)
have h0 : ∀ v : V, v ∈ h.extend (Set.subset_univ _) → v ≠ 0 := by
intro v hv
simpa [bsv] using bsv.ne_zero ⟨v, hv⟩
rw [← linearIndependent_subtype_iff,
linearIndependent_set_iff_affineIndependent_vadd_union_singleton k h0 p₁] at hsvi
refine ⟨{p₁} ∪ (fun v => v +ᵥ p₁) '' h.extend (Set.subset_univ _), ?_, ?_⟩
· refine Set.Subset.trans ?_ (Set.union_subset_union_right _ (Set.image_subset _ hsv))
simp [Set.image_image]
· use hsvi
exact affineSpan_singleton_union_vadd_eq_top_of_span_eq_top p₁ hsvt
variable (k V)
theorem exists_affineIndependent (s : Set P) :
∃ t ⊆ s, affineSpan k t = affineSpan k s ∧ AffineIndependent k ((↑) : t → P) := by
rcases s.eq_empty_or_nonempty with (rfl | ⟨p, hp⟩)
· exact ⟨∅, Set.empty_subset ∅, rfl, affineIndependent_of_subsingleton k _⟩
obtain ⟨b, hb₁, hb₂, hb₃⟩ := exists_linearIndependent k ((Equiv.vaddConst p).symm '' s)
have hb₀ : ∀ v : V, v ∈ b → v ≠ 0 := fun v hv => hb₃.ne_zero (⟨v, hv⟩ : b)
rw [linearIndependent_set_iff_affineIndependent_vadd_union_singleton k hb₀ p] at hb₃
refine ⟨{p} ∪ Equiv.vaddConst p '' b, ?_, ?_, hb₃⟩
· apply Set.union_subset (Set.singleton_subset_iff.mpr hp)
rwa [← (Equiv.vaddConst p).subset_symm_image b s]
· rw [Equiv.coe_vaddConst_symm, ← vectorSpan_eq_span_vsub_set_right k hp] at hb₂
apply AffineSubspace.ext_of_direction_eq
· have : Submodule.span k b = Submodule.span k (insert 0 b) := by simp
simp only [direction_affineSpan, ← hb₂, Equiv.coe_vaddConst, Set.singleton_union,
vectorSpan_eq_span_vsub_set_right k (Set.mem_insert p _), this]
congr
change (Equiv.vaddConst p).symm '' insert p (Equiv.vaddConst p '' b) = _
rw [Set.image_insert_eq, ← Set.image_comp]
simp
· use p
simp only [Equiv.coe_vaddConst, Set.singleton_union, Set.mem_inter_iff]
exact ⟨mem_affineSpan k (Set.mem_insert p _), mem_affineSpan k hp⟩
variable {V}
/-- Two different points are affinely independent. -/
theorem affineIndependent_of_ne {p₁ p₂ : P} (h : p₁ ≠ p₂) : AffineIndependent k ![p₁, p₂] := by
rw [affineIndependent_iff_linearIndependent_vsub k ![p₁, p₂] 0]
let i₁ : { x // x ≠ (0 : Fin 2) } := ⟨1, by norm_num⟩
have he' : ∀ i, i = i₁ := by
rintro ⟨i, hi⟩
ext
fin_cases i
· simp at hi
· simp [i₁]
haveI : Unique { x // x ≠ (0 : Fin 2) } := ⟨⟨i₁⟩, he'⟩
apply linearIndependent_unique
rw [he' default]
simpa using h.symm
variable {k}
/-- If all but one point of a family are affinely independent, and that point does not lie in
the affine span of that family, the family is affinely independent. -/
theorem AffineIndependent.affineIndependent_of_not_mem_span {p : ι → P} {i : ι}
(ha : AffineIndependent k fun x : { y // y ≠ i } => p x)
(hi : p i ∉ affineSpan k (p '' { x | x ≠ i })) : AffineIndependent k p := by
classical
intro s w hw hs
let s' : Finset { y // y ≠ i } := s.subtype (· ≠ i)
let p' : { y // y ≠ i } → P := fun x => p x
by_cases his : i ∈ s ∧ w i ≠ 0
· refine False.elim (hi ?_)
let wm : ι → k := -(w i)⁻¹ • w
have hms : s.weightedVSub p wm = (0 : V) := by simp [wm, hs]
have hwm : ∑ i ∈ s, wm i = 0 := by simp [wm, ← Finset.mul_sum, hw]
have hwmi : wm i = -1 := by simp [wm, his.2]
let w' : { y // y ≠ i } → k := fun x => wm x
have hw' : ∑ x ∈ s', w' x = 1 := by
simp_rw [w', s', Finset.sum_subtype_eq_sum_filter]
rw [← s.sum_filter_add_sum_filter_not (· ≠ i)] at hwm
simpa only [not_not, Finset.filter_eq' _ i, if_pos his.1, sum_singleton, hwmi,
add_neg_eq_zero] using hwm
rw [← s.affineCombination_eq_of_weightedVSub_eq_zero_of_eq_neg_one hms his.1 hwmi, ←
(Subtype.range_coe : _ = { x | x ≠ i }), ← Set.range_comp, ←
s.affineCombination_subtype_eq_filter]
exact affineCombination_mem_affineSpan hw' p'
· rw [not_and_or, Classical.not_not] at his
let w' : { y // y ≠ i } → k := fun x => w x
have hw' : ∑ x ∈ s', w' x = 0 := by
simp_rw [w', s', Finset.sum_subtype_eq_sum_filter]
rw [Finset.sum_filter_of_ne, hw]
rintro x hxs hwx rfl
exact hwx (his.neg_resolve_left hxs)
have hs' : s'.weightedVSub p' w' = (0 : V) := by
simp_rw [w', s', p', Finset.weightedVSub_subtype_eq_filter]
rw [Finset.weightedVSub_filter_of_ne, hs]
rintro x hxs hwx rfl
exact hwx (his.neg_resolve_left hxs)
intro j hj
by_cases hji : j = i
· rw [hji] at hj
exact hji.symm ▸ his.neg_resolve_left hj
· exact ha s' w' hw' hs' ⟨j, hji⟩ (Finset.mem_subtype.2 hj)
/-- If distinct points `p₁` and `p₂` lie in `s` but `p₃` does not, the three points are affinely
independent. -/
theorem affineIndependent_of_ne_of_mem_of_mem_of_not_mem {s : AffineSubspace k P} {p₁ p₂ p₃ : P}
(hp₁p₂ : p₁ ≠ p₂) (hp₁ : p₁ ∈ s) (hp₂ : p₂ ∈ s) (hp₃ : p₃ ∉ s) :
AffineIndependent k ![p₁, p₂, p₃] := by
have ha : AffineIndependent k fun x : { x : Fin 3 // x ≠ 2 } => ![p₁, p₂, p₃] x := by
rw [← affineIndependent_equiv (finSuccAboveEquiv (2 : Fin 3))]
convert affineIndependent_of_ne k hp₁p₂
ext x
fin_cases x <;> rfl
refine ha.affineIndependent_of_not_mem_span ?_
intro h
refine hp₃ ((AffineSubspace.le_def' _ s).1 ?_ p₃ h)
simp_rw [affineSpan_le, Set.image_subset_iff, Set.subset_def, Set.mem_preimage]
intro x
fin_cases x <;> simp +decide [hp₁, hp₂]
/-- If distinct points `p₁` and `p₃` lie in `s` but `p₂` does not, the three points are affinely
independent. -/
theorem affineIndependent_of_ne_of_mem_of_not_mem_of_mem {s : AffineSubspace k P} {p₁ p₂ p₃ : P}
(hp₁p₃ : p₁ ≠ p₃) (hp₁ : p₁ ∈ s) (hp₂ : p₂ ∉ s) (hp₃ : p₃ ∈ s) :
AffineIndependent k ![p₁, p₂, p₃] := by
rw [← affineIndependent_equiv (Equiv.swap (1 : Fin 3) 2)]
convert affineIndependent_of_ne_of_mem_of_mem_of_not_mem hp₁p₃ hp₁ hp₃ hp₂ using 1
ext x
fin_cases x <;> rfl
/-- If distinct points `p₂` and `p₃` lie in `s` but `p₁` does not, the three points are affinely
independent. -/
theorem affineIndependent_of_ne_of_not_mem_of_mem_of_mem {s : AffineSubspace k P} {p₁ p₂ p₃ : P}
(hp₂p₃ : p₂ ≠ p₃) (hp₁ : p₁ ∉ s) (hp₂ : p₂ ∈ s) (hp₃ : p₃ ∈ s) :
AffineIndependent k ![p₁, p₂, p₃] := by
rw [← affineIndependent_equiv (Equiv.swap (0 : Fin 3) 2)]
convert affineIndependent_of_ne_of_mem_of_mem_of_not_mem hp₂p₃.symm hp₃ hp₂ hp₁ using 1
ext x
fin_cases x <;> rfl
end DivisionRing
section Ordered
variable {k : Type*} {V : Type*} {P : Type*} [Ring k] [LinearOrder k] [IsStrictOrderedRing k]
[AddCommGroup V]
variable [Module k V] [AffineSpace V P] {ι : Type*}
/-- Given an affinely independent family of points, suppose that an affine combination lies in
the span of two points given as affine combinations, and suppose that, for two indices, the
coefficients in the first point in the span are zero and those in the second point in the span
have the same sign. Then the coefficients in the combination lying in the span have the same
sign. -/
theorem sign_eq_of_affineCombination_mem_affineSpan_pair {p : ι → P} (h : AffineIndependent k p)
{w w₁ w₂ : ι → k} {s : Finset ι} (hw : ∑ i ∈ s, w i = 1) (hw₁ : ∑ i ∈ s, w₁ i = 1)
(hw₂ : ∑ i ∈ s, w₂ i = 1)
(hs :
s.affineCombination k p w ∈ line[k, s.affineCombination k p w₁, s.affineCombination k p w₂])
{i j : ι} (hi : i ∈ s) (hj : j ∈ s) (hi0 : w₁ i = 0) (hj0 : w₁ j = 0)
(hij : SignType.sign (w₂ i) = SignType.sign (w₂ j)) :
SignType.sign (w i) = SignType.sign (w j) := by
rw [affineCombination_mem_affineSpan_pair h hw hw₁ hw₂] at hs
rcases hs with ⟨r, hr⟩
rw [hr i hi, hr j hj, hi0, hj0, add_zero, add_zero, sub_zero, sub_zero, sign_mul, sign_mul, hij]
/-- Given an affinely independent family of points, suppose that an affine combination lies in
the span of one point of that family and a combination of another two points of that family given
by `lineMap` with coefficient between 0 and 1. Then the coefficients of those two points in the
combination lying in the span have the same sign. -/
theorem sign_eq_of_affineCombination_mem_affineSpan_single_lineMap {p : ι → P}
(h : AffineIndependent k p) {w : ι → k} {s : Finset ι} (hw : ∑ i ∈ s, w i = 1) {i₁ i₂ i₃ : ι}
(h₁ : i₁ ∈ s) (h₂ : i₂ ∈ s) (h₃ : i₃ ∈ s) (h₁₂ : i₁ ≠ i₂) (h₁₃ : i₁ ≠ i₃) (h₂₃ : i₂ ≠ i₃)
{c : k} (hc0 : 0 < c) (hc1 : c < 1)
(hs : s.affineCombination k p w ∈ line[k, p i₁, AffineMap.lineMap (p i₂) (p i₃) c]) :
SignType.sign (w i₂) = SignType.sign (w i₃) := by
classical
rw [← s.affineCombination_affineCombinationSingleWeights k p h₁, ←
s.affineCombination_affineCombinationLineMapWeights p h₂ h₃ c] at hs
refine
sign_eq_of_affineCombination_mem_affineSpan_pair h hw
(s.sum_affineCombinationSingleWeights k h₁)
| (s.sum_affineCombinationLineMapWeights h₂ h₃ c) hs h₂ h₃
(Finset.affineCombinationSingleWeights_apply_of_ne k h₁₂.symm)
(Finset.affineCombinationSingleWeights_apply_of_ne k h₁₃.symm) ?_
rw [Finset.affineCombinationLineMapWeights_apply_left h₂₃,
Finset.affineCombinationLineMapWeights_apply_right h₂₃]
simp_all only [sub_pos, sign_pos]
end Ordered
namespace Affine
| Mathlib/LinearAlgebra/AffineSpace/Independent.lean | 752 | 762 |
/-
Copyright (c) 2020 Jujian Zhang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jujian Zhang, Johan Commelin
-/
import Mathlib.RingTheory.GradedAlgebra.Homogeneous.Ideal
import Mathlib.Topology.Category.TopCat.Basic
import Mathlib.Topology.Sets.Opens
import Mathlib.Data.Set.Subsingleton
/-!
# Projective spectrum of a graded ring
The projective spectrum of a graded commutative ring is the subtype of all homogeneous ideals that
are prime and do not contain the irrelevant ideal.
It is naturally endowed with a topology: the Zariski topology.
## Notation
- `R` is a commutative semiring;
- `A` is a commutative ring and an `R`-algebra;
- `𝒜 : ℕ → Submodule R A` is the grading of `A`;
## Main definitions
* `ProjectiveSpectrum 𝒜`: The projective spectrum of a graded ring `A`, or equivalently, the set of
all homogeneous ideals of `A` that is both prime and relevant i.e. not containing irrelevant
ideal. Henceforth, we call elements of projective spectrum *relevant homogeneous prime ideals*.
* `ProjectiveSpectrum.zeroLocus 𝒜 s`: The zero locus of a subset `s` of `A`
is the subset of `ProjectiveSpectrum 𝒜` consisting of all relevant homogeneous prime ideals that
contain `s`.
* `ProjectiveSpectrum.vanishingIdeal t`: The vanishing ideal of a subset `t` of
`ProjectiveSpectrum 𝒜` is the intersection of points in `t` (viewed as relevant homogeneous prime
ideals).
* `ProjectiveSpectrum.Top`: the topological space of `ProjectiveSpectrum 𝒜` endowed with the
Zariski topology.
-/
noncomputable section
open DirectSum Pointwise SetLike TopCat TopologicalSpace CategoryTheory Opposite
variable {R A : Type*}
variable [CommSemiring R] [CommRing A] [Algebra R A]
variable (𝒜 : ℕ → Submodule R A) [GradedAlgebra 𝒜]
/-- The projective spectrum of a graded commutative ring is the subtype of all homogeneous ideals
that are prime and do not contain the irrelevant ideal. -/
@[ext]
structure ProjectiveSpectrum where
asHomogeneousIdeal : HomogeneousIdeal 𝒜
isPrime : asHomogeneousIdeal.toIdeal.IsPrime
not_irrelevant_le : ¬HomogeneousIdeal.irrelevant 𝒜 ≤ asHomogeneousIdeal
attribute [instance] ProjectiveSpectrum.isPrime
namespace ProjectiveSpectrum
instance (x : ProjectiveSpectrum 𝒜) : Ideal.IsPrime x.asHomogeneousIdeal.toIdeal := x.isPrime
/-- The zero locus of a set `s` of elements of a commutative ring `A` is the set of all relevant
homogeneous prime ideals of the ring that contain the set `s`.
An element `f` of `A` can be thought of as a dependent function on the projective spectrum of `𝒜`.
At a point `x` (a homogeneous prime ideal) the function (i.e., element) `f` takes values in the
quotient ring `A` modulo the prime ideal `x`. In this manner, `zeroLocus s` is exactly the subset
of `ProjectiveSpectrum 𝒜` where all "functions" in `s` vanish simultaneously. -/
def zeroLocus (s : Set A) : Set (ProjectiveSpectrum 𝒜) :=
{ x | s ⊆ x.asHomogeneousIdeal }
@[simp]
theorem mem_zeroLocus (x : ProjectiveSpectrum 𝒜) (s : Set A) :
x ∈ zeroLocus 𝒜 s ↔ s ⊆ x.asHomogeneousIdeal :=
Iff.rfl
@[simp]
theorem zeroLocus_span (s : Set A) : zeroLocus 𝒜 (Ideal.span s) = zeroLocus 𝒜 s := by
ext x
exact (Submodule.gi _ _).gc s x.asHomogeneousIdeal.toIdeal
variable {𝒜}
/-- The vanishing ideal of a set `t` of points of the projective spectrum of a commutative ring `R`
is the intersection of all the relevant homogeneous prime ideals in the set `t`.
An element `f` of `A` can be thought of as a dependent function on the projective spectrum of `𝒜`.
At a point `x` (a homogeneous prime ideal) the function (i.e., element) `f` takes values in the
quotient ring `A` modulo the prime ideal `x`. In this manner, `vanishingIdeal t` is exactly the
ideal of `A` consisting of all "functions" that vanish on all of `t`. -/
def vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) : HomogeneousIdeal 𝒜 :=
⨅ (x : ProjectiveSpectrum 𝒜) (_ : x ∈ t), x.asHomogeneousIdeal
theorem coe_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) :
(vanishingIdeal t : Set A) =
{ f | ∀ x : ProjectiveSpectrum 𝒜, x ∈ t → f ∈ x.asHomogeneousIdeal } := by
ext f
rw [vanishingIdeal, SetLike.mem_coe, ← HomogeneousIdeal.mem_iff, HomogeneousIdeal.toIdeal_iInf,
Submodule.mem_iInf]
refine forall_congr' fun x => ?_
rw [HomogeneousIdeal.toIdeal_iInf, Submodule.mem_iInf, HomogeneousIdeal.mem_iff]
theorem mem_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) (f : A) :
f ∈ vanishingIdeal t ↔ ∀ x : ProjectiveSpectrum 𝒜, x ∈ t → f ∈ x.asHomogeneousIdeal := by
rw [← SetLike.mem_coe, coe_vanishingIdeal, Set.mem_setOf_eq]
@[simp]
theorem vanishingIdeal_singleton (x : ProjectiveSpectrum 𝒜) :
vanishingIdeal ({x} : Set (ProjectiveSpectrum 𝒜)) = x.asHomogeneousIdeal := by
simp [vanishingIdeal]
theorem subset_zeroLocus_iff_le_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) (I : Ideal A) :
t ⊆ zeroLocus 𝒜 I ↔ I ≤ (vanishingIdeal t).toIdeal :=
⟨fun h _ k => (mem_vanishingIdeal _ _).mpr fun _ j => (mem_zeroLocus _ _ _).mpr (h j) k, fun h =>
fun x j =>
| (mem_zeroLocus _ _ _).mpr (le_trans h fun _ h => ((mem_vanishingIdeal _ _).mp h) x j)⟩
variable (𝒜)
| Mathlib/AlgebraicGeometry/ProjectiveSpectrum/Topology.lean | 115 | 117 |
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Kenny Lau, Johan Commelin, Mario Carneiro, Kevin Buzzard,
Amelia Livingston, Yury Kudryashov
-/
import Mathlib.Algebra.Group.Action.Faithful
import Mathlib.Algebra.Group.Nat.Defs
import Mathlib.Algebra.Group.Prod
import Mathlib.Algebra.Group.Submonoid.Basic
import Mathlib.Algebra.Group.Submonoid.MulAction
import Mathlib.Algebra.Group.TypeTags.Basic
/-!
# Operations on `Submonoid`s
In this file we define various operations on `Submonoid`s and `MonoidHom`s.
## Main definitions
### Conversion between multiplicative and additive definitions
* `Submonoid.toAddSubmonoid`, `Submonoid.toAddSubmonoid'`, `AddSubmonoid.toSubmonoid`,
`AddSubmonoid.toSubmonoid'`: convert between multiplicative and additive submonoids of `M`,
`Multiplicative M`, and `Additive M`. These are stated as `OrderIso`s.
### (Commutative) monoid structure on a submonoid
* `Submonoid.toMonoid`, `Submonoid.toCommMonoid`: a submonoid inherits a (commutative) monoid
structure.
### Group actions by submonoids
* `Submonoid.MulAction`, `Submonoid.DistribMulAction`: a submonoid inherits (distributive)
multiplicative actions.
### Operations on submonoids
* `Submonoid.comap`: preimage of a submonoid under a monoid homomorphism as a submonoid of the
domain;
* `Submonoid.map`: image of a submonoid under a monoid homomorphism as a submonoid of the codomain;
* `Submonoid.prod`: product of two submonoids `s : Submonoid M` and `t : Submonoid N` as a submonoid
of `M × N`;
### Monoid homomorphisms between submonoid
* `Submonoid.subtype`: embedding of a submonoid into the ambient monoid.
* `Submonoid.inclusion`: given two submonoids `S`, `T` such that `S ≤ T`, `S.inclusion T` is the
inclusion of `S` into `T` as a monoid homomorphism;
* `MulEquiv.submonoidCongr`: converts a proof of `S = T` into a monoid isomorphism between `S`
and `T`.
* `Submonoid.prodEquiv`: monoid isomorphism between `s.prod t` and `s × t`;
### Operations on `MonoidHom`s
* `MonoidHom.mrange`: range of a monoid homomorphism as a submonoid of the codomain;
* `MonoidHom.mker`: kernel of a monoid homomorphism as a submonoid of the domain;
* `MonoidHom.restrict`: restrict a monoid homomorphism to a submonoid;
* `MonoidHom.codRestrict`: restrict the codomain of a monoid homomorphism to a submonoid;
* `MonoidHom.mrangeRestrict`: restrict a monoid homomorphism to its range;
## Tags
submonoid, range, product, map, comap
-/
assert_not_exists MonoidWithZero
open Function
variable {M N P : Type*} [MulOneClass M] [MulOneClass N] [MulOneClass P] (S : Submonoid M)
/-!
### Conversion to/from `Additive`/`Multiplicative`
-/
section
/-- Submonoids of monoid `M` are isomorphic to additive submonoids of `Additive M`. -/
@[simps]
def Submonoid.toAddSubmonoid : Submonoid M ≃o AddSubmonoid (Additive M) where
toFun S :=
{ carrier := Additive.toMul ⁻¹' S
zero_mem' := S.one_mem'
add_mem' := fun ha hb => S.mul_mem' ha hb }
invFun S :=
{ carrier := Additive.ofMul ⁻¹' S
one_mem' := S.zero_mem'
mul_mem' := fun ha hb => S.add_mem' ha hb}
left_inv x := by cases x; rfl
right_inv x := by cases x; rfl
map_rel_iff' := Iff.rfl
/-- Additive submonoids of an additive monoid `Additive M` are isomorphic to submonoids of `M`. -/
abbrev AddSubmonoid.toSubmonoid' : AddSubmonoid (Additive M) ≃o Submonoid M :=
Submonoid.toAddSubmonoid.symm
theorem Submonoid.toAddSubmonoid_closure (S : Set M) :
Submonoid.toAddSubmonoid (Submonoid.closure S)
= AddSubmonoid.closure (Additive.toMul ⁻¹' S) :=
le_antisymm
(Submonoid.toAddSubmonoid.le_symm_apply.1 <|
Submonoid.closure_le.2 (AddSubmonoid.subset_closure (M := Additive M)))
(AddSubmonoid.closure_le.2 <| Submonoid.subset_closure (M := M))
theorem AddSubmonoid.toSubmonoid'_closure (S : Set (Additive M)) :
AddSubmonoid.toSubmonoid' (AddSubmonoid.closure S)
= Submonoid.closure (Additive.ofMul ⁻¹' S) :=
le_antisymm
(AddSubmonoid.toSubmonoid'.le_symm_apply.1 <|
AddSubmonoid.closure_le.2 (Submonoid.subset_closure (M := M)))
(Submonoid.closure_le.2 <| AddSubmonoid.subset_closure (M := Additive M))
end
section
variable {A : Type*} [AddZeroClass A]
/-- Additive submonoids of an additive monoid `A` are isomorphic to
multiplicative submonoids of `Multiplicative A`. -/
@[simps]
def AddSubmonoid.toSubmonoid : AddSubmonoid A ≃o Submonoid (Multiplicative A) where
toFun S :=
{ carrier := Multiplicative.toAdd ⁻¹' S
one_mem' := S.zero_mem'
mul_mem' := fun ha hb => S.add_mem' ha hb }
invFun S :=
{ carrier := Multiplicative.ofAdd ⁻¹' S
zero_mem' := S.one_mem'
add_mem' := fun ha hb => S.mul_mem' ha hb}
left_inv x := by cases x; rfl
right_inv x := by cases x; rfl
map_rel_iff' := Iff.rfl
/-- Submonoids of a monoid `Multiplicative A` are isomorphic to additive submonoids of `A`. -/
abbrev Submonoid.toAddSubmonoid' : Submonoid (Multiplicative A) ≃o AddSubmonoid A :=
AddSubmonoid.toSubmonoid.symm
theorem AddSubmonoid.toSubmonoid_closure (S : Set A) :
(AddSubmonoid.toSubmonoid) (AddSubmonoid.closure S)
= Submonoid.closure (Multiplicative.toAdd ⁻¹' S) :=
le_antisymm
(AddSubmonoid.toSubmonoid.to_galoisConnection.l_le <|
AddSubmonoid.closure_le.2 <| Submonoid.subset_closure (M := Multiplicative A))
(Submonoid.closure_le.2 <| AddSubmonoid.subset_closure (M := A))
theorem Submonoid.toAddSubmonoid'_closure (S : Set (Multiplicative A)) :
Submonoid.toAddSubmonoid' (Submonoid.closure S)
= AddSubmonoid.closure (Multiplicative.ofAdd ⁻¹' S) :=
le_antisymm
(Submonoid.toAddSubmonoid'.to_galoisConnection.l_le <|
Submonoid.closure_le.2 <| AddSubmonoid.subset_closure (M := A))
(AddSubmonoid.closure_le.2 <| Submonoid.subset_closure (M := Multiplicative A))
end
namespace Submonoid
variable {F : Type*} [FunLike F M N] [mc : MonoidHomClass F M N]
open Set
/-!
### `comap` and `map`
-/
/-- The preimage of a submonoid along a monoid homomorphism is a submonoid. -/
@[to_additive
"The preimage of an `AddSubmonoid` along an `AddMonoid` homomorphism is an `AddSubmonoid`."]
def comap (f : F) (S : Submonoid N) :
Submonoid M where
carrier := f ⁻¹' S
one_mem' := show f 1 ∈ S by rw [map_one]; exact S.one_mem
mul_mem' ha hb := show f (_ * _) ∈ S by rw [map_mul]; exact S.mul_mem ha hb
@[to_additive (attr := simp)]
theorem coe_comap (S : Submonoid N) (f : F) : (S.comap f : Set M) = f ⁻¹' S :=
rfl
@[to_additive (attr := simp)]
theorem mem_comap {S : Submonoid N} {f : F} {x : M} : x ∈ S.comap f ↔ f x ∈ S :=
Iff.rfl
@[to_additive]
theorem comap_comap (S : Submonoid P) (g : N →* P) (f : M →* N) :
(S.comap g).comap f = S.comap (g.comp f) :=
rfl
@[to_additive (attr := simp)]
theorem comap_id (S : Submonoid P) : S.comap (MonoidHom.id P) = S :=
ext (by simp)
/-- The image of a submonoid along a monoid homomorphism is a submonoid. -/
@[to_additive
"The image of an `AddSubmonoid` along an `AddMonoid` homomorphism is an `AddSubmonoid`."]
def map (f : F) (S : Submonoid M) :
Submonoid N where
carrier := f '' S
one_mem' := ⟨1, S.one_mem, map_one f⟩
mul_mem' := by
rintro _ _ ⟨x, hx, rfl⟩ ⟨y, hy, rfl⟩
exact ⟨x * y, S.mul_mem hx hy, by rw [map_mul]⟩
@[to_additive (attr := simp)]
theorem coe_map (f : F) (S : Submonoid M) : (S.map f : Set N) = f '' S :=
rfl
@[to_additive (attr := simp)]
theorem map_coe_toMonoidHom (f : F) (S : Submonoid M) : S.map (f : M →* N) = S.map f :=
rfl
@[to_additive (attr := simp)]
theorem map_coe_toMulEquiv {F} [EquivLike F M N] [MulEquivClass F M N] (f : F) (S : Submonoid M) :
S.map (f : M ≃* N) = S.map f :=
rfl
@[to_additive (attr := simp)]
theorem mem_map {f : F} {S : Submonoid M} {y : N} : y ∈ S.map f ↔ ∃ x ∈ S, f x = y := Iff.rfl
@[to_additive]
theorem mem_map_of_mem (f : F) {S : Submonoid M} {x : M} (hx : x ∈ S) : f x ∈ S.map f :=
mem_image_of_mem f hx
@[to_additive]
theorem apply_coe_mem_map (f : F) (S : Submonoid M) (x : S) : f x ∈ S.map f :=
mem_map_of_mem f x.2
@[to_additive]
theorem map_map (g : N →* P) (f : M →* N) : (S.map f).map g = S.map (g.comp f) :=
SetLike.coe_injective <| image_image _ _ _
-- The simpNF linter says that the LHS can be simplified via `Submonoid.mem_map`.
-- However this is a higher priority lemma.
-- It seems the side condition `hf` is not applied by `simpNF`.
-- https://github.com/leanprover/std4/issues/207
@[to_additive (attr := simp 1100, nolint simpNF)]
theorem mem_map_iff_mem {f : F} (hf : Function.Injective f) {S : Submonoid M} {x : M} :
f x ∈ S.map f ↔ x ∈ S :=
hf.mem_set_image
@[to_additive]
theorem map_le_iff_le_comap {f : F} {S : Submonoid M} {T : Submonoid N} :
S.map f ≤ T ↔ S ≤ T.comap f :=
image_subset_iff
@[to_additive]
theorem gc_map_comap (f : F) : GaloisConnection (map f) (comap f) := fun _ _ => map_le_iff_le_comap
@[to_additive]
theorem map_le_of_le_comap {T : Submonoid N} {f : F} : S ≤ T.comap f → S.map f ≤ T :=
(gc_map_comap f).l_le
@[to_additive]
theorem le_comap_of_map_le {T : Submonoid N} {f : F} : S.map f ≤ T → S ≤ T.comap f :=
(gc_map_comap f).le_u
@[to_additive]
theorem le_comap_map {f : F} : S ≤ (S.map f).comap f :=
(gc_map_comap f).le_u_l _
@[to_additive]
theorem map_comap_le {S : Submonoid N} {f : F} : (S.comap f).map f ≤ S :=
(gc_map_comap f).l_u_le _
@[to_additive]
theorem monotone_map {f : F} : Monotone (map f) :=
(gc_map_comap f).monotone_l
@[to_additive]
theorem monotone_comap {f : F} : Monotone (comap f) :=
(gc_map_comap f).monotone_u
@[to_additive (attr := simp)]
theorem map_comap_map {f : F} : ((S.map f).comap f).map f = S.map f :=
(gc_map_comap f).l_u_l_eq_l _
@[to_additive (attr := simp)]
theorem comap_map_comap {S : Submonoid N} {f : F} : ((S.comap f).map f).comap f = S.comap f :=
(gc_map_comap f).u_l_u_eq_u _
@[to_additive]
theorem map_sup (S T : Submonoid M) (f : F) : (S ⊔ T).map f = S.map f ⊔ T.map f :=
(gc_map_comap f : GaloisConnection (map f) (comap f)).l_sup
@[to_additive]
theorem map_iSup {ι : Sort*} (f : F) (s : ι → Submonoid M) : (iSup s).map f = ⨆ i, (s i).map f :=
(gc_map_comap f : GaloisConnection (map f) (comap f)).l_iSup
@[to_additive]
theorem map_inf (S T : Submonoid M) (f : F) (hf : Function.Injective f) :
(S ⊓ T).map f = S.map f ⊓ T.map f := SetLike.coe_injective (Set.image_inter hf)
@[to_additive]
theorem map_iInf {ι : Sort*} [Nonempty ι] (f : F) (hf : Function.Injective f)
(s : ι → Submonoid M) : (iInf s).map f = ⨅ i, (s i).map f := by
apply SetLike.coe_injective
simpa using (Set.injOn_of_injective hf).image_iInter_eq (s := SetLike.coe ∘ s)
@[to_additive]
theorem comap_inf (S T : Submonoid N) (f : F) : (S ⊓ T).comap f = S.comap f ⊓ T.comap f :=
(gc_map_comap f : GaloisConnection (map f) (comap f)).u_inf
@[to_additive]
theorem comap_iInf {ι : Sort*} (f : F) (s : ι → Submonoid N) :
(iInf s).comap f = ⨅ i, (s i).comap f :=
(gc_map_comap f : GaloisConnection (map f) (comap f)).u_iInf
@[to_additive (attr := simp)]
theorem map_bot (f : F) : (⊥ : Submonoid M).map f = ⊥ :=
(gc_map_comap f).l_bot
@[to_additive (attr := simp)]
theorem comap_top (f : F) : (⊤ : Submonoid N).comap f = ⊤ :=
(gc_map_comap f).u_top
@[to_additive (attr := simp)]
theorem map_id (S : Submonoid M) : S.map (MonoidHom.id M) = S :=
ext fun _ => ⟨fun ⟨_, h, rfl⟩ => h, fun h => ⟨_, h, rfl⟩⟩
section GaloisCoinsertion
variable {ι : Type*} {f : F}
/-- `map f` and `comap f` form a `GaloisCoinsertion` when `f` is injective. -/
@[to_additive "`map f` and `comap f` form a `GaloisCoinsertion` when `f` is injective."]
def gciMapComap (hf : Function.Injective f) : GaloisCoinsertion (map f) (comap f) :=
(gc_map_comap f).toGaloisCoinsertion fun S x => by simp [mem_comap, mem_map, hf.eq_iff]
variable (hf : Function.Injective f)
include hf
@[to_additive]
theorem comap_map_eq_of_injective (S : Submonoid M) : (S.map f).comap f = S :=
(gciMapComap hf).u_l_eq _
@[to_additive]
theorem comap_surjective_of_injective : Function.Surjective (comap f) :=
(gciMapComap hf).u_surjective
@[to_additive]
theorem map_injective_of_injective : Function.Injective (map f) :=
(gciMapComap hf).l_injective
@[to_additive]
theorem comap_inf_map_of_injective (S T : Submonoid M) : (S.map f ⊓ T.map f).comap f = S ⊓ T :=
(gciMapComap hf).u_inf_l _ _
@[to_additive]
theorem comap_iInf_map_of_injective (S : ι → Submonoid M) : (⨅ i, (S i).map f).comap f = iInf S :=
(gciMapComap hf).u_iInf_l _
@[to_additive]
theorem comap_sup_map_of_injective (S T : Submonoid M) : (S.map f ⊔ T.map f).comap f = S ⊔ T :=
(gciMapComap hf).u_sup_l _ _
@[to_additive]
theorem comap_iSup_map_of_injective (S : ι → Submonoid M) : (⨆ i, (S i).map f).comap f = iSup S :=
(gciMapComap hf).u_iSup_l _
@[to_additive]
theorem map_le_map_iff_of_injective {S T : Submonoid M} : S.map f ≤ T.map f ↔ S ≤ T :=
(gciMapComap hf).l_le_l_iff
@[to_additive]
theorem map_strictMono_of_injective : StrictMono (map f) :=
(gciMapComap hf).strictMono_l
end GaloisCoinsertion
section GaloisInsertion
variable {ι : Type*} {f : F}
/-- `map f` and `comap f` form a `GaloisInsertion` when `f` is surjective. -/
@[to_additive "`map f` and `comap f` form a `GaloisInsertion` when `f` is surjective."]
def giMapComap (hf : Function.Surjective f) : GaloisInsertion (map f) (comap f) :=
(gc_map_comap f).toGaloisInsertion fun S x h =>
let ⟨y, hy⟩ := hf x
mem_map.2 ⟨y, by simp [hy, h]⟩
variable (hf : Function.Surjective f)
include hf
@[to_additive]
theorem map_comap_eq_of_surjective (S : Submonoid N) : (S.comap f).map f = S :=
(giMapComap hf).l_u_eq _
@[to_additive]
theorem map_surjective_of_surjective : Function.Surjective (map f) :=
(giMapComap hf).l_surjective
@[to_additive]
theorem comap_injective_of_surjective : Function.Injective (comap f) :=
(giMapComap hf).u_injective
@[to_additive]
theorem map_inf_comap_of_surjective (S T : Submonoid N) : (S.comap f ⊓ T.comap f).map f = S ⊓ T :=
(giMapComap hf).l_inf_u _ _
@[to_additive]
theorem map_iInf_comap_of_surjective (S : ι → Submonoid N) : (⨅ i, (S i).comap f).map f = iInf S :=
(giMapComap hf).l_iInf_u _
@[to_additive]
theorem map_sup_comap_of_surjective (S T : Submonoid N) : (S.comap f ⊔ T.comap f).map f = S ⊔ T :=
(giMapComap hf).l_sup_u _ _
@[to_additive]
theorem map_iSup_comap_of_surjective (S : ι → Submonoid N) : (⨆ i, (S i).comap f).map f = iSup S :=
(giMapComap hf).l_iSup_u _
@[to_additive]
theorem comap_le_comap_iff_of_surjective {S T : Submonoid N} : S.comap f ≤ T.comap f ↔ S ≤ T :=
(giMapComap hf).u_le_u_iff
@[to_additive]
theorem comap_strictMono_of_surjective : StrictMono (comap f) :=
(giMapComap hf).strictMono_u
end GaloisInsertion
variable {M : Type*} [MulOneClass M] (S : Submonoid M)
/-- The top submonoid is isomorphic to the monoid. -/
@[to_additive (attr := simps) "The top additive submonoid is isomorphic to the additive monoid."]
def topEquiv : (⊤ : Submonoid M) ≃* M where
toFun x := x
invFun x := ⟨x, mem_top x⟩
left_inv x := x.eta _
right_inv _ := rfl
map_mul' _ _ := rfl
@[to_additive (attr := simp)]
theorem topEquiv_toMonoidHom : ((topEquiv : _ ≃* M) : _ →* M) = (⊤ : Submonoid M).subtype :=
rfl
/-- A subgroup is isomorphic to its image under an injective function. If you have an isomorphism,
use `MulEquiv.submonoidMap` for better definitional equalities. -/
@[to_additive "An additive subgroup is isomorphic to its image under an injective function. If you
have an isomorphism, use `AddEquiv.addSubmonoidMap` for better definitional equalities."]
noncomputable def equivMapOfInjective (f : M →* N) (hf : Function.Injective f) : S ≃* S.map f :=
{ Equiv.Set.image f S hf with map_mul' := fun _ _ => Subtype.ext (f.map_mul _ _) }
@[to_additive (attr := simp)]
theorem coe_equivMapOfInjective_apply (f : M →* N) (hf : Function.Injective f) (x : S) :
(equivMapOfInjective S f hf x : N) = f x :=
rfl
@[to_additive (attr := simp)]
theorem closure_closure_coe_preimage {s : Set M} : closure (((↑) : closure s → M) ⁻¹' s) = ⊤ :=
eq_top_iff.2 fun x _ ↦ Subtype.recOn x fun _ hx' ↦
closure_induction (fun _ h ↦ subset_closure h) (one_mem _) (fun _ _ _ _ ↦ mul_mem) hx'
/-- Given submonoids `s`, `t` of monoids `M`, `N` respectively, `s × t` as a submonoid
of `M × N`. -/
@[to_additive prod
"Given `AddSubmonoid`s `s`, `t` of `AddMonoid`s `A`, `B` respectively, `s × t`
as an `AddSubmonoid` of `A × B`."]
def prod (s : Submonoid M) (t : Submonoid N) :
Submonoid (M × N) where
carrier := s ×ˢ t
one_mem' := ⟨s.one_mem, t.one_mem⟩
mul_mem' hp hq := ⟨s.mul_mem hp.1 hq.1, t.mul_mem hp.2 hq.2⟩
@[to_additive coe_prod]
theorem coe_prod (s : Submonoid M) (t : Submonoid N) :
(s.prod t : Set (M × N)) = (s : Set M) ×ˢ (t : Set N) :=
rfl
@[to_additive mem_prod]
theorem mem_prod {s : Submonoid M} {t : Submonoid N} {p : M × N} :
p ∈ s.prod t ↔ p.1 ∈ s ∧ p.2 ∈ t :=
Iff.rfl
@[to_additive prod_mono]
theorem prod_mono {s₁ s₂ : Submonoid M} {t₁ t₂ : Submonoid N} (hs : s₁ ≤ s₂) (ht : t₁ ≤ t₂) :
s₁.prod t₁ ≤ s₂.prod t₂ :=
Set.prod_mono hs ht
@[to_additive prod_top]
theorem prod_top (s : Submonoid M) : s.prod (⊤ : Submonoid N) = s.comap (MonoidHom.fst M N) :=
ext fun x => by simp [mem_prod, MonoidHom.coe_fst]
@[to_additive top_prod]
theorem top_prod (s : Submonoid N) : (⊤ : Submonoid M).prod s = s.comap (MonoidHom.snd M N) :=
ext fun x => by simp [mem_prod, MonoidHom.coe_snd]
@[to_additive (attr := simp) top_prod_top]
theorem top_prod_top : (⊤ : Submonoid M).prod (⊤ : Submonoid N) = ⊤ :=
(top_prod _).trans <| comap_top _
@[to_additive bot_prod_bot]
theorem bot_prod_bot : (⊥ : Submonoid M).prod (⊥ : Submonoid N) = ⊥ :=
SetLike.coe_injective <| by simp [coe_prod]
/-- The product of submonoids is isomorphic to their product as monoids. -/
@[to_additive prodEquiv
"The product of additive submonoids is isomorphic to their product as additive monoids"]
def prodEquiv (s : Submonoid M) (t : Submonoid N) : s.prod t ≃* s × t :=
{ (Equiv.Set.prod (s : Set M) (t : Set N)) with
map_mul' := fun _ _ => rfl }
open MonoidHom
@[to_additive]
theorem map_inl (s : Submonoid M) : s.map (inl M N) = s.prod ⊥ :=
ext fun p =>
⟨fun ⟨_, hx, hp⟩ => hp ▸ ⟨hx, Set.mem_singleton 1⟩, fun ⟨hps, hp1⟩ =>
⟨p.1, hps, Prod.ext rfl <| (Set.eq_of_mem_singleton hp1).symm⟩⟩
@[to_additive]
theorem map_inr (s : Submonoid N) : s.map (inr M N) = prod ⊥ s :=
ext fun p =>
⟨fun ⟨_, hx, hp⟩ => hp ▸ ⟨Set.mem_singleton 1, hx⟩, fun ⟨hp1, hps⟩ =>
⟨p.2, hps, Prod.ext (Set.eq_of_mem_singleton hp1).symm rfl⟩⟩
@[to_additive (attr := simp) prod_bot_sup_bot_prod]
theorem prod_bot_sup_bot_prod (s : Submonoid M) (t : Submonoid N) :
(prod s ⊥) ⊔ (prod ⊥ t) = prod s t :=
(le_antisymm (sup_le (prod_mono (le_refl s) bot_le) (prod_mono bot_le (le_refl t))))
fun p hp => Prod.fst_mul_snd p ▸ mul_mem
((le_sup_left : prod s ⊥ ≤ prod s ⊥ ⊔ prod ⊥ t) ⟨hp.1, Set.mem_singleton 1⟩)
((le_sup_right : prod ⊥ t ≤ prod s ⊥ ⊔ prod ⊥ t) ⟨Set.mem_singleton 1, hp.2⟩)
@[to_additive]
theorem mem_map_equiv {f : M ≃* N} {K : Submonoid M} {x : N} :
x ∈ K.map f.toMonoidHom ↔ f.symm x ∈ K :=
Set.mem_image_equiv
@[to_additive]
theorem map_equiv_eq_comap_symm (f : M ≃* N) (K : Submonoid M) :
K.map f = K.comap f.symm :=
SetLike.coe_injective (f.toEquiv.image_eq_preimage K)
@[to_additive]
theorem comap_equiv_eq_map_symm (f : N ≃* M) (K : Submonoid M) :
K.comap f = K.map f.symm :=
(map_equiv_eq_comap_symm f.symm K).symm
@[to_additive (attr := simp)]
theorem map_equiv_top (f : M ≃* N) : (⊤ : Submonoid M).map f = ⊤ :=
SetLike.coe_injective <| Set.image_univ.trans f.surjective.range_eq
@[to_additive le_prod_iff]
theorem le_prod_iff {s : Submonoid M} {t : Submonoid N} {u : Submonoid (M × N)} :
u ≤ s.prod t ↔ u.map (fst M N) ≤ s ∧ u.map (snd M N) ≤ t := by
constructor
· intro h
constructor
· rintro x ⟨⟨y1, y2⟩, ⟨hy1, rfl⟩⟩
exact (h hy1).1
· rintro x ⟨⟨y1, y2⟩, ⟨hy1, rfl⟩⟩
exact (h hy1).2
· rintro ⟨hH, hK⟩ ⟨x1, x2⟩ h
exact ⟨hH ⟨_, h, rfl⟩, hK ⟨_, h, rfl⟩⟩
@[to_additive prod_le_iff]
theorem prod_le_iff {s : Submonoid M} {t : Submonoid N} {u : Submonoid (M × N)} :
s.prod t ≤ u ↔ s.map (inl M N) ≤ u ∧ t.map (inr M N) ≤ u := by
constructor
· intro h
constructor
· rintro _ ⟨x, hx, rfl⟩
apply h
exact ⟨hx, Submonoid.one_mem _⟩
· rintro _ ⟨x, hx, rfl⟩
apply h
exact ⟨Submonoid.one_mem _, hx⟩
· rintro ⟨hH, hK⟩ ⟨x1, x2⟩ ⟨h1, h2⟩
have h1' : inl M N x1 ∈ u := by
apply hH
simpa using h1
have h2' : inr M N x2 ∈ u := by
apply hK
simpa using h2
simpa using Submonoid.mul_mem _ h1' h2'
@[to_additive closure_prod]
theorem closure_prod {s : Set M} {t : Set N} (hs : 1 ∈ s) (ht : 1 ∈ t) :
closure (s ×ˢ t) = (closure s).prod (closure t) :=
le_antisymm
(closure_le.2 <| Set.prod_subset_prod_iff.2 <| .inl ⟨subset_closure, subset_closure⟩)
(prod_le_iff.2 ⟨
map_le_of_le_comap _ <| closure_le.2 fun _x hx => subset_closure ⟨hx, ht⟩,
map_le_of_le_comap _ <| closure_le.2 fun _y hy => subset_closure ⟨hs, hy⟩⟩)
@[to_additive (attr := simp) closure_prod_zero]
lemma closure_prod_one (s : Set M) : closure (s ×ˢ ({1} : Set N)) = (closure s).prod ⊥ :=
le_antisymm
(closure_le.2 <| Set.prod_subset_prod_iff.2 <| .inl ⟨subset_closure, .rfl⟩)
(prod_le_iff.2 ⟨
map_le_of_le_comap _ <| closure_le.2 fun _x hx => subset_closure ⟨hx, rfl⟩,
by simp⟩)
@[to_additive (attr := simp) closure_zero_prod]
lemma closure_one_prod (t : Set N) : closure (({1} : Set M) ×ˢ t) = .prod ⊥ (closure t) :=
le_antisymm
(closure_le.2 <| Set.prod_subset_prod_iff.2 <| .inl ⟨.rfl, subset_closure⟩)
(prod_le_iff.2 ⟨by simp,
map_le_of_le_comap _ <| closure_le.2 fun _y hy => subset_closure ⟨rfl, hy⟩⟩)
end Submonoid
namespace MonoidHom
variable {F : Type*} [FunLike F M N] [mc : MonoidHomClass F M N]
open Submonoid
library_note "range copy pattern"/--
For many categories (monoids, modules, rings, ...) the set-theoretic image of a morphism `f` is
a subobject of the codomain. When this is the case, it is useful to define the range of a morphism
in such a way that the underlying carrier set of the range subobject is definitionally
`Set.range f`. In particular this means that the types `↥(Set.range f)` and `↥f.range` are
interchangeable without proof obligations.
A convenient candidate definition for range which is mathematically correct is `map ⊤ f`, just as
`Set.range` could have been defined as `f '' Set.univ`. However, this lacks the desired definitional
convenience, in that it both does not match `Set.range`, and that it introduces a redundant `x ∈ ⊤`
term which clutters proofs. In such a case one may resort to the `copy`
pattern. A `copy` function converts the definitional problem for the carrier set of a subobject
into a one-off propositional proof obligation which one discharges while writing the definition of
the definitionally convenient range (the parameter `hs` in the example below).
A good example is the case of a morphism of monoids. A convenient definition for
`MonoidHom.mrange` would be `(⊤ : Submonoid M).map f`. However since this lacks the required
definitional convenience, we first define `Submonoid.copy` as follows:
```lean
protected def copy (S : Submonoid M) (s : Set M) (hs : s = S) : Submonoid M :=
{ carrier := s,
one_mem' := hs.symm ▸ S.one_mem',
mul_mem' := hs.symm ▸ S.mul_mem' }
```
and then finally define:
```lean
def mrange (f : M →* N) : Submonoid N :=
((⊤ : Submonoid M).map f).copy (Set.range f) Set.image_univ.symm
```
-/
/-- The range of a monoid homomorphism is a submonoid. See Note [range copy pattern]. -/
@[to_additive "The range of an `AddMonoidHom` is an `AddSubmonoid`."]
def mrange (f : F) : Submonoid N :=
((⊤ : Submonoid M).map f).copy (Set.range f) Set.image_univ.symm
@[to_additive (attr := simp)]
theorem coe_mrange (f : F) : (mrange f : Set N) = Set.range f :=
rfl
@[to_additive (attr := simp)]
theorem mem_mrange {f : F} {y : N} : y ∈ mrange f ↔ ∃ x, f x = y :=
Iff.rfl
@[to_additive]
lemma mrange_comp {O : Type*} [MulOneClass O] (f : N →* O) (g : M →* N) :
mrange (f.comp g) = (mrange g).map f := SetLike.coe_injective <| Set.range_comp f _
@[to_additive]
theorem mrange_eq_map (f : F) : mrange f = (⊤ : Submonoid M).map f :=
Submonoid.copy_eq _
@[to_additive (attr := simp)]
theorem mrange_id : mrange (MonoidHom.id M) = ⊤ := by
simp [mrange_eq_map]
@[to_additive]
theorem map_mrange (g : N →* P) (f : M →* N) : (mrange f).map g = mrange (comp g f) := by
simpa only [mrange_eq_map] using (⊤ : Submonoid M).map_map g f
@[to_additive]
theorem mrange_eq_top {f : F} : mrange f = (⊤ : Submonoid N) ↔ Surjective f :=
SetLike.ext'_iff.trans <| Iff.trans (by rw [coe_mrange, coe_top]) Set.range_eq_univ
@[deprecated (since := "2024-11-11")]
alias mrange_top_iff_surjective := mrange_eq_top
/-- The range of a surjective monoid hom is the whole of the codomain. -/
@[to_additive (attr := simp)
"The range of a surjective `AddMonoid` hom is the whole of the codomain."]
theorem mrange_eq_top_of_surjective (f : F) (hf : Function.Surjective f) :
mrange f = (⊤ : Submonoid N) :=
mrange_eq_top.2 hf
@[deprecated (since := "2024-11-11")] alias mrange_top_of_surjective := mrange_eq_top_of_surjective
@[to_additive]
theorem mclosure_preimage_le (f : F) (s : Set N) : closure (f ⁻¹' s) ≤ (closure s).comap f :=
closure_le.2 fun _ hx => SetLike.mem_coe.2 <| mem_comap.2 <| subset_closure hx
/-- The image under a monoid hom of the submonoid generated by a set equals the submonoid generated
by the image of the set. -/
@[to_additive
"The image under an `AddMonoid` hom of the `AddSubmonoid` generated by a set equals
the `AddSubmonoid` generated by the image of the set."]
theorem map_mclosure (f : F) (s : Set M) : (closure s).map f = closure (f '' s) :=
Set.image_preimage.l_comm_of_u_comm (gc_map_comap f) (Submonoid.gi N).gc (Submonoid.gi M).gc
fun _ ↦ rfl
@[to_additive (attr := simp)]
theorem mclosure_range (f : F) : closure (Set.range f) = mrange f := by
rw [← Set.image_univ, ← map_mclosure, mrange_eq_map, closure_univ]
/-- Restriction of a monoid hom to a submonoid of the domain. -/
@[to_additive "Restriction of an `AddMonoid` hom to an `AddSubmonoid` of the domain."]
def restrict {N S : Type*} [MulOneClass N] [SetLike S M] [SubmonoidClass S M] (f : M →* N)
(s : S) : s →* N :=
f.comp (SubmonoidClass.subtype _)
@[to_additive (attr := simp)]
theorem restrict_apply {N S : Type*} [MulOneClass N] [SetLike S M] [SubmonoidClass S M]
(f : M →* N) (s : S) (x : s) : f.restrict s x = f x :=
rfl
@[to_additive (attr := simp)]
theorem restrict_mrange (f : M →* N) : mrange (f.restrict S) = S.map f := by
simp [SetLike.ext_iff]
/-- Restriction of a monoid hom to a submonoid of the codomain. -/
@[to_additive (attr := simps apply)
"Restriction of an `AddMonoid` hom to an `AddSubmonoid` of the codomain."]
def codRestrict {S} [SetLike S N] [SubmonoidClass S N] (f : M →* N) (s : S) (h : ∀ x, f x ∈ s) :
M →* s where
toFun n := ⟨f n, h n⟩
map_one' := Subtype.eq f.map_one
map_mul' x y := Subtype.eq (f.map_mul x y)
@[to_additive (attr := simp)]
lemma injective_codRestrict {S} [SetLike S N] [SubmonoidClass S N] (f : M →* N) (s : S)
(h : ∀ x, f x ∈ s) : Function.Injective (f.codRestrict s h) ↔ Function.Injective f :=
⟨fun H _ _ hxy ↦ H <| Subtype.eq hxy, fun H _ _ hxy ↦ H (congr_arg Subtype.val hxy)⟩
/-- Restriction of a monoid hom to its range interpreted as a submonoid. -/
@[to_additive "Restriction of an `AddMonoid` hom to its range interpreted as a submonoid."]
def mrangeRestrict {N} [MulOneClass N] (f : M →* N) : M →* (mrange f) :=
(f.codRestrict (mrange f)) fun x => ⟨x, rfl⟩
@[to_additive (attr := simp)]
theorem coe_mrangeRestrict {N} [MulOneClass N] (f : M →* N) (x : M) :
(f.mrangeRestrict x : N) = f x :=
rfl
@[to_additive]
theorem mrangeRestrict_surjective (f : M →* N) : Function.Surjective f.mrangeRestrict :=
fun ⟨_, ⟨x, rfl⟩⟩ => ⟨x, rfl⟩
/-- The multiplicative kernel of a monoid hom is the submonoid of elements `x : G` such
that `f x = 1` -/
@[to_additive
"The additive kernel of an `AddMonoid` hom is the `AddSubmonoid` of
elements such that `f x = 0`"]
def mker (f : F) : Submonoid M :=
(⊥ : Submonoid N).comap f
@[to_additive (attr := simp)]
theorem mem_mker {f : F} {x : M} : x ∈ mker f ↔ f x = 1 :=
Iff.rfl
@[to_additive]
theorem coe_mker (f : F) : (mker f : Set M) = (f : M → N) ⁻¹' {1} :=
rfl
@[to_additive]
instance decidableMemMker [DecidableEq N] (f : F) : DecidablePred (· ∈ mker f) := fun x =>
decidable_of_iff (f x = 1) mem_mker
@[to_additive]
theorem comap_mker (g : N →* P) (f : M →* N) : (mker g).comap f = mker (comp g f) :=
rfl
@[to_additive (attr := simp)]
theorem comap_bot' (f : F) : (⊥ : Submonoid N).comap f = mker f :=
rfl
@[to_additive (attr := simp)]
theorem restrict_mker (f : M →* N) : mker (f.restrict S) = (MonoidHom.mker f).comap S.subtype :=
rfl
@[to_additive]
theorem mrangeRestrict_mker (f : M →* N) : mker (mrangeRestrict f) = mker f := by
ext x
change (⟨f x, _⟩ : mrange f) = ⟨1, _⟩ ↔ f x = 1
simp
@[to_additive (attr := simp)]
theorem mker_one : mker (1 : M →* N) = ⊤ := by
ext
simp [mem_mker]
@[to_additive prod_map_comap_prod']
theorem prod_map_comap_prod' {M' : Type*} {N' : Type*} [MulOneClass M'] [MulOneClass N']
(f : M →* N) (g : M' →* N') (S : Submonoid N) (S' : Submonoid N') :
(S.prod S').comap (prodMap f g) = (S.comap f).prod (S'.comap g) :=
SetLike.coe_injective <| Set.preimage_prod_map_prod f g _ _
@[to_additive mker_prod_map]
theorem mker_prod_map {M' : Type*} {N' : Type*} [MulOneClass M'] [MulOneClass N'] (f : M →* N)
(g : M' →* N') : mker (prodMap f g) = (mker f).prod (mker g) := by
rw [← comap_bot', ← comap_bot', ← comap_bot', ← prod_map_comap_prod', bot_prod_bot]
@[to_additive (attr := simp)]
theorem mker_inl : mker (inl M N) = ⊥ := by
ext x
simp [mem_mker]
@[to_additive (attr := simp)]
theorem mker_inr : mker (inr M N) = ⊥ := by
ext x
simp [mem_mker]
@[to_additive (attr := simp)]
lemma mker_fst : mker (fst M N) = .prod ⊥ ⊤ := SetLike.ext fun _ => (iff_of_eq (and_true _)).symm
@[to_additive (attr := simp)]
lemma mker_snd : mker (snd M N) = .prod ⊤ ⊥ := SetLike.ext fun _ => (iff_of_eq (true_and _)).symm
/-- The `MonoidHom` from the preimage of a submonoid to itself. -/
@[to_additive (attr := simps)
"the `AddMonoidHom` from the preimage of an additive submonoid to itself."]
def submonoidComap (f : M →* N) (N' : Submonoid N) :
N'.comap f →* N' where
toFun x := ⟨f x, x.2⟩
map_one' := Subtype.eq f.map_one
map_mul' x y := Subtype.eq (f.map_mul x y)
@[to_additive]
lemma submonoidComap_surjective_of_surjective (f : M →* N) (N' : Submonoid N) (hf : Surjective f) :
Surjective (f.submonoidComap N') := fun y ↦ by
obtain ⟨x, hx⟩ := hf y
use ⟨x, mem_comap.mpr (hx ▸ y.2)⟩
apply Subtype.val_injective
simp [hx]
/-- The `MonoidHom` from a submonoid to its image.
See `MulEquiv.SubmonoidMap` for a variant for `MulEquiv`s. -/
@[to_additive (attr := simps)
"the `AddMonoidHom` from an additive submonoid to its image. See
`AddEquiv.AddSubmonoidMap` for a variant for `AddEquiv`s."]
def submonoidMap (f : M →* N) (M' : Submonoid M) : M' →* M'.map f where
toFun x := ⟨f x, ⟨x, x.2, rfl⟩⟩
map_one' := Subtype.eq <| f.map_one
map_mul' x y := Subtype.eq <| f.map_mul x y
@[to_additive]
theorem submonoidMap_surjective (f : M →* N) (M' : Submonoid M) :
Function.Surjective (f.submonoidMap M') := by
rintro ⟨_, x, hx, rfl⟩
exact ⟨⟨x, hx⟩, rfl⟩
end MonoidHom
namespace Submonoid
open MonoidHom
@[to_additive]
theorem mrange_inl : mrange (inl M N) = prod ⊤ ⊥ := by simpa only [mrange_eq_map] using map_inl ⊤
@[to_additive]
theorem mrange_inr : mrange (inr M N) = prod ⊥ ⊤ := by simpa only [mrange_eq_map] using map_inr ⊤
@[to_additive]
theorem mrange_inl' : mrange (inl M N) = comap (snd M N) ⊥ :=
mrange_inl.trans (top_prod _)
@[to_additive]
theorem mrange_inr' : mrange (inr M N) = comap (fst M N) ⊥ :=
mrange_inr.trans (prod_top _)
@[to_additive (attr := simp)]
theorem mrange_fst : mrange (fst M N) = ⊤ :=
mrange_eq_top_of_surjective (fst M N) <| @Prod.fst_surjective _ _ ⟨1⟩
@[to_additive (attr := simp)]
theorem mrange_snd : mrange (snd M N) = ⊤ :=
mrange_eq_top_of_surjective (snd M N) <| @Prod.snd_surjective _ _ ⟨1⟩
@[to_additive prod_eq_bot_iff]
theorem prod_eq_bot_iff {s : Submonoid M} {t : Submonoid N} : s.prod t = ⊥ ↔ s = ⊥ ∧ t = ⊥ := by
simp only [eq_bot_iff, prod_le_iff, (gc_map_comap _).le_iff_le, comap_bot', mker_inl, mker_inr]
@[to_additive prod_eq_top_iff]
theorem prod_eq_top_iff {s : Submonoid M} {t : Submonoid N} : s.prod t = ⊤ ↔ s = ⊤ ∧ t = ⊤ := by
simp only [eq_top_iff, le_prod_iff, ← (gc_map_comap _).le_iff_le, ← mrange_eq_map, mrange_fst,
mrange_snd]
@[to_additive (attr := simp)]
theorem mrange_inl_sup_mrange_inr : mrange (inl M N) ⊔ mrange (inr M N) = ⊤ := by
simp only [mrange_inl, mrange_inr, prod_bot_sup_bot_prod, top_prod_top]
/-- The monoid hom associated to an inclusion of submonoids. -/
@[to_additive
"The `AddMonoid` hom associated to an inclusion of submonoids."]
def inclusion {S T : Submonoid M} (h : S ≤ T) : S →* T :=
S.subtype.codRestrict _ fun x => h x.2
@[to_additive (attr := simp)]
theorem mrange_subtype (s : Submonoid M) : mrange s.subtype = s :=
SetLike.coe_injective <| (coe_mrange _).trans <| Subtype.range_coe
-- `alias` doesn't add the deprecation suggestion to the `to_additive` version
-- see https://github.com/leanprover-community/mathlib4/issues/19424
@[to_additive] alias range_subtype := mrange_subtype
attribute [deprecated mrange_subtype (since := "2024-11-25")] range_subtype
attribute [deprecated AddSubmonoid.mrange_subtype (since := "2024-11-25")]
AddSubmonoid.range_subtype
@[to_additive]
theorem eq_top_iff' : S = ⊤ ↔ ∀ x : M, x ∈ S :=
eq_top_iff.trans ⟨fun h m => h <| mem_top m, fun h m _ => h m⟩
@[to_additive]
theorem eq_bot_iff_forall : S = ⊥ ↔ ∀ x ∈ S, x = (1 : M) :=
SetLike.ext_iff.trans <| by simp +contextual [iff_def, S.one_mem]
@[to_additive]
theorem eq_bot_of_subsingleton [Subsingleton S] : S = ⊥ := by
rw [eq_bot_iff_forall]
intro y hy
simpa using congr_arg ((↑) : S → M) <| Subsingleton.elim (⟨y, hy⟩ : S) 1
@[to_additive]
theorem nontrivial_iff_exists_ne_one (S : Submonoid M) : Nontrivial S ↔ ∃ x ∈ S, x ≠ (1 : M) :=
calc
Nontrivial S ↔ ∃ x : S, x ≠ 1 := nontrivial_iff_exists_ne 1
_ ↔ ∃ (x : _) (hx : x ∈ S), (⟨x, hx⟩ : S) ≠ ⟨1, S.one_mem⟩ := Subtype.exists
_ ↔ ∃ x ∈ S, x ≠ (1 : M) := by simp [Ne]
/-- A submonoid is either the trivial submonoid or nontrivial. -/
@[to_additive "An additive submonoid is either the trivial additive submonoid or nontrivial."]
theorem bot_or_nontrivial (S : Submonoid M) : S = ⊥ ∨ Nontrivial S := by
simp only [eq_bot_iff_forall, nontrivial_iff_exists_ne_one, ← not_forall, ← Classical.not_imp,
Classical.em]
/-- A submonoid is either the trivial submonoid or contains a nonzero element. -/
@[to_additive
"An additive submonoid is either the trivial additive submonoid or contains a nonzero
element."]
theorem bot_or_exists_ne_one (S : Submonoid M) : S = ⊥ ∨ ∃ x ∈ S, x ≠ (1 : M) :=
S.bot_or_nontrivial.imp_right S.nontrivial_iff_exists_ne_one.mp
end Submonoid
namespace MulEquiv
variable {S} {T : Submonoid M}
/-- Makes the identity isomorphism from a proof that two submonoids of a multiplicative
monoid are equal. -/
@[to_additive
"Makes the identity additive isomorphism from a proof two
submonoids of an additive monoid are equal."]
def submonoidCongr (h : S = T) : S ≃* T :=
{ Equiv.setCongr <| congr_arg _ h with map_mul' := fun _ _ => rfl }
-- this name is primed so that the version to `f.range` instead of `f.mrange` can be unprimed.
/-- A monoid homomorphism `f : M →* N` with a left-inverse `g : N → M` defines a multiplicative
equivalence between `M` and `f.mrange`.
This is a bidirectional version of `MonoidHom.mrange_restrict`. -/
@[to_additive (attr := simps +simpRhs)
"An additive monoid homomorphism `f : M →+ N` with a left-inverse `g : N → M`
defines an additive equivalence between `M` and `f.mrange`.
This is a bidirectional version of `AddMonoidHom.mrange_restrict`. "]
def ofLeftInverse' (f : M →* N) {g : N → M} (h : Function.LeftInverse g f) :
M ≃* MonoidHom.mrange f :=
{ f.mrangeRestrict with
toFun := f.mrangeRestrict
invFun := g ∘ (MonoidHom.mrange f).subtype
left_inv := h
right_inv := fun x =>
Subtype.ext <|
let ⟨x', hx'⟩ := MonoidHom.mem_mrange.mp x.2
show f (g x) = x by rw [← hx', h x'] }
/-- A `MulEquiv` `φ` between two monoids `M` and `N` induces a `MulEquiv` between
a submonoid `S ≤ M` and the submonoid `φ(S) ≤ N`.
See `MonoidHom.submonoidMap` for a variant for `MonoidHom`s. -/
@[to_additive
"An `AddEquiv` `φ` between two additive monoids `M` and `N` induces an `AddEquiv`
between a submonoid `S ≤ M` and the submonoid `φ(S) ≤ N`. See
`AddMonoidHom.addSubmonoidMap` for a variant for `AddMonoidHom`s."]
def submonoidMap (e : M ≃* N) (S : Submonoid M) : S ≃* S.map e :=
{ (e : M ≃ N).image S with map_mul' := fun _ _ => Subtype.ext (map_mul e _ _) }
@[to_additive (attr := simp)]
theorem coe_submonoidMap_apply (e : M ≃* N) (S : Submonoid M) (g : S) :
((submonoidMap e S g : S.map (e : M →* N)) : N) = e g :=
rfl
@[to_additive (attr := simp) AddEquiv.add_submonoid_map_symm_apply]
theorem submonoidMap_symm_apply (e : M ≃* N) (S : Submonoid M) (g : S.map (e : M →* N)) :
(e.submonoidMap S).symm g = ⟨e.symm g, SetLike.mem_coe.1 <| Set.mem_image_equiv.1 g.2⟩ :=
rfl
end MulEquiv
@[to_additive (attr := simp)]
theorem Submonoid.equivMapOfInjective_coe_mulEquiv (e : M ≃* N) :
S.equivMapOfInjective (e : M →* N) (EquivLike.injective e) = e.submonoidMap S := by
ext
rfl
@[to_additive]
instance Submonoid.faithfulSMul {M' α : Type*} [MulOneClass M'] [SMul M' α] {S : Submonoid M'}
[FaithfulSMul M' α] : FaithfulSMul S α :=
⟨fun h => Subtype.ext <| eq_of_smul_eq_smul h⟩
section Units
namespace Submonoid
/-- The multiplicative equivalence between the type of units of `M` and the submonoid of unit
elements of `M`. -/
@[to_additive (attr := simps!) " The additive equivalence between the type of additive units of `M`
and the additive submonoid whose elements are the additive units of `M`. "]
noncomputable def unitsTypeEquivIsUnitSubmonoid [Monoid M] : Mˣ ≃* IsUnit.submonoid M where
toFun x := ⟨x, Units.isUnit x⟩
invFun x := x.prop.unit
left_inv _ := IsUnit.unit_of_val_units _
right_inv x := by simp_rw [IsUnit.unit_spec]
map_mul' x y := by simp_rw [Units.val_mul]; rfl
end Submonoid
end Units
open AddSubmonoid Set
namespace Nat
@[simp] lemma addSubmonoid_closure_one : closure ({1} : Set ℕ) = ⊤ := by
refine (eq_top_iff' _).2 <| Nat.rec (zero_mem _) ?_
simp_rw [Nat.succ_eq_add_one]
exact fun n hn ↦ AddSubmonoid.add_mem _ hn <| subset_closure <| Set.mem_singleton _
end Nat
namespace Submonoid
variable {F : Type*} [FunLike F M N] [mc : MonoidHomClass F M N]
@[to_additive]
theorem map_comap_eq (f : F) (S : Submonoid N) : (S.comap f).map f = S ⊓ MonoidHom.mrange f :=
SetLike.coe_injective Set.image_preimage_eq_inter_range
@[to_additive]
theorem map_comap_eq_self {f : F} {S : Submonoid N} (h : S ≤ MonoidHom.mrange f) :
(S.comap f).map f = S := by
simpa only [inf_of_le_left h] using map_comap_eq f S
@[to_additive]
theorem map_comap_eq_self_of_surjective {f : F} (h : Function.Surjective f) {S : Submonoid N} :
map f (comap f S) = S :=
map_comap_eq_self (MonoidHom.mrange_eq_top_of_surjective _ h ▸ le_top)
end Submonoid
| Mathlib/Algebra/Group/Submonoid/Operations.lean | 1,259 | 1,260 | |
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.Algebra.CharP.Defs
import Mathlib.Algebra.Field.Defs
import Mathlib.Algebra.GroupWithZero.Invertible
import Mathlib.Algebra.Ring.Int.Defs
import Mathlib.Data.Int.GCD
import Mathlib.Data.Nat.Cast.Commute
/-!
# Invertibility of elements given a characteristic
This file includes some instances of `Invertible` for specific numbers in
characteristic zero. Some more cases are given as a `def`, to be included only
when needed. To construct instances for concrete numbers,
`invertibleOfNonzero` is a useful definition.
-/
variable {R K : Type*}
section Ring
variable [Ring R] {p : ℕ} [CharP R p]
theorem CharP.intCast_mul_natCast_gcdA_eq_gcd (n : ℕ) :
(n * n.gcdA p : R) = n.gcd p := by
suffices ↑(n * n.gcdA p + p * n.gcdB p : ℤ) = ((n.gcd p : ℤ) : R) by simpa using this
rw [← Nat.gcd_eq_gcd_ab]
|
theorem CharP.natCast_gcdA_mul_intCast_eq_gcd (n : ℕ) :
(n.gcdA p * n : R) = n.gcd p :=
| Mathlib/Algebra/CharP/Invertible.lean | 32 | 34 |
/-
Copyright (c) 2020 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Computability.Halting
import Mathlib.Computability.TuringMachine
import Mathlib.Data.Num.Lemmas
import Mathlib.Tactic.DeriveFintype
import Mathlib.Computability.TMConfig
/-!
# Modelling partial recursive functions using Turing machines
The files `TMConfig` and `TMToPartrec` define a simplified basis for partial recursive functions,
and a `Turing.TM2` model
Turing machine for evaluating these functions. This amounts to a constructive proof that every
`Partrec` function can be evaluated by a Turing machine.
## Main definitions
* `PartrecToTM2.tr`: A TM2 turing machine which can evaluate `code` programs
-/
open List (Vector)
open Function (update)
open Relation
namespace Turing
/-!
## Simulating sequentialized partial recursive functions in TM2
At this point we have a sequential model of partial recursive functions: the `Cfg` type and
`step : Cfg → Option Cfg` function from `TMConfig.lean`. The key feature of this model is that
it does a finite amount of computation (in fact, an amount which is statically bounded by the size
of the program) between each step, and no individual step can diverge (unlike the compositional
semantics, where every sub-part of the computation is potentially divergent). So we can utilize the
same techniques as in the other TM simulations in `Computability.TuringMachine` to prove that
each step corresponds to a finite number of steps in a lower level model. (We don't prove it here,
but in anticipation of the complexity class P, the simulation is actually polynomial-time as well.)
The target model is `Turing.TM2`, which has a fixed finite set of stacks, a bit of local storage,
with programs selected from a potentially infinite (but finitely accessible) set of program
positions, or labels `Λ`, each of which executes a finite sequence of basic stack commands.
For this program we will need four stacks, each on an alphabet `Γ'` like so:
inductive Γ' | consₗ | cons | bit0 | bit1
We represent a number as a bit sequence, lists of numbers by putting `cons` after each element, and
lists of lists of natural numbers by putting `consₗ` after each list. For example:
0 ~> []
1 ~> [bit1]
6 ~> [bit0, bit1, bit1]
[1, 2] ~> [bit1, cons, bit0, bit1, cons]
[[], [1, 2]] ~> [consₗ, bit1, cons, bit0, bit1, cons, consₗ]
The four stacks are `main`, `rev`, `aux`, `stack`. In normal mode, `main` contains the input to the
current program (a `List ℕ`) and `stack` contains data (a `List (List ℕ)`) associated to the
current continuation, and in `ret` mode `main` contains the value that is being passed to the
continuation and `stack` contains the data for the continuation. The `rev` and `aux` stacks are
usually empty; `rev` is used to store reversed data when e.g. moving a value from one stack to
another, while `aux` is used as a temporary for a `main`/`stack` swap that happens during `cons₁`
evaluation.
The only local store we need is `Option Γ'`, which stores the result of the last pop
operation. (Most of our working data are natural numbers, which are too large to fit in the local
store.)
The continuations from the previous section are data-carrying, containing all the values that have
been computed and are awaiting other arguments. In order to have only a finite number of
continuations appear in the program so that they can be used in machine states, we separate the
data part (anything with type `List ℕ`) from the `Cont` type, producing a `Cont'` type that lacks
this information. The data is kept on the `stack` stack.
Because we want to have subroutines for e.g. moving an entire stack to another place, we use an
infinite inductive type `Λ'` so that we can execute a program and then return to do something else
without having to define too many different kinds of intermediate states. (We must nevertheless
prove that only finitely many labels are accessible.) The labels are:
* `move p k₁ k₂ q`: move elements from stack `k₁` to `k₂` while `p` holds of the value being moved.
The last element, that fails `p`, is placed in neither stack but left in the local store.
At the end of the operation, `k₂` will have the elements of `k₁` in reverse order. Then do `q`.
* `clear p k q`: delete elements from stack `k` until `p` is true. Like `move`, the last element is
left in the local storage. Then do `q`.
* `copy q`: Move all elements from `rev` to both `main` and `stack` (in reverse order),
then do `q`. That is, it takes `(a, b, c, d)` to `(b.reverse ++ a, [], c, b.reverse ++ d)`.
* `push k f q`: push `f s`, where `s` is the local store, to stack `k`, then do `q`. This is a
duplicate of the `push` instruction that is part of the TM2 model, but by having a subroutine
just for this purpose we can build up programs to execute inside a `goto` statement, where we
have the flexibility to be general recursive.
* `read (f : Option Γ' → Λ')`: go to state `f s` where `s` is the local store. Again this is only
here for convenience.
* `succ q`: perform a successor operation. Assuming `[n]` is encoded on `main` before,
`[n+1]` will be on main after. This implements successor for binary natural numbers.
* `pred q₁ q₂`: perform a predecessor operation or `case` statement. If `[]` is encoded on
`main` before, then we transition to `q₁` with `[]` on main; if `(0 :: v)` is on `main` before
then `v` will be on `main` after and we transition to `q₁`; and if `(n+1 :: v)` is on `main`
before then `n :: v` will be on `main` after and we transition to `q₂`.
* `ret k`: call continuation `k`. Each continuation has its own interpretation of the data in
`stack` and sets up the data for the next continuation.
* `ret (cons₁ fs k)`: `v :: KData` on `stack` and `ns` on `main`, and the next step expects
`v` on `main` and `ns :: KData` on `stack`. So we have to do a little dance here with six
reverse-moves using the `aux` stack to perform a three-point swap, each of which involves two
reversals.
* `ret (cons₂ k)`: `ns :: KData` is on `stack` and `v` is on `main`, and we have to put
`ns.headI :: v` on `main` and `KData` on `stack`. This is done using the `head` subroutine.
* `ret (fix f k)`: This stores no data, so we just check if `main` starts with `0` and
if so, remove it and call `k`, otherwise `clear` the first value and call `f`.
* `ret halt`: the stack is empty, and `main` has the output. Do nothing and halt.
In addition to these basic states, we define some additional subroutines that are used in the
above:
* `push'`, `peek'`, `pop'` are special versions of the builtins that use the local store to supply
inputs and outputs.
* `unrev`: special case `move false rev main` to move everything from `rev` back to `main`. Used as
a cleanup operation in several functions.
* `moveExcl p k₁ k₂ q`: same as `move` but pushes the last value read back onto the source stack.
* `move₂ p k₁ k₂ q`: double `move`, so that the result comes out in the right order at the target
stack. Implemented as `moveExcl p k rev; move false rev k₂`. Assumes that neither `k₁` nor `k₂`
is `rev` and `rev` is initially empty.
* `head k q`: get the first natural number from stack `k` and reverse-move it to `rev`, then clear
the rest of the list at `k` and then `unrev` to reverse-move the head value to `main`. This is
used with `k = main` to implement regular `head`, i.e. if `v` is on `main` before then `[v.headI]`
will be on `main` after; and also with `k = stack` for the `cons` operation, which has `v` on
`main` and `ns :: KData` on `stack`, and results in `KData` on `stack` and `ns.headI :: v` on
`main`.
* `trNormal` is the main entry point, defining states that perform a given `code` computation.
It mostly just dispatches to functions written above.
The main theorem of this section is `tr_eval`, which asserts that for each that for each code `c`,
the state `init c v` steps to `halt v'` in finitely many steps if and only if
`Code.eval c v = some v'`.
-/
namespace PartrecToTM2
section
open ToPartrec
/-- The alphabet for the stacks in the program. `bit0` and `bit1` are used to represent `ℕ` values
as lists of binary digits, `cons` is used to separate `List ℕ` values, and `consₗ` is used to
separate `List (List ℕ)` values. See the section documentation. -/
inductive Γ'
| consₗ
| cons
| bit0
| bit1
deriving DecidableEq, Inhabited, Fintype
/-- The four stacks used by the program. `main` is used to store the input value in `trNormal`
mode and the output value in `Λ'.ret` mode, while `stack` is used to keep all the data for the
continuations. `rev` is used to store reversed lists when transferring values between stacks, and
`aux` is only used once in `cons₁`. See the section documentation. -/
inductive K'
| main
| rev
| aux
| stack
deriving DecidableEq, Inhabited
open K'
/-- Continuations as in `ToPartrec.Cont` but with the data removed. This is done because we want
the set of all continuations in the program to be finite (so that it can ultimately be encoded into
the finite state machine of a Turing machine), but a continuation can handle a potentially infinite
number of data values during execution. -/
inductive Cont'
| halt
| cons₁ : Code → Cont' → Cont'
| cons₂ : Cont' → Cont'
| comp : Code → Cont' → Cont'
| fix : Code → Cont' → Cont'
deriving DecidableEq, Inhabited
/-- The set of program positions. We make extensive use of inductive types here to let us describe
"subroutines"; for example `clear p k q` is a program that clears stack `k`, then does `q` where
`q` is another label. In order to prevent this from resulting in an infinite number of distinct
accessible states, we are careful to be non-recursive (although loops are okay). See the section
documentation for a description of all the programs. -/
inductive Λ'
| move (p : Γ' → Bool) (k₁ k₂ : K') (q : Λ')
| clear (p : Γ' → Bool) (k : K') (q : Λ')
| copy (q : Λ')
| push (k : K') (s : Option Γ' → Option Γ') (q : Λ')
| read (f : Option Γ' → Λ')
| succ (q : Λ')
| pred (q₁ q₂ : Λ')
| ret (k : Cont')
compile_inductive% Code
compile_inductive% Cont'
compile_inductive% K'
compile_inductive% Λ'
instance Λ'.instInhabited : Inhabited Λ' :=
⟨Λ'.ret Cont'.halt⟩
instance Λ'.instDecidableEq : DecidableEq Λ' := fun a b => by
induction a generalizing b <;> cases b <;> first
| apply Decidable.isFalse; rintro ⟨⟨⟩⟩; done
| exact decidable_of_iff' _ (by simp [funext_iff]; rfl)
/-- The type of TM2 statements used by this machine. -/
def Stmt' :=
TM2.Stmt (fun _ : K' => Γ') Λ' (Option Γ') deriving Inhabited
/-- The type of TM2 configurations used by this machine. -/
def Cfg' :=
TM2.Cfg (fun _ : K' => Γ') Λ' (Option Γ') deriving Inhabited
open TM2.Stmt
/-- A predicate that detects the end of a natural number, either `Γ'.cons` or `Γ'.consₗ` (or
implicitly the end of the list), for use in predicate-taking functions like `move` and `clear`. -/
@[simp]
def natEnd : Γ' → Bool
| Γ'.consₗ => true
| Γ'.cons => true
| _ => false
attribute [nolint simpNF] natEnd.eq_3
/-- Pop a value from the stack and place the result in local store. -/
@[simp]
def pop' (k : K') : Stmt' → Stmt' :=
pop k fun _ v => v
/-- Peek a value from the stack and place the result in local store. -/
@[simp]
def peek' (k : K') : Stmt' → Stmt' :=
peek k fun _ v => v
/-- Push the value in the local store to the given stack. -/
@[simp]
def push' (k : K') : Stmt' → Stmt' :=
push k fun x => x.iget
/-- Move everything from the `rev` stack to the `main` stack (reversed). -/
def unrev :=
Λ'.move (fun _ => false) rev main
/-- Move elements from `k₁` to `k₂` while `p` holds, with the last element being left on `k₁`. -/
def moveExcl (p k₁ k₂ q) :=
Λ'.move p k₁ k₂ <| Λ'.push k₁ id q
/-- Move elements from `k₁` to `k₂` without reversion, by performing a double move via the `rev`
stack. -/
def move₂ (p k₁ k₂ q) :=
moveExcl p k₁ rev <| Λ'.move (fun _ => false) rev k₂ q
/-- Assuming `trList v` is on the front of stack `k`, remove it, and push `v.headI` onto `main`.
See the section documentation. -/
def head (k : K') (q : Λ') : Λ' :=
Λ'.move natEnd k rev <|
(Λ'.push rev fun _ => some Γ'.cons) <|
Λ'.read fun s =>
(if s = some Γ'.consₗ then id else Λ'.clear (fun x => x = Γ'.consₗ) k) <| unrev q
/-- The program that evaluates code `c` with continuation `k`. This expects an initial state where
`trList v` is on `main`, `trContStack k` is on `stack`, and `aux` and `rev` are empty.
See the section documentation for details. -/
@[simp]
def trNormal : Code → Cont' → Λ'
| Code.zero', k => (Λ'.push main fun _ => some Γ'.cons) <| Λ'.ret k
| Code.succ, k => head main <| Λ'.succ <| Λ'.ret k
| Code.tail, k => Λ'.clear natEnd main <| Λ'.ret k
| Code.cons f fs, k =>
(Λ'.push stack fun _ => some Γ'.consₗ) <|
Λ'.move (fun _ => false) main rev <| Λ'.copy <| trNormal f (Cont'.cons₁ fs k)
| Code.comp f g, k => trNormal g (Cont'.comp f k)
| Code.case f g, k => Λ'.pred (trNormal f k) (trNormal g k)
| Code.fix f, k => trNormal f (Cont'.fix f k)
/-- The main program. See the section documentation for details. -/
def tr : Λ' → Stmt'
| Λ'.move p k₁ k₂ q =>
pop' k₁ <|
branch (fun s => s.elim true p) (goto fun _ => q)
(push' k₂ <| goto fun _ => Λ'.move p k₁ k₂ q)
| Λ'.push k f q =>
branch (fun s => (f s).isSome) ((push k fun s => (f s).iget) <| goto fun _ => q)
(goto fun _ => q)
| Λ'.read q => goto q
| Λ'.clear p k q =>
pop' k <| branch (fun s => s.elim true p) (goto fun _ => q) (goto fun _ => Λ'.clear p k q)
| Λ'.copy q =>
pop' rev <|
branch Option.isSome (push' main <| push' stack <| goto fun _ => Λ'.copy q) (goto fun _ => q)
| Λ'.succ q =>
pop' main <|
branch (fun s => s = some Γ'.bit1) ((push rev fun _ => Γ'.bit0) <| goto fun _ => Λ'.succ q) <|
branch (fun s => s = some Γ'.cons)
((push main fun _ => Γ'.cons) <| (push main fun _ => Γ'.bit1) <| goto fun _ => unrev q)
((push main fun _ => Γ'.bit1) <| goto fun _ => unrev q)
| Λ'.pred q₁ q₂ =>
pop' main <|
branch (fun s => s = some Γ'.bit0)
((push rev fun _ => Γ'.bit1) <| goto fun _ => Λ'.pred q₁ q₂) <|
branch (fun s => natEnd s.iget) (goto fun _ => q₁)
(peek' main <|
branch (fun s => natEnd s.iget) (goto fun _ => unrev q₂)
((push rev fun _ => Γ'.bit0) <| goto fun _ => unrev q₂))
| Λ'.ret (Cont'.cons₁ fs k) =>
goto fun _ =>
move₂ (fun _ => false) main aux <|
move₂ (fun s => s = Γ'.consₗ) stack main <|
move₂ (fun _ => false) aux stack <| trNormal fs (Cont'.cons₂ k)
| Λ'.ret (Cont'.cons₂ k) => goto fun _ => head stack <| Λ'.ret k
| Λ'.ret (Cont'.comp f k) => goto fun _ => trNormal f k
| Λ'.ret (Cont'.fix f k) =>
pop' main <|
goto fun s =>
cond (natEnd s.iget) (Λ'.ret k) <| Λ'.clear natEnd main <| trNormal f (Cont'.fix f k)
| Λ'.ret Cont'.halt => (load fun _ => none) <| halt
@[simp]
theorem tr_move (p k₁ k₂ q) : tr (Λ'.move p k₁ k₂ q) =
pop' k₁ (branch (fun s => s.elim true p) (goto fun _ => q)
(push' k₂ <| goto fun _ => Λ'.move p k₁ k₂ q)) := rfl
@[simp]
theorem tr_push (k f q) : tr (Λ'.push k f q) = branch (fun s => (f s).isSome)
((push k fun s => (f s).iget) <| goto fun _ => q) (goto fun _ => q) := rfl
@[simp]
theorem tr_read (q) : tr (Λ'.read q) = goto q := rfl
@[simp]
theorem tr_clear (p k q) : tr (Λ'.clear p k q) = pop' k (branch
(fun s => s.elim true p) (goto fun _ => q) (goto fun _ => Λ'.clear p k q)) := rfl
@[simp]
theorem tr_copy (q) : tr (Λ'.copy q) = pop' rev (branch Option.isSome
(push' main <| push' stack <| goto fun _ => Λ'.copy q) (goto fun _ => q)) := rfl
@[simp]
theorem tr_succ (q) : tr (Λ'.succ q) = pop' main (branch (fun s => s = some Γ'.bit1)
((push rev fun _ => Γ'.bit0) <| goto fun _ => Λ'.succ q) <|
branch (fun s => s = some Γ'.cons)
((push main fun _ => Γ'.cons) <| (push main fun _ => Γ'.bit1) <| goto fun _ => unrev q)
((push main fun _ => Γ'.bit1) <| goto fun _ => unrev q)) := rfl
@[simp]
theorem tr_pred (q₁ q₂) : tr (Λ'.pred q₁ q₂) = pop' main (branch (fun s => s = some Γ'.bit0)
((push rev fun _ => Γ'.bit1) <| goto fun _ => Λ'.pred q₁ q₂) <|
branch (fun s => natEnd s.iget) (goto fun _ => q₁)
(peek' main <|
branch (fun s => natEnd s.iget) (goto fun _ => unrev q₂)
((push rev fun _ => Γ'.bit0) <| goto fun _ => unrev q₂))) := rfl
@[simp]
theorem tr_ret_cons₁ (fs k) : tr (Λ'.ret (Cont'.cons₁ fs k)) = goto fun _ =>
move₂ (fun _ => false) main aux <|
move₂ (fun s => s = Γ'.consₗ) stack main <|
move₂ (fun _ => false) aux stack <| trNormal fs (Cont'.cons₂ k) := rfl
@[simp]
theorem tr_ret_cons₂ (k) : tr (Λ'.ret (Cont'.cons₂ k)) =
goto fun _ => head stack <| Λ'.ret k := rfl
@[simp]
theorem tr_ret_comp (f k) : tr (Λ'.ret (Cont'.comp f k)) = goto fun _ => trNormal f k := rfl
@[simp]
theorem tr_ret_fix (f k) : tr (Λ'.ret (Cont'.fix f k)) = pop' main (goto fun s =>
cond (natEnd s.iget) (Λ'.ret k) <| Λ'.clear natEnd main <| trNormal f (Cont'.fix f k)) := rfl
@[simp]
theorem tr_ret_halt : tr (Λ'.ret Cont'.halt) = (load fun _ => none) halt := rfl
/-- Translating a `Cont` continuation to a `Cont'` continuation simply entails dropping all the
data. This data is instead encoded in `trContStack` in the configuration. -/
def trCont : Cont → Cont'
| Cont.halt => Cont'.halt
| Cont.cons₁ c _ k => Cont'.cons₁ c (trCont k)
| Cont.cons₂ _ k => Cont'.cons₂ (trCont k)
| Cont.comp c k => Cont'.comp c (trCont k)
| Cont.fix c k => Cont'.fix c (trCont k)
/-- We use `PosNum` to define the translation of binary natural numbers. A natural number is
represented as a little-endian list of `bit0` and `bit1` elements:
1 = [bit1]
2 = [bit0, bit1]
3 = [bit1, bit1]
4 = [bit0, bit0, bit1]
In particular, this representation guarantees no trailing `bit0`'s at the end of the list. -/
def trPosNum : PosNum → List Γ'
| PosNum.one => [Γ'.bit1]
| PosNum.bit0 n => Γ'.bit0 :: trPosNum n
| PosNum.bit1 n => Γ'.bit1 :: trPosNum n
/-- We use `Num` to define the translation of binary natural numbers. Positive numbers are
translated using `trPosNum`, and `trNum 0 = []`. So there are never any trailing `bit0`'s in
a translated `Num`.
0 = []
1 = [bit1]
2 = [bit0, bit1]
3 = [bit1, bit1]
4 = [bit0, bit0, bit1]
-/
def trNum : Num → List Γ'
| Num.zero => []
| Num.pos n => trPosNum n
/-- Because we use binary encoding, we define `trNat` in terms of `trNum`, using `Num`, which are
binary natural numbers. (We could also use `Nat.binaryRecOn`, but `Num` and `PosNum` make for
easy inductions.) -/
def trNat (n : ℕ) : List Γ' :=
trNum n
@[simp]
theorem trNat_zero : trNat 0 = [] := by rw [trNat, Nat.cast_zero]; rfl
theorem trNat_default : trNat default = [] :=
trNat_zero
/-- Lists are translated with a `cons` after each encoded number.
For example:
[] = []
[0] = [cons]
[1] = [bit1, cons]
[6, 0] = [bit0, bit1, bit1, cons, cons]
-/
@[simp]
def trList : List ℕ → List Γ'
| [] => []
| n::ns => trNat n ++ Γ'.cons :: trList ns
/-- Lists of lists are translated with a `consₗ` after each encoded list.
For example:
[] = []
[[]] = [consₗ]
[[], []] = [consₗ, consₗ]
[[0]] = [cons, consₗ]
[[1, 2], [0]] = [bit1, cons, bit0, bit1, cons, consₗ, cons, consₗ]
-/
@[simp]
def trLList : List (List ℕ) → List Γ'
| [] => []
| l::ls => trList l ++ Γ'.consₗ :: trLList ls
/-- The data part of a continuation is a list of lists, which is encoded on the `stack` stack
using `trLList`. -/
@[simp]
def contStack : Cont → List (List ℕ)
| Cont.halt => []
| Cont.cons₁ _ ns k => ns :: contStack k
| Cont.cons₂ ns k => ns :: contStack k
| Cont.comp _ k => contStack k
| Cont.fix _ k => contStack k
/-- The data part of a continuation is a list of lists, which is encoded on the `stack` stack
using `trLList`. -/
def trContStack (k : Cont) :=
trLList (contStack k)
/-- This is the nondependent eliminator for `K'`, but we use it specifically here in order to
represent the stack data as four lists rather than as a function `K' → List Γ'`, because this makes
rewrites easier. The theorems `K'.elim_update_main` et. al. show how such a function is updated
after an `update` to one of the components. -/
def K'.elim (a b c d : List Γ') : K' → List Γ'
| K'.main => a
| K'.rev => b
| K'.aux => c
| K'.stack => d
-- The equation lemma of `elim` simplifies to `match` structures.
theorem K'.elim_main (a b c d) : K'.elim a b c d K'.main = a := rfl
theorem K'.elim_rev (a b c d) : K'.elim a b c d K'.rev = b := rfl
theorem K'.elim_aux (a b c d) : K'.elim a b c d K'.aux = c := rfl
theorem K'.elim_stack (a b c d) : K'.elim a b c d K'.stack = d := rfl
attribute [simp] K'.elim
@[simp]
theorem K'.elim_update_main {a b c d a'} : update (K'.elim a b c d) main a' = K'.elim a' b c d := by
funext x; cases x <;> rfl
@[simp]
theorem K'.elim_update_rev {a b c d b'} : update (K'.elim a b c d) rev b' = K'.elim a b' c d := by
funext x; cases x <;> rfl
@[simp]
theorem K'.elim_update_aux {a b c d c'} : update (K'.elim a b c d) aux c' = K'.elim a b c' d := by
funext x; cases x <;> rfl
@[simp]
theorem K'.elim_update_stack {a b c d d'} :
update (K'.elim a b c d) stack d' = K'.elim a b c d' := by funext x; cases x <;> rfl
/-- The halting state corresponding to a `List ℕ` output value. -/
def halt (v : List ℕ) : Cfg' :=
⟨none, none, K'.elim (trList v) [] [] []⟩
/-- The `Cfg` states map to `Cfg'` states almost one to one, except that in normal operation the
local store contains an arbitrary garbage value. To make the final theorem cleaner we explicitly
clear it in the halt state so that there is exactly one configuration corresponding to output `v`.
-/
def TrCfg : Cfg → Cfg' → Prop
| Cfg.ret k v, c' =>
∃ s, c' = ⟨some (Λ'.ret (trCont k)), s, K'.elim (trList v) [] [] (trContStack k)⟩
| Cfg.halt v, c' => c' = halt v
/-- This could be a general list definition, but it is also somewhat specialized to this
application. `splitAtPred p L` will search `L` for the first element satisfying `p`.
If it is found, say `L = l₁ ++ a :: l₂` where `a` satisfies `p` but `l₁` does not, then it returns
`(l₁, some a, l₂)`. Otherwise, if there is no such element, it returns `(L, none, [])`. -/
def splitAtPred {α} (p : α → Bool) : List α → List α × Option α × List α
| [] => ([], none, [])
| a :: as =>
cond (p a) ([], some a, as) <|
let ⟨l₁, o, l₂⟩ := splitAtPred p as
⟨a::l₁, o, l₂⟩
theorem splitAtPred_eq {α} (p : α → Bool) :
∀ L l₁ o l₂,
(∀ x ∈ l₁, p x = false) →
Option.elim' (L = l₁ ∧ l₂ = []) (fun a => p a = true ∧ L = l₁ ++ a::l₂) o →
splitAtPred p L = (l₁, o, l₂)
| [], _, none, _, _, ⟨rfl, rfl⟩ => rfl
| [], l₁, some o, l₂, _, ⟨_, h₃⟩ => by simp at h₃
| a :: L, l₁, o, l₂, h₁, h₂ => by
rw [splitAtPred]
have IH := splitAtPred_eq p L
rcases o with - | o
· rcases l₁ with - | ⟨a', l₁⟩ <;> rcases h₂ with ⟨⟨⟩, rfl⟩
rw [h₁ a (List.Mem.head _), cond, IH L none [] _ ⟨rfl, rfl⟩]
exact fun x h => h₁ x (List.Mem.tail _ h)
· rcases l₁ with - | ⟨a', l₁⟩ <;> rcases h₂ with ⟨h₂, ⟨⟩⟩
· rw [h₂, cond]
rw [h₁ a (List.Mem.head _), cond, IH l₁ (some o) l₂ _ ⟨h₂, _⟩] <;> try rfl
exact fun x h => h₁ x (List.Mem.tail _ h)
theorem splitAtPred_false {α} (L : List α) : splitAtPred (fun _ => false) L = (L, none, []) :=
splitAtPred_eq _ _ _ _ _ (fun _ _ => rfl) ⟨rfl, rfl⟩
theorem move_ok {p k₁ k₂ q s L₁ o L₂} {S : K' → List Γ'} (h₁ : k₁ ≠ k₂)
(e : splitAtPred p (S k₁) = (L₁, o, L₂)) :
Reaches₁ (TM2.step tr) ⟨some (Λ'.move p k₁ k₂ q), s, S⟩
⟨some q, o, update (update S k₁ L₂) k₂ (L₁.reverseAux (S k₂))⟩ := by
induction' L₁ with a L₁ IH generalizing S s
· rw [(_ : [].reverseAux _ = _), Function.update_eq_self]
swap
· rw [Function.update_of_ne h₁.symm, List.reverseAux_nil]
refine TransGen.head' rfl ?_
rw [tr]; simp only [pop', TM2.stepAux]
revert e; rcases S k₁ with - | ⟨a, Sk⟩ <;> intro e
· cases e
rfl
simp only [splitAtPred, Option.elim, List.head?, List.tail_cons, Option.iget_some] at e ⊢
revert e; cases p a <;> intro e <;>
simp only [cond_false, cond_true, Prod.mk.injEq, true_and, false_and, reduceCtorEq] at e ⊢
simp only [e]
rfl
· refine TransGen.head rfl ?_
rw [tr]; simp only [pop', Option.elim, TM2.stepAux, push']
rcases e₁ : S k₁ with - | ⟨a', Sk⟩ <;> rw [e₁, splitAtPred] at e
· cases e
cases e₂ : p a' <;> simp only [e₂, cond] at e
swap
· cases e
rcases e₃ : splitAtPred p Sk with ⟨_, _, _⟩
rw [e₃] at e
cases e
simp only [List.head?_cons, e₂, List.tail_cons, ne_eq, cond_false]
convert @IH _ (update (update S k₁ Sk) k₂ (a :: S k₂)) _ using 2 <;>
simp [Function.update_of_ne, h₁, h₁.symm, e₃, List.reverseAux]
simp [Function.update_comm h₁.symm]
theorem unrev_ok {q s} {S : K' → List Γ'} :
Reaches₁ (TM2.step tr) ⟨some (unrev q), s, S⟩
⟨some q, none, update (update S rev []) main (List.reverseAux (S rev) (S main))⟩ :=
move_ok (by decide) <| splitAtPred_false _
theorem move₂_ok {p k₁ k₂ q s L₁ o L₂} {S : K' → List Γ'} (h₁ : k₁ ≠ rev ∧ k₂ ≠ rev ∧ k₁ ≠ k₂)
(h₂ : S rev = []) (e : splitAtPred p (S k₁) = (L₁, o, L₂)) :
Reaches₁ (TM2.step tr) ⟨some (move₂ p k₁ k₂ q), s, S⟩
⟨some q, none, update (update S k₁ (o.elim id List.cons L₂)) k₂ (L₁ ++ S k₂)⟩ := by
refine (move_ok h₁.1 e).trans (TransGen.head rfl ?_)
simp only [TM2.step, Option.mem_def, TM2.stepAux, id_eq, ne_eq, Option.elim]
cases o <;> simp only [Option.elim] <;> rw [tr]
<;> simp only [id, TM2.stepAux, Option.isSome, cond_true, cond_false]
· convert move_ok h₁.2.1.symm (splitAtPred_false _) using 2
simp only [Function.update_comm h₁.1, Function.update_idem]
rw [show update S rev [] = S by rw [← h₂, Function.update_eq_self]]
simp only [Function.update_of_ne h₁.2.2.symm, Function.update_of_ne h₁.2.1,
Function.update_of_ne h₁.1.symm, List.reverseAux_eq, h₂, Function.update_self,
List.append_nil, List.reverse_reverse]
· convert move_ok h₁.2.1.symm (splitAtPred_false _) using 2
simp only [h₂, Function.update_comm h₁.1, List.reverseAux_eq, Function.update_self,
List.append_nil, Function.update_idem]
rw [show update S rev [] = S by rw [← h₂, Function.update_eq_self]]
simp only [Function.update_of_ne h₁.1.symm, Function.update_of_ne h₁.2.2.symm,
Function.update_of_ne h₁.2.1, Function.update_self, List.reverse_reverse]
theorem clear_ok {p k q s L₁ o L₂} {S : K' → List Γ'} (e : splitAtPred p (S k) = (L₁, o, L₂)) :
Reaches₁ (TM2.step tr) ⟨some (Λ'.clear p k q), s, S⟩ ⟨some q, o, update S k L₂⟩ := by
induction' L₁ with a L₁ IH generalizing S s
· refine TransGen.head' rfl ?_
rw [tr]; simp only [pop', TM2.step, Option.mem_def, TM2.stepAux, Option.elim]
revert e; rcases S k with - | ⟨a, Sk⟩ <;> intro e
· cases e
rfl
simp only [splitAtPred, Option.elim, List.head?, List.tail_cons] at e ⊢
revert e; cases p a <;> intro e <;>
simp only [cond_false, cond_true, Prod.mk.injEq, true_and, false_and, reduceCtorEq] at e ⊢
rcases e with ⟨e₁, e₂⟩
rw [e₁, e₂]
· refine TransGen.head rfl ?_
rw [tr]; simp only [pop', TM2.step, Option.mem_def, TM2.stepAux, Option.elim]
rcases e₁ : S k with - | ⟨a', Sk⟩ <;> rw [e₁, splitAtPred] at e
· cases e
cases e₂ : p a' <;> simp only [e₂, cond] at e
swap
· cases e
rcases e₃ : splitAtPred p Sk with ⟨_, _, _⟩
rw [e₃] at e
cases e
simp only [List.head?_cons, e₂, List.tail_cons, cond_false]
convert @IH _ (update S k Sk) _ using 2 <;> simp [e₃]
theorem copy_ok (q s a b c d) :
Reaches₁ (TM2.step tr) ⟨some (Λ'.copy q), s, K'.elim a b c d⟩
⟨some q, none, K'.elim (List.reverseAux b a) [] c (List.reverseAux b d)⟩ := by
induction' b with x b IH generalizing a d s
· refine TransGen.single ?_
simp
refine TransGen.head rfl ?_
rw [tr]
simp only [TM2.step, Option.mem_def, TM2.stepAux, elim_rev, List.head?_cons, Option.isSome_some,
List.tail_cons, elim_update_rev, ne_eq, Function.update_of_ne, elim_main, elim_update_main,
elim_stack, elim_update_stack, cond_true, List.reverseAux_cons, pop', push']
exact IH _ _ _
theorem trPosNum_natEnd : ∀ (n), ∀ x ∈ trPosNum n, natEnd x = false
| PosNum.one, _, List.Mem.head _ => rfl
| PosNum.bit0 _, _, List.Mem.head _ => rfl
| PosNum.bit0 n, _, List.Mem.tail _ h => trPosNum_natEnd n _ h
| PosNum.bit1 _, _, List.Mem.head _ => rfl
| PosNum.bit1 n, _, List.Mem.tail _ h => trPosNum_natEnd n _ h
theorem trNum_natEnd : ∀ (n), ∀ x ∈ trNum n, natEnd x = false
| Num.pos n, x, h => trPosNum_natEnd n x h
theorem trNat_natEnd (n) : ∀ x ∈ trNat n, natEnd x = false :=
trNum_natEnd _
theorem trList_ne_consₗ : ∀ (l), ∀ x ∈ trList l, x ≠ Γ'.consₗ
| a :: l, x, h => by
simp only [trList, List.mem_append, List.mem_cons] at h
obtain h | rfl | h := h
· rintro rfl
cases trNat_natEnd _ _ h
· rintro ⟨⟩
· exact trList_ne_consₗ l _ h
theorem head_main_ok {q s L} {c d : List Γ'} :
Reaches₁ (TM2.step tr) ⟨some (head main q), s, K'.elim (trList L) [] c d⟩
⟨some q, none, K'.elim (trList [L.headI]) [] c d⟩ := by
let o : Option Γ' := List.casesOn L none fun _ _ => some Γ'.cons
refine
(move_ok (by decide)
(splitAtPred_eq _ _ (trNat L.headI) o (trList L.tail) (trNat_natEnd _) ?_)).trans
(TransGen.head rfl (TransGen.head rfl ?_))
· cases L <;> simp [o]
rw [tr]
simp only [TM2.step, Option.mem_def, TM2.stepAux, elim_update_main, elim_rev, elim_update_rev,
Function.update_self, trList]
rw [if_neg (show o ≠ some Γ'.consₗ by cases L <;> simp [o])]
refine (clear_ok (splitAtPred_eq _ _ _ none [] ?_ ⟨rfl, rfl⟩)).trans ?_
· exact fun x h => Bool.decide_false (trList_ne_consₗ _ _ h)
convert unrev_ok using 2; simp [List.reverseAux_eq]
theorem head_stack_ok {q s L₁ L₂ L₃} :
Reaches₁ (TM2.step tr)
⟨some (head stack q), s, K'.elim (trList L₁) [] [] (trList L₂ ++ Γ'.consₗ :: L₃)⟩
⟨some q, none, K'.elim (trList (L₂.headI :: L₁)) [] [] L₃⟩ := by
rcases L₂ with - | ⟨a, L₂⟩
· refine
TransGen.trans
(move_ok (by decide)
(splitAtPred_eq _ _ [] (some Γ'.consₗ) L₃ (by rintro _ ⟨⟩) ⟨rfl, rfl⟩))
(TransGen.head rfl (TransGen.head rfl ?_))
rw [tr]
simp only [TM2.step, Option.mem_def, TM2.stepAux, ite_true, id_eq, trList, List.nil_append,
elim_update_stack, elim_rev, List.reverseAux_nil, elim_update_rev, Function.update_self,
List.headI_nil, trNat_default]
convert unrev_ok using 2
simp
· refine
TransGen.trans
(move_ok (by decide)
(splitAtPred_eq _ _ (trNat a) (some Γ'.cons) (trList L₂ ++ Γ'.consₗ :: L₃)
(trNat_natEnd _) ⟨rfl, by simp⟩))
(TransGen.head rfl (TransGen.head rfl ?_))
simp only [TM2.step, Option.mem_def, TM2.stepAux, ite_false, trList, List.append_assoc,
List.cons_append, elim_update_stack, elim_rev, elim_update_rev, Function.update_self,
List.headI_cons]
refine
TransGen.trans
(clear_ok
(splitAtPred_eq _ _ (trList L₂) (some Γ'.consₗ) L₃
(fun x h => Bool.decide_false (trList_ne_consₗ _ _ h)) ⟨rfl, by simp⟩))
?_
convert unrev_ok using 2
simp [List.reverseAux_eq]
theorem succ_ok {q s n} {c d : List Γ'} :
Reaches₁ (TM2.step tr) ⟨some (Λ'.succ q), s, K'.elim (trList [n]) [] c d⟩
⟨some q, none, K'.elim (trList [n.succ]) [] c d⟩ := by
simp only [TM2.step, trList, trNat.eq_1, Nat.cast_succ, Num.add_one]
rcases (n : Num) with - | a
· refine TransGen.head rfl ?_
simp only [Option.mem_def, TM2.stepAux, elim_main, decide_false, elim_update_main, ne_eq,
Function.update_of_ne, elim_rev, elim_update_rev, decide_true, Function.update_self,
cond_true, cond_false]
convert unrev_ok using 1
simp only [elim_update_rev, elim_rev, elim_main, List.reverseAux_nil, elim_update_main]
rfl
simp only [trNum, Num.succ, Num.succ']
suffices ∀ l₁, ∃ l₁' l₂' s',
List.reverseAux l₁ (trPosNum a.succ) = List.reverseAux l₁' l₂' ∧
Reaches₁ (TM2.step tr) ⟨some q.succ, s, K'.elim (trPosNum a ++ [Γ'.cons]) l₁ c d⟩
⟨some (unrev q), s', K'.elim (l₂' ++ [Γ'.cons]) l₁' c d⟩ by
obtain ⟨l₁', l₂', s', e, h⟩ := this []
simp? [List.reverseAux] at e says simp only [List.reverseAux, List.reverseAux_eq] at e
refine h.trans ?_
convert unrev_ok using 2
simp [e, List.reverseAux_eq]
induction' a with m IH m _ generalizing s <;> intro l₁
· refine ⟨Γ'.bit0 :: l₁, [Γ'.bit1], some Γ'.cons, rfl, TransGen.head rfl (TransGen.single ?_)⟩
simp [trPosNum]
· obtain ⟨l₁', l₂', s', e, h⟩ := IH (Γ'.bit0 :: l₁)
refine ⟨l₁', l₂', s', e, TransGen.head ?_ h⟩
simp [PosNum.succ, trPosNum]
rfl
· refine ⟨l₁, _, some Γ'.bit0, rfl, TransGen.single ?_⟩
simp only [TM2.step]; rw [tr]
simp only [TM2.stepAux, pop', elim_main, elim_update_main, ne_eq, Function.update_of_ne,
elim_rev, elim_update_rev, Function.update_self, Option.mem_def, Option.some.injEq]
rfl
theorem pred_ok (q₁ q₂ s v) (c d : List Γ') : ∃ s',
Reaches₁ (TM2.step tr) ⟨some (Λ'.pred q₁ q₂), s, K'.elim (trList v) [] c d⟩
(v.headI.rec ⟨some q₁, s', K'.elim (trList v.tail) [] c d⟩ fun n _ =>
⟨some q₂, s', K'.elim (trList (n::v.tail)) [] c d⟩) := by
rcases v with (_ | ⟨_ | n, v⟩)
· refine ⟨none, TransGen.single ?_⟩
simp
· refine ⟨some Γ'.cons, TransGen.single ?_⟩
simp
refine ⟨none, ?_⟩
simp only [TM2.step, trList, trNat.eq_1, trNum, Nat.cast_succ, Num.add_one, Num.succ,
List.tail_cons, List.headI_cons]
rcases (n : Num) with - | a
· simp only [trPosNum, Num.succ', List.singleton_append, List.nil_append]
refine TransGen.head rfl ?_
rw [tr]; simp only [pop', TM2.stepAux, cond_false]
convert unrev_ok using 2
simp
simp only [Num.succ']
suffices ∀ l₁, ∃ l₁' l₂' s',
List.reverseAux l₁ (trPosNum a) = List.reverseAux l₁' l₂' ∧
Reaches₁ (TM2.step tr)
⟨some (q₁.pred q₂), s, K'.elim (trPosNum a.succ ++ Γ'.cons :: trList v) l₁ c d⟩
⟨some (unrev q₂), s', K'.elim (l₂' ++ Γ'.cons :: trList v) l₁' c d⟩ by
obtain ⟨l₁', l₂', s', e, h⟩ := this []
simp only [List.reverseAux] at e
refine h.trans ?_
convert unrev_ok using 2
simp [e, List.reverseAux_eq]
induction' a with m IH m IH generalizing s <;> intro l₁
· refine ⟨Γ'.bit1::l₁, [], some Γ'.cons, rfl, TransGen.head rfl (TransGen.single ?_)⟩
simp [trPosNum, show PosNum.one.succ = PosNum.one.bit0 from rfl]
· obtain ⟨l₁', l₂', s', e, h⟩ := IH (some Γ'.bit0) (Γ'.bit1 :: l₁)
refine ⟨l₁', l₂', s', e, TransGen.head ?_ h⟩
simp
rfl
· obtain ⟨a, l, e, h⟩ : ∃ a l, (trPosNum m = a::l) ∧ natEnd a = false := by
cases m <;> refine ⟨_, _, rfl, rfl⟩
refine ⟨Γ'.bit0 :: l₁, _, some a, rfl, TransGen.single ?_⟩
simp [trPosNum, PosNum.succ, e, h, show some Γ'.bit1 ≠ some Γ'.bit0 by decide,
Option.iget, -natEnd]
rfl
theorem trNormal_respects (c k v s) :
∃ b₂,
TrCfg (stepNormal c k v) b₂ ∧
Reaches₁ (TM2.step tr)
⟨some (trNormal c (trCont k)), s, K'.elim (trList v) [] [] (trContStack k)⟩ b₂ := by
induction c generalizing k v s with
| zero' => refine ⟨_, ⟨s, rfl⟩, TransGen.single ?_⟩; simp
| succ => refine ⟨_, ⟨none, rfl⟩, head_main_ok.trans succ_ok⟩
| tail =>
let o : Option Γ' := List.casesOn v none fun _ _ => some Γ'.cons
refine ⟨_, ⟨o, rfl⟩, ?_⟩; convert clear_ok _ using 2
· simp; rfl
swap
refine splitAtPred_eq _ _ (trNat v.headI) _ _ (trNat_natEnd _) ?_
cases v <;> simp [o]
| cons f fs IHf _ =>
obtain ⟨c, h₁, h₂⟩ := IHf (Cont.cons₁ fs v k) v none
refine ⟨c, h₁, TransGen.head rfl <| (move_ok (by decide) (splitAtPred_false _)).trans ?_⟩
simp only [TM2.step, Option.mem_def, elim_stack, elim_update_stack, elim_update_main, ne_eq,
Function.update_of_ne, elim_main, elim_rev, elim_update_rev]
refine (copy_ok _ none [] (trList v).reverse _ _).trans ?_
convert h₂ using 2
simp [List.reverseAux_eq, trContStack]
| comp f _ _ IHg => exact IHg (Cont.comp f k) v s
| case f g IHf IHg =>
rw [stepNormal]
simp only
obtain ⟨s', h⟩ := pred_ok _ _ s v _ _
revert h; rcases v.headI with - | n <;> intro h
· obtain ⟨c, h₁, h₂⟩ := IHf k _ s'
exact ⟨_, h₁, h.trans h₂⟩
· obtain ⟨c, h₁, h₂⟩ := IHg k _ s'
exact ⟨_, h₁, h.trans h₂⟩
| fix f IH => apply IH
theorem tr_ret_respects (k v s) : ∃ b₂,
TrCfg (stepRet k v) b₂ ∧
Reaches₁ (TM2.step tr)
⟨some (Λ'.ret (trCont k)), s, K'.elim (trList v) [] [] (trContStack k)⟩ b₂ := by
induction k generalizing v s with
| halt => exact ⟨_, rfl, TransGen.single rfl⟩
| cons₁ fs as k _ =>
obtain ⟨s', h₁, h₂⟩ := trNormal_respects fs (Cont.cons₂ v k) as none
refine ⟨s', h₁, TransGen.head rfl ?_⟩; simp
refine (move₂_ok (by decide) ?_ (splitAtPred_false _)).trans ?_; · rfl
simp only [TM2.step, Option.mem_def, Option.elim, id_eq, elim_update_main, elim_main, elim_aux,
List.append_nil, elim_update_aux]
refine (move₂_ok (L₁ := ?_) (o := ?_) (L₂ := ?_) (by decide) rfl ?_).trans ?_
pick_goal 4
· exact splitAtPred_eq _ _ _ (some Γ'.consₗ) _
(fun x h => Bool.decide_false (trList_ne_consₗ _ _ h)) ⟨rfl, rfl⟩
refine (move₂_ok (by decide) ?_ (splitAtPred_false _)).trans ?_; · rfl
simp only [TM2.step, Option.mem_def, Option.elim, elim_update_stack, elim_main,
List.append_nil, elim_update_main, id_eq, elim_update_aux, ne_eq, Function.update_of_ne,
elim_aux, elim_stack]
exact h₂
| cons₂ ns k IH =>
obtain ⟨c, h₁, h₂⟩ := IH (ns.headI :: v) none
exact ⟨c, h₁, TransGen.head rfl <| head_stack_ok.trans h₂⟩
| comp f k _ =>
obtain ⟨s', h₁, h₂⟩ := trNormal_respects f k v s
exact ⟨_, h₁, TransGen.head rfl h₂⟩
| fix f k IH =>
rw [stepRet]
have :
if v.headI = 0 then natEnd (trList v).head?.iget = true ∧ (trList v).tail = trList v.tail
else
natEnd (trList v).head?.iget = false ∧
(trList v).tail = (trNat v.headI).tail ++ Γ'.cons :: trList v.tail := by
obtain - | n := v
· exact ⟨rfl, rfl⟩
rcases n with - | n
· simp
rw [trList, List.headI, trNat, Nat.cast_succ, Num.add_one, Num.succ, List.tail]
cases (n : Num).succ' <;> exact ⟨rfl, rfl⟩
by_cases h : v.headI = 0 <;> simp only [h, ite_true, ite_false] at this ⊢
· obtain ⟨c, h₁, h₂⟩ := IH v.tail (trList v).head?
refine ⟨c, h₁, TransGen.head rfl ?_⟩
rw [trCont, tr]; simp only [pop', TM2.stepAux, elim_main, this, elim_update_main]
exact h₂
· obtain ⟨s', h₁, h₂⟩ := trNormal_respects f (Cont.fix f k) v.tail (some Γ'.cons)
refine ⟨_, h₁, TransGen.head rfl <| TransGen.trans ?_ h₂⟩
rw [trCont, tr]; simp only [pop', TM2.stepAux, elim_main, this.1]
convert clear_ok (splitAtPred_eq _ _ (trNat v.headI).tail (some Γ'.cons) _ _ _) using 2
· simp
convert rfl
· exact fun x h => trNat_natEnd _ _ (List.tail_subset _ h)
· exact ⟨rfl, this.2⟩
theorem tr_respects : Respects step (TM2.step tr) TrCfg
| Cfg.ret _ _, _, ⟨_, rfl⟩ => tr_ret_respects _ _ _
| Cfg.halt _, _, rfl => rfl
/-- The initial state, evaluating function `c` on input `v`. -/
def init (c : Code) (v : List ℕ) : Cfg' :=
⟨some (trNormal c Cont'.halt), none, K'.elim (trList v) [] [] []⟩
theorem tr_init (c v) :
∃ b, TrCfg (stepNormal c Cont.halt v) b ∧ Reaches₁ (TM2.step tr) (init c v) b :=
trNormal_respects _ _ _ _
theorem tr_eval (c v) : eval (TM2.step tr) (init c v) = halt <$> Code.eval c v := by
obtain ⟨i, h₁, h₂⟩ := tr_init c v
refine Part.ext fun x => ?_
rw [reaches_eval h₂.to_reflTransGen]; simp only [Part.map_eq_map, Part.mem_map_iff]
refine ⟨fun h => ?_, ?_⟩
· obtain ⟨c, hc₁, hc₂⟩ := tr_eval_rev tr_respects h₁ h
simp [stepNormal_eval] at hc₂
obtain ⟨v', hv, rfl⟩ := hc₂
exact ⟨_, hv, hc₁.symm⟩
· rintro ⟨v', hv, rfl⟩
have := Turing.tr_eval (b₁ := Cfg.halt v') tr_respects h₁
simp only [stepNormal_eval, Part.map_eq_map, Part.mem_map_iff, Cfg.halt.injEq,
exists_eq_right] at this
obtain ⟨_, ⟨⟩, h⟩ := this hv
exact h
/-- The set of machine states reachable via downward label jumps, discounting jumps via `ret`. -/
def trStmts₁ : Λ' → Finset Λ'
| Q@(Λ'.move _ _ _ q) => insert Q <| trStmts₁ q
| Q@(Λ'.push _ _ q) => insert Q <| trStmts₁ q
| Q@(Λ'.read q) => insert Q <| Finset.univ.biUnion fun s => trStmts₁ (q s)
| Q@(Λ'.clear _ _ q) => insert Q <| trStmts₁ q
| Q@(Λ'.copy q) => insert Q <| trStmts₁ q
| Q@(Λ'.succ q) => insert Q <| insert (unrev q) <| trStmts₁ q
| Q@(Λ'.pred q₁ q₂) => insert Q <| trStmts₁ q₁ ∪ insert (unrev q₂) (trStmts₁ q₂)
| Q@(Λ'.ret _) => {Q}
theorem trStmts₁_trans {q q'} : q' ∈ trStmts₁ q → trStmts₁ q' ⊆ trStmts₁ q := by
induction q with
| move _ _ _ q q_ih => _ | clear _ _ q q_ih => _ | copy q q_ih => _ | push _ _ q q_ih => _
| read q q_ih => _ | succ q q_ih => _ | pred q₁ q₂ q₁_ih q₂_ih => _ | ret => _ <;>
all_goals
simp +contextual only [trStmts₁, Finset.mem_insert, Finset.mem_union,
or_imp, Finset.mem_singleton, Finset.Subset.refl, imp_true_iff, true_and]
repeat exact fun h => Finset.Subset.trans (q_ih h) (Finset.subset_insert _ _)
· simp
intro s h x h'
simp only [Finset.mem_biUnion, Finset.mem_univ, true_and, Finset.mem_insert]
exact Or.inr ⟨_, q_ih s h h'⟩
· constructor
· rintro rfl
apply Finset.subset_insert
· intro h x h'
simp only [Finset.mem_insert]
exact Or.inr (Or.inr <| q_ih h h')
· refine ⟨fun h x h' => ?_, fun _ x h' => ?_, fun h x h' => ?_⟩ <;> simp
· exact Or.inr (Or.inr <| Or.inl <| q₁_ih h h')
· rcases Finset.mem_insert.1 h' with h' | h' <;> simp [h', unrev]
· exact Or.inr (Or.inr <| Or.inr <| q₂_ih h h')
theorem trStmts₁_self (q) : q ∈ trStmts₁ q := by
induction q <;> · first |apply Finset.mem_singleton_self|apply Finset.mem_insert_self
/-- The (finite!) set of machine states visited during the course of evaluation of `c`,
including the state `ret k` but not any states after that (that is, the states visited while
evaluating `k`). -/
def codeSupp' : Code → Cont' → Finset Λ'
| c@Code.zero', k => trStmts₁ (trNormal c k)
| c@Code.succ, k => trStmts₁ (trNormal c k)
| c@Code.tail, k => trStmts₁ (trNormal c k)
| c@(Code.cons f fs), k =>
trStmts₁ (trNormal c k) ∪
(codeSupp' f (Cont'.cons₁ fs k) ∪
(trStmts₁
(move₂ (fun _ => false) main aux <|
move₂ (fun s => s = Γ'.consₗ) stack main <|
move₂ (fun _ => false) aux stack <| trNormal fs (Cont'.cons₂ k)) ∪
(codeSupp' fs (Cont'.cons₂ k) ∪ trStmts₁ (head stack <| Λ'.ret k))))
| c@(Code.comp f g), k =>
trStmts₁ (trNormal c k) ∪
(codeSupp' g (Cont'.comp f k) ∪ (trStmts₁ (trNormal f k) ∪ codeSupp' f k))
| c@(Code.case f g), k => trStmts₁ (trNormal c k) ∪ (codeSupp' f k ∪ codeSupp' g k)
| c@(Code.fix f), k =>
trStmts₁ (trNormal c k) ∪
(codeSupp' f (Cont'.fix f k) ∪
(trStmts₁ (Λ'.clear natEnd main <| trNormal f (Cont'.fix f k)) ∪ {Λ'.ret k}))
@[simp]
theorem codeSupp'_self (c k) : trStmts₁ (trNormal c k) ⊆ codeSupp' c k := by
cases c <;> first | rfl | exact Finset.union_subset_left (fun _ a ↦ a)
/-- The (finite!) set of machine states visited during the course of evaluation of a continuation
`k`, not including the initial state `ret k`. -/
def contSupp : Cont' → Finset Λ'
| Cont'.cons₁ fs k =>
trStmts₁
(move₂ (fun _ => false) main aux <|
move₂ (fun s => s = Γ'.consₗ) stack main <|
move₂ (fun _ => false) aux stack <| trNormal fs (Cont'.cons₂ k)) ∪
(codeSupp' fs (Cont'.cons₂ k) ∪ (trStmts₁ (head stack <| Λ'.ret k) ∪ contSupp k))
| Cont'.cons₂ k => trStmts₁ (head stack <| Λ'.ret k) ∪ contSupp k
| Cont'.comp f k => codeSupp' f k ∪ contSupp k
| Cont'.fix f k => codeSupp' (Code.fix f) k ∪ contSupp k
| Cont'.halt => ∅
/-- The (finite!) set of machine states visited during the course of evaluation of `c` in
continuation `k`. This is actually closed under forward simulation (see `tr_supports`), and the
existence of this set means that the machine constructed in this section is in fact a proper
Turing machine, with a finite set of states. -/
def codeSupp (c : Code) (k : Cont') : Finset Λ' :=
codeSupp' c k ∪ contSupp k
@[simp]
theorem codeSupp_self (c k) : trStmts₁ (trNormal c k) ⊆ codeSupp c k :=
Finset.Subset.trans (codeSupp'_self _ _) (Finset.union_subset_left fun _ a ↦ a)
@[simp]
theorem codeSupp_zero (k) : codeSupp Code.zero' k = trStmts₁ (trNormal Code.zero' k) ∪ contSupp k :=
rfl
@[simp]
theorem codeSupp_succ (k) : codeSupp Code.succ k = trStmts₁ (trNormal Code.succ k) ∪ contSupp k :=
rfl
@[simp]
theorem codeSupp_tail (k) : codeSupp Code.tail k = trStmts₁ (trNormal Code.tail k) ∪ contSupp k :=
rfl
@[simp]
theorem codeSupp_cons (f fs k) :
codeSupp (Code.cons f fs) k =
trStmts₁ (trNormal (Code.cons f fs) k) ∪ codeSupp f (Cont'.cons₁ fs k) := by
simp [codeSupp, codeSupp', contSupp, Finset.union_assoc]
@[simp]
theorem codeSupp_comp (f g k) :
codeSupp (Code.comp f g) k =
trStmts₁ (trNormal (Code.comp f g) k) ∪ codeSupp g (Cont'.comp f k) := by
simp only [codeSupp, codeSupp', trNormal, Finset.union_assoc, contSupp]
rw [← Finset.union_assoc _ _ (contSupp k),
Finset.union_eq_right.2 (codeSupp'_self _ _)]
@[simp]
theorem codeSupp_case (f g k) :
codeSupp (Code.case f g) k =
trStmts₁ (trNormal (Code.case f g) k) ∪ (codeSupp f k ∪ codeSupp g k) := by
simp [codeSupp, codeSupp', contSupp, Finset.union_assoc, Finset.union_left_comm]
@[simp]
theorem codeSupp_fix (f k) :
codeSupp (Code.fix f) k = trStmts₁ (trNormal (Code.fix f) k) ∪ codeSupp f (Cont'.fix f k) := by
simp [codeSupp, codeSupp', contSupp, Finset.union_assoc, Finset.union_left_comm,
Finset.union_left_idem]
@[simp]
theorem contSupp_cons₁ (fs k) :
contSupp (Cont'.cons₁ fs k) =
trStmts₁
(move₂ (fun _ => false) main aux <|
move₂ (fun s => s = Γ'.consₗ) stack main <|
move₂ (fun _ => false) aux stack <| trNormal fs (Cont'.cons₂ k)) ∪
codeSupp fs (Cont'.cons₂ k) := by
simp [codeSupp, codeSupp', contSupp, Finset.union_assoc]
@[simp]
theorem contSupp_cons₂ (k) :
contSupp (Cont'.cons₂ k) = trStmts₁ (head stack <| Λ'.ret k) ∪ contSupp k :=
rfl
@[simp]
theorem contSupp_comp (f k) : contSupp (Cont'.comp f k) = codeSupp f k :=
rfl
theorem contSupp_fix (f k) : contSupp (Cont'.fix f k) = codeSupp f (Cont'.fix f k) := by
simp +contextual [codeSupp, codeSupp', contSupp, Finset.union_assoc,
Finset.subset_iff]
@[simp]
theorem contSupp_halt : contSupp Cont'.halt = ∅ :=
rfl
/-- The statement `Λ'.Supports S q` means that `contSupp k ⊆ S` for any `ret k`
reachable from `q`.
(This is a technical condition used in the proof that the machine is supported.) -/
def Λ'.Supports (S : Finset Λ') : Λ' → Prop
| Λ'.move _ _ _ q => Λ'.Supports S q
| Λ'.push _ _ q => Λ'.Supports S q
| Λ'.read q => ∀ s, Λ'.Supports S (q s)
| Λ'.clear _ _ q => Λ'.Supports S q
| Λ'.copy q => Λ'.Supports S q
| Λ'.succ q => Λ'.Supports S q
| Λ'.pred q₁ q₂ => Λ'.Supports S q₁ ∧ Λ'.Supports S q₂
| Λ'.ret k => contSupp k ⊆ S
/-- A shorthand for the predicate that we are proving in the main theorems `trStmts₁_supports`,
`codeSupp'_supports`, `contSupp_supports`, `codeSupp_supports`. The set `S` is fixed throughout
the proof, and denotes the full set of states in the machine, while `K` is a subset that we are
currently proving a property about. The predicate asserts that every state in `K` is closed in `S`
under forward simulation, i.e. stepping forward through evaluation starting from any state in `K`
stays entirely within `S`. -/
def Supports (K S : Finset Λ') :=
∀ q ∈ K, TM2.SupportsStmt S (tr q)
theorem supports_insert {K S q} :
Supports (insert q K) S ↔ TM2.SupportsStmt S (tr q) ∧ Supports K S := by simp [Supports]
theorem supports_singleton {S q} : Supports {q} S ↔ TM2.SupportsStmt S (tr q) := by simp [Supports]
theorem supports_union {K₁ K₂ S} : Supports (K₁ ∪ K₂) S ↔ Supports K₁ S ∧ Supports K₂ S := by
simp [Supports, or_imp, forall_and]
theorem supports_biUnion {K : Option Γ' → Finset Λ'} {S} :
Supports (Finset.univ.biUnion K) S ↔ ∀ a, Supports (K a) S := by
simpa [Supports] using forall_swap
theorem head_supports {S k q} (H : (q : Λ').Supports S) : (head k q).Supports S := fun _ => by
dsimp only; split_ifs <;> exact H
theorem ret_supports {S k} (H₁ : contSupp k ⊆ S) : TM2.SupportsStmt S (tr (Λ'.ret k)) := by
have W := fun {q} => trStmts₁_self q
cases k with
| halt => trivial
| cons₁ => rw [contSupp_cons₁, Finset.union_subset_iff] at H₁; exact fun _ => H₁.1 W
| cons₂ => rw [contSupp_cons₂, Finset.union_subset_iff] at H₁; exact fun _ => H₁.1 W
| comp => rw [contSupp_comp] at H₁; exact fun _ => H₁ (codeSupp_self _ _ W)
| fix =>
rw [contSupp_fix] at H₁
have L := @Finset.mem_union_left; have R := @Finset.mem_union_right
intro s; dsimp only; cases natEnd s.iget
· refine H₁ (R _ <| L _ <| R _ <| R _ <| L _ W)
· exact H₁ (R _ <| L _ <| R _ <| R _ <| R _ <| Finset.mem_singleton_self _)
theorem trStmts₁_supports {S q} (H₁ : (q : Λ').Supports S) (HS₁ : trStmts₁ q ⊆ S) :
Supports (trStmts₁ q) S := by
have W := fun {q} => trStmts₁_self q
induction q with
| move _ _ _ q q_ih => _ | clear _ _ q q_ih => _ | copy q q_ih => _ | push _ _ q q_ih => _
| read q q_ih => _ | succ q q_ih => _ | pred q₁ q₂ q₁_ih q₂_ih => _ | ret => _ <;>
simp [trStmts₁, -Finset.singleton_subset_iff] at HS₁ ⊢
any_goals
obtain ⟨h₁, h₂⟩ := Finset.insert_subset_iff.1 HS₁
first | have h₃ := h₂ W | try simp [Finset.subset_iff] at h₂
· exact supports_insert.2 ⟨⟨fun _ => h₃, fun _ => h₁⟩, q_ih H₁ h₂⟩ -- move
· exact supports_insert.2 ⟨⟨fun _ => h₃, fun _ => h₁⟩, q_ih H₁ h₂⟩ -- clear
· exact supports_insert.2 ⟨⟨fun _ => h₁, fun _ => h₃⟩, q_ih H₁ h₂⟩ -- copy
· exact supports_insert.2 ⟨⟨fun _ => h₃, fun _ => h₃⟩, q_ih H₁ h₂⟩ -- push
· refine supports_insert.2 ⟨fun _ => h₂ _ W, ?_⟩ -- read
exact supports_biUnion.2 fun _ => q_ih _ (H₁ _) fun _ h => h₂ _ h
· refine supports_insert.2 ⟨⟨fun _ => h₁, fun _ => h₂.1, fun _ => h₂.1⟩, ?_⟩ -- succ
exact supports_insert.2 ⟨⟨fun _ => h₂.2 _ W, fun _ => h₂.1⟩, q_ih H₁ h₂.2⟩
· refine -- pred
supports_insert.2 ⟨⟨fun _ => h₁, fun _ => h₂.2 _ (Or.inl W),
fun _ => h₂.1, fun _ => h₂.1⟩, ?_⟩
refine supports_insert.2 ⟨⟨fun _ => h₂.2 _ (Or.inr W), fun _ => h₂.1⟩, ?_⟩
refine supports_union.2 ⟨?_, ?_⟩
· exact q₁_ih H₁.1 fun _ h => h₂.2 _ (Or.inl h)
· exact q₂_ih H₁.2 fun _ h => h₂.2 _ (Or.inr h)
· exact supports_singleton.2 (ret_supports H₁) -- ret
theorem trStmts₁_supports' {S q K} (H₁ : (q : Λ').Supports S) (H₂ : trStmts₁ q ∪ K ⊆ S)
(H₃ : K ⊆ S → Supports K S) : Supports (trStmts₁ q ∪ K) S := by
simp only [Finset.union_subset_iff] at H₂
exact supports_union.2 ⟨trStmts₁_supports H₁ H₂.1, H₃ H₂.2⟩
theorem trNormal_supports {S c k} (Hk : codeSupp c k ⊆ S) : (trNormal c k).Supports S := by
induction c generalizing k with simp [Λ'.Supports, head]
| zero' => exact Finset.union_subset_right Hk
| succ => intro; split_ifs <;> exact Finset.union_subset_right Hk
| tail => exact Finset.union_subset_right Hk
| cons f fs IHf _ =>
apply IHf
rw [codeSupp_cons] at Hk
exact Finset.union_subset_right Hk
| comp f g _ IHg => apply IHg; rw [codeSupp_comp] at Hk; exact Finset.union_subset_right Hk
| case f g IHf IHg =>
simp only [codeSupp_case, Finset.union_subset_iff] at Hk
exact ⟨IHf Hk.2.1, IHg Hk.2.2⟩
| fix f IHf => apply IHf; rw [codeSupp_fix] at Hk; exact Finset.union_subset_right Hk
theorem codeSupp'_supports {S c k} (H : codeSupp c k ⊆ S) : Supports (codeSupp' c k) S := by
induction c generalizing k with
| cons f fs IHf IHfs =>
have H' := H; simp only [codeSupp_cons, Finset.union_subset_iff] at H'
refine trStmts₁_supports' (trNormal_supports H) (Finset.union_subset_left H) fun h => ?_
refine supports_union.2 ⟨IHf H'.2, ?_⟩
refine trStmts₁_supports' (trNormal_supports ?_) (Finset.union_subset_right h) fun h => ?_
· simp only [codeSupp, Finset.union_subset_iff, contSupp] at h H ⊢
exact ⟨h.2.2.1, h.2.2.2, H.2⟩
refine supports_union.2 ⟨IHfs ?_, ?_⟩
· rw [codeSupp, contSupp_cons₁] at H'
exact Finset.union_subset_right (Finset.union_subset_right H'.2)
exact
trStmts₁_supports (head_supports <| Finset.union_subset_right H)
(Finset.union_subset_right h)
| comp f g IHf IHg =>
have H' := H; rw [codeSupp_comp] at H'; have H' := Finset.union_subset_right H'
refine trStmts₁_supports' (trNormal_supports H) (Finset.union_subset_left H) fun h => ?_
refine supports_union.2 ⟨IHg H', ?_⟩
refine trStmts₁_supports' (trNormal_supports ?_) (Finset.union_subset_right h) fun _ => ?_
· simp only [codeSupp', codeSupp, Finset.union_subset_iff, contSupp] at h H ⊢
exact ⟨h.2.2, H.2⟩
exact IHf (Finset.union_subset_right H')
| case f g IHf IHg =>
have H' := H; simp only [codeSupp_case, Finset.union_subset_iff] at H'
refine trStmts₁_supports' (trNormal_supports H) (Finset.union_subset_left H) fun _ => ?_
exact supports_union.2 ⟨IHf H'.2.1, IHg H'.2.2⟩
| fix f IHf =>
have H' := H; simp only [codeSupp_fix, Finset.union_subset_iff] at H'
refine trStmts₁_supports' (trNormal_supports H) (Finset.union_subset_left H) fun h => ?_
refine supports_union.2 ⟨IHf H'.2, ?_⟩
refine trStmts₁_supports' (trNormal_supports ?_) (Finset.union_subset_right h) fun _ => ?_
· simp only [codeSupp', codeSupp, Finset.union_subset_iff, contSupp, trStmts₁,
Finset.insert_subset_iff] at h H ⊢
exact ⟨h.1, ⟨H.1.1, h⟩, H.2⟩
exact supports_singleton.2 (ret_supports <| Finset.union_subset_right H)
| _ => exact trStmts₁_supports (trNormal_supports H) (Finset.Subset.trans (codeSupp_self _ _) H)
theorem contSupp_supports {S k} (H : contSupp k ⊆ S) : Supports (contSupp k) S := by
induction k with
| halt => simp [contSupp_halt, Supports]
| cons₁ f k IH =>
have H₁ := H; rw [contSupp_cons₁] at H₁; have H₂ := Finset.union_subset_right H₁
refine trStmts₁_supports' (trNormal_supports H₂) H₁ fun h => ?_
refine supports_union.2 ⟨codeSupp'_supports H₂, ?_⟩
simp only [codeSupp, contSupp_cons₂, Finset.union_subset_iff] at H₂
exact trStmts₁_supports' (head_supports H₂.2.2) (Finset.union_subset_right h) IH
| cons₂ k IH =>
have H' := H; rw [contSupp_cons₂] at H'
exact trStmts₁_supports' (head_supports <| Finset.union_subset_right H') H' IH
| comp f k IH =>
have H' := H; rw [contSupp_comp] at H'; have H₂ := Finset.union_subset_right H'
exact supports_union.2 ⟨codeSupp'_supports H', IH H₂⟩
| fix f k IH =>
rw [contSupp] at H
exact supports_union.2 ⟨codeSupp'_supports H, IH (Finset.union_subset_right H)⟩
theorem codeSupp_supports {S c k} (H : codeSupp c k ⊆ S) : Supports (codeSupp c k) S :=
supports_union.2 ⟨codeSupp'_supports H, contSupp_supports (Finset.union_subset_right H)⟩
/-- The set `codeSupp c k` is a finite set that witnesses the effective finiteness of the `tr`
Turing machine. Starting from the initial state `trNormal c k`, forward simulation uses only
states in `codeSupp c k`, so this is a finite state machine. Even though the underlying type of
state labels `Λ'` is infinite, for a given partial recursive function `c` and continuation `k`,
only finitely many states are accessed, corresponding roughly to subterms of `c`. -/
theorem tr_supports (c k) : @TM2.Supports _ _ _ _ ⟨trNormal c k⟩ tr (codeSupp c k) :=
⟨codeSupp_self _ _ (trStmts₁_self _), fun _ => codeSupp_supports (Finset.Subset.refl _) _⟩
end
end PartrecToTM2
end Turing
| Mathlib/Computability/TMToPartrec.lean | 1,932 | 1,944 | |
/-
Copyright (c) 2021 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.Analysis.SpecialFunctions.Pow.Real
import Mathlib.LinearAlgebra.FreeModule.PID
import Mathlib.LinearAlgebra.Matrix.AbsoluteValue
import Mathlib.NumberTheory.ClassNumber.AdmissibleAbsoluteValue
import Mathlib.RingTheory.ClassGroup
import Mathlib.RingTheory.DedekindDomain.IntegralClosure
import Mathlib.RingTheory.Norm.Basic
/-!
# Class numbers of global fields
In this file, we use the notion of "admissible absolute value" to prove
finiteness of the class group for number fields and function fields.
## Main definitions
- `ClassGroup.fintypeOfAdmissibleOfAlgebraic`: if `R` has an admissible absolute value,
its integral closure has a finite class group
-/
open scoped nonZeroDivisors
namespace ClassGroup
open Ring
section EuclideanDomain
variable {R S : Type*} (K L : Type*) [EuclideanDomain R] [CommRing S] [IsDomain S]
variable [Field K] [Field L]
variable [Algebra R K] [IsFractionRing R K]
variable [Algebra K L] [FiniteDimensional K L] [Algebra.IsSeparable K L]
variable [algRL : Algebra R L] [IsScalarTower R K L]
variable [Algebra R S] [Algebra S L]
variable [ist : IsScalarTower R S L]
variable (abv : AbsoluteValue R ℤ)
variable {ι : Type*} [DecidableEq ι] [Fintype ι] (bS : Basis ι R S)
/-- If `b` is an `R`-basis of `S` of cardinality `n`, then `normBound abv b` is an integer
such that for every `R`-integral element `a : S` with coordinates `≤ y`,
we have algebra.norm a ≤ norm_bound abv b * y ^ n`. (See also `norm_le` and `norm_lt`). -/
noncomputable def normBound : ℤ :=
let n := Fintype.card ι
let i : ι := Nonempty.some bS.index_nonempty
let m : ℤ :=
Finset.max'
(Finset.univ.image fun ijk : ι × ι × ι =>
abv (Algebra.leftMulMatrix bS (bS ijk.1) ijk.2.1 ijk.2.2))
⟨_, Finset.mem_image.mpr ⟨⟨i, i, i⟩, Finset.mem_univ _, rfl⟩⟩
Nat.factorial n • (n • m) ^ n
theorem normBound_pos : 0 < normBound abv bS := by
obtain ⟨i, j, k, hijk⟩ : ∃ i j k, Algebra.leftMulMatrix bS (bS i) j k ≠ 0 := by
by_contra! h
| obtain ⟨i⟩ := bS.index_nonempty
apply bS.ne_zero i
apply
(injective_iff_map_eq_zero (Algebra.leftMulMatrix bS)).mp (Algebra.leftMulMatrix_injective bS)
ext j k
simp [h, DMatrix.zero_apply]
simp only [normBound, Algebra.smul_def, eq_natCast]
apply mul_pos (Int.natCast_pos.mpr (Nat.factorial_pos _))
refine pow_pos (mul_pos (Int.natCast_pos.mpr (Fintype.card_pos_iff.mpr ⟨i⟩)) ?_) _
refine lt_of_lt_of_le (abv.pos hijk) (Finset.le_max' _ _ ?_)
exact Finset.mem_image.mpr ⟨⟨i, j, k⟩, Finset.mem_univ _, rfl⟩
/-- If the `R`-integral element `a : S` has coordinates `≤ y` with respect to some basis `b`,
its norm is less than `normBound abv b * y ^ dim S`. -/
| Mathlib/NumberTheory/ClassNumber/Finite.lean | 58 | 71 |
/-
Copyright (c) 2021 Julian Kuelshammer. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Julian Kuelshammer
-/
import Mathlib.Algebra.CharP.Algebra
import Mathlib.Algebra.CharP.Invertible
import Mathlib.Algebra.CharP.Lemmas
import Mathlib.Algebra.EuclideanDomain.Field
import Mathlib.Algebra.Field.ZMod
import Mathlib.Algebra.Polynomial.Roots
import Mathlib.RingTheory.Polynomial.Chebyshev
/-!
# Dickson polynomials
The (generalised) Dickson polynomials are a family of polynomials indexed by `ℕ × ℕ`,
with coefficients in a commutative ring `R` depending on an element `a∈R`. More precisely, the
they satisfy the recursion `dickson k a (n + 2) = X * (dickson k a n + 1) - a * (dickson k a n)`
with starting values `dickson k a 0 = 3 - k` and `dickson k a 1 = X`. In the literature,
`dickson k a n` is called the `n`-th Dickson polynomial of the `k`-th kind associated to the
parameter `a : R`. They are closely related to the Chebyshev polynomials in the case that `a=1`.
When `a=0` they are just the family of monomials `X ^ n`.
## Main definition
* `Polynomial.dickson`: the generalised Dickson polynomials.
## Main statements
* `Polynomial.dickson_one_one_mul`, the `(m * n)`-th Dickson polynomial of the first kind for
parameter `1 : R` is the composition of the `m`-th and `n`-th Dickson polynomials of the first
kind for `1 : R`.
* `Polynomial.dickson_one_one_charP`, for a prime number `p`, the `p`-th Dickson polynomial of the
first kind associated to parameter `1 : R` is congruent to `X ^ p` modulo `p`.
## References
* [R. Lidl, G. L. Mullen and G. Turnwald, _Dickson polynomials_][MR1237403]
## TODO
* Redefine `dickson` in terms of `LinearRecurrence`.
* Show that `dickson 2 1` is equal to the characteristic polynomial of the adjacency matrix of a
type A Dynkin diagram.
* Prove that the adjacency matrices of simply laced Dynkin diagrams are precisely the adjacency
matrices of simple connected graphs which annihilate `dickson 2 1`.
-/
noncomputable section
namespace Polynomial
variable {R S : Type*} [CommRing R] [CommRing S] (k : ℕ) (a : R)
/-- `dickson` is the `n`-th (generalised) Dickson polynomial of the `k`-th kind associated to the
element `a ∈ R`. -/
noncomputable def dickson : ℕ → R[X]
| 0 => 3 - k
| 1 => X
| n + 2 => X * dickson (n + 1) - C a * dickson n
@[simp]
theorem dickson_zero : dickson k a 0 = 3 - k :=
rfl
@[simp]
theorem dickson_one : dickson k a 1 = X :=
rfl
theorem dickson_two : dickson k a 2 = X ^ 2 - C a * (3 - k : R[X]) := by
simp only [dickson, sq]
@[simp]
theorem dickson_add_two (n : ℕ) :
dickson k a (n + 2) = X * dickson k a (n + 1) - C a * dickson k a n := by rw [dickson]
theorem dickson_of_two_le {n : ℕ} (h : 2 ≤ n) :
dickson k a n = X * dickson k a (n - 1) - C a * dickson k a (n - 2) := by
obtain ⟨n, rfl⟩ := Nat.exists_eq_add_of_le h
| rw [add_comm]
exact dickson_add_two k a n
| Mathlib/RingTheory/Polynomial/Dickson.lean | 82 | 83 |
/-
Copyright (c) 2020 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne, Sébastien Gouëzel
-/
import Mathlib.Analysis.NormedSpace.IndicatorFunction
import Mathlib.Data.Fintype.Order
import Mathlib.MeasureTheory.Function.AEEqFun
import Mathlib.MeasureTheory.Function.LpSeminorm.Defs
import Mathlib.MeasureTheory.Function.SpecialFunctions.Basic
import Mathlib.MeasureTheory.Integral.Lebesgue.Countable
import Mathlib.MeasureTheory.Integral.Lebesgue.Sub
/-!
# Basic theorems about ℒp space
-/
noncomputable section
open TopologicalSpace MeasureTheory Filter
open scoped NNReal ENNReal Topology ComplexConjugate
variable {α ε ε' E F G : Type*} {m m0 : MeasurableSpace α} {p : ℝ≥0∞} {q : ℝ} {μ ν : Measure α}
[NormedAddCommGroup E] [NormedAddCommGroup F] [NormedAddCommGroup G] [ENorm ε] [ENorm ε']
namespace MeasureTheory
section Lp
section Top
theorem MemLp.eLpNorm_lt_top [TopologicalSpace ε] {f : α → ε} (hfp : MemLp f p μ) :
eLpNorm f p μ < ∞ :=
hfp.2
@[deprecated (since := "2025-02-21")]
alias Memℒp.eLpNorm_lt_top := MemLp.eLpNorm_lt_top
theorem MemLp.eLpNorm_ne_top [TopologicalSpace ε] {f : α → ε} (hfp : MemLp f p μ) :
eLpNorm f p μ ≠ ∞ :=
ne_of_lt hfp.2
@[deprecated (since := "2025-02-21")]
alias Memℒp.eLpNorm_ne_top := MemLp.eLpNorm_ne_top
theorem lintegral_rpow_enorm_lt_top_of_eLpNorm'_lt_top {f : α → ε} (hq0_lt : 0 < q)
(hfq : eLpNorm' f q μ < ∞) : ∫⁻ a, ‖f a‖ₑ ^ q ∂μ < ∞ := by
rw [lintegral_rpow_enorm_eq_rpow_eLpNorm' hq0_lt]
exact ENNReal.rpow_lt_top_of_nonneg (le_of_lt hq0_lt) (ne_of_lt hfq)
@[deprecated (since := "2025-01-17")]
alias lintegral_rpow_nnnorm_lt_top_of_eLpNorm'_lt_top' :=
lintegral_rpow_enorm_lt_top_of_eLpNorm'_lt_top
theorem lintegral_rpow_enorm_lt_top_of_eLpNorm_lt_top {f : α → ε} (hp_ne_zero : p ≠ 0)
(hp_ne_top : p ≠ ∞) (hfp : eLpNorm f p μ < ∞) : ∫⁻ a, ‖f a‖ₑ ^ p.toReal ∂μ < ∞ := by
apply lintegral_rpow_enorm_lt_top_of_eLpNorm'_lt_top
· exact ENNReal.toReal_pos hp_ne_zero hp_ne_top
· simpa [eLpNorm_eq_eLpNorm' hp_ne_zero hp_ne_top] using hfp
@[deprecated (since := "2025-01-17")]
alias lintegral_rpow_nnnorm_lt_top_of_eLpNorm_lt_top :=
lintegral_rpow_enorm_lt_top_of_eLpNorm_lt_top
theorem eLpNorm_lt_top_iff_lintegral_rpow_enorm_lt_top {f : α → ε} (hp_ne_zero : p ≠ 0)
(hp_ne_top : p ≠ ∞) : eLpNorm f p μ < ∞ ↔ ∫⁻ a, (‖f a‖ₑ) ^ p.toReal ∂μ < ∞ :=
⟨lintegral_rpow_enorm_lt_top_of_eLpNorm_lt_top hp_ne_zero hp_ne_top, by
intro h
have hp' := ENNReal.toReal_pos hp_ne_zero hp_ne_top
have : 0 < 1 / p.toReal := div_pos zero_lt_one hp'
simpa [eLpNorm_eq_lintegral_rpow_enorm hp_ne_zero hp_ne_top] using
ENNReal.rpow_lt_top_of_nonneg (le_of_lt this) (ne_of_lt h)⟩
@[deprecated (since := "2025-02-04")] alias
eLpNorm_lt_top_iff_lintegral_rpow_nnnorm_lt_top := eLpNorm_lt_top_iff_lintegral_rpow_enorm_lt_top
end Top
section Zero
@[simp]
theorem eLpNorm'_exponent_zero {f : α → ε} : eLpNorm' f 0 μ = 1 := by
rw [eLpNorm', div_zero, ENNReal.rpow_zero]
@[simp]
theorem eLpNorm_exponent_zero {f : α → ε} : eLpNorm f 0 μ = 0 := by simp [eLpNorm]
@[simp]
theorem memLp_zero_iff_aestronglyMeasurable [TopologicalSpace ε] {f : α → ε} :
MemLp f 0 μ ↔ AEStronglyMeasurable f μ := by simp [MemLp, eLpNorm_exponent_zero]
@[deprecated (since := "2025-02-21")]
alias memℒp_zero_iff_aestronglyMeasurable := memLp_zero_iff_aestronglyMeasurable
section ENormedAddMonoid
variable {ε : Type*} [TopologicalSpace ε] [ENormedAddMonoid ε]
@[simp]
theorem eLpNorm'_zero (hp0_lt : 0 < q) : eLpNorm' (0 : α → ε) q μ = 0 := by
simp [eLpNorm'_eq_lintegral_enorm, hp0_lt]
@[simp]
theorem eLpNorm'_zero' (hq0_ne : q ≠ 0) (hμ : μ ≠ 0) : eLpNorm' (0 : α → ε) q μ = 0 := by
rcases le_or_lt 0 q with hq0 | hq_neg
· exact eLpNorm'_zero (lt_of_le_of_ne hq0 hq0_ne.symm)
· simp [eLpNorm'_eq_lintegral_enorm, ENNReal.rpow_eq_zero_iff, hμ, hq_neg]
@[simp]
theorem eLpNormEssSup_zero : eLpNormEssSup (0 : α → ε) μ = 0 := by
simp [eLpNormEssSup, ← bot_eq_zero', essSup_const_bot]
@[simp]
theorem eLpNorm_zero : eLpNorm (0 : α → ε) p μ = 0 := by
by_cases h0 : p = 0
· simp [h0]
by_cases h_top : p = ∞
· simp only [h_top, eLpNorm_exponent_top, eLpNormEssSup_zero]
rw [← Ne] at h0
simp [eLpNorm_eq_eLpNorm' h0 h_top, ENNReal.toReal_pos h0 h_top]
@[simp]
theorem eLpNorm_zero' : eLpNorm (fun _ : α => (0 : ε)) p μ = 0 := eLpNorm_zero
@[simp] lemma MemLp.zero : MemLp (0 : α → ε) p μ :=
⟨aestronglyMeasurable_zero, by rw [eLpNorm_zero]; exact ENNReal.coe_lt_top⟩
@[simp] lemma MemLp.zero' : MemLp (fun _ : α => (0 : ε)) p μ := MemLp.zero
@[deprecated (since := "2025-02-21")]
alias Memℒp.zero' := MemLp.zero'
@[deprecated (since := "2025-01-21")] alias zero_memℒp := MemLp.zero
@[deprecated (since := "2025-01-21")] alias zero_mem_ℒp := MemLp.zero'
variable [MeasurableSpace α]
theorem eLpNorm'_measure_zero_of_pos {f : α → ε} (hq_pos : 0 < q) :
eLpNorm' f q (0 : Measure α) = 0 := by simp [eLpNorm', hq_pos]
theorem eLpNorm'_measure_zero_of_exponent_zero {f : α → ε} : eLpNorm' f 0 (0 : Measure α) = 1 := by
simp [eLpNorm']
theorem eLpNorm'_measure_zero_of_neg {f : α → ε} (hq_neg : q < 0) :
eLpNorm' f q (0 : Measure α) = ∞ := by simp [eLpNorm', hq_neg]
end ENormedAddMonoid
@[simp]
theorem eLpNormEssSup_measure_zero {f : α → ε} : eLpNormEssSup f (0 : Measure α) = 0 := by
simp [eLpNormEssSup]
@[simp]
theorem eLpNorm_measure_zero {f : α → ε} : eLpNorm f p (0 : Measure α) = 0 := by
by_cases h0 : p = 0
· simp [h0]
by_cases h_top : p = ∞
· simp [h_top]
rw [← Ne] at h0
simp [eLpNorm_eq_eLpNorm' h0 h_top, eLpNorm', ENNReal.toReal_pos h0 h_top]
section ContinuousENorm
variable {ε : Type*} [TopologicalSpace ε] [ContinuousENorm ε]
@[simp] lemma memLp_measure_zero {f : α → ε} : MemLp f p (0 : Measure α) := by
simp [MemLp]
@[deprecated (since := "2025-02-21")]
alias memℒp_measure_zero := memLp_measure_zero
end ContinuousENorm
end Zero
section Neg
@[simp]
theorem eLpNorm'_neg (f : α → F) (q : ℝ) (μ : Measure α) : eLpNorm' (-f) q μ = eLpNorm' f q μ := by
simp [eLpNorm'_eq_lintegral_enorm]
@[simp]
theorem eLpNorm_neg (f : α → F) (p : ℝ≥0∞) (μ : Measure α) : eLpNorm (-f) p μ = eLpNorm f p μ := by
by_cases h0 : p = 0
· simp [h0]
by_cases h_top : p = ∞
· simp [h_top, eLpNormEssSup_eq_essSup_enorm]
simp [eLpNorm_eq_eLpNorm' h0 h_top]
lemma eLpNorm_sub_comm (f g : α → E) (p : ℝ≥0∞) (μ : Measure α) :
eLpNorm (f - g) p μ = eLpNorm (g - f) p μ := by simp [← eLpNorm_neg (f := f - g)]
theorem MemLp.neg {f : α → E} (hf : MemLp f p μ) : MemLp (-f) p μ :=
⟨AEStronglyMeasurable.neg hf.1, by simp [hf.right]⟩
@[deprecated (since := "2025-02-21")]
alias Memℒp.neg := MemLp.neg
theorem memLp_neg_iff {f : α → E} : MemLp (-f) p μ ↔ MemLp f p μ :=
⟨fun h => neg_neg f ▸ h.neg, MemLp.neg⟩
@[deprecated (since := "2025-02-21")]
alias memℒp_neg_iff := memLp_neg_iff
end Neg
section Const
variable {ε' ε'' : Type*} [TopologicalSpace ε'] [ContinuousENorm ε']
[TopologicalSpace ε''] [ENormedAddMonoid ε'']
theorem eLpNorm'_const (c : ε) (hq_pos : 0 < q) :
eLpNorm' (fun _ : α => c) q μ = ‖c‖ₑ * μ Set.univ ^ (1 / q) := by
rw [eLpNorm'_eq_lintegral_enorm, lintegral_const,
ENNReal.mul_rpow_of_nonneg _ _ (by simp [hq_pos.le] : 0 ≤ 1 / q)]
congr
rw [← ENNReal.rpow_mul]
suffices hq_cancel : q * (1 / q) = 1 by rw [hq_cancel, ENNReal.rpow_one]
rw [one_div, mul_inv_cancel₀ (ne_of_lt hq_pos).symm]
-- Generalising this to ENormedAddMonoid requires a case analysis whether ‖c‖ₑ = ⊤,
-- and will happen in a future PR.
theorem eLpNorm'_const' [IsFiniteMeasure μ] (c : F) (hc_ne_zero : c ≠ 0) (hq_ne_zero : q ≠ 0) :
eLpNorm' (fun _ : α => c) q μ = ‖c‖ₑ * μ Set.univ ^ (1 / q) := by
rw [eLpNorm'_eq_lintegral_enorm, lintegral_const,
ENNReal.mul_rpow_of_ne_top _ (measure_ne_top μ Set.univ)]
· congr
rw [← ENNReal.rpow_mul]
suffices hp_cancel : q * (1 / q) = 1 by rw [hp_cancel, ENNReal.rpow_one]
rw [one_div, mul_inv_cancel₀ hq_ne_zero]
· rw [Ne, ENNReal.rpow_eq_top_iff, not_or, not_and_or, not_and_or]
simp [hc_ne_zero]
theorem eLpNormEssSup_const (c : ε) (hμ : μ ≠ 0) : eLpNormEssSup (fun _ : α => c) μ = ‖c‖ₑ := by
rw [eLpNormEssSup_eq_essSup_enorm, essSup_const _ hμ]
theorem eLpNorm'_const_of_isProbabilityMeasure (c : ε) (hq_pos : 0 < q) [IsProbabilityMeasure μ] :
eLpNorm' (fun _ : α => c) q μ = ‖c‖ₑ := by simp [eLpNorm'_const c hq_pos, measure_univ]
theorem eLpNorm_const (c : ε) (h0 : p ≠ 0) (hμ : μ ≠ 0) :
eLpNorm (fun _ : α => c) p μ = ‖c‖ₑ * μ Set.univ ^ (1 / ENNReal.toReal p) := by
by_cases h_top : p = ∞
· simp [h_top, eLpNormEssSup_const c hμ]
simp [eLpNorm_eq_eLpNorm' h0 h_top, eLpNorm'_const, ENNReal.toReal_pos h0 h_top]
theorem eLpNorm_const' (c : ε) (h0 : p ≠ 0) (h_top : p ≠ ∞) :
eLpNorm (fun _ : α => c) p μ = ‖c‖ₑ * μ Set.univ ^ (1 / ENNReal.toReal p) := by
simp [eLpNorm_eq_eLpNorm' h0 h_top, eLpNorm'_const, ENNReal.toReal_pos h0 h_top]
-- NB. If ‖c‖ₑ = ∞ and μ is finite, this claim is false: the right has side is true,
-- but the left hand side is false (as the norm is infinite).
theorem eLpNorm_const_lt_top_iff_enorm {c : ε''} (hc' : ‖c‖ₑ ≠ ∞)
{p : ℝ≥0∞} (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
eLpNorm (fun _ : α ↦ c) p μ < ∞ ↔ c = 0 ∨ μ Set.univ < ∞ := by
have hp : 0 < p.toReal := ENNReal.toReal_pos hp_ne_zero hp_ne_top
by_cases hμ : μ = 0
· simp only [hμ, Measure.coe_zero, Pi.zero_apply, or_true, ENNReal.zero_lt_top,
eLpNorm_measure_zero]
by_cases hc : c = 0
· simp only [hc, true_or, eq_self_iff_true, ENNReal.zero_lt_top, eLpNorm_zero']
rw [eLpNorm_const' c hp_ne_zero hp_ne_top]
obtain hμ_top | hμ_ne_top := eq_or_ne (μ .univ) ∞
· simp [hc, hμ_top, hp]
rw [ENNReal.mul_lt_top_iff]
simpa [hμ, hc, hμ_ne_top, hμ_ne_top.lt_top, hc, hc'.lt_top] using
ENNReal.rpow_lt_top_of_nonneg (inv_nonneg.mpr hp.le) hμ_ne_top
theorem eLpNorm_const_lt_top_iff {p : ℝ≥0∞} {c : F} (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
eLpNorm (fun _ : α => c) p μ < ∞ ↔ c = 0 ∨ μ Set.univ < ∞ :=
eLpNorm_const_lt_top_iff_enorm enorm_ne_top hp_ne_zero hp_ne_top
theorem memLp_const_enorm {c : ε'} (hc : ‖c‖ₑ ≠ ⊤) [IsFiniteMeasure μ] :
MemLp (fun _ : α ↦ c) p μ := by
refine ⟨aestronglyMeasurable_const, ?_⟩
by_cases h0 : p = 0
· simp [h0]
by_cases hμ : μ = 0
· simp [hμ]
rw [eLpNorm_const c h0 hμ]
exact ENNReal.mul_lt_top hc.lt_top (ENNReal.rpow_lt_top_of_nonneg (by simp)
(measure_ne_top μ Set.univ))
theorem memLp_const (c : E) [IsFiniteMeasure μ] : MemLp (fun _ : α => c) p μ :=
memLp_const_enorm enorm_ne_top
@[deprecated (since := "2025-02-21")]
alias memℒp_const := memLp_const
theorem memLp_top_const_enorm {c : ε'} (hc : ‖c‖ₑ ≠ ⊤) :
MemLp (fun _ : α ↦ c) ∞ μ :=
⟨aestronglyMeasurable_const, by by_cases h : μ = 0 <;> simp [eLpNorm_const _, h, hc.lt_top]⟩
theorem memLp_top_const (c : E) : MemLp (fun _ : α => c) ∞ μ :=
memLp_top_const_enorm enorm_ne_top
@[deprecated (since := "2025-02-21")]
alias memℒp_top_const := memLp_top_const
theorem memLp_const_iff_enorm
{p : ℝ≥0∞} {c : ε''} (hc : ‖c‖ₑ ≠ ⊤) (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
MemLp (fun _ : α ↦ c) p μ ↔ c = 0 ∨ μ Set.univ < ∞ := by
simp_all [MemLp, aestronglyMeasurable_const,
eLpNorm_const_lt_top_iff_enorm hc hp_ne_zero hp_ne_top]
theorem memLp_const_iff {p : ℝ≥0∞} {c : E} (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
MemLp (fun _ : α => c) p μ ↔ c = 0 ∨ μ Set.univ < ∞ :=
memLp_const_iff_enorm enorm_ne_top hp_ne_zero hp_ne_top
@[deprecated (since := "2025-02-21")]
alias memℒp_const_iff := memLp_const_iff
end Const
variable {f : α → F}
lemma eLpNorm'_mono_enorm_ae {f : α → ε} {g : α → ε'} (hq : 0 ≤ q) (h : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ ‖g x‖ₑ) :
eLpNorm' f q μ ≤ eLpNorm' g q μ := by
simp only [eLpNorm'_eq_lintegral_enorm]
gcongr ?_ ^ (1/q)
refine lintegral_mono_ae (h.mono fun x hx => ?_)
gcongr
lemma eLpNorm'_mono_nnnorm_ae {f : α → F} {g : α → G} (hq : 0 ≤ q) (h : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ ‖g x‖₊) :
eLpNorm' f q μ ≤ eLpNorm' g q μ := by
simp only [eLpNorm'_eq_lintegral_enorm]
gcongr ?_ ^ (1/q)
refine lintegral_mono_ae (h.mono fun x hx => ?_)
dsimp [enorm]
gcongr
theorem eLpNorm'_mono_ae {f : α → F} {g : α → G} (hq : 0 ≤ q) (h : ∀ᵐ x ∂μ, ‖f x‖ ≤ ‖g x‖) :
eLpNorm' f q μ ≤ eLpNorm' g q μ :=
eLpNorm'_mono_enorm_ae hq (by simpa only [enorm_le_iff_norm_le] using h)
theorem eLpNorm'_congr_enorm_ae {f g : α → ε} (hfg : ∀ᵐ x ∂μ, ‖f x‖ₑ = ‖g x‖ₑ) :
eLpNorm' f q μ = eLpNorm' g q μ := by
have : (‖f ·‖ₑ ^ q) =ᵐ[μ] (‖g ·‖ₑ ^ q) := hfg.mono fun x hx ↦ by simp [hx]
simp only [eLpNorm'_eq_lintegral_enorm, lintegral_congr_ae this]
theorem eLpNorm'_congr_nnnorm_ae {f g : α → F} (hfg : ∀ᵐ x ∂μ, ‖f x‖₊ = ‖g x‖₊) :
eLpNorm' f q μ = eLpNorm' g q μ := by
have : (‖f ·‖ₑ ^ q) =ᵐ[μ] (‖g ·‖ₑ ^ q) := hfg.mono fun x hx ↦ by simp [enorm, hx]
simp only [eLpNorm'_eq_lintegral_enorm, lintegral_congr_ae this]
theorem eLpNorm'_congr_norm_ae {f g : α → F} (hfg : ∀ᵐ x ∂μ, ‖f x‖ = ‖g x‖) :
eLpNorm' f q μ = eLpNorm' g q μ :=
eLpNorm'_congr_nnnorm_ae <| hfg.mono fun _x hx => NNReal.eq hx
theorem eLpNorm'_congr_ae {f g : α → ε} (hfg : f =ᵐ[μ] g) : eLpNorm' f q μ = eLpNorm' g q μ :=
eLpNorm'_congr_enorm_ae (hfg.fun_comp _)
theorem eLpNormEssSup_congr_ae {f g : α → ε} (hfg : f =ᵐ[μ] g) :
eLpNormEssSup f μ = eLpNormEssSup g μ :=
essSup_congr_ae (hfg.fun_comp enorm)
theorem eLpNormEssSup_mono_enorm_ae {f g : α → ε} (hfg : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ ‖g x‖ₑ) :
eLpNormEssSup f μ ≤ eLpNormEssSup g μ :=
essSup_mono_ae <| hfg
theorem eLpNormEssSup_mono_nnnorm_ae {f g : α → F} (hfg : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ ‖g x‖₊) :
eLpNormEssSup f μ ≤ eLpNormEssSup g μ :=
essSup_mono_ae <| hfg.mono fun _x hx => ENNReal.coe_le_coe.mpr hx
theorem eLpNorm_mono_enorm_ae {f : α → ε} {g : α → ε'} (h : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ ‖g x‖ₑ) :
eLpNorm f p μ ≤ eLpNorm g p μ := by
simp only [eLpNorm]
split_ifs
· exact le_rfl
· exact essSup_mono_ae h
· exact eLpNorm'_mono_enorm_ae ENNReal.toReal_nonneg h
theorem eLpNorm_mono_nnnorm_ae {f : α → F} {g : α → G} (h : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ ‖g x‖₊) :
eLpNorm f p μ ≤ eLpNorm g p μ := by
simp only [eLpNorm]
split_ifs
· exact le_rfl
· exact essSup_mono_ae (h.mono fun x hx => ENNReal.coe_le_coe.mpr hx)
· exact eLpNorm'_mono_nnnorm_ae ENNReal.toReal_nonneg h
theorem eLpNorm_mono_ae {f : α → F} {g : α → G} (h : ∀ᵐ x ∂μ, ‖f x‖ ≤ ‖g x‖) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_enorm_ae (by simpa only [enorm_le_iff_norm_le] using h)
theorem eLpNorm_mono_ae' {ε' : Type*} [ENorm ε']
{f : α → ε} {g : α → ε'} (h : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ ‖g x‖ₑ) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_enorm_ae (by simpa only [enorm_le_iff_norm_le] using h)
theorem eLpNorm_mono_ae_real {f : α → F} {g : α → ℝ} (h : ∀ᵐ x ∂μ, ‖f x‖ ≤ g x) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_ae <| h.mono fun _x hx =>
hx.trans ((le_abs_self _).trans (Real.norm_eq_abs _).symm.le)
theorem eLpNorm_mono_enorm {f : α → ε} {g : α → ε'} (h : ∀ x, ‖f x‖ₑ ≤ ‖g x‖ₑ) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_enorm_ae (Eventually.of_forall h)
theorem eLpNorm_mono_nnnorm {f : α → F} {g : α → G} (h : ∀ x, ‖f x‖₊ ≤ ‖g x‖₊) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_nnnorm_ae (Eventually.of_forall h)
theorem eLpNorm_mono {f : α → F} {g : α → G} (h : ∀ x, ‖f x‖ ≤ ‖g x‖) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_ae (Eventually.of_forall h)
theorem eLpNorm_mono_real {f : α → F} {g : α → ℝ} (h : ∀ x, ‖f x‖ ≤ g x) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_ae_real (Eventually.of_forall h)
theorem eLpNormEssSup_le_of_ae_enorm_bound {f : α → ε} {C : ℝ≥0∞} (hfC : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ C) :
eLpNormEssSup f μ ≤ C :=
essSup_le_of_ae_le C hfC
theorem eLpNormEssSup_le_of_ae_nnnorm_bound {f : α → F} {C : ℝ≥0} (hfC : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ C) :
eLpNormEssSup f μ ≤ C :=
essSup_le_of_ae_le (C : ℝ≥0∞) <| hfC.mono fun _x hx => ENNReal.coe_le_coe.mpr hx
theorem eLpNormEssSup_le_of_ae_bound {f : α → F} {C : ℝ} (hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) :
eLpNormEssSup f μ ≤ ENNReal.ofReal C :=
eLpNormEssSup_le_of_ae_nnnorm_bound <| hfC.mono fun _x hx => hx.trans C.le_coe_toNNReal
theorem eLpNormEssSup_lt_top_of_ae_enorm_bound {f : α → ε} {C : ℝ≥0} (hfC : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ C) :
eLpNormEssSup f μ < ∞ :=
(eLpNormEssSup_le_of_ae_enorm_bound hfC).trans_lt ENNReal.coe_lt_top
theorem eLpNormEssSup_lt_top_of_ae_nnnorm_bound {f : α → F} {C : ℝ≥0} (hfC : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ C) :
eLpNormEssSup f μ < ∞ :=
(eLpNormEssSup_le_of_ae_nnnorm_bound hfC).trans_lt ENNReal.coe_lt_top
theorem eLpNormEssSup_lt_top_of_ae_bound {f : α → F} {C : ℝ} (hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) :
eLpNormEssSup f μ < ∞ :=
(eLpNormEssSup_le_of_ae_bound hfC).trans_lt ENNReal.ofReal_lt_top
theorem eLpNorm_le_of_ae_enorm_bound {ε} [TopologicalSpace ε] [ENormedAddMonoid ε]
{f : α → ε} {C : ℝ≥0∞} (hfC : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ C) :
eLpNorm f p μ ≤ C • μ Set.univ ^ p.toReal⁻¹ := by
rcases eq_zero_or_neZero μ with rfl | hμ
· simp
by_cases hp : p = 0
· simp [hp]
have : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ ‖C‖ₑ := hfC.mono fun x hx ↦ hx.trans (Preorder.le_refl C)
refine (eLpNorm_mono_enorm_ae this).trans_eq ?_
rw [eLpNorm_const _ hp (NeZero.ne μ), one_div, enorm_eq_self, smul_eq_mul]
theorem eLpNorm_le_of_ae_nnnorm_bound {f : α → F} {C : ℝ≥0} (hfC : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ C) :
eLpNorm f p μ ≤ C • μ Set.univ ^ p.toReal⁻¹ := by
rcases eq_zero_or_neZero μ with rfl | hμ
· simp
by_cases hp : p = 0
· simp [hp]
have : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ ‖(C : ℝ)‖₊ := hfC.mono fun x hx => hx.trans_eq C.nnnorm_eq.symm
refine (eLpNorm_mono_ae this).trans_eq ?_
rw [eLpNorm_const _ hp (NeZero.ne μ), C.enorm_eq, one_div, ENNReal.smul_def, smul_eq_mul]
theorem eLpNorm_le_of_ae_bound {f : α → F} {C : ℝ} (hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) :
eLpNorm f p μ ≤ μ Set.univ ^ p.toReal⁻¹ * ENNReal.ofReal C := by
rw [← mul_comm]
exact eLpNorm_le_of_ae_nnnorm_bound (hfC.mono fun x hx => hx.trans C.le_coe_toNNReal)
theorem eLpNorm_congr_enorm_ae {f : α → ε} {g : α → ε'} (hfg : ∀ᵐ x ∂μ, ‖f x‖ₑ = ‖g x‖ₑ) :
eLpNorm f p μ = eLpNorm g p μ :=
le_antisymm (eLpNorm_mono_enorm_ae <| EventuallyEq.le hfg)
(eLpNorm_mono_enorm_ae <| (EventuallyEq.symm hfg).le)
theorem eLpNorm_congr_nnnorm_ae {f : α → F} {g : α → G} (hfg : ∀ᵐ x ∂μ, ‖f x‖₊ = ‖g x‖₊) :
eLpNorm f p μ = eLpNorm g p μ :=
le_antisymm (eLpNorm_mono_nnnorm_ae <| EventuallyEq.le hfg)
(eLpNorm_mono_nnnorm_ae <| (EventuallyEq.symm hfg).le)
theorem eLpNorm_congr_norm_ae {f : α → F} {g : α → G} (hfg : ∀ᵐ x ∂μ, ‖f x‖ = ‖g x‖) :
eLpNorm f p μ = eLpNorm g p μ :=
eLpNorm_congr_nnnorm_ae <| hfg.mono fun _x hx => NNReal.eq hx
open scoped symmDiff in
theorem eLpNorm_indicator_sub_indicator (s t : Set α) (f : α → E) :
eLpNorm (s.indicator f - t.indicator f) p μ = eLpNorm ((s ∆ t).indicator f) p μ :=
eLpNorm_congr_norm_ae <| ae_of_all _ fun x ↦ by simp [Set.apply_indicator_symmDiff norm_neg]
@[simp]
theorem eLpNorm'_norm {f : α → F} : eLpNorm' (fun a => ‖f a‖) q μ = eLpNorm' f q μ := by
simp [eLpNorm'_eq_lintegral_enorm]
@[simp]
theorem eLpNorm'_enorm {f : α → ε} : eLpNorm' (fun a => ‖f a‖ₑ) q μ = eLpNorm' f q μ := by
simp [eLpNorm'_eq_lintegral_enorm]
@[simp]
theorem eLpNorm_norm (f : α → F) : eLpNorm (fun x => ‖f x‖) p μ = eLpNorm f p μ :=
eLpNorm_congr_norm_ae <| Eventually.of_forall fun _ => norm_norm _
@[simp]
theorem eLpNorm_enorm (f : α → ε) : eLpNorm (fun x ↦ ‖f x‖ₑ) p μ = eLpNorm f p μ :=
eLpNorm_congr_enorm_ae <| Eventually.of_forall fun _ => enorm_enorm _
theorem eLpNorm'_norm_rpow (f : α → F) (p q : ℝ) (hq_pos : 0 < q) :
eLpNorm' (fun x => ‖f x‖ ^ q) p μ = eLpNorm' f (p * q) μ ^ q := by
simp_rw [eLpNorm', ← ENNReal.rpow_mul, ← one_div_mul_one_div, one_div,
mul_assoc, inv_mul_cancel₀ hq_pos.ne.symm, mul_one, ← ofReal_norm_eq_enorm,
Real.norm_eq_abs, abs_eq_self.mpr (Real.rpow_nonneg (norm_nonneg _) _), mul_comm p,
← ENNReal.ofReal_rpow_of_nonneg (norm_nonneg _) hq_pos.le, ENNReal.rpow_mul]
theorem eLpNorm_norm_rpow (f : α → F) (hq_pos : 0 < q) :
eLpNorm (fun x => ‖f x‖ ^ q) p μ = eLpNorm f (p * ENNReal.ofReal q) μ ^ q := by
by_cases h0 : p = 0
· simp [h0, ENNReal.zero_rpow_of_pos hq_pos]
by_cases hp_top : p = ∞
· simp only [hp_top, eLpNorm_exponent_top, ENNReal.top_mul', hq_pos.not_le,
ENNReal.ofReal_eq_zero, if_false, eLpNorm_exponent_top, eLpNormEssSup_eq_essSup_enorm]
have h_rpow : essSup (‖‖f ·‖ ^ q‖ₑ) μ = essSup (‖f ·‖ₑ ^ q) μ := by
congr
ext1 x
conv_rhs => rw [← enorm_norm]
rw [← Real.enorm_rpow_of_nonneg (norm_nonneg _) hq_pos.le]
rw [h_rpow]
have h_rpow_mono := ENNReal.strictMono_rpow_of_pos hq_pos
have h_rpow_surj := (ENNReal.rpow_left_bijective hq_pos.ne.symm).2
let iso := h_rpow_mono.orderIsoOfSurjective _ h_rpow_surj
exact (iso.essSup_apply (fun x => ‖f x‖ₑ) μ).symm
rw [eLpNorm_eq_eLpNorm' h0 hp_top, eLpNorm_eq_eLpNorm' _ _]
swap
· refine mul_ne_zero h0 ?_
rwa [Ne, ENNReal.ofReal_eq_zero, not_le]
swap; · exact ENNReal.mul_ne_top hp_top ENNReal.ofReal_ne_top
rw [ENNReal.toReal_mul, ENNReal.toReal_ofReal hq_pos.le]
exact eLpNorm'_norm_rpow f p.toReal q hq_pos
theorem eLpNorm_congr_ae {f g : α → ε} (hfg : f =ᵐ[μ] g) : eLpNorm f p μ = eLpNorm g p μ :=
eLpNorm_congr_enorm_ae <| hfg.mono fun _x hx => hx ▸ rfl
theorem memLp_congr_ae [TopologicalSpace ε] {f g : α → ε} (hfg : f =ᵐ[μ] g) :
MemLp f p μ ↔ MemLp g p μ := by
simp only [MemLp, eLpNorm_congr_ae hfg, aestronglyMeasurable_congr hfg]
@[deprecated (since := "2025-02-21")]
alias memℒp_congr_ae := memLp_congr_ae
theorem MemLp.ae_eq [TopologicalSpace ε] {f g : α → ε} (hfg : f =ᵐ[μ] g) (hf_Lp : MemLp f p μ) :
MemLp g p μ :=
(memLp_congr_ae hfg).1 hf_Lp
@[deprecated (since := "2025-02-21")]
alias Memℒp.ae_eq := MemLp.ae_eq
theorem MemLp.of_le {f : α → E} {g : α → F} (hg : MemLp g p μ) (hf : AEStronglyMeasurable f μ)
(hfg : ∀ᵐ x ∂μ, ‖f x‖ ≤ ‖g x‖) : MemLp f p μ :=
⟨hf, (eLpNorm_mono_ae hfg).trans_lt hg.eLpNorm_lt_top⟩
@[deprecated (since := "2025-02-21")] alias Memℒp.of_le := MemLp.of_le
alias MemLp.mono := MemLp.of_le
@[deprecated (since := "2025-02-21")] alias Memℒp.mono := MemLp.mono
theorem MemLp.mono' {f : α → E} {g : α → ℝ} (hg : MemLp g p μ) (hf : AEStronglyMeasurable f μ)
(h : ∀ᵐ a ∂μ, ‖f a‖ ≤ g a) : MemLp f p μ :=
hg.mono hf <| h.mono fun _x hx => le_trans hx (le_abs_self _)
@[deprecated (since := "2025-02-21")]
alias Memℒp.mono' := MemLp.mono'
theorem MemLp.congr_norm {f : α → E} {g : α → F} (hf : MemLp f p μ) (hg : AEStronglyMeasurable g μ)
(h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) : MemLp g p μ :=
hf.mono hg <| EventuallyEq.le <| EventuallyEq.symm h
@[deprecated (since := "2025-02-21")]
alias Memℒp.congr_norm := MemLp.congr_norm
theorem memLp_congr_norm {f : α → E} {g : α → F} (hf : AEStronglyMeasurable f μ)
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) : MemLp f p μ ↔ MemLp g p μ :=
⟨fun h2f => h2f.congr_norm hg h, fun h2g => h2g.congr_norm hf <| EventuallyEq.symm h⟩
@[deprecated (since := "2025-02-21")]
alias memℒp_congr_norm := memLp_congr_norm
theorem memLp_top_of_bound {f : α → E} (hf : AEStronglyMeasurable f μ) (C : ℝ)
(hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) : MemLp f ∞ μ :=
⟨hf, by
rw [eLpNorm_exponent_top]
exact eLpNormEssSup_lt_top_of_ae_bound hfC⟩
@[deprecated (since := "2025-02-21")]
alias memℒp_top_of_bound := memLp_top_of_bound
theorem MemLp.of_bound [IsFiniteMeasure μ] {f : α → E} (hf : AEStronglyMeasurable f μ) (C : ℝ)
(hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) : MemLp f p μ :=
(memLp_const C).of_le hf (hfC.mono fun _x hx => le_trans hx (le_abs_self _))
@[deprecated (since := "2025-02-21")]
alias Memℒp.of_bound := MemLp.of_bound
theorem memLp_of_bounded [IsFiniteMeasure μ]
{a b : ℝ} {f : α → ℝ} (h : ∀ᵐ x ∂μ, f x ∈ Set.Icc a b)
(hX : AEStronglyMeasurable f μ) (p : ENNReal) : MemLp f p μ :=
have ha : ∀ᵐ x ∂μ, a ≤ f x := h.mono fun ω h => h.1
have hb : ∀ᵐ x ∂μ, f x ≤ b := h.mono fun ω h => h.2
(memLp_const (max |a| |b|)).mono' hX (by filter_upwards [ha, hb] with x using abs_le_max_abs_abs)
@[deprecated (since := "2025-02-21")]
alias memℒp_of_bounded := memLp_of_bounded
@[gcongr, mono]
theorem eLpNorm'_mono_measure (f : α → ε) (hμν : ν ≤ μ) (hq : 0 ≤ q) :
eLpNorm' f q ν ≤ eLpNorm' f q μ := by
simp_rw [eLpNorm']
gcongr
exact lintegral_mono' hμν le_rfl
@[gcongr, mono]
theorem eLpNormEssSup_mono_measure (f : α → ε) (hμν : ν ≪ μ) :
eLpNormEssSup f ν ≤ eLpNormEssSup f μ := by
simp_rw [eLpNormEssSup]
exact essSup_mono_measure hμν
@[gcongr, mono]
theorem eLpNorm_mono_measure (f : α → ε) (hμν : ν ≤ μ) : eLpNorm f p ν ≤ eLpNorm f p μ := by
by_cases hp0 : p = 0
· simp [hp0]
by_cases hp_top : p = ∞
· simp [hp_top, eLpNormEssSup_mono_measure f (Measure.absolutelyContinuous_of_le hμν)]
simp_rw [eLpNorm_eq_eLpNorm' hp0 hp_top]
exact eLpNorm'_mono_measure f hμν ENNReal.toReal_nonneg
theorem MemLp.mono_measure [TopologicalSpace ε] {f : α → ε} (hμν : ν ≤ μ) (hf : MemLp f p μ) :
MemLp f p ν :=
⟨hf.1.mono_measure hμν, (eLpNorm_mono_measure f hμν).trans_lt hf.2⟩
@[deprecated (since := "2025-02-21")]
alias Memℒp.mono_measure := MemLp.mono_measure
section Indicator
variable {ε : Type*} [TopologicalSpace ε] [ENormedAddMonoid ε]
{c : ε} {hf : AEStronglyMeasurable f μ} {s : Set α}
lemma eLpNorm_indicator_eq_eLpNorm_restrict {f : α → ε} {s : Set α} (hs : MeasurableSet s) :
eLpNorm (s.indicator f) p μ = eLpNorm f p (μ.restrict s) := by
by_cases hp_zero : p = 0
· simp only [hp_zero, eLpNorm_exponent_zero]
by_cases hp_top : p = ∞
· simp_rw [hp_top, eLpNorm_exponent_top, eLpNormEssSup_eq_essSup_enorm,
enorm_indicator_eq_indicator_enorm, ENNReal.essSup_indicator_eq_essSup_restrict hs]
simp_rw [eLpNorm_eq_lintegral_rpow_enorm hp_zero hp_top]
suffices (∫⁻ x, (‖s.indicator f x‖ₑ) ^ p.toReal ∂μ) =
∫⁻ x in s, ‖f x‖ₑ ^ p.toReal ∂μ by rw [this]
rw [← lintegral_indicator hs]
congr
simp_rw [enorm_indicator_eq_indicator_enorm]
rw [eq_comm, ← Function.comp_def (fun x : ℝ≥0∞ => x ^ p.toReal), Set.indicator_comp_of_zero,
Function.comp_def]
simp [ENNReal.toReal_pos hp_zero hp_top]
@[deprecated (since := "2025-01-07")]
| alias eLpNorm_indicator_eq_restrict := eLpNorm_indicator_eq_eLpNorm_restrict
lemma eLpNormEssSup_indicator_eq_eLpNormEssSup_restrict (hs : MeasurableSet s) :
eLpNormEssSup (s.indicator f) μ = eLpNormEssSup f (μ.restrict s) := by
| Mathlib/MeasureTheory/Function/LpSeminorm/Basic.lean | 654 | 657 |
/-
Copyright (c) 2019 Calle Sönne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Calle Sönne
-/
import Mathlib.Analysis.SpecialFunctions.Trigonometric.Basic
import Mathlib.Analysis.Normed.Group.AddCircle
import Mathlib.Algebra.CharZero.Quotient
import Mathlib.Topology.Instances.Sign
/-!
# The type of angles
In this file we define `Real.Angle` to be the quotient group `ℝ/2πℤ` and prove a few simple lemmas
about trigonometric functions and angles.
-/
open Real
noncomputable section
namespace Real
/-- The type of angles -/
def Angle : Type :=
AddCircle (2 * π)
-- The `NormedAddCommGroup, Inhabited` instances should be constructed by a deriving handler.
-- https://github.com/leanprover-community/mathlib4/issues/380
namespace Angle
instance : NormedAddCommGroup Angle :=
inferInstanceAs (NormedAddCommGroup (AddCircle (2 * π)))
instance : Inhabited Angle :=
inferInstanceAs (Inhabited (AddCircle (2 * π)))
/-- The canonical map from `ℝ` to the quotient `Angle`. -/
@[coe]
protected def coe (r : ℝ) : Angle := QuotientAddGroup.mk r
instance : Coe ℝ Angle := ⟨Angle.coe⟩
instance : CircularOrder Real.Angle :=
QuotientAddGroup.circularOrder (hp' := ⟨by norm_num [pi_pos]⟩)
@[continuity]
theorem continuous_coe : Continuous ((↑) : ℝ → Angle) :=
continuous_quotient_mk'
/-- Coercion `ℝ → Angle` as an additive homomorphism. -/
def coeHom : ℝ →+ Angle :=
QuotientAddGroup.mk' _
@[simp]
theorem coe_coeHom : (coeHom : ℝ → Angle) = ((↑) : ℝ → Angle) :=
rfl
/-- An induction principle to deduce results for `Angle` from those for `ℝ`, used with
`induction θ using Real.Angle.induction_on`. -/
@[elab_as_elim]
protected theorem induction_on {p : Angle → Prop} (θ : Angle) (h : ∀ x : ℝ, p x) : p θ :=
Quotient.inductionOn' θ h
@[simp]
theorem coe_zero : ↑(0 : ℝ) = (0 : Angle) :=
rfl
@[simp]
theorem coe_add (x y : ℝ) : ↑(x + y : ℝ) = (↑x + ↑y : Angle) :=
rfl
@[simp]
theorem coe_neg (x : ℝ) : ↑(-x : ℝ) = -(↑x : Angle) :=
rfl
@[simp]
theorem coe_sub (x y : ℝ) : ↑(x - y : ℝ) = (↑x - ↑y : Angle) :=
rfl
theorem coe_nsmul (n : ℕ) (x : ℝ) : ↑(n • x : ℝ) = n • (↑x : Angle) :=
rfl
theorem coe_zsmul (z : ℤ) (x : ℝ) : ↑(z • x : ℝ) = z • (↑x : Angle) :=
rfl
theorem coe_eq_zero_iff {x : ℝ} : (x : Angle) = 0 ↔ ∃ n : ℤ, n • (2 * π) = x :=
AddCircle.coe_eq_zero_iff (2 * π)
@[simp, norm_cast]
theorem natCast_mul_eq_nsmul (x : ℝ) (n : ℕ) : ↑((n : ℝ) * x) = n • (↑x : Angle) := by
simpa only [nsmul_eq_mul] using coeHom.map_nsmul x n
@[simp, norm_cast]
theorem intCast_mul_eq_zsmul (x : ℝ) (n : ℤ) : ↑((n : ℝ) * x : ℝ) = n • (↑x : Angle) := by
simpa only [zsmul_eq_mul] using coeHom.map_zsmul x n
theorem angle_eq_iff_two_pi_dvd_sub {ψ θ : ℝ} : (θ : Angle) = ψ ↔ ∃ k : ℤ, θ - ψ = 2 * π * k := by
simp only [QuotientAddGroup.eq, AddSubgroup.zmultiples_eq_closure,
AddSubgroup.mem_closure_singleton, zsmul_eq_mul', (sub_eq_neg_add _ _).symm, eq_comm]
rw [Angle.coe, Angle.coe, QuotientAddGroup.eq]
simp only [AddSubgroup.zmultiples_eq_closure,
AddSubgroup.mem_closure_singleton, zsmul_eq_mul', (sub_eq_neg_add _ _).symm, eq_comm]
@[simp]
theorem coe_two_pi : ↑(2 * π : ℝ) = (0 : Angle) :=
angle_eq_iff_two_pi_dvd_sub.2 ⟨1, by rw [sub_zero, Int.cast_one, mul_one]⟩
@[simp]
theorem neg_coe_pi : -(π : Angle) = π := by
rw [← coe_neg, angle_eq_iff_two_pi_dvd_sub]
use -1
simp [two_mul, sub_eq_add_neg]
@[simp]
theorem two_nsmul_coe_div_two (θ : ℝ) : (2 : ℕ) • (↑(θ / 2) : Angle) = θ := by
rw [← coe_nsmul, two_nsmul, add_halves]
@[simp]
theorem two_zsmul_coe_div_two (θ : ℝ) : (2 : ℤ) • (↑(θ / 2) : Angle) = θ := by
rw [← coe_zsmul, two_zsmul, add_halves]
theorem two_nsmul_neg_pi_div_two : (2 : ℕ) • (↑(-π / 2) : Angle) = π := by
rw [two_nsmul_coe_div_two, coe_neg, neg_coe_pi]
theorem two_zsmul_neg_pi_div_two : (2 : ℤ) • (↑(-π / 2) : Angle) = π := by
rw [two_zsmul, ← two_nsmul, two_nsmul_neg_pi_div_two]
theorem sub_coe_pi_eq_add_coe_pi (θ : Angle) : θ - π = θ + π := by
rw [sub_eq_add_neg, neg_coe_pi]
@[simp]
theorem two_nsmul_coe_pi : (2 : ℕ) • (π : Angle) = 0 := by simp [← natCast_mul_eq_nsmul]
@[simp]
theorem two_zsmul_coe_pi : (2 : ℤ) • (π : Angle) = 0 := by simp [← intCast_mul_eq_zsmul]
@[simp]
theorem coe_pi_add_coe_pi : (π : Real.Angle) + π = 0 := by rw [← two_nsmul, two_nsmul_coe_pi]
theorem zsmul_eq_iff {ψ θ : Angle} {z : ℤ} (hz : z ≠ 0) :
z • ψ = z • θ ↔ ∃ k : Fin z.natAbs, ψ = θ + (k : ℕ) • (2 * π / z : ℝ) :=
QuotientAddGroup.zmultiples_zsmul_eq_zsmul_iff hz
theorem nsmul_eq_iff {ψ θ : Angle} {n : ℕ} (hz : n ≠ 0) :
n • ψ = n • θ ↔ ∃ k : Fin n, ψ = θ + (k : ℕ) • (2 * π / n : ℝ) :=
QuotientAddGroup.zmultiples_nsmul_eq_nsmul_iff hz
theorem two_zsmul_eq_iff {ψ θ : Angle} : (2 : ℤ) • ψ = (2 : ℤ) • θ ↔ ψ = θ ∨ ψ = θ + ↑π := by
have : Int.natAbs 2 = 2 := rfl
rw [zsmul_eq_iff two_ne_zero, this, Fin.exists_fin_two, Fin.val_zero,
Fin.val_one, zero_smul, add_zero, one_smul, Int.cast_two,
mul_div_cancel_left₀ (_ : ℝ) two_ne_zero]
theorem two_nsmul_eq_iff {ψ θ : Angle} : (2 : ℕ) • ψ = (2 : ℕ) • θ ↔ ψ = θ ∨ ψ = θ + ↑π := by
simp_rw [← natCast_zsmul, Nat.cast_ofNat, two_zsmul_eq_iff]
theorem two_nsmul_eq_zero_iff {θ : Angle} : (2 : ℕ) • θ = 0 ↔ θ = 0 ∨ θ = π := by
convert two_nsmul_eq_iff <;> simp
theorem two_nsmul_ne_zero_iff {θ : Angle} : (2 : ℕ) • θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by
rw [← not_or, ← two_nsmul_eq_zero_iff]
theorem two_zsmul_eq_zero_iff {θ : Angle} : (2 : ℤ) • θ = 0 ↔ θ = 0 ∨ θ = π := by
simp_rw [two_zsmul, ← two_nsmul, two_nsmul_eq_zero_iff]
theorem two_zsmul_ne_zero_iff {θ : Angle} : (2 : ℤ) • θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by
rw [← not_or, ← two_zsmul_eq_zero_iff]
theorem eq_neg_self_iff {θ : Angle} : θ = -θ ↔ θ = 0 ∨ θ = π := by
rw [← add_eq_zero_iff_eq_neg, ← two_nsmul, two_nsmul_eq_zero_iff]
theorem ne_neg_self_iff {θ : Angle} : θ ≠ -θ ↔ θ ≠ 0 ∧ θ ≠ π := by
rw [← not_or, ← eq_neg_self_iff.not]
theorem neg_eq_self_iff {θ : Angle} : -θ = θ ↔ θ = 0 ∨ θ = π := by rw [eq_comm, eq_neg_self_iff]
theorem neg_ne_self_iff {θ : Angle} : -θ ≠ θ ↔ θ ≠ 0 ∧ θ ≠ π := by
rw [← not_or, ← neg_eq_self_iff.not]
theorem two_nsmul_eq_pi_iff {θ : Angle} : (2 : ℕ) • θ = π ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by
have h : (π : Angle) = ((2 : ℕ) • (π / 2 : ℝ):) := by rw [two_nsmul, add_halves]
nth_rw 1 [h]
rw [coe_nsmul, two_nsmul_eq_iff]
-- Porting note: `congr` didn't simplify the goal of iff of `Or`s
convert Iff.rfl
rw [add_comm, ← coe_add, ← sub_eq_zero, ← coe_sub, neg_div, ← neg_sub, sub_neg_eq_add, add_assoc,
add_halves, ← two_mul, coe_neg, coe_two_pi, neg_zero]
theorem two_zsmul_eq_pi_iff {θ : Angle} : (2 : ℤ) • θ = π ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by
rw [two_zsmul, ← two_nsmul, two_nsmul_eq_pi_iff]
theorem cos_eq_iff_coe_eq_or_eq_neg {θ ψ : ℝ} :
cos θ = cos ψ ↔ (θ : Angle) = ψ ∨ (θ : Angle) = -ψ := by
constructor
· intro Hcos
rw [← sub_eq_zero, cos_sub_cos, mul_eq_zero, mul_eq_zero, neg_eq_zero,
eq_false (two_ne_zero' ℝ), false_or, sin_eq_zero_iff, sin_eq_zero_iff] at Hcos
rcases Hcos with (⟨n, hn⟩ | ⟨n, hn⟩)
· right
rw [eq_div_iff_mul_eq (two_ne_zero' ℝ), ← sub_eq_iff_eq_add] at hn
rw [← hn, coe_sub, eq_neg_iff_add_eq_zero, sub_add_cancel, mul_assoc, intCast_mul_eq_zsmul,
mul_comm, coe_two_pi, zsmul_zero]
· left
rw [eq_div_iff_mul_eq (two_ne_zero' ℝ), eq_sub_iff_add_eq] at hn
rw [← hn, coe_add, mul_assoc, intCast_mul_eq_zsmul, mul_comm, coe_two_pi, zsmul_zero,
zero_add]
· rw [angle_eq_iff_two_pi_dvd_sub, ← coe_neg, angle_eq_iff_two_pi_dvd_sub]
rintro (⟨k, H⟩ | ⟨k, H⟩)
· rw [← sub_eq_zero, cos_sub_cos, H, mul_assoc 2 π k, mul_div_cancel_left₀ _ (two_ne_zero' ℝ),
mul_comm π _, sin_int_mul_pi, mul_zero]
rw [← sub_eq_zero, cos_sub_cos, ← sub_neg_eq_add, H, mul_assoc 2 π k,
mul_div_cancel_left₀ _ (two_ne_zero' ℝ), mul_comm π _, sin_int_mul_pi, mul_zero,
zero_mul]
theorem sin_eq_iff_coe_eq_or_add_eq_pi {θ ψ : ℝ} :
sin θ = sin ψ ↔ (θ : Angle) = ψ ∨ (θ : Angle) + ψ = π := by
constructor
· intro Hsin
rw [← cos_pi_div_two_sub, ← cos_pi_div_two_sub] at Hsin
rcases cos_eq_iff_coe_eq_or_eq_neg.mp Hsin with h | h
· left
rw [coe_sub, coe_sub] at h
exact sub_right_inj.1 h
right
rw [coe_sub, coe_sub, eq_neg_iff_add_eq_zero, add_sub, sub_add_eq_add_sub, ← coe_add,
add_halves, sub_sub, sub_eq_zero] at h
exact h.symm
· rw [angle_eq_iff_two_pi_dvd_sub, ← eq_sub_iff_add_eq, ← coe_sub, angle_eq_iff_two_pi_dvd_sub]
rintro (⟨k, H⟩ | ⟨k, H⟩)
· rw [← sub_eq_zero, sin_sub_sin, H, mul_assoc 2 π k, mul_div_cancel_left₀ _ (two_ne_zero' ℝ),
mul_comm π _, sin_int_mul_pi, mul_zero, zero_mul]
have H' : θ + ψ = 2 * k * π + π := by
rwa [← sub_add, sub_add_eq_add_sub, sub_eq_iff_eq_add, mul_assoc, mul_comm π _, ←
mul_assoc] at H
rw [← sub_eq_zero, sin_sub_sin, H', add_div, mul_assoc 2 _ π,
mul_div_cancel_left₀ _ (two_ne_zero' ℝ), cos_add_pi_div_two, sin_int_mul_pi, neg_zero,
mul_zero]
theorem cos_sin_inj {θ ψ : ℝ} (Hcos : cos θ = cos ψ) (Hsin : sin θ = sin ψ) : (θ : Angle) = ψ := by
rcases cos_eq_iff_coe_eq_or_eq_neg.mp Hcos with hc | hc; · exact hc
rcases sin_eq_iff_coe_eq_or_add_eq_pi.mp Hsin with hs | hs; · exact hs
rw [eq_neg_iff_add_eq_zero, hs] at hc
obtain ⟨n, hn⟩ : ∃ n, n • _ = _ := QuotientAddGroup.leftRel_apply.mp (Quotient.exact' hc)
rw [← neg_one_mul, add_zero, ← sub_eq_zero, zsmul_eq_mul, ← mul_assoc, ← sub_mul, mul_eq_zero,
eq_false (ne_of_gt pi_pos), or_false, sub_neg_eq_add, ← Int.cast_zero, ← Int.cast_one,
← Int.cast_ofNat, ← Int.cast_mul, ← Int.cast_add, Int.cast_inj] at hn
have : (n * 2 + 1) % (2 : ℤ) = 0 % (2 : ℤ) := congr_arg (· % (2 : ℤ)) hn
rw [add_comm, Int.add_mul_emod_self_right] at this
exact absurd this one_ne_zero
/-- The sine of a `Real.Angle`. -/
def sin (θ : Angle) : ℝ :=
sin_periodic.lift θ
@[simp]
theorem sin_coe (x : ℝ) : sin (x : Angle) = Real.sin x :=
rfl
@[continuity]
theorem continuous_sin : Continuous sin :=
Real.continuous_sin.quotient_liftOn' _
/-- The cosine of a `Real.Angle`. -/
def cos (θ : Angle) : ℝ :=
cos_periodic.lift θ
@[simp]
theorem cos_coe (x : ℝ) : cos (x : Angle) = Real.cos x :=
rfl
@[continuity]
theorem continuous_cos : Continuous cos :=
Real.continuous_cos.quotient_liftOn' _
theorem cos_eq_real_cos_iff_eq_or_eq_neg {θ : Angle} {ψ : ℝ} :
cos θ = Real.cos ψ ↔ θ = ψ ∨ θ = -ψ := by
induction θ using Real.Angle.induction_on
exact cos_eq_iff_coe_eq_or_eq_neg
theorem cos_eq_iff_eq_or_eq_neg {θ ψ : Angle} : cos θ = cos ψ ↔ θ = ψ ∨ θ = -ψ := by
induction ψ using Real.Angle.induction_on
exact cos_eq_real_cos_iff_eq_or_eq_neg
theorem sin_eq_real_sin_iff_eq_or_add_eq_pi {θ : Angle} {ψ : ℝ} :
sin θ = Real.sin ψ ↔ θ = ψ ∨ θ + ψ = π := by
induction θ using Real.Angle.induction_on
exact sin_eq_iff_coe_eq_or_add_eq_pi
theorem sin_eq_iff_eq_or_add_eq_pi {θ ψ : Angle} : sin θ = sin ψ ↔ θ = ψ ∨ θ + ψ = π := by
induction ψ using Real.Angle.induction_on
exact sin_eq_real_sin_iff_eq_or_add_eq_pi
@[simp]
theorem sin_zero : sin (0 : Angle) = 0 := by rw [← coe_zero, sin_coe, Real.sin_zero]
theorem sin_coe_pi : sin (π : Angle) = 0 := by rw [sin_coe, Real.sin_pi]
theorem sin_eq_zero_iff {θ : Angle} : sin θ = 0 ↔ θ = 0 ∨ θ = π := by
nth_rw 1 [← sin_zero]
rw [sin_eq_iff_eq_or_add_eq_pi]
simp
theorem sin_ne_zero_iff {θ : Angle} : sin θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by
rw [← not_or, ← sin_eq_zero_iff]
@[simp]
theorem sin_neg (θ : Angle) : sin (-θ) = -sin θ := by
induction θ using Real.Angle.induction_on
exact Real.sin_neg _
theorem sin_antiperiodic : Function.Antiperiodic sin (π : Angle) := by
intro θ
induction θ using Real.Angle.induction_on
exact Real.sin_antiperiodic _
@[simp]
theorem sin_add_pi (θ : Angle) : sin (θ + π) = -sin θ :=
sin_antiperiodic θ
@[simp]
theorem sin_sub_pi (θ : Angle) : sin (θ - π) = -sin θ :=
sin_antiperiodic.sub_eq θ
@[simp]
theorem cos_zero : cos (0 : Angle) = 1 := by rw [← coe_zero, cos_coe, Real.cos_zero]
theorem cos_coe_pi : cos (π : Angle) = -1 := by rw [cos_coe, Real.cos_pi]
@[simp]
theorem cos_neg (θ : Angle) : cos (-θ) = cos θ := by
induction θ using Real.Angle.induction_on
exact Real.cos_neg _
theorem cos_antiperiodic : Function.Antiperiodic cos (π : Angle) := by
intro θ
induction θ using Real.Angle.induction_on
exact Real.cos_antiperiodic _
@[simp]
theorem cos_add_pi (θ : Angle) : cos (θ + π) = -cos θ :=
cos_antiperiodic θ
@[simp]
theorem cos_sub_pi (θ : Angle) : cos (θ - π) = -cos θ :=
cos_antiperiodic.sub_eq θ
theorem cos_eq_zero_iff {θ : Angle} : cos θ = 0 ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by
rw [← cos_pi_div_two, ← cos_coe, cos_eq_iff_eq_or_eq_neg, ← coe_neg, ← neg_div]
|
theorem sin_add (θ₁ θ₂ : Real.Angle) : sin (θ₁ + θ₂) = sin θ₁ * cos θ₂ + cos θ₁ * sin θ₂ := by
induction θ₁ using Real.Angle.induction_on
| Mathlib/Analysis/SpecialFunctions/Trigonometric/Angle.lean | 352 | 354 |
/-
Copyright (c) 2021 Yakov Pechersky. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yakov Pechersky
-/
import Mathlib.Data.List.MinMax
import Mathlib.Algebra.Tropical.Basic
import Mathlib.Order.ConditionallyCompleteLattice.Finset
import Mathlib.Algebra.BigOperators.Group.Finset.Basic
/-!
# Tropicalization of finitary operations
This file provides the "big-op" or notation-based finitary operations on tropicalized types.
This allows easy conversion between sums to Infs and prods to sums. Results here are important
for expressing that evaluation of tropical polynomials are the minimum over a finite piecewise
collection of linear functions.
## Main declarations
* `untrop_sum`
## Implementation notes
No concrete (semi)ring is used here, only ones with inferable order/lattice structure, to support
`Real`, `Rat`, `EReal`, and others (`ERat` is not yet defined).
Minima over `List α` are defined as producing a value in `WithTop α` so proofs about lists do not
directly transfer to minima over multisets or finsets.
-/
variable {R S : Type*}
open Tropical Finset
theorem List.trop_sum [AddMonoid R] (l : List R) : trop l.sum = List.prod (l.map trop) := by
induction' l with hd tl IH
· simp
· simp [← IH]
theorem Multiset.trop_sum [AddCommMonoid R] (s : Multiset R) :
trop s.sum = Multiset.prod (s.map trop) :=
Quotient.inductionOn s (by simpa using List.trop_sum)
theorem trop_sum [AddCommMonoid R] (s : Finset S) (f : S → R) :
trop (∑ i ∈ s, f i) = ∏ i ∈ s, trop (f i) := by
convert Multiset.trop_sum (s.val.map f)
simp only [Multiset.map_map, Function.comp_apply]
rfl
theorem List.untrop_prod [AddMonoid R] (l : List (Tropical R)) :
untrop l.prod = List.sum (l.map untrop) := by
induction' l with hd tl IH
· simp
· simp [← IH]
theorem Multiset.untrop_prod [AddCommMonoid R] (s : Multiset (Tropical R)) :
untrop s.prod = Multiset.sum (s.map untrop) :=
Quotient.inductionOn s (by simpa using List.untrop_prod)
theorem untrop_prod [AddCommMonoid R] (s : Finset S) (f : S → Tropical R) :
untrop (∏ i ∈ s, f i) = ∑ i ∈ s, untrop (f i) := by
convert Multiset.untrop_prod (s.val.map f)
simp only [Multiset.map_map, Function.comp_apply]
rfl
theorem List.trop_minimum [LinearOrder R] (l : List R) :
trop l.minimum = List.sum (l.map (trop ∘ WithTop.some)) := by
induction' l with hd tl IH
· simp
· simp [List.minimum_cons, ← IH]
theorem Multiset.trop_inf [LinearOrder R] [OrderTop R] (s : Multiset R) :
trop s.inf = Multiset.sum (s.map trop) := by
induction' s using Multiset.induction with s x IH
· simp
· simp [← IH]
theorem Finset.trop_inf [LinearOrder R] [OrderTop R] (s : Finset S) (f : S → R) :
trop (s.inf f) = ∑ i ∈ s, trop (f i) := by
convert Multiset.trop_inf (s.val.map f)
simp only [Multiset.map_map, Function.comp_apply]
rfl
theorem trop_sInf_image [ConditionallyCompleteLinearOrder R] (s : Finset S) (f : S → WithTop R) :
trop (sInf (f '' s)) = ∑ i ∈ s, trop (f i) := by
rcases s.eq_empty_or_nonempty with (rfl | h)
· simp only [Set.image_empty, coe_empty, sum_empty, WithTop.sInf_empty, trop_top]
rw [← inf'_eq_csInf_image _ h, inf'_eq_inf, s.trop_inf]
theorem trop_iInf [ConditionallyCompleteLinearOrder R] [Fintype S] (f : S → WithTop R) :
trop (⨅ i : S, f i) = ∑ i : S, trop (f i) := by
rw [iInf, ← Set.image_univ, ← coe_univ, trop_sInf_image]
theorem Multiset.untrop_sum [LinearOrder R] [OrderTop R] (s : Multiset (Tropical R)) :
untrop s.sum = Multiset.inf (s.map untrop) := by
induction' s using Multiset.induction with s x IH
· simp
· simp only [sum_cons, untrop_add, untrop_le_iff, map_cons, inf_cons, ← IH]
theorem Finset.untrop_sum' [LinearOrder R] [OrderTop R] (s : Finset S) (f : S → Tropical R) :
untrop (∑ i ∈ s, f i) = s.inf (untrop ∘ f) := by
convert Multiset.untrop_sum (s.val.map f)
simp only [Multiset.map_map, Function.comp_apply, inf_def]
theorem untrop_sum_eq_sInf_image [ConditionallyCompleteLinearOrder R] (s : Finset S)
(f : S → Tropical (WithTop R)) : untrop (∑ i ∈ s, f i) = sInf (untrop ∘ f '' s) := by
rcases s.eq_empty_or_nonempty with (rfl | h)
· simp only [Set.image_empty, coe_empty, sum_empty, WithTop.sInf_empty, untrop_zero]
· rw [← inf'_eq_csInf_image _ h, inf'_eq_inf, Finset.untrop_sum']
theorem untrop_sum [ConditionallyCompleteLinearOrder R] [Fintype S] (f : S → Tropical (WithTop R)) :
untrop (∑ i : S, f i) = ⨅ i : S, untrop (f i) := by
rw [iInf, ← Set.image_univ, ← coe_univ, untrop_sum_eq_sInf_image, Function.comp_def]
/-- Note we cannot use `i ∈ s` instead of `i : s` here
as it is simply not true on conditionally complete lattices! -/
theorem Finset.untrop_sum [ConditionallyCompleteLinearOrder R] (s : Finset S)
(f : S → Tropical (WithTop R)) : untrop (∑ i ∈ s, f i) = ⨅ i : s, untrop (f i) := by
simpa [← _root_.untrop_sum] using (sum_attach _ _).symm
| Mathlib/Algebra/Tropical/BigOperators.lean | 141 | 143 | |
/-
Copyright (c) 2024 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Analysis.LocallyConvex.Bounded
import Mathlib.Topology.Algebra.Module.Multilinear.Basic
/-!
# Images of (von Neumann) bounded sets under continuous multilinear maps
In this file we prove that continuous multilinear maps
send von Neumann bounded sets to von Neumann bounded sets.
We prove 2 versions of the theorem:
one assumes that the index type is nonempty,
and the other assumes that the codomain is a topological vector space.
## Implementation notes
We do not assume the index type `ι` to be finite.
While for a nonzero continuous multilinear map
the family `∀ i, E i` has to be essentially finite
(more precisely, all but finitely many `E i` has to be trivial),
proving theorems without a `[Finite ι]` assumption saves us some typeclass searches here and there.
-/
open Bornology Filter Set Function
open scoped Topology
namespace Bornology.IsVonNBounded
variable {ι 𝕜 F : Type*} {E : ι → Type*} [NormedField 𝕜]
[∀ i, AddCommGroup (E i)] [∀ i, Module 𝕜 (E i)] [∀ i, TopologicalSpace (E i)]
[AddCommGroup F] [Module 𝕜 F] [TopologicalSpace F]
/-- The image of a von Neumann bounded set under a continuous multilinear map
is von Neumann bounded.
This version does not assume that the topologies on the domain and on the codomain
agree with the vector space structure in any way
but it assumes that `ι` is nonempty.
-/
theorem image_multilinear' [Nonempty ι] {s : Set (∀ i, E i)} (hs : IsVonNBounded 𝕜 s)
(f : ContinuousMultilinearMap 𝕜 E F) : IsVonNBounded 𝕜 (f '' s) := fun V hV ↦ by
classical
if h₁ : ∀ c : 𝕜, ‖c‖ ≤ 1 then
exact absorbs_iff_norm.2 ⟨2, fun c hc ↦ by linarith [h₁ c]⟩
else
let _ : NontriviallyNormedField 𝕜 := ⟨by simpa using h₁⟩
obtain ⟨I, t, ht₀, hft⟩ :
∃ (I : Finset ι) (t : ∀ i, Set (E i)), (∀ i, t i ∈ 𝓝 0) ∧ Set.pi I t ⊆ f ⁻¹' V := by
have hfV : f ⁻¹' V ∈ 𝓝 0 := (map_continuous f).tendsto' _ _ f.map_zero hV
rwa [nhds_pi, Filter.mem_pi, exists_finite_iff_finset] at hfV
have : ∀ i, ∃ c : 𝕜, c ≠ 0 ∧ ∀ c' : 𝕜, ‖c'‖ ≤ ‖c‖ → ∀ x ∈ s, c' • x i ∈ t i := fun i ↦ by
rw [isVonNBounded_pi_iff] at hs
have := (hs i).tendsto_smallSets_nhds.eventually (mem_lift' (ht₀ i))
rcases NormedAddCommGroup.nhds_zero_basis_norm_lt.eventually_iff.1 this with ⟨r, hr₀, hr⟩
rcases NormedField.exists_norm_lt 𝕜 hr₀ with ⟨c, hc₀, hc⟩
refine ⟨c, norm_pos_iff.1 hc₀, fun c' hle x hx ↦ ?_⟩
exact hr (hle.trans_lt hc) ⟨_, ⟨x, hx, rfl⟩, rfl⟩
choose c hc₀ hc using this
rw [absorbs_iff_eventually_nhds_zero (mem_of_mem_nhds hV),
NormedAddCommGroup.nhds_zero_basis_norm_lt.eventually_iff]
have hc₀' : ∏ i ∈ I, c i ≠ 0 := Finset.prod_ne_zero_iff.2 fun i _ ↦ hc₀ i
refine ⟨‖∏ i ∈ I, c i‖, norm_pos_iff.2 hc₀', fun a ha ↦ mapsTo_image_iff.2 fun x hx ↦ ?_⟩
let ⟨i₀⟩ := ‹Nonempty ι›
set y := I.piecewise (fun i ↦ c i • x i) x
calc
f (update y i₀ ((a / ∏ i ∈ I, c i) • y i₀)) ∈ V := hft fun i hi => by
rcases eq_or_ne i i₀ with rfl | hne
· simp_rw [update_self, y, I.piecewise_eq_of_mem _ _ hi, smul_smul]
refine hc _ _ ?_ _ hx
calc
‖(a / ∏ i ∈ I, c i) * c i‖ ≤ (‖∏ i ∈ I, c i‖ / ‖∏ i ∈ I, c i‖) * ‖c i‖ := by
rw [norm_mul, norm_div]; gcongr; exact ha.out.le
_ ≤ 1 * ‖c i‖ := by gcongr; apply div_self_le_one
_ = ‖c i‖ := one_mul _
· simp_rw [update_of_ne hne, y, I.piecewise_eq_of_mem _ _ hi]
exact hc _ _ le_rfl _ hx
_ = a • f x := by
rw [f.map_update_smul, update_eq_self, f.map_piecewise_smul, div_eq_mul_inv, mul_smul,
inv_smul_smul₀ hc₀']
/-- The image of a von Neumann bounded set under a continuous multilinear map
is von Neumann bounded.
This version assumes that the codomain is a topological vector space.
-/
| theorem image_multilinear [ContinuousSMul 𝕜 F] {s : Set (∀ i, E i)} (hs : IsVonNBounded 𝕜 s)
(f : ContinuousMultilinearMap 𝕜 E F) : IsVonNBounded 𝕜 (f '' s) := by
cases isEmpty_or_nonempty ι with
| inl h =>
exact (isBounded_iff_isVonNBounded _).1 <|
@Set.Finite.isBounded _ (vonNBornology 𝕜 F) _ (s.toFinite.image _)
| inr h => exact hs.image_multilinear' f
| Mathlib/Topology/Algebra/Module/Multilinear/Bounded.lean | 90 | 96 |
/-
Copyright (c) 2021 Yakov Pechersky. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yakov Pechersky
-/
import Mathlib.Algebra.Order.Group.Nat
import Mathlib.Data.List.Rotate
import Mathlib.GroupTheory.Perm.Support
/-!
# Permutations from a list
A list `l : List α` can be interpreted as an `Equiv.Perm α` where each element in the list
is permuted to the next one, defined as `formPerm`. When we have that `Nodup l`,
we prove that `Equiv.Perm.support (formPerm l) = l.toFinset`, and that
`formPerm l` is rotationally invariant, in `formPerm_rotate`.
When there are duplicate elements in `l`, how and in what arrangement with respect to the other
elements they appear in the list determines the formed permutation.
This is because `List.formPerm` is implemented as a product of `Equiv.swap`s.
That means that presence of a sublist of two adjacent duplicates like `[..., x, x, ...]`
will produce the same permutation as if the adjacent duplicates were not present.
The `List.formPerm` definition is meant to primarily be used with `Nodup l`, so that
the resulting permutation is cyclic (if `l` has at least two elements).
The presence of duplicates in a particular placement can lead `List.formPerm` to produce a
nontrivial permutation that is noncyclic.
-/
namespace List
variable {α β : Type*}
section FormPerm
variable [DecidableEq α] (l : List α)
open Equiv Equiv.Perm
/-- A list `l : List α` can be interpreted as an `Equiv.Perm α` where each element in the list
is permuted to the next one, defined as `formPerm`. When we have that `Nodup l`,
we prove that `Equiv.Perm.support (formPerm l) = l.toFinset`, and that
`formPerm l` is rotationally invariant, in `formPerm_rotate`.
-/
def formPerm : Equiv.Perm α :=
(zipWith Equiv.swap l l.tail).prod
@[simp]
theorem formPerm_nil : formPerm ([] : List α) = 1 :=
rfl
@[simp]
theorem formPerm_singleton (x : α) : formPerm [x] = 1 :=
rfl
@[simp]
theorem formPerm_cons_cons (x y : α) (l : List α) :
formPerm (x :: y :: l) = swap x y * formPerm (y :: l) :=
prod_cons
theorem formPerm_pair (x y : α) : formPerm [x, y] = swap x y :=
rfl
theorem mem_or_mem_of_zipWith_swap_prod_ne : ∀ {l l' : List α} {x : α},
(zipWith swap l l').prod x ≠ x → x ∈ l ∨ x ∈ l'
| [], _, _ => by simp
| _, [], _ => by simp
| a::l, b::l', x => fun hx ↦
if h : (zipWith swap l l').prod x = x then
(eq_or_eq_of_swap_apply_ne_self (a := a) (b := b) (x := x) (by simpa [h] using hx)).imp
(by rintro rfl; exact .head _) (by rintro rfl; exact .head _)
else
(mem_or_mem_of_zipWith_swap_prod_ne h).imp (.tail _) (.tail _)
theorem zipWith_swap_prod_support' (l l' : List α) :
{ x | (zipWith swap l l').prod x ≠ x } ≤ l.toFinset ⊔ l'.toFinset := fun _ h ↦ by
simpa using mem_or_mem_of_zipWith_swap_prod_ne h
theorem zipWith_swap_prod_support [Fintype α] (l l' : List α) :
(zipWith swap l l').prod.support ≤ l.toFinset ⊔ l'.toFinset := by
intro x hx
have hx' : x ∈ { x | (zipWith swap l l').prod x ≠ x } := by simpa using hx
simpa using zipWith_swap_prod_support' _ _ hx'
theorem support_formPerm_le' : { x | formPerm l x ≠ x } ≤ l.toFinset := by
refine (zipWith_swap_prod_support' l l.tail).trans ?_
simpa [Finset.subset_iff] using tail_subset l
theorem support_formPerm_le [Fintype α] : support (formPerm l) ≤ l.toFinset := by
intro x hx
have hx' : x ∈ { x | formPerm l x ≠ x } := by simpa using hx
simpa using support_formPerm_le' _ hx'
variable {l} {x : α}
theorem mem_of_formPerm_apply_ne (h : l.formPerm x ≠ x) : x ∈ l := by
simpa [or_iff_left_of_imp mem_of_mem_tail] using mem_or_mem_of_zipWith_swap_prod_ne h
theorem formPerm_apply_of_not_mem (h : x ∉ l) : formPerm l x = x :=
not_imp_comm.1 mem_of_formPerm_apply_ne h
theorem formPerm_apply_mem_of_mem (h : x ∈ l) : formPerm l x ∈ l := by
rcases l with - | ⟨y, l⟩
· simp at h
induction' l with z l IH generalizing x y
· simpa using h
· by_cases hx : x ∈ z :: l
· rw [formPerm_cons_cons, mul_apply, swap_apply_def]
split_ifs
· simp [IH _ hx]
· simp
· simp [*]
· replace h : x = y := Or.resolve_right (mem_cons.1 h) hx
simp [formPerm_apply_of_not_mem hx, ← h]
theorem mem_of_formPerm_apply_mem (h : l.formPerm x ∈ l) : x ∈ l := by
contrapose h
rwa [formPerm_apply_of_not_mem h]
@[simp]
theorem formPerm_mem_iff_mem : l.formPerm x ∈ l ↔ x ∈ l :=
⟨l.mem_of_formPerm_apply_mem, l.formPerm_apply_mem_of_mem⟩
@[simp]
theorem formPerm_cons_concat_apply_last (x y : α) (xs : List α) :
formPerm (x :: (xs ++ [y])) y = x := by
induction' xs with z xs IH generalizing x y
· simp
· simp [IH]
@[simp]
theorem formPerm_apply_getLast (x : α) (xs : List α) :
formPerm (x :: xs) ((x :: xs).getLast (cons_ne_nil x xs)) = x := by
induction' xs using List.reverseRecOn with xs y _ generalizing x <;> simp
@[simp]
theorem formPerm_apply_getElem_length (x : α) (xs : List α) :
formPerm (x :: xs) (x :: xs)[xs.length] = x := by
rw [getElem_cons_length rfl, formPerm_apply_getLast]
theorem formPerm_apply_head (x y : α) (xs : List α) (h : Nodup (x :: y :: xs)) :
formPerm (x :: y :: xs) x = y := by simp [formPerm_apply_of_not_mem h.not_mem]
theorem formPerm_apply_getElem_zero (l : List α) (h : Nodup l) (hl : 1 < l.length) :
formPerm l l[0] = l[1] := by
rcases l with (_ | ⟨x, _ | ⟨y, tl⟩⟩)
· simp at hl
· simp at hl
| · rw [getElem_cons_zero, formPerm_apply_head _ _ _ h, getElem_cons_succ, getElem_cons_zero]
variable (l)
| Mathlib/GroupTheory/Perm/List.lean | 150 | 152 |
/-
Copyright (c) 2024 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.TotalComplex
/-! The symmetry of the total complex of a bicomplex
Let `K : HomologicalComplex₂ C c₁ c₂` be a bicomplex. If we assume both
`[TotalComplexShape c₁ c₂ c]` and `[TotalComplexShape c₂ c₁ c]`, we may form
the total complex `K.total c` and `K.flip.total c`.
In this file, we show that if we assume `[TotalComplexShapeSymmetry c₁ c₂ c]`,
then there is an isomorphism `K.totalFlipIso c : K.flip.total c ≅ K.total c`.
Moreover, if we also have `[TotalComplexShapeSymmetry c₂ c₁ c]` and that the signs
are compatible `[TotalComplexShapeSymmetrySymmetry c₁ c₂ c]`, then the isomorphisms
`K.totalFlipIso c` and `K.flip.totalFlipIso c` are inverse to each other.
-/
assert_not_exists Ideal TwoSidedIdeal
open CategoryTheory Category Limits
namespace HomologicalComplex₂
variable {C I₁ I₂ J : Type*} [Category C] [Preadditive C]
{c₁ : ComplexShape I₁} {c₂ : ComplexShape I₂} (K : HomologicalComplex₂ C c₁ c₂)
(c : ComplexShape J) [TotalComplexShape c₁ c₂ c] [TotalComplexShape c₂ c₁ c]
[TotalComplexShapeSymmetry c₁ c₂ c]
instance [K.HasTotal c] : K.flip.HasTotal c := fun j =>
hasCoproduct_of_equiv_of_iso (K.toGradedObject.mapObjFun (ComplexShape.π c₁ c₂ c) j) _
(ComplexShape.symmetryEquiv c₁ c₂ c j) (fun _ => Iso.refl _)
lemma flip_hasTotal_iff : K.flip.HasTotal c ↔ K.HasTotal c := by
constructor
· intro
change K.flip.flip.HasTotal c
have := TotalComplexShapeSymmetry.symmetry c₁ c₂ c
infer_instance
| · intro
infer_instance
variable [K.HasTotal c] [DecidableEq J]
attribute [local simp] smul_smul
/-- Auxiliary definition for `totalFlipIso`. -/
noncomputable def totalFlipIsoX (j : J) : (K.flip.total c).X j ≅ (K.total c).X j where
hom := K.flip.totalDesc (fun i₂ i₁ h => ComplexShape.σ c₁ c₂ c i₁ i₂ • K.ιTotal c i₁ i₂ j (by
rw [← ComplexShape.π_symm c₁ c₂ c i₁ i₂, h]))
inv := K.totalDesc (fun i₁ i₂ h => ComplexShape.σ c₁ c₂ c i₁ i₂ • K.flip.ιTotal c i₂ i₁ j (by
rw [ComplexShape.π_symm c₁ c₂ c i₁ i₂, h]))
hom_inv_id := by ext; simp
inv_hom_id := by ext; simp
@[reassoc]
lemma totalFlipIsoX_hom_D₁ (j j' : J) :
(K.totalFlipIsoX c j).hom ≫ K.D₁ c j j' =
K.flip.D₂ c j j' ≫ (K.totalFlipIsoX c j').hom := by
| Mathlib/Algebra/Homology/TotalComplexSymmetry.lean | 44 | 63 |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.MeasureTheory.OuterMeasure.Operations
import Mathlib.Analysis.SpecificLimits.Basic
/-!
# Outer measures from functions
Given an arbitrary function `m : Set α → ℝ≥0∞` that sends `∅` to `0` we can define an outer
measure on `α` that on `s` is defined to be the infimum of `∑ᵢ, m (sᵢ)` for all collections of sets
`sᵢ` that cover `s`. This is the unique maximal outer measure that is at most the given function.
Given an outer measure `m`, the Carathéodory-measurable sets are the sets `s` such that
for all sets `t` we have `m t = m (t ∩ s) + m (t \ s)`. This forms a measurable space.
## Main definitions and statements
* `OuterMeasure.boundedBy` is the greatest outer measure that is at most the given function.
If you know that the given function sends `∅` to `0`, then `OuterMeasure.ofFunction` is a
special case.
* `sInf_eq_boundedBy_sInfGen` is a characterization of the infimum of outer measures.
## References
* <https://en.wikipedia.org/wiki/Outer_measure>
* <https://en.wikipedia.org/wiki/Carath%C3%A9odory%27s_criterion>
## Tags
outer measure, Carathéodory-measurable, Carathéodory's criterion
-/
assert_not_exists Basis
noncomputable section
open Set Function Filter
open scoped NNReal Topology ENNReal
namespace MeasureTheory
namespace OuterMeasure
section OfFunction
variable {α : Type*}
/-- Given any function `m` assigning measures to sets satisfying `m ∅ = 0`, there is
a unique maximal outer measure `μ` satisfying `μ s ≤ m s` for all `s : Set α`. -/
protected def ofFunction (m : Set α → ℝ≥0∞) (m_empty : m ∅ = 0) : OuterMeasure α :=
let μ s := ⨅ (f : ℕ → Set α) (_ : s ⊆ ⋃ i, f i), ∑' i, m (f i)
{ measureOf := μ
empty :=
le_antisymm
((iInf_le_of_le fun _ => ∅) <| iInf_le_of_le (empty_subset _) <| by simp [m_empty])
(zero_le _)
mono := fun {_ _} hs => iInf_mono fun _ => iInf_mono' fun hb => ⟨hs.trans hb, le_rfl⟩
iUnion_nat := fun s _ =>
ENNReal.le_of_forall_pos_le_add <| by
intro ε hε (hb : (∑' i, μ (s i)) < ∞)
rcases ENNReal.exists_pos_sum_of_countable (ENNReal.coe_pos.2 hε).ne' ℕ with ⟨ε', hε', hl⟩
refine le_trans ?_ (add_le_add_left (le_of_lt hl) _)
rw [← ENNReal.tsum_add]
choose f hf using
show ∀ i, ∃ f : ℕ → Set α, (s i ⊆ ⋃ i, f i) ∧ (∑' i, m (f i)) < μ (s i) + ε' i by
intro i
have : μ (s i) < μ (s i) + ε' i :=
ENNReal.lt_add_right (ne_top_of_le_ne_top hb.ne <| ENNReal.le_tsum _)
(by simpa using (hε' i).ne')
rcases iInf_lt_iff.mp this with ⟨t, ht⟩
exists t
contrapose! ht
exact le_iInf ht
refine le_trans ?_ (ENNReal.tsum_le_tsum fun i => le_of_lt (hf i).2)
rw [← ENNReal.tsum_prod, ← Nat.pairEquiv.symm.tsum_eq]
refine iInf_le_of_le _ (iInf_le _ ?_)
apply iUnion_subset
intro i
apply Subset.trans (hf i).1
apply iUnion_subset
simp only [Nat.pairEquiv_symm_apply]
rw [iUnion_unpair]
intro j
apply subset_iUnion₂ i }
variable (m : Set α → ℝ≥0∞) (m_empty : m ∅ = 0)
/-- `ofFunction` of a set `s` is the infimum of `∑ᵢ, m (tᵢ)` for all collections of sets
`tᵢ` that cover `s`. -/
theorem ofFunction_apply (s : Set α) :
OuterMeasure.ofFunction m m_empty s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, m (t n) :=
rfl
/-- `ofFunction` of a set `s` is the infimum of `∑ᵢ, m (tᵢ)` for all collections of sets
`tᵢ` that cover `s`, with all `tᵢ` satisfying a predicate `P` such that `m` is infinite for sets
that don't satisfy `P`.
This is similar to `ofFunction_apply`, except that the sets `tᵢ` satisfy `P`.
The hypothesis `m_top` applies in particular to a function of the form `extend m'`. -/
theorem ofFunction_eq_iInf_mem {P : Set α → Prop} (m_top : ∀ s, ¬ P s → m s = ∞) (s : Set α) :
OuterMeasure.ofFunction m m_empty s =
⨅ (t : ℕ → Set α) (_ : ∀ i, P (t i)) (_ : s ⊆ ⋃ i, t i), ∑' i, m (t i) := by
rw [OuterMeasure.ofFunction_apply]
apply le_antisymm
· exact le_iInf fun t ↦ le_iInf fun _ ↦ le_iInf fun h ↦ iInf₂_le _ (by exact h)
· simp_rw [le_iInf_iff]
refine fun t ht_subset ↦ iInf_le_of_le t ?_
by_cases ht : ∀ i, P (t i)
· exact iInf_le_of_le ht (iInf_le_of_le ht_subset le_rfl)
· simp only [ht, not_false_eq_true, iInf_neg, top_le_iff]
push_neg at ht
obtain ⟨i, hti_not_mem⟩ := ht
have hfi_top : m (t i) = ∞ := m_top _ hti_not_mem
exact ENNReal.tsum_eq_top_of_eq_top ⟨i, hfi_top⟩
variable {m m_empty}
theorem ofFunction_le (s : Set α) : OuterMeasure.ofFunction m m_empty s ≤ m s :=
let f : ℕ → Set α := fun i => Nat.casesOn i s fun _ => ∅
iInf_le_of_le f <|
iInf_le_of_le (subset_iUnion f 0) <|
le_of_eq <| tsum_eq_single 0 <| by
rintro (_ | i)
· simp
· simp [f, m_empty]
theorem ofFunction_eq (s : Set α) (m_mono : ∀ ⦃t : Set α⦄, s ⊆ t → m s ≤ m t)
(m_subadd : ∀ s : ℕ → Set α, m (⋃ i, s i) ≤ ∑' i, m (s i)) :
OuterMeasure.ofFunction m m_empty s = m s :=
le_antisymm (ofFunction_le s) <|
le_iInf fun f => le_iInf fun hf => le_trans (m_mono hf) (m_subadd f)
theorem le_ofFunction {μ : OuterMeasure α} :
μ ≤ OuterMeasure.ofFunction m m_empty ↔ ∀ s, μ s ≤ m s :=
⟨fun H s => le_trans (H s) (ofFunction_le s), fun H _ =>
le_iInf fun f =>
le_iInf fun hs =>
le_trans (μ.mono hs) <| le_trans (measure_iUnion_le f) <| ENNReal.tsum_le_tsum fun _ => H _⟩
theorem isGreatest_ofFunction :
IsGreatest { μ : OuterMeasure α | ∀ s, μ s ≤ m s } (OuterMeasure.ofFunction m m_empty) :=
⟨fun _ => ofFunction_le _, fun _ => le_ofFunction.2⟩
theorem ofFunction_eq_sSup : OuterMeasure.ofFunction m m_empty = sSup { μ | ∀ s, μ s ≤ m s } :=
(@isGreatest_ofFunction α m m_empty).isLUB.sSup_eq.symm
/-- If `m u = ∞` for any set `u` that has nonempty intersection both with `s` and `t`, then
`μ (s ∪ t) = μ s + μ t`, where `μ = MeasureTheory.OuterMeasure.ofFunction m m_empty`.
E.g., if `α` is an (e)metric space and `m u = ∞` on any set of diameter `≥ r`, then this lemma
implies that `μ (s ∪ t) = μ s + μ t` on any two sets such that `r ≤ edist x y` for all `x ∈ s`
and `y ∈ t`. -/
theorem ofFunction_union_of_top_of_nonempty_inter {s t : Set α}
(h : ∀ u, (s ∩ u).Nonempty → (t ∩ u).Nonempty → m u = ∞) :
OuterMeasure.ofFunction m m_empty (s ∪ t) =
OuterMeasure.ofFunction m m_empty s + OuterMeasure.ofFunction m m_empty t := by
refine le_antisymm (measure_union_le _ _) (le_iInf₂ fun f hf ↦ ?_)
set μ := OuterMeasure.ofFunction m m_empty
rcases Classical.em (∃ i, (s ∩ f i).Nonempty ∧ (t ∩ f i).Nonempty) with (⟨i, hs, ht⟩ | he)
· calc
μ s + μ t ≤ ∞ := le_top
_ = m (f i) := (h (f i) hs ht).symm
_ ≤ ∑' i, m (f i) := ENNReal.le_tsum i
set I := fun s => { i : ℕ | (s ∩ f i).Nonempty }
have hd : Disjoint (I s) (I t) := disjoint_iff_inf_le.mpr fun i hi => he ⟨i, hi⟩
have hI : ∀ u ⊆ s ∪ t, μ u ≤ ∑' i : I u, μ (f i) := fun u hu =>
calc
μ u ≤ μ (⋃ i : I u, f i) :=
μ.mono fun x hx =>
let ⟨i, hi⟩ := mem_iUnion.1 (hf (hu hx))
mem_iUnion.2 ⟨⟨i, ⟨x, hx, hi⟩⟩, hi⟩
_ ≤ ∑' i : I u, μ (f i) := measure_iUnion_le _
calc
μ s + μ t ≤ (∑' i : I s, μ (f i)) + ∑' i : I t, μ (f i) :=
add_le_add (hI _ subset_union_left) (hI _ subset_union_right)
_ = ∑' i : ↑(I s ∪ I t), μ (f i) :=
(ENNReal.summable.tsum_union_disjoint (f := fun i => μ (f i)) hd ENNReal.summable).symm
_ ≤ ∑' i, μ (f i) :=
(ENNReal.summable.tsum_le_tsum_of_inj (↑) Subtype.coe_injective (fun _ _ => zero_le _)
(fun _ => le_rfl) ENNReal.summable)
_ ≤ ∑' i, m (f i) := ENNReal.tsum_le_tsum fun i => ofFunction_le _
theorem comap_ofFunction {β} (f : β → α) (h : Monotone m ∨ Surjective f) :
comap f (OuterMeasure.ofFunction m m_empty) =
OuterMeasure.ofFunction (fun s => m (f '' s)) (by simp; simp [m_empty]) := by
refine le_antisymm (le_ofFunction.2 fun s => ?_) fun s => ?_
· rw [comap_apply]
apply ofFunction_le
· rw [comap_apply, ofFunction_apply, ofFunction_apply]
refine iInf_mono' fun t => ⟨fun k => f ⁻¹' t k, ?_⟩
refine iInf_mono' fun ht => ?_
rw [Set.image_subset_iff, preimage_iUnion] at ht
refine ⟨ht, ENNReal.tsum_le_tsum fun n => ?_⟩
rcases h with hl | hr
exacts [hl (image_preimage_subset _ _), (congr_arg m (hr.image_preimage (t n))).le]
theorem map_ofFunction_le {β} (f : α → β) :
map f (OuterMeasure.ofFunction m m_empty) ≤
OuterMeasure.ofFunction (fun s => m (f ⁻¹' s)) m_empty :=
le_ofFunction.2 fun s => by
rw [map_apply]
apply ofFunction_le
theorem map_ofFunction {β} {f : α → β} (hf : Injective f) :
map f (OuterMeasure.ofFunction m m_empty) =
OuterMeasure.ofFunction (fun s => m (f ⁻¹' s)) m_empty := by
refine (map_ofFunction_le _).antisymm fun s => ?_
simp only [ofFunction_apply, map_apply, le_iInf_iff]
intro t ht
refine iInf_le_of_le (fun n => (range f)ᶜ ∪ f '' t n) (iInf_le_of_le ?_ ?_)
· rw [← union_iUnion, ← inter_subset, ← image_preimage_eq_inter_range, ← image_iUnion]
exact image_subset _ ht
· refine ENNReal.tsum_le_tsum fun n => le_of_eq ?_
simp [hf.preimage_image]
-- TODO (kmill): change `m (t ∩ s)` to `m (s ∩ t)`
theorem restrict_ofFunction (s : Set α) (hm : Monotone m) :
restrict s (OuterMeasure.ofFunction m m_empty) =
OuterMeasure.ofFunction (fun t => m (t ∩ s)) (by simp; simp [m_empty]) := by
rw [restrict]
simp only [inter_comm _ s, LinearMap.comp_apply]
rw [comap_ofFunction _ (Or.inl hm)]
simp only [map_ofFunction Subtype.coe_injective, Subtype.image_preimage_coe]
theorem smul_ofFunction {c : ℝ≥0∞} (hc : c ≠ ∞) : c • OuterMeasure.ofFunction m m_empty =
OuterMeasure.ofFunction (c • m) (by simp [m_empty]) := by
ext1 s
haveI : Nonempty { t : ℕ → Set α // s ⊆ ⋃ i, t i } := ⟨⟨fun _ => s, subset_iUnion (fun _ => s) 0⟩⟩
simp only [smul_apply, ofFunction_apply, ENNReal.tsum_mul_left, Pi.smul_apply, smul_eq_mul,
iInf_subtype']
rw [ENNReal.mul_iInf fun h => (hc h).elim]
end OfFunction
section BoundedBy
variable {α : Type*} (m : Set α → ℝ≥0∞)
/-- Given any function `m` assigning measures to sets, there is a unique maximal outer measure `μ`
satisfying `μ s ≤ m s` for all `s : Set α`. This is the same as `OuterMeasure.ofFunction`,
except that it doesn't require `m ∅ = 0`. -/
def boundedBy : OuterMeasure α :=
OuterMeasure.ofFunction (fun s => ⨆ _ : s.Nonempty, m s) (by simp [Set.not_nonempty_empty])
variable {m}
theorem boundedBy_le (s : Set α) : boundedBy m s ≤ m s :=
(ofFunction_le _).trans iSup_const_le
theorem boundedBy_eq_ofFunction (m_empty : m ∅ = 0) (s : Set α) :
boundedBy m s = OuterMeasure.ofFunction m m_empty s := by
have : (fun s : Set α => ⨆ _ : s.Nonempty, m s) = m := by
ext1 t
rcases t.eq_empty_or_nonempty with h | h <;> simp [h, Set.not_nonempty_empty, m_empty]
simp [boundedBy, this]
theorem boundedBy_apply (s : Set α) :
boundedBy m s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t),
∑' n, ⨆ _ : (t n).Nonempty, m (t n) := by
simp [boundedBy, ofFunction_apply]
theorem boundedBy_eq (s : Set α) (m_empty : m ∅ = 0) (m_mono : ∀ ⦃t : Set α⦄, s ⊆ t → m s ≤ m t)
(m_subadd : ∀ s : ℕ → Set α, m (⋃ i, s i) ≤ ∑' i, m (s i)) : boundedBy m s = m s := by
rw [boundedBy_eq_ofFunction m_empty, ofFunction_eq s m_mono m_subadd]
@[simp]
theorem boundedBy_eq_self (m : OuterMeasure α) : boundedBy m = m :=
ext fun _ => boundedBy_eq _ measure_empty (fun _ ht => measure_mono ht) measure_iUnion_le
theorem le_boundedBy {μ : OuterMeasure α} : μ ≤ boundedBy m ↔ ∀ s, μ s ≤ m s := by
rw [boundedBy , le_ofFunction, forall_congr']; intro s
rcases s.eq_empty_or_nonempty with h | h <;> simp [h, Set.not_nonempty_empty]
theorem le_boundedBy' {μ : OuterMeasure α} :
μ ≤ boundedBy m ↔ ∀ s : Set α, s.Nonempty → μ s ≤ m s := by
rw [le_boundedBy, forall_congr']
intro s
rcases s.eq_empty_or_nonempty with h | h <;> simp [h]
@[simp]
theorem boundedBy_top : boundedBy (⊤ : Set α → ℝ≥0∞) = ⊤ := by
rw [eq_top_iff, le_boundedBy']
intro s hs
rw [top_apply hs]
exact le_rfl
@[simp]
theorem boundedBy_zero : boundedBy (0 : Set α → ℝ≥0∞) = 0 := by
rw [← coe_bot, eq_bot_iff]
apply boundedBy_le
theorem smul_boundedBy {c : ℝ≥0∞} (hc : c ≠ ∞) : c • boundedBy m = boundedBy (c • m) := by
simp only [boundedBy , smul_ofFunction hc]
congr 1 with s : 1
rcases s.eq_empty_or_nonempty with (rfl | hs) <;> simp [*]
theorem comap_boundedBy {β} (f : β → α)
(h : (Monotone fun s : { s : Set α // s.Nonempty } => m s) ∨ Surjective f) :
comap f (boundedBy m) = boundedBy fun s => m (f '' s) := by
refine (comap_ofFunction _ ?_).trans ?_
· refine h.imp (fun H s t hst => iSup_le fun hs => ?_) id
have ht : t.Nonempty := hs.mono hst
exact (@H ⟨s, hs⟩ ⟨t, ht⟩ hst).trans (le_iSup (fun _ : t.Nonempty => m t) ht)
· dsimp only [boundedBy]
congr with s : 1
rw [image_nonempty]
/-- If `m u = ∞` for any set `u` that has nonempty intersection both with `s` and `t`, then
`μ (s ∪ t) = μ s + μ t`, where `μ = MeasureTheory.OuterMeasure.boundedBy m`.
E.g., if `α` is an (e)metric space and `m u = ∞` on any set of diameter `≥ r`, then this lemma
implies that `μ (s ∪ t) = μ s + μ t` on any two sets such that `r ≤ edist x y` for all `x ∈ s`
and `y ∈ t`. -/
theorem boundedBy_union_of_top_of_nonempty_inter {s t : Set α}
(h : ∀ u, (s ∩ u).Nonempty → (t ∩ u).Nonempty → m u = ∞) :
boundedBy m (s ∪ t) = boundedBy m s + boundedBy m t :=
ofFunction_union_of_top_of_nonempty_inter fun u hs ht =>
top_unique <| (h u hs ht).ge.trans <| le_iSup (fun _ => m u) (hs.mono inter_subset_right)
end BoundedBy
section sInfGen
variable {α : Type*}
/-- Given a set of outer measures, we define a new function that on a set `s` is defined to be the
infimum of `μ(s)` for the outer measures `μ` in the collection. We ensure that this
function is defined to be `0` on `∅`, even if the collection of outer measures is empty.
The outer measure generated by this function is the infimum of the given outer measures. -/
def sInfGen (m : Set (OuterMeasure α)) (s : Set α) : ℝ≥0∞ :=
⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ s
theorem sInfGen_def (m : Set (OuterMeasure α)) (t : Set α) :
sInfGen m t = ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ t :=
rfl
theorem sInf_eq_boundedBy_sInfGen (m : Set (OuterMeasure α)) :
sInf m = OuterMeasure.boundedBy (sInfGen m) := by
refine le_antisymm ?_ ?_
· refine le_boundedBy.2 fun s => le_iInf₂ fun μ hμ => ?_
apply sInf_le hμ
· refine le_sInf ?_
intro μ hμ t
exact le_trans (boundedBy_le t) (iInf₂_le μ hμ)
theorem iSup_sInfGen_nonempty {m : Set (OuterMeasure α)} (h : m.Nonempty) (t : Set α) :
⨆ _ : t.Nonempty, sInfGen m t = ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ t := by
rcases t.eq_empty_or_nonempty with (rfl | ht)
· simp [biInf_const h]
· simp [ht, sInfGen_def]
/-- The value of the Infimum of a nonempty set of outer measures on a set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem sInf_apply {m : Set (OuterMeasure α)} {s : Set α} (h : m.Nonempty) :
sInf m s =
⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ (t n) := by
simp_rw [sInf_eq_boundedBy_sInfGen, boundedBy_apply, iSup_sInfGen_nonempty h]
/-- The value of the Infimum of a set of outer measures on a nonempty set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem sInf_apply' {m : Set (OuterMeasure α)} {s : Set α} (h : s.Nonempty) :
sInf m s =
⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ (t n) :=
m.eq_empty_or_nonempty.elim (fun hm => by simp [hm, h]) sInf_apply
/-- The value of the Infimum of a nonempty family of outer measures on a set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem iInf_apply {ι} [Nonempty ι] (m : ι → OuterMeasure α) (s : Set α) :
(⨅ i, m i) s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ i, m i (t n) := by
rw [iInf, sInf_apply (range_nonempty m)]
simp only [iInf_range]
/-- The value of the Infimum of a family of outer measures on a nonempty set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem iInf_apply' {ι} (m : ι → OuterMeasure α) {s : Set α} (hs : s.Nonempty) :
(⨅ i, m i) s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ i, m i (t n) := by
rw [iInf, sInf_apply' hs]
simp only [iInf_range]
/-- The value of the Infimum of a nonempty family of outer measures on a set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem biInf_apply {ι} {I : Set ι} (hI : I.Nonempty) (m : ι → OuterMeasure α) (s : Set α) :
(⨅ i ∈ I, m i) s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ i ∈ I, m i (t n) := by
| haveI := hI.to_subtype
simp only [← iInf_subtype'', iInf_apply]
/-- The value of the Infimum of a nonempty family of outer measures on a set is not simply
| Mathlib/MeasureTheory/OuterMeasure/OfFunction.lean | 393 | 396 |
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Kevin Buzzard
-/
import Mathlib.Algebra.BigOperators.Field
import Mathlib.RingTheory.PowerSeries.Inverse
import Mathlib.RingTheory.PowerSeries.WellKnown
/-!
# Bernoulli numbers
The Bernoulli numbers are a sequence of rational numbers that frequently show up in
number theory.
## Mathematical overview
The Bernoulli numbers $(B_0, B_1, B_2, \ldots)=(1, -1/2, 1/6, 0, -1/30, \ldots)$ are
a sequence of rational numbers. They show up in the formula for the sums of $k$th
powers. They are related to the Taylor series expansions of $x/\tan(x)$ and
of $\coth(x)$, and also show up in the values that the Riemann Zeta function
takes both at both negative and positive integers (and hence in the
theory of modular forms). For example, if $1 \leq n$ then
$$\zeta(2n)=\sum_{t\geq1}t^{-2n}=(-1)^{n+1}\frac{(2\pi)^{2n}B_{2n}}{2(2n)!}.$$
This result is formalised in Lean: `riemannZeta_two_mul_nat`.
The Bernoulli numbers can be formally defined using the power series
$$\sum B_n\frac{t^n}{n!}=\frac{t}{1-e^{-t}}$$
although that happens to not be the definition in mathlib (this is an *implementation
detail* and need not concern the mathematician).
Note that $B_1=-1/2$, meaning that we are using the $B_n^-$ of
[from Wikipedia](https://en.wikipedia.org/wiki/Bernoulli_number).
## Implementation detail
The Bernoulli numbers are defined using well-founded induction, by the formula
$$B_n=1-\sum_{k\lt n}\frac{\binom{n}{k}}{n-k+1}B_k.$$
This formula is true for all $n$ and in particular $B_0=1$. Note that this is the definition
for positive Bernoulli numbers, which we call `bernoulli'`. The negative Bernoulli numbers are
then defined as `bernoulli := (-1)^n * bernoulli'`.
## Main theorems
`sum_bernoulli : ∑ k ∈ Finset.range n, (n.choose k : ℚ) * bernoulli k = if n = 1 then 1 else 0`
-/
open Nat Finset Finset.Nat PowerSeries
variable (A : Type*) [CommRing A] [Algebra ℚ A]
/-! ### Definitions -/
/-- The Bernoulli numbers:
the $n$-th Bernoulli number $B_n$ is defined recursively via
$$B_n = 1 - \sum_{k < n} \binom{n}{k}\frac{B_k}{n+1-k}$$ -/
def bernoulli' : ℕ → ℚ :=
WellFounded.fix Nat.lt_wfRel.wf fun n bernoulli' =>
1 - ∑ k : Fin n, n.choose k / (n - k + 1) * bernoulli' k k.2
theorem bernoulli'_def' (n : ℕ) :
bernoulli' n = 1 - ∑ k : Fin n, n.choose k / (n - k + 1) * bernoulli' k :=
WellFounded.fix_eq _ _ _
theorem bernoulli'_def (n : ℕ) :
bernoulli' n = 1 - ∑ k ∈ range n, n.choose k / (n - k + 1) * bernoulli' k := by
rw [bernoulli'_def', ← Fin.sum_univ_eq_sum_range]
theorem bernoulli'_spec (n : ℕ) :
(∑ k ∈ range n.succ, (n.choose (n - k) : ℚ) / (n - k + 1) * bernoulli' k) = 1 := by
rw [sum_range_succ_comm, bernoulli'_def n, tsub_self, choose_zero_right, sub_self, zero_add,
div_one, cast_one, one_mul, sub_add, ← sum_sub_distrib, ← sub_eq_zero, sub_sub_cancel_left,
neg_eq_zero]
exact Finset.sum_eq_zero (fun x hx => by rw [choose_symm (le_of_lt (mem_range.1 hx)), sub_self])
theorem bernoulli'_spec' (n : ℕ) :
(∑ k ∈ antidiagonal n, ((k.1 + k.2).choose k.2 : ℚ) / (k.2 + 1) * bernoulli' k.1) = 1 := by
refine ((sum_antidiagonal_eq_sum_range_succ_mk _ n).trans ?_).trans (bernoulli'_spec n)
refine sum_congr rfl fun x hx => ?_
simp only [add_tsub_cancel_of_le, mem_range_succ_iff.mp hx, cast_sub]
/-! ### Examples -/
section Examples
@[simp]
theorem bernoulli'_zero : bernoulli' 0 = 1 := by
rw [bernoulli'_def]
norm_num
@[simp]
theorem bernoulli'_one : bernoulli' 1 = 1 / 2 := by
rw [bernoulli'_def]
norm_num
@[simp]
theorem bernoulli'_two : bernoulli' 2 = 1 / 6 := by
rw [bernoulli'_def]
norm_num [sum_range_succ, sum_range_succ, sum_range_zero]
@[simp]
theorem bernoulli'_three : bernoulli' 3 = 0 := by
rw [bernoulli'_def]
norm_num [sum_range_succ, sum_range_succ, sum_range_zero]
@[simp]
theorem bernoulli'_four : bernoulli' 4 = -1 / 30 := by
have : Nat.choose 4 2 = 6 := by decide -- shrug
rw [bernoulli'_def]
norm_num [sum_range_succ, sum_range_succ, sum_range_zero, this]
end Examples
@[simp]
theorem sum_bernoulli' (n : ℕ) : (∑ k ∈ range n, (n.choose k : ℚ) * bernoulli' k) = n := by
cases n with | zero => simp | succ n =>
suffices
((n + 1 : ℚ) * ∑ k ∈ range n, ↑(n.choose k) / (n - k + 1) * bernoulli' k) =
∑ x ∈ range n, ↑(n.succ.choose x) * bernoulli' x by
rw_mod_cast [sum_range_succ, bernoulli'_def, ← this, choose_succ_self_right]
ring
simp_rw [mul_sum, ← mul_assoc]
refine sum_congr rfl fun k hk => ?_
congr
have : ((n - k : ℕ) : ℚ) + 1 ≠ 0 := by norm_cast
field_simp [← cast_sub (mem_range.1 hk).le, mul_comm]
rw_mod_cast [tsub_add_eq_add_tsub (mem_range.1 hk).le, choose_mul_succ_eq]
/-- The exponential generating function for the Bernoulli numbers `bernoulli' n`. -/
def bernoulli'PowerSeries :=
mk fun n => algebraMap ℚ A (bernoulli' n / n !)
theorem bernoulli'PowerSeries_mul_exp_sub_one :
bernoulli'PowerSeries A * (exp A - 1) = X * exp A := by
ext n
-- constant coefficient is a special case
cases n with | zero => simp | succ n =>
rw [bernoulli'PowerSeries, coeff_mul, mul_comm X, sum_antidiagonal_succ']
suffices (∑ p ∈ antidiagonal n,
bernoulli' p.1 / p.1! * ((p.2 + 1) * p.2! : ℚ)⁻¹) = (n ! : ℚ)⁻¹ by
simpa [map_sum, Nat.factorial] using congr_arg (algebraMap ℚ A) this
apply eq_inv_of_mul_eq_one_left
rw [sum_mul]
convert bernoulli'_spec' n using 1
apply sum_congr rfl
simp_rw [mem_antidiagonal]
rintro ⟨i, j⟩ rfl
have := factorial_mul_factorial_dvd_factorial_add i j
field_simp [mul_comm _ (bernoulli' i), mul_assoc, add_choose]
norm_cast
simp [mul_comm (j + 1)]
/-- Odd Bernoulli numbers (greater than 1) are zero. -/
theorem bernoulli'_odd_eq_zero {n : ℕ} (h_odd : Odd n) (hlt : 1 < n) : bernoulli' n = 0 := by
let B := mk fun n => bernoulli' n / (n ! : ℚ)
suffices (B - evalNegHom B) * (exp ℚ - 1) = X * (exp ℚ - 1) by
rcases mul_eq_mul_right_iff.mp this with h | h <;>
simp only [PowerSeries.ext_iff, evalNegHom, coeff_X] at h
· apply eq_zero_of_neg_eq
specialize h n
split_ifs at h <;> simp_all [B, h_odd.neg_one_pow, factorial_ne_zero]
· simpa +decide [Nat.factorial] using h 1
have h : B * (exp ℚ - 1) = X * exp ℚ := by
simpa [bernoulli'PowerSeries] using bernoulli'PowerSeries_mul_exp_sub_one ℚ
rw [sub_mul, h, mul_sub X, sub_right_inj, ← neg_sub, mul_neg, neg_eq_iff_eq_neg]
suffices evalNegHom (B * (exp ℚ - 1)) * exp ℚ = evalNegHom (X * exp ℚ) * exp ℚ by
simpa [mul_assoc, sub_mul, mul_comm (evalNegHom (exp ℚ)), exp_mul_exp_neg_eq_one]
congr
/-- The Bernoulli numbers are defined to be `bernoulli'` with a parity sign. -/
def bernoulli (n : ℕ) : ℚ :=
(-1) ^ n * bernoulli' n
theorem bernoulli'_eq_bernoulli (n : ℕ) : bernoulli' n = (-1) ^ n * bernoulli n := by
simp [bernoulli, ← mul_assoc, ← sq, ← pow_mul, mul_comm n 2]
@[simp]
theorem bernoulli_zero : bernoulli 0 = 1 := by simp [bernoulli]
@[simp]
theorem bernoulli_one : bernoulli 1 = -1 / 2 := by norm_num [bernoulli]
theorem bernoulli_eq_bernoulli'_of_ne_one {n : ℕ} (hn : n ≠ 1) : bernoulli n = bernoulli' n := by
by_cases h0 : n = 0; · simp [h0]
rw [bernoulli, neg_one_pow_eq_pow_mod_two]
rcases mod_two_eq_zero_or_one n with h | h
· simp [h]
· simp [bernoulli'_odd_eq_zero (odd_iff.mpr h) (one_lt_iff_ne_zero_and_ne_one.mpr ⟨h0, hn⟩)]
@[simp]
theorem sum_bernoulli (n : ℕ) :
(∑ k ∈ range n, (n.choose k : ℚ) * bernoulli k) = if n = 1 then 1 else 0 := by
cases n with | zero => simp | succ n =>
cases n with | zero => rw [sum_range_one]; simp | succ n =>
suffices (∑ i ∈ range n, ↑((n + 2).choose (i + 2)) * bernoulli (i + 2)) = n / 2 by
simp only [this, sum_range_succ', cast_succ, bernoulli_one, bernoulli_zero, choose_one_right,
mul_one, choose_zero_right, cast_zero, if_false, zero_add, succ_succ_ne_one]
ring
have f := sum_bernoulli' n.succ.succ
simp_rw [sum_range_succ', cast_succ, ← eq_sub_iff_add_eq] at f
refine Eq.trans ?_ (Eq.trans f ?_)
· congr
funext x
rw [bernoulli_eq_bernoulli'_of_ne_one (succ_ne_zero x ∘ succ.inj)]
· simp only [one_div, mul_one, bernoulli'_zero, cast_one, choose_zero_right, add_sub_cancel_right,
| zero_add, choose_one_right, cast_succ, cast_add, cast_one, bernoulli'_one, one_div]
| Mathlib/NumberTheory/Bernoulli.lean | 213 | 213 |
/-
Copyright (c) 2020 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.Algebra.BigOperators.Ring.Finset
import Mathlib.Algebra.Module.BigOperators
import Mathlib.NumberTheory.Divisors
import Mathlib.Data.Nat.Squarefree
import Mathlib.Data.Nat.GCD.BigOperators
import Mathlib.Data.Nat.Factorization.Induction
import Mathlib.Tactic.ArithMult
/-!
# Arithmetic Functions and Dirichlet Convolution
This file defines arithmetic functions, which are functions from `ℕ` to a specified type that map 0
to 0. In the literature, they are often instead defined as functions from `ℕ+`. These arithmetic
functions are endowed with a multiplication, given by Dirichlet convolution, and pointwise addition,
to form the Dirichlet ring.
## Main Definitions
* `ArithmeticFunction R` consists of functions `f : ℕ → R` such that `f 0 = 0`.
* An arithmetic function `f` `IsMultiplicative` when `x.Coprime y → f (x * y) = f x * f y`.
* The pointwise operations `pmul` and `ppow` differ from the multiplication
and power instances on `ArithmeticFunction R`, which use Dirichlet multiplication.
* `ζ` is the arithmetic function such that `ζ x = 1` for `0 < x`.
* `σ k` is the arithmetic function such that `σ k x = ∑ y ∈ divisors x, y ^ k` for `0 < x`.
* `pow k` is the arithmetic function such that `pow k x = x ^ k` for `0 < x`.
* `id` is the identity arithmetic function on `ℕ`.
* `ω n` is the number of distinct prime factors of `n`.
* `Ω n` is the number of prime factors of `n` counted with multiplicity.
* `μ` is the Möbius function (spelled `moebius` in code).
## Main Results
* Several forms of Möbius inversion:
* `sum_eq_iff_sum_mul_moebius_eq` for functions to a `CommRing`
* `sum_eq_iff_sum_smul_moebius_eq` for functions to an `AddCommGroup`
* `prod_eq_iff_prod_pow_moebius_eq` for functions to a `CommGroup`
* `prod_eq_iff_prod_pow_moebius_eq_of_nonzero` for functions to a `CommGroupWithZero`
* And variants that apply when the equalities only hold on a set `S : Set ℕ` such that
`m ∣ n → n ∈ S → m ∈ S`:
* `sum_eq_iff_sum_mul_moebius_eq_on` for functions to a `CommRing`
* `sum_eq_iff_sum_smul_moebius_eq_on` for functions to an `AddCommGroup`
* `prod_eq_iff_prod_pow_moebius_eq_on` for functions to a `CommGroup`
* `prod_eq_iff_prod_pow_moebius_eq_on_of_nonzero` for functions to a `CommGroupWithZero`
## Notation
All notation is localized in the namespace `ArithmeticFunction`.
The arithmetic functions `ζ`, `σ`, `ω`, `Ω` and `μ` have Greek letter names.
In addition, there are separate locales `ArithmeticFunction.zeta` for `ζ`,
`ArithmeticFunction.sigma` for `σ`, `ArithmeticFunction.omega` for `ω`,
`ArithmeticFunction.Omega` for `Ω`, and `ArithmeticFunction.Moebius` for `μ`,
to allow for selective access to these notations.
The arithmetic function $$n \mapsto \prod_{p \mid n} f(p)$$ is given custom notation
`∏ᵖ p ∣ n, f p` when applied to `n`.
## Tags
arithmetic functions, dirichlet convolution, divisors
-/
open Finset
open Nat
variable (R : Type*)
/-- An arithmetic function is a function from `ℕ` that maps 0 to 0. In the literature, they are
often instead defined as functions from `ℕ+`. Multiplication on `ArithmeticFunctions` is by
Dirichlet convolution. -/
def ArithmeticFunction [Zero R] :=
ZeroHom ℕ R
instance ArithmeticFunction.zero [Zero R] : Zero (ArithmeticFunction R) :=
inferInstanceAs (Zero (ZeroHom ℕ R))
instance [Zero R] : Inhabited (ArithmeticFunction R) := inferInstanceAs (Inhabited (ZeroHom ℕ R))
variable {R}
namespace ArithmeticFunction
section Zero
variable [Zero R]
instance : FunLike (ArithmeticFunction R) ℕ R :=
inferInstanceAs (FunLike (ZeroHom ℕ R) ℕ R)
@[simp]
theorem toFun_eq (f : ArithmeticFunction R) : f.toFun = f := rfl
@[simp]
theorem coe_mk (f : ℕ → R) (hf) : @DFunLike.coe (ArithmeticFunction R) _ _ _
(ZeroHom.mk f hf) = f := rfl
@[simp]
theorem map_zero {f : ArithmeticFunction R} : f 0 = 0 :=
ZeroHom.map_zero' f
theorem coe_inj {f g : ArithmeticFunction R} : (f : ℕ → R) = g ↔ f = g :=
DFunLike.coe_fn_eq
@[simp]
theorem zero_apply {x : ℕ} : (0 : ArithmeticFunction R) x = 0 :=
ZeroHom.zero_apply x
@[ext]
theorem ext ⦃f g : ArithmeticFunction R⦄ (h : ∀ x, f x = g x) : f = g :=
ZeroHom.ext h
section One
variable [One R]
instance one : One (ArithmeticFunction R) :=
⟨⟨fun x => ite (x = 1) 1 0, rfl⟩⟩
theorem one_apply {x : ℕ} : (1 : ArithmeticFunction R) x = ite (x = 1) 1 0 :=
rfl
@[simp]
theorem one_one : (1 : ArithmeticFunction R) 1 = 1 :=
rfl
@[simp]
theorem one_apply_ne {x : ℕ} (h : x ≠ 1) : (1 : ArithmeticFunction R) x = 0 :=
if_neg h
end One
end Zero
/-- Coerce an arithmetic function with values in `ℕ` to one with values in `R`. We cannot inline
this in `natCoe` because it gets unfolded too much. -/
@[coe]
def natToArithmeticFunction [AddMonoidWithOne R] :
(ArithmeticFunction ℕ) → (ArithmeticFunction R) :=
fun f => ⟨fun n => ↑(f n), by simp⟩
instance natCoe [AddMonoidWithOne R] : Coe (ArithmeticFunction ℕ) (ArithmeticFunction R) :=
⟨natToArithmeticFunction⟩
@[simp]
theorem natCoe_nat (f : ArithmeticFunction ℕ) : natToArithmeticFunction f = f :=
ext fun _ => cast_id _
@[simp]
theorem natCoe_apply [AddMonoidWithOne R] {f : ArithmeticFunction ℕ} {x : ℕ} :
(f : ArithmeticFunction R) x = f x :=
rfl
/-- Coerce an arithmetic function with values in `ℤ` to one with values in `R`. We cannot inline
this in `intCoe` because it gets unfolded too much. -/
@[coe]
def ofInt [AddGroupWithOne R] :
(ArithmeticFunction ℤ) → (ArithmeticFunction R) :=
fun f => ⟨fun n => ↑(f n), by simp⟩
instance intCoe [AddGroupWithOne R] : Coe (ArithmeticFunction ℤ) (ArithmeticFunction R) :=
⟨ofInt⟩
@[simp]
theorem intCoe_int (f : ArithmeticFunction ℤ) : ofInt f = f :=
ext fun _ => Int.cast_id
@[simp]
theorem intCoe_apply [AddGroupWithOne R] {f : ArithmeticFunction ℤ} {x : ℕ} :
(f : ArithmeticFunction R) x = f x := rfl
@[simp]
theorem coe_coe [AddGroupWithOne R] {f : ArithmeticFunction ℕ} :
((f : ArithmeticFunction ℤ) : ArithmeticFunction R) = (f : ArithmeticFunction R) := by
ext
simp
@[simp]
theorem natCoe_one [AddMonoidWithOne R] :
((1 : ArithmeticFunction ℕ) : ArithmeticFunction R) = 1 := by
ext n
simp [one_apply]
@[simp]
theorem intCoe_one [AddGroupWithOne R] : ((1 : ArithmeticFunction ℤ) :
ArithmeticFunction R) = 1 := by
ext n
simp [one_apply]
section AddMonoid
variable [AddMonoid R]
instance add : Add (ArithmeticFunction R) :=
⟨fun f g => ⟨fun n => f n + g n, by simp⟩⟩
@[simp]
theorem add_apply {f g : ArithmeticFunction R} {n : ℕ} : (f + g) n = f n + g n :=
rfl
instance instAddMonoid : AddMonoid (ArithmeticFunction R) :=
{ ArithmeticFunction.zero R,
ArithmeticFunction.add with
add_assoc := fun _ _ _ => ext fun _ => add_assoc _ _ _
zero_add := fun _ => ext fun _ => zero_add _
add_zero := fun _ => ext fun _ => add_zero _
nsmul := nsmulRec }
end AddMonoid
instance instAddMonoidWithOne [AddMonoidWithOne R] : AddMonoidWithOne (ArithmeticFunction R) :=
{ ArithmeticFunction.instAddMonoid,
ArithmeticFunction.one with
natCast := fun n => ⟨fun x => if x = 1 then (n : R) else 0, by simp⟩
natCast_zero := by ext; simp
natCast_succ := fun n => by ext x; by_cases h : x = 1 <;> simp [h] }
instance instAddCommMonoid [AddCommMonoid R] : AddCommMonoid (ArithmeticFunction R) :=
{ ArithmeticFunction.instAddMonoid with add_comm := fun _ _ => ext fun _ => add_comm _ _ }
instance [NegZeroClass R] : Neg (ArithmeticFunction R) where
neg f := ⟨fun n => -f n, by simp⟩
instance [AddGroup R] : AddGroup (ArithmeticFunction R) :=
{ ArithmeticFunction.instAddMonoid with
neg_add_cancel := fun _ => ext fun _ => neg_add_cancel _
zsmul := zsmulRec }
instance [AddCommGroup R] : AddCommGroup (ArithmeticFunction R) :=
{ show AddGroup (ArithmeticFunction R) by infer_instance with
add_comm := fun _ _ ↦ add_comm _ _ }
section SMul
variable {M : Type*} [Zero R] [AddCommMonoid M] [SMul R M]
/-- The Dirichlet convolution of two arithmetic functions `f` and `g` is another arithmetic function
such that `(f * g) n` is the sum of `f x * g y` over all `(x,y)` such that `x * y = n`. -/
instance : SMul (ArithmeticFunction R) (ArithmeticFunction M) :=
⟨fun f g => ⟨fun n => ∑ x ∈ divisorsAntidiagonal n, f x.fst • g x.snd, by simp⟩⟩
@[simp]
theorem smul_apply {f : ArithmeticFunction R} {g : ArithmeticFunction M} {n : ℕ} :
(f • g) n = ∑ x ∈ divisorsAntidiagonal n, f x.fst • g x.snd :=
rfl
end SMul
/-- The Dirichlet convolution of two arithmetic functions `f` and `g` is another arithmetic function
such that `(f * g) n` is the sum of `f x * g y` over all `(x,y)` such that `x * y = n`. -/
instance [Semiring R] : Mul (ArithmeticFunction R) :=
⟨(· • ·)⟩
@[simp]
theorem mul_apply [Semiring R] {f g : ArithmeticFunction R} {n : ℕ} :
(f * g) n = ∑ x ∈ divisorsAntidiagonal n, f x.fst * g x.snd :=
rfl
theorem mul_apply_one [Semiring R] {f g : ArithmeticFunction R} : (f * g) 1 = f 1 * g 1 := by simp
@[simp, norm_cast]
theorem natCoe_mul [Semiring R] {f g : ArithmeticFunction ℕ} :
(↑(f * g) : ArithmeticFunction R) = f * g := by
ext n
simp
@[simp, norm_cast]
theorem intCoe_mul [Ring R] {f g : ArithmeticFunction ℤ} :
(↑(f * g) : ArithmeticFunction R) = ↑f * g := by
ext n
simp
section Module
variable {M : Type*} [Semiring R] [AddCommMonoid M] [Module R M]
theorem mul_smul' (f g : ArithmeticFunction R) (h : ArithmeticFunction M) :
(f * g) • h = f • g • h := by
ext n
simp only [mul_apply, smul_apply, sum_smul, mul_smul, smul_sum, Finset.sum_sigma']
apply Finset.sum_nbij' (fun ⟨⟨_i, j⟩, ⟨k, l⟩⟩ ↦ ⟨(k, l * j), (l, j)⟩)
(fun ⟨⟨i, _j⟩, ⟨k, l⟩⟩ ↦ ⟨(i * k, l), (i, k)⟩) <;> aesop (add simp mul_assoc)
theorem one_smul' (b : ArithmeticFunction M) : (1 : ArithmeticFunction R) • b = b := by
ext x
rw [smul_apply]
by_cases x0 : x = 0
· simp [x0]
have h : {(1, x)} ⊆ divisorsAntidiagonal x := by simp [x0]
rw [← sum_subset h]
· simp
intro y ymem ynmem
have y1ne : y.fst ≠ 1 := fun con => by simp_all [Prod.ext_iff]
simp [y1ne]
end Module
section Semiring
variable [Semiring R]
instance instMonoid : Monoid (ArithmeticFunction R) :=
{ one := One.one
mul := Mul.mul
one_mul := one_smul'
mul_one := fun f => by
ext x
rw [mul_apply]
by_cases x0 : x = 0
· simp [x0]
have h : {(x, 1)} ⊆ divisorsAntidiagonal x := by simp [x0]
rw [← sum_subset h]
· simp
intro ⟨y₁, y₂⟩ ymem ynmem
have y2ne : y₂ ≠ 1 := by
intro con
simp_all
simp [y2ne]
mul_assoc := mul_smul' }
instance instSemiring : Semiring (ArithmeticFunction R) :=
{ ArithmeticFunction.instAddMonoidWithOne,
ArithmeticFunction.instMonoid,
ArithmeticFunction.instAddCommMonoid with
zero_mul := fun f => by
ext
simp
mul_zero := fun f => by
ext
simp
left_distrib := fun a b c => by
ext
simp [← sum_add_distrib, mul_add]
right_distrib := fun a b c => by
ext
simp [← sum_add_distrib, add_mul] }
end Semiring
instance [CommSemiring R] : CommSemiring (ArithmeticFunction R) :=
{ ArithmeticFunction.instSemiring with
mul_comm := fun f g => by
ext
rw [mul_apply, ← map_swap_divisorsAntidiagonal, sum_map]
simp [mul_comm] }
instance [CommRing R] : CommRing (ArithmeticFunction R) :=
{ ArithmeticFunction.instSemiring with
neg_add_cancel := neg_add_cancel
mul_comm := mul_comm
zsmul := (· • ·) }
instance {M : Type*} [Semiring R] [AddCommMonoid M] [Module R M] :
Module (ArithmeticFunction R) (ArithmeticFunction M) where
one_smul := one_smul'
mul_smul := mul_smul'
smul_add r x y := by
ext
simp only [sum_add_distrib, smul_add, smul_apply, add_apply]
smul_zero r := by
ext
simp only [smul_apply, sum_const_zero, smul_zero, zero_apply]
add_smul r s x := by
ext
simp only [add_smul, sum_add_distrib, smul_apply, add_apply]
zero_smul r := by
ext
simp only [smul_apply, sum_const_zero, zero_smul, zero_apply]
section Zeta
/-- `ζ 0 = 0`, otherwise `ζ x = 1`. The Dirichlet Series is the Riemann `ζ`. -/
def zeta : ArithmeticFunction ℕ :=
⟨fun x => ite (x = 0) 0 1, rfl⟩
@[inherit_doc]
scoped[ArithmeticFunction] notation "ζ" => ArithmeticFunction.zeta
@[inherit_doc]
scoped[ArithmeticFunction.zeta] notation "ζ" => ArithmeticFunction.zeta
@[simp]
theorem zeta_apply {x : ℕ} : ζ x = if x = 0 then 0 else 1 :=
rfl
theorem zeta_apply_ne {x : ℕ} (h : x ≠ 0) : ζ x = 1 :=
if_neg h
-- Porting note: removed `@[simp]`, LHS not in normal form
theorem coe_zeta_smul_apply {M} [Semiring R] [AddCommMonoid M] [MulAction R M]
{f : ArithmeticFunction M} {x : ℕ} :
((↑ζ : ArithmeticFunction R) • f) x = ∑ i ∈ divisors x, f i := by
rw [smul_apply]
trans ∑ i ∈ divisorsAntidiagonal x, f i.snd
· refine sum_congr rfl fun i hi => ?_
rcases mem_divisorsAntidiagonal.1 hi with ⟨rfl, h⟩
rw [natCoe_apply, zeta_apply_ne (left_ne_zero_of_mul h), cast_one, one_smul]
· rw [← map_div_left_divisors, sum_map, Function.Embedding.coeFn_mk]
theorem coe_zeta_mul_apply [Semiring R] {f : ArithmeticFunction R} {x : ℕ} :
(↑ζ * f) x = ∑ i ∈ divisors x, f i :=
coe_zeta_smul_apply
theorem coe_mul_zeta_apply [Semiring R] {f : ArithmeticFunction R} {x : ℕ} :
(f * ζ) x = ∑ i ∈ divisors x, f i := by
rw [mul_apply]
trans ∑ i ∈ divisorsAntidiagonal x, f i.1
· refine sum_congr rfl fun i hi => ?_
rcases mem_divisorsAntidiagonal.1 hi with ⟨rfl, h⟩
rw [natCoe_apply, zeta_apply_ne (right_ne_zero_of_mul h), cast_one, mul_one]
· rw [← map_div_right_divisors, sum_map, Function.Embedding.coeFn_mk]
theorem zeta_mul_apply {f : ArithmeticFunction ℕ} {x : ℕ} : (ζ * f) x = ∑ i ∈ divisors x, f i := by
rw [← natCoe_nat ζ, coe_zeta_mul_apply]
theorem mul_zeta_apply {f : ArithmeticFunction ℕ} {x : ℕ} : (f * ζ) x = ∑ i ∈ divisors x, f i := by
rw [← natCoe_nat ζ, coe_mul_zeta_apply]
end Zeta
open ArithmeticFunction
section Pmul
/-- This is the pointwise product of `ArithmeticFunction`s. -/
def pmul [MulZeroClass R] (f g : ArithmeticFunction R) : ArithmeticFunction R :=
⟨fun x => f x * g x, by simp⟩
@[simp]
theorem pmul_apply [MulZeroClass R] {f g : ArithmeticFunction R} {x : ℕ} : f.pmul g x = f x * g x :=
rfl
theorem pmul_comm [CommMonoidWithZero R] (f g : ArithmeticFunction R) : f.pmul g = g.pmul f := by
ext
simp [mul_comm]
lemma pmul_assoc [SemigroupWithZero R] (f₁ f₂ f₃ : ArithmeticFunction R) :
pmul (pmul f₁ f₂) f₃ = pmul f₁ (pmul f₂ f₃) := by
ext
simp only [pmul_apply, mul_assoc]
section NonAssocSemiring
variable [NonAssocSemiring R]
@[simp]
theorem pmul_zeta (f : ArithmeticFunction R) : f.pmul ↑ζ = f := by
ext x
cases x <;> simp [Nat.succ_ne_zero]
@[simp]
theorem zeta_pmul (f : ArithmeticFunction R) : (ζ : ArithmeticFunction R).pmul f = f := by
ext x
cases x <;> simp [Nat.succ_ne_zero]
end NonAssocSemiring
variable [Semiring R]
/-- This is the pointwise power of `ArithmeticFunction`s. -/
def ppow (f : ArithmeticFunction R) (k : ℕ) : ArithmeticFunction R :=
if h0 : k = 0 then ζ else ⟨fun x ↦ f x ^ k, by simp_rw [map_zero, zero_pow h0]⟩
@[simp]
theorem ppow_zero {f : ArithmeticFunction R} : f.ppow 0 = ζ := by rw [ppow, dif_pos rfl]
@[simp]
theorem ppow_apply {f : ArithmeticFunction R} {k x : ℕ} (kpos : 0 < k) : f.ppow k x = f x ^ k := by
rw [ppow, dif_neg (Nat.ne_of_gt kpos), coe_mk]
theorem ppow_succ' {f : ArithmeticFunction R} {k : ℕ} : f.ppow (k + 1) = f.pmul (f.ppow k) := by
ext x
rw [ppow_apply (Nat.succ_pos k), _root_.pow_succ']
induction k <;> simp
theorem ppow_succ {f : ArithmeticFunction R} {k : ℕ} {kpos : 0 < k} :
f.ppow (k + 1) = (f.ppow k).pmul f := by
ext x
rw [ppow_apply (Nat.succ_pos k), _root_.pow_succ]
induction k <;> simp
end Pmul
section Pdiv
/-- This is the pointwise division of `ArithmeticFunction`s. -/
def pdiv [GroupWithZero R] (f g : ArithmeticFunction R) : ArithmeticFunction R :=
⟨fun n => f n / g n, by simp only [map_zero, ne_eq, not_true, div_zero]⟩
@[simp]
theorem pdiv_apply [GroupWithZero R] (f g : ArithmeticFunction R) (n : ℕ) :
pdiv f g n = f n / g n := rfl
/-- This result only holds for `DivisionSemiring`s instead of `GroupWithZero`s because zeta takes
values in ℕ, and hence the coercion requires an `AddMonoidWithOne`. TODO: Generalise zeta -/
@[simp]
theorem pdiv_zeta [DivisionSemiring R] (f : ArithmeticFunction R) :
pdiv f zeta = f := by
ext n
cases n <;> simp [succ_ne_zero]
end Pdiv
section ProdPrimeFactors
/-- The map $n \mapsto \prod_{p \mid n} f(p)$ as an arithmetic function -/
def prodPrimeFactors [CommMonoidWithZero R] (f : ℕ → R) : ArithmeticFunction R where
toFun d := if d = 0 then 0 else ∏ p ∈ d.primeFactors, f p
map_zero' := if_pos rfl
open Batteries.ExtendedBinder
/-- `∏ᵖ p ∣ n, f p` is custom notation for `prodPrimeFactors f n` -/
scoped syntax (name := bigproddvd) "∏ᵖ " extBinder " ∣ " term ", " term:67 : term
scoped macro_rules (kind := bigproddvd)
| `(∏ᵖ $x:ident ∣ $n, $r) => `(prodPrimeFactors (fun $x ↦ $r) $n)
@[simp]
theorem prodPrimeFactors_apply [CommMonoidWithZero R] {f : ℕ → R} {n : ℕ} (hn : n ≠ 0) :
∏ᵖ p ∣ n, f p = ∏ p ∈ n.primeFactors, f p :=
if_neg hn
end ProdPrimeFactors
/-- Multiplicative functions -/
def IsMultiplicative [MonoidWithZero R] (f : ArithmeticFunction R) : Prop :=
f 1 = 1 ∧ ∀ {m n : ℕ}, m.Coprime n → f (m * n) = f m * f n
namespace IsMultiplicative
section MonoidWithZero
variable [MonoidWithZero R]
@[simp, arith_mult]
theorem map_one {f : ArithmeticFunction R} (h : f.IsMultiplicative) : f 1 = 1 :=
h.1
@[simp]
theorem map_mul_of_coprime {f : ArithmeticFunction R} (hf : f.IsMultiplicative) {m n : ℕ}
(h : m.Coprime n) : f (m * n) = f m * f n :=
hf.2 h
end MonoidWithZero
open scoped Function in -- required for scoped `on` notation
theorem map_prod {ι : Type*} [CommMonoidWithZero R] (g : ι → ℕ) {f : ArithmeticFunction R}
(hf : f.IsMultiplicative) (s : Finset ι) (hs : (s : Set ι).Pairwise (Coprime on g)) :
f (∏ i ∈ s, g i) = ∏ i ∈ s, f (g i) := by
classical
induction s using Finset.induction_on with
| empty => simp [hf]
| insert _ _ has ih =>
rw [coe_insert, Set.pairwise_insert_of_symmetric (Coprime.symmetric.comap g)] at hs
rw [prod_insert has, prod_insert has, hf.map_mul_of_coprime, ih hs.1]
exact .prod_right fun i hi => hs.2 _ hi (hi.ne_of_not_mem has).symm
theorem map_prod_of_prime [CommMonoidWithZero R] {f : ArithmeticFunction R}
(h_mult : ArithmeticFunction.IsMultiplicative f)
(t : Finset ℕ) (ht : ∀ p ∈ t, p.Prime) :
f (∏ a ∈ t, a) = ∏ a ∈ t, f a :=
map_prod _ h_mult t fun x hx y hy hxy => (coprime_primes (ht x hx) (ht y hy)).mpr hxy
theorem map_prod_of_subset_primeFactors [CommMonoidWithZero R] {f : ArithmeticFunction R}
(h_mult : ArithmeticFunction.IsMultiplicative f) (l : ℕ)
(t : Finset ℕ) (ht : t ⊆ l.primeFactors) :
f (∏ a ∈ t, a) = ∏ a ∈ t, f a :=
map_prod_of_prime h_mult t fun _ a => prime_of_mem_primeFactors (ht a)
theorem map_div_of_coprime [GroupWithZero R] {f : ArithmeticFunction R}
(hf : IsMultiplicative f) {l d : ℕ} (hdl : d ∣ l) (hl : (l / d).Coprime d) (hd : f d ≠ 0) :
f (l / d) = f l / f d := by
apply (div_eq_of_eq_mul hd ..).symm
rw [← hf.right hl, Nat.div_mul_cancel hdl]
@[arith_mult]
theorem natCast {f : ArithmeticFunction ℕ} [Semiring R] (h : f.IsMultiplicative) :
IsMultiplicative (f : ArithmeticFunction R) :=
⟨by simp [h], fun {m n} cop => by simp [h.2 cop]⟩
@[arith_mult]
theorem intCast {f : ArithmeticFunction ℤ} [Ring R] (h : f.IsMultiplicative) :
IsMultiplicative (f : ArithmeticFunction R) :=
⟨by simp [h], fun {m n} cop => by simp [h.2 cop]⟩
@[arith_mult]
theorem mul [CommSemiring R] {f g : ArithmeticFunction R} (hf : f.IsMultiplicative)
(hg : g.IsMultiplicative) : IsMultiplicative (f * g) := by
refine ⟨by simp [hf.1, hg.1], ?_⟩
simp only [mul_apply]
intro m n cop
rw [sum_mul_sum, ← sum_product']
symm
apply sum_nbij fun ((i, j), k, l) ↦ (i * k, j * l)
· rintro ⟨⟨a1, a2⟩, ⟨b1, b2⟩⟩ h
simp only [mem_divisorsAntidiagonal, Ne, mem_product] at h
rcases h with ⟨⟨rfl, ha⟩, ⟨rfl, hb⟩⟩
simp only [mem_divisorsAntidiagonal, Nat.mul_eq_zero, Ne]
constructor
· ring
rw [Nat.mul_eq_zero] at *
apply not_or_intro ha hb
· simp only [Set.InjOn, mem_coe, mem_divisorsAntidiagonal, Ne, mem_product, Prod.mk_inj]
rintro ⟨⟨a1, a2⟩, ⟨b1, b2⟩⟩ ⟨⟨rfl, ha⟩, ⟨rfl, hb⟩⟩ ⟨⟨c1, c2⟩, ⟨d1, d2⟩⟩ hcd h
simp only [Prod.mk_inj] at h
ext <;> dsimp only
· trans Nat.gcd (a1 * a2) (a1 * b1)
· rw [Nat.gcd_mul_left, cop.coprime_mul_left.coprime_mul_right_right.gcd_eq_one, mul_one]
· rw [← hcd.1.1, ← hcd.2.1] at cop
rw [← hcd.1.1, h.1, Nat.gcd_mul_left,
cop.coprime_mul_left.coprime_mul_right_right.gcd_eq_one, mul_one]
· trans Nat.gcd (a1 * a2) (a2 * b2)
· rw [mul_comm, Nat.gcd_mul_left, cop.coprime_mul_right.coprime_mul_left_right.gcd_eq_one,
mul_one]
· rw [← hcd.1.1, ← hcd.2.1] at cop
rw [← hcd.1.1, h.2, mul_comm, Nat.gcd_mul_left,
cop.coprime_mul_right.coprime_mul_left_right.gcd_eq_one, mul_one]
· trans Nat.gcd (b1 * b2) (a1 * b1)
· rw [mul_comm, Nat.gcd_mul_right,
cop.coprime_mul_right.coprime_mul_left_right.symm.gcd_eq_one, one_mul]
· rw [← hcd.1.1, ← hcd.2.1] at cop
rw [← hcd.2.1, h.1, mul_comm c1 d1, Nat.gcd_mul_left,
cop.coprime_mul_right.coprime_mul_left_right.symm.gcd_eq_one, mul_one]
· trans Nat.gcd (b1 * b2) (a2 * b2)
· rw [Nat.gcd_mul_right, cop.coprime_mul_left.coprime_mul_right_right.symm.gcd_eq_one,
one_mul]
· rw [← hcd.1.1, ← hcd.2.1] at cop
rw [← hcd.2.1, h.2, Nat.gcd_mul_right,
cop.coprime_mul_left.coprime_mul_right_right.symm.gcd_eq_one, one_mul]
· simp only [Set.SurjOn, Set.subset_def, mem_coe, mem_divisorsAntidiagonal, Ne, mem_product,
Set.mem_image, exists_prop, Prod.mk_inj]
rintro ⟨b1, b2⟩ h
dsimp at h
use ((b1.gcd m, b2.gcd m), (b1.gcd n, b2.gcd n))
rw [← cop.gcd_mul _, ← cop.gcd_mul _, ← h.1, Nat.gcd_mul_gcd_of_coprime_of_mul_eq_mul cop h.1,
Nat.gcd_mul_gcd_of_coprime_of_mul_eq_mul cop.symm _]
· rw [Nat.mul_eq_zero, not_or] at h
simp [h.2.1, h.2.2]
rw [mul_comm n m, h.1]
· simp only [mem_divisorsAntidiagonal, Ne, mem_product]
rintro ⟨⟨a1, a2⟩, ⟨b1, b2⟩⟩ ⟨⟨rfl, ha⟩, ⟨rfl, hb⟩⟩
dsimp only
rw [hf.map_mul_of_coprime cop.coprime_mul_right.coprime_mul_right_right,
hg.map_mul_of_coprime cop.coprime_mul_left.coprime_mul_left_right]
ring
@[arith_mult]
theorem pmul [CommSemiring R] {f g : ArithmeticFunction R} (hf : f.IsMultiplicative)
(hg : g.IsMultiplicative) : IsMultiplicative (f.pmul g) :=
⟨by simp [hf, hg], fun {m n} cop => by
simp only [pmul_apply, hf.map_mul_of_coprime cop, hg.map_mul_of_coprime cop]
ring⟩
@[arith_mult]
theorem pdiv [CommGroupWithZero R] {f g : ArithmeticFunction R} (hf : IsMultiplicative f)
(hg : IsMultiplicative g) : IsMultiplicative (pdiv f g) :=
⟨by simp [hf, hg], fun {m n} cop => by
simp only [pdiv_apply, map_mul_of_coprime hf cop, map_mul_of_coprime hg cop,
div_eq_mul_inv, mul_inv]
apply mul_mul_mul_comm ⟩
/-- For any multiplicative function `f` and any `n > 0`,
we can evaluate `f n` by evaluating `f` at `p ^ k` over the factorization of `n` -/
theorem multiplicative_factorization [CommMonoidWithZero R] (f : ArithmeticFunction R)
(hf : f.IsMultiplicative) {n : ℕ} (hn : n ≠ 0) :
f n = n.factorization.prod fun p k => f (p ^ k) :=
Nat.multiplicative_factorization f (fun _ _ => hf.2) hf.1 hn
/-- A recapitulation of the definition of multiplicative that is simpler for proofs -/
theorem iff_ne_zero [MonoidWithZero R] {f : ArithmeticFunction R} :
IsMultiplicative f ↔
f 1 = 1 ∧ ∀ {m n : ℕ}, m ≠ 0 → n ≠ 0 → m.Coprime n → f (m * n) = f m * f n := by
refine and_congr_right' (forall₂_congr fun m n => ⟨fun h _ _ => h, fun h hmn => ?_⟩)
rcases eq_or_ne m 0 with (rfl | hm)
· simp
rcases eq_or_ne n 0 with (rfl | hn)
· simp
exact h hm hn hmn
/-- Two multiplicative functions `f` and `g` are equal if and only if
they agree on prime powers -/
theorem eq_iff_eq_on_prime_powers [CommMonoidWithZero R] (f : ArithmeticFunction R)
(hf : f.IsMultiplicative) (g : ArithmeticFunction R) (hg : g.IsMultiplicative) :
f = g ↔ ∀ p i : ℕ, Nat.Prime p → f (p ^ i) = g (p ^ i) := by
constructor
· intro h p i _
rw [h]
intro h
ext n
by_cases hn : n = 0
· rw [hn, ArithmeticFunction.map_zero, ArithmeticFunction.map_zero]
rw [multiplicative_factorization f hf hn, multiplicative_factorization g hg hn]
exact Finset.prod_congr rfl fun p hp ↦ h p _ (Nat.prime_of_mem_primeFactors hp)
@[arith_mult]
theorem prodPrimeFactors [CommMonoidWithZero R] (f : ℕ → R) :
IsMultiplicative (prodPrimeFactors f) := by
rw [iff_ne_zero]
simp only [ne_eq, one_ne_zero, not_false_eq_true, prodPrimeFactors_apply, primeFactors_one,
prod_empty, true_and]
intro x y hx hy hxy
have hxy₀ : x * y ≠ 0 := mul_ne_zero hx hy
rw [prodPrimeFactors_apply hxy₀, prodPrimeFactors_apply hx, prodPrimeFactors_apply hy,
Nat.primeFactors_mul hx hy, ← Finset.prod_union hxy.disjoint_primeFactors]
theorem prodPrimeFactors_add_of_squarefree [CommSemiring R] {f g : ArithmeticFunction R}
(hf : IsMultiplicative f) (hg : IsMultiplicative g) {n : ℕ} (hn : Squarefree n) :
∏ᵖ p ∣ n, (f + g) p = (f * g) n := by
rw [prodPrimeFactors_apply hn.ne_zero]
simp_rw [add_apply (f := f) (g := g)]
rw [Finset.prod_add, mul_apply, sum_divisorsAntidiagonal (f · * g ·),
← divisors_filter_squarefree_of_squarefree hn, sum_divisors_filter_squarefree hn.ne_zero,
factors_eq]
apply Finset.sum_congr rfl
intro t ht
rw [t.prod_val, Function.id_def,
← prod_primeFactors_sdiff_of_squarefree hn (Finset.mem_powerset.mp ht),
hf.map_prod_of_subset_primeFactors n t (Finset.mem_powerset.mp ht),
← hg.map_prod_of_subset_primeFactors n (_ \ t) Finset.sdiff_subset]
theorem lcm_apply_mul_gcd_apply [CommMonoidWithZero R] {f : ArithmeticFunction R}
(hf : f.IsMultiplicative) {x y : ℕ} :
f (x.lcm y) * f (x.gcd y) = f x * f y := by
by_cases hx : x = 0
· simp only [hx, f.map_zero, zero_mul, Nat.lcm_zero_left, Nat.gcd_zero_left]
by_cases hy : y = 0
· simp only [hy, f.map_zero, mul_zero, Nat.lcm_zero_right, Nat.gcd_zero_right, zero_mul]
have hgcd_ne_zero : x.gcd y ≠ 0 := gcd_ne_zero_left hx
have hlcm_ne_zero : x.lcm y ≠ 0 := lcm_ne_zero hx hy
have hfi_zero : ∀ {i}, f (i ^ 0) = 1 := by
intro i; rw [Nat.pow_zero, hf.1]
iterate 4 rw [hf.multiplicative_factorization f (by assumption),
Finsupp.prod_of_support_subset _ _ _ (fun _ _ => hfi_zero)
(s := (x.primeFactors ∪ y.primeFactors))]
· rw [← Finset.prod_mul_distrib, ← Finset.prod_mul_distrib]
apply Finset.prod_congr rfl
intro p _
rcases Nat.le_or_le (x.factorization p) (y.factorization p) with h | h <;>
simp only [factorization_lcm hx hy, Finsupp.sup_apply, h, sup_of_le_right,
sup_of_le_left, inf_of_le_right, Nat.factorization_gcd hx hy, Finsupp.inf_apply,
inf_of_le_left, mul_comm]
· apply Finset.subset_union_right
· apply Finset.subset_union_left
· rw [factorization_gcd hx hy, Finsupp.support_inf]
apply Finset.inter_subset_union
· simp [factorization_lcm hx hy]
theorem map_gcd [CommGroupWithZero R] {f : ArithmeticFunction R}
(hf : f.IsMultiplicative) {x y : ℕ} (hf_lcm : f (x.lcm y) ≠ 0) :
f (x.gcd y) = f x * f y / f (x.lcm y) := by
rw [← hf.lcm_apply_mul_gcd_apply, mul_div_cancel_left₀ _ hf_lcm]
theorem map_lcm [CommGroupWithZero R] {f : ArithmeticFunction R}
(hf : f.IsMultiplicative) {x y : ℕ} (hf_gcd : f (x.gcd y) ≠ 0) :
f (x.lcm y) = f x * f y / f (x.gcd y) := by
rw [← hf.lcm_apply_mul_gcd_apply, mul_div_cancel_right₀ _ hf_gcd]
theorem eq_zero_of_squarefree_of_dvd_eq_zero [MonoidWithZero R] {f : ArithmeticFunction R}
(hf : IsMultiplicative f) {m n : ℕ} (hn : Squarefree n) (hmn : m ∣ n)
(h_zero : f m = 0) :
f n = 0 := by
rcases hmn with ⟨k, rfl⟩
simp only [MulZeroClass.zero_mul, eq_self_iff_true, hf.map_mul_of_coprime
(coprime_of_squarefree_mul hn), h_zero]
end IsMultiplicative
section SpecialFunctions
/-- The identity on `ℕ` as an `ArithmeticFunction`. -/
def id : ArithmeticFunction ℕ :=
⟨_root_.id, rfl⟩
@[simp]
theorem id_apply {x : ℕ} : id x = x :=
rfl
/-- `pow k n = n ^ k`, except `pow 0 0 = 0`. -/
def pow (k : ℕ) : ArithmeticFunction ℕ :=
id.ppow k
@[simp]
theorem pow_apply {k n : ℕ} : pow k n = if k = 0 ∧ n = 0 then 0 else n ^ k := by
cases k <;> simp [pow]
theorem pow_zero_eq_zeta : pow 0 = ζ := by
ext n
simp
/-- `σ k n` is the sum of the `k`th powers of the divisors of `n` -/
def sigma (k : ℕ) : ArithmeticFunction ℕ :=
⟨fun n => ∑ d ∈ divisors n, d ^ k, by simp⟩
@[inherit_doc]
scoped[ArithmeticFunction] notation "σ" => ArithmeticFunction.sigma
@[inherit_doc]
scoped[ArithmeticFunction.sigma] notation "σ" => ArithmeticFunction.sigma
theorem sigma_apply {k n : ℕ} : σ k n = ∑ d ∈ divisors n, d ^ k :=
rfl
theorem sigma_apply_prime_pow {k p i : ℕ} (hp : p.Prime) :
σ k (p ^ i) = ∑ j ∈ .range (i + 1), p ^ (j * k) := by
simp [sigma_apply, divisors_prime_pow hp, Nat.pow_mul]
theorem sigma_one_apply (n : ℕ) : σ 1 n = ∑ d ∈ divisors n, d := by simp [sigma_apply]
theorem sigma_one_apply_prime_pow {p i : ℕ} (hp : p.Prime) :
σ 1 (p ^ i) = ∑ k ∈ .range (i + 1), p ^ k := by
simp [sigma_apply_prime_pow hp]
theorem sigma_zero_apply (n : ℕ) : σ 0 n = #n.divisors := by simp [sigma_apply]
theorem sigma_zero_apply_prime_pow {p i : ℕ} (hp : p.Prime) : σ 0 (p ^ i) = i + 1 := by
simp [sigma_apply_prime_pow hp]
theorem zeta_mul_pow_eq_sigma {k : ℕ} : ζ * pow k = σ k := by
ext
rw [sigma, zeta_mul_apply]
apply sum_congr rfl
intro x hx
rw [pow_apply, if_neg (not_and_of_not_right _ _)]
contrapose! hx
simp [hx]
@[arith_mult]
theorem isMultiplicative_one [MonoidWithZero R] : IsMultiplicative (1 : ArithmeticFunction R) :=
IsMultiplicative.iff_ne_zero.2
⟨by simp, by
intro m n hm _hn hmn
rcases eq_or_ne m 1 with (rfl | hm')
· simp
rw [one_apply_ne, one_apply_ne hm', zero_mul]
rw [Ne, mul_eq_one, not_and_or]
exact Or.inl hm'⟩
@[arith_mult]
theorem isMultiplicative_zeta : IsMultiplicative ζ :=
IsMultiplicative.iff_ne_zero.2 ⟨by simp, by simp +contextual⟩
@[arith_mult]
theorem isMultiplicative_id : IsMultiplicative ArithmeticFunction.id :=
⟨rfl, fun {_ _} _ => rfl⟩
@[arith_mult]
theorem IsMultiplicative.ppow [CommSemiring R] {f : ArithmeticFunction R} (hf : f.IsMultiplicative)
{k : ℕ} : IsMultiplicative (f.ppow k) := by
induction k with
| zero => exact isMultiplicative_zeta.natCast
| succ k hi => rw [ppow_succ']; apply hf.pmul hi
@[arith_mult]
theorem isMultiplicative_pow {k : ℕ} : IsMultiplicative (pow k) :=
isMultiplicative_id.ppow
@[arith_mult]
theorem isMultiplicative_sigma {k : ℕ} : IsMultiplicative (σ k) := by
rw [← zeta_mul_pow_eq_sigma]
apply isMultiplicative_zeta.mul isMultiplicative_pow
/-- `Ω n` is the number of prime factors of `n`. -/
def cardFactors : ArithmeticFunction ℕ :=
⟨fun n => n.primeFactorsList.length, by simp⟩
@[inherit_doc]
scoped[ArithmeticFunction] notation "Ω" => ArithmeticFunction.cardFactors
@[inherit_doc]
scoped[ArithmeticFunction.Omega] notation "Ω" => ArithmeticFunction.cardFactors
theorem cardFactors_apply {n : ℕ} : Ω n = n.primeFactorsList.length :=
rfl
lemma cardFactors_zero : Ω 0 = 0 := by simp
@[simp] theorem cardFactors_one : Ω 1 = 0 := by simp [cardFactors_apply]
@[simp]
theorem cardFactors_eq_one_iff_prime {n : ℕ} : Ω n = 1 ↔ n.Prime := by
refine ⟨fun h => ?_, fun h => List.length_eq_one_iff.2 ⟨n, primeFactorsList_prime h⟩⟩
cases n with | zero => simp at h | succ n =>
rcases List.length_eq_one_iff.1 h with ⟨x, hx⟩
rw [← prod_primeFactorsList n.add_one_ne_zero, hx, List.prod_singleton]
apply prime_of_mem_primeFactorsList
rw [hx, List.mem_singleton]
theorem cardFactors_mul {m n : ℕ} (m0 : m ≠ 0) (n0 : n ≠ 0) : Ω (m * n) = Ω m + Ω n := by
rw [cardFactors_apply, cardFactors_apply, cardFactors_apply, ← Multiset.coe_card, ← factors_eq,
UniqueFactorizationMonoid.normalizedFactors_mul m0 n0, factors_eq, factors_eq,
Multiset.card_add, Multiset.coe_card, Multiset.coe_card]
theorem cardFactors_multiset_prod {s : Multiset ℕ} (h0 : s.prod ≠ 0) :
Ω s.prod = (Multiset.map Ω s).sum := by
induction s using Multiset.induction_on with
| empty => simp
| cons ih => simp_all [cardFactors_mul, not_or]
@[simp]
theorem cardFactors_apply_prime {p : ℕ} (hp : p.Prime) : Ω p = 1 :=
cardFactors_eq_one_iff_prime.2 hp
@[simp]
theorem cardFactors_apply_prime_pow {p k : ℕ} (hp : p.Prime) : Ω (p ^ k) = k := by
rw [cardFactors_apply, hp.primeFactorsList_pow, List.length_replicate]
/-- `ω n` is the number of distinct prime factors of `n`. -/
def cardDistinctFactors : ArithmeticFunction ℕ :=
⟨fun n => n.primeFactorsList.dedup.length, by simp⟩
@[inherit_doc]
scoped[ArithmeticFunction] notation "ω" => ArithmeticFunction.cardDistinctFactors
@[inherit_doc]
scoped[ArithmeticFunction.omega] notation "ω" => ArithmeticFunction.cardDistinctFactors
theorem cardDistinctFactors_zero : ω 0 = 0 := by simp
@[simp]
theorem cardDistinctFactors_one : ω 1 = 0 := by simp [cardDistinctFactors]
theorem cardDistinctFactors_apply {n : ℕ} : ω n = n.primeFactorsList.dedup.length :=
rfl
theorem cardDistinctFactors_eq_cardFactors_iff_squarefree {n : ℕ} (h0 : n ≠ 0) :
ω n = Ω n ↔ Squarefree n := by
rw [squarefree_iff_nodup_primeFactorsList h0, cardDistinctFactors_apply]
constructor <;> intro h
· rw [← n.primeFactorsList.dedup_sublist.eq_of_length h]
apply List.nodup_dedup
· simp [h.dedup, cardFactors]
@[simp]
theorem cardDistinctFactors_apply_prime_pow {p k : ℕ} (hp : p.Prime) (hk : k ≠ 0) :
ω (p ^ k) = 1 := by
rw [cardDistinctFactors_apply, hp.primeFactorsList_pow, List.replicate_dedup hk,
List.length_singleton]
@[simp]
theorem cardDistinctFactors_apply_prime {p : ℕ} (hp : p.Prime) : ω p = 1 := by
rw [← pow_one p, cardDistinctFactors_apply_prime_pow hp one_ne_zero]
/-- `μ` is the Möbius function. If `n` is squarefree with an even number of distinct prime factors,
`μ n = 1`. If `n` is squarefree with an odd number of distinct prime factors, `μ n = -1`.
If `n` is not squarefree, `μ n = 0`. -/
def moebius : ArithmeticFunction ℤ :=
⟨fun n => if Squarefree n then (-1) ^ cardFactors n else 0, by simp⟩
@[inherit_doc]
scoped[ArithmeticFunction] notation "μ" => ArithmeticFunction.moebius
@[inherit_doc]
scoped[ArithmeticFunction.Moebius] notation "μ" => ArithmeticFunction.moebius
@[simp]
theorem moebius_apply_of_squarefree {n : ℕ} (h : Squarefree n) : μ n = (-1) ^ cardFactors n :=
if_pos h
| Mathlib/NumberTheory/ArithmeticFunction.lean | 965 | 965 | |
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Chris Hughes, Floris van Doorn, Yaël Dillies
-/
import Mathlib.Data.Nat.Basic
import Mathlib.Tactic.GCongr.CoreAttrs
import Mathlib.Tactic.Common
import Mathlib.Tactic.Monotonicity.Attr
/-!
# Factorial and variants
This file defines the factorial, along with the ascending and descending variants.
For the proof that the factorial of `n` counts the permutations of an `n`-element set,
see `Fintype.card_perm`.
## Main declarations
* `Nat.factorial`: The factorial.
* `Nat.ascFactorial`: The ascending factorial. It is the product of natural numbers from `n` to
`n + k - 1`.
* `Nat.descFactorial`: The descending factorial. It is the product of natural numbers from
`n - k + 1` to `n`.
-/
namespace Nat
/-- `Nat.factorial n` is the factorial of `n`. -/
def factorial : ℕ → ℕ
| 0 => 1
| succ n => succ n * factorial n
/-- factorial notation `(n)!` for `Nat.factorial n`.
In Lean, names can end with exclamation marks (e.g. `List.get!`), so you cannot write
`n!` in Lean, but must write `(n)!` or `n !` instead. The former is preferred, since
Lean can confuse the `!` in `n !` as the (prefix) boolean negation operation in some
cases.
For numerals the parentheses are not required, so e.g. `0!` or `1!` work fine.
Todo: replace occurrences of `n !` with `(n)!` in Mathlib. -/
scoped notation:10000 n "!" => Nat.factorial n
section Factorial
variable {m n : ℕ}
@[simp] theorem factorial_zero : 0! = 1 :=
rfl
theorem factorial_succ (n : ℕ) : (n + 1)! = (n + 1) * n ! :=
rfl
@[simp] theorem factorial_one : 1! = 1 :=
rfl
@[simp] theorem factorial_two : 2! = 2 :=
rfl
theorem mul_factorial_pred (hn : n ≠ 0) : n * (n - 1)! = n ! :=
Nat.sub_add_cancel (one_le_iff_ne_zero.mpr hn) ▸ rfl
theorem factorial_pos : ∀ n, 0 < n !
| 0 => Nat.zero_lt_one
| succ n => Nat.mul_pos (succ_pos _) (factorial_pos n)
theorem factorial_ne_zero (n : ℕ) : n ! ≠ 0 :=
ne_of_gt (factorial_pos _)
theorem factorial_dvd_factorial {m n} (h : m ≤ n) : m ! ∣ n ! := by
induction h with
| refl => exact Nat.dvd_refl _
| step _ ih => exact Nat.dvd_trans ih (Nat.dvd_mul_left _ _)
theorem dvd_factorial : ∀ {m n}, 0 < m → m ≤ n → m ∣ n !
| succ _, _, _, h => Nat.dvd_trans (Nat.dvd_mul_right _ _) (factorial_dvd_factorial h)
@[mono, gcongr]
theorem factorial_le {m n} (h : m ≤ n) : m ! ≤ n ! :=
le_of_dvd (factorial_pos _) (factorial_dvd_factorial h)
theorem factorial_mul_pow_le_factorial : ∀ {m n : ℕ}, m ! * (m + 1) ^ n ≤ (m + n)!
| m, 0 => by simp
| m, n + 1 => by
rw [← Nat.add_assoc, factorial_succ, Nat.mul_comm (_ + 1), Nat.pow_succ, ← Nat.mul_assoc]
exact Nat.mul_le_mul factorial_mul_pow_le_factorial (succ_le_succ (le_add_right _ _))
theorem factorial_lt (hn : 0 < n) : n ! < m ! ↔ n < m := by
refine ⟨fun h => not_le.mp fun hmn => Nat.not_le_of_lt h (factorial_le hmn), fun h => ?_⟩
have : ∀ {n}, 0 < n → n ! < (n + 1)! := by
intro k hk
rw [factorial_succ, succ_mul, Nat.lt_add_left_iff_pos]
exact Nat.mul_pos hk k.factorial_pos
induction h generalizing hn with
| refl => exact this hn
| step hnk ih => exact lt_trans (ih hn) <| this <| lt_trans hn <| lt_of_succ_le hnk
@[gcongr]
lemma factorial_lt_of_lt {m n : ℕ} (hn : 0 < n) (h : n < m) : n ! < m ! := (factorial_lt hn).mpr h
@[simp] lemma one_lt_factorial : 1 < n ! ↔ 1 < n := factorial_lt Nat.one_pos
@[simp]
theorem factorial_eq_one : n ! = 1 ↔ n ≤ 1 := by
constructor
· intro h
rw [← not_lt, ← one_lt_factorial, h]
apply lt_irrefl
· rintro (_|_|_) <;> rfl
theorem factorial_inj (hn : 1 < n) : n ! = m ! ↔ n = m := by
refine ⟨fun h => ?_, congr_arg _⟩
obtain hnm | rfl | hnm := lt_trichotomy n m
· rw [← factorial_lt <| lt_of_succ_lt hn, h] at hnm
cases lt_irrefl _ hnm
· rfl
rw [← one_lt_factorial, h, one_lt_factorial] at hn
rw [← factorial_lt <| lt_of_succ_lt hn, h] at hnm
cases lt_irrefl _ hnm
theorem factorial_inj' (h : 1 < n ∨ 1 < m) : n ! = m ! ↔ n = m := by
obtain hn|hm := h
· exact factorial_inj hn
· rw [eq_comm, factorial_inj hm, eq_comm]
theorem self_le_factorial : ∀ n : ℕ, n ≤ n !
| 0 => Nat.zero_le _
| k + 1 => Nat.le_mul_of_pos_right _ (Nat.one_le_of_lt k.factorial_pos)
theorem lt_factorial_self {n : ℕ} (hi : 3 ≤ n) : n < n ! := by
have : 0 < n := by omega
have hn : 1 < pred n := le_pred_of_lt (succ_le_iff.mp hi)
rw [← succ_pred_eq_of_pos ‹0 < n›, factorial_succ]
exact (Nat.lt_mul_iff_one_lt_right (pred n).succ_pos).2
((Nat.lt_of_lt_of_le hn (self_le_factorial _)))
theorem add_factorial_succ_lt_factorial_add_succ {i : ℕ} (n : ℕ) (hi : 2 ≤ i) :
i + (n + 1)! < (i + n + 1)! := by
rw [factorial_succ (i + _), Nat.add_mul, Nat.one_mul]
have := (i + n).self_le_factorial
refine Nat.add_lt_add_of_lt_of_le (Nat.lt_of_le_of_lt ?_ ((Nat.lt_mul_iff_one_lt_right ?_).2 ?_))
(factorial_le ?_) <;> omega
theorem add_factorial_lt_factorial_add {i n : ℕ} (hi : 2 ≤ i) (hn : 1 ≤ n) :
i + n ! < (i + n)! := by
cases hn
· rw [factorial_one]
exact lt_factorial_self (succ_le_succ hi)
exact add_factorial_succ_lt_factorial_add_succ _ hi
theorem add_factorial_succ_le_factorial_add_succ (i : ℕ) (n : ℕ) :
i + (n + 1)! ≤ (i + (n + 1))! := by
cases (le_or_lt (2 : ℕ) i)
· rw [← Nat.add_assoc]
apply Nat.le_of_lt
apply add_factorial_succ_lt_factorial_add_succ
assumption
· match i with
| 0 => simp
| 1 =>
rw [← Nat.add_assoc, factorial_succ (1 + n), Nat.add_mul, Nat.one_mul, Nat.add_comm 1 n,
Nat.add_le_add_iff_right]
exact Nat.mul_pos n.succ_pos n.succ.factorial_pos
| succ (succ n) => contradiction
theorem add_factorial_le_factorial_add (i : ℕ) {n : ℕ} (n1 : 1 ≤ n) : i + n ! ≤ (i + n)! := by
rcases n1 with - | @h
· exact self_le_factorial _
exact add_factorial_succ_le_factorial_add_succ i h
theorem factorial_mul_pow_sub_le_factorial {n m : ℕ} (hnm : n ≤ m) : n ! * n ^ (m - n) ≤ m ! := by
calc
_ ≤ n ! * (n + 1) ^ (m - n) := Nat.mul_le_mul_left _ (Nat.pow_le_pow_left n.le_succ _)
_ ≤ _ := by simpa [hnm] using @Nat.factorial_mul_pow_le_factorial n (m - n)
lemma factorial_le_pow : ∀ n, n ! ≤ n ^ n
| 0 => le_refl _
| n + 1 =>
calc
_ ≤ (n + 1) * n ^ n := Nat.mul_le_mul_left _ n.factorial_le_pow
_ ≤ (n + 1) * (n + 1) ^ n := Nat.mul_le_mul_left _ (Nat.pow_le_pow_left n.le_succ _)
_ = _ := by rw [pow_succ']
end Factorial
/-! ### Ascending and descending factorials -/
section AscFactorial
/-- `n.ascFactorial k = n (n + 1) ⋯ (n + k - 1)`. This is closely related to `ascPochhammer`, but
much less general. -/
def ascFactorial (n : ℕ) : ℕ → ℕ
| 0 => 1
| k + 1 => (n + k) * ascFactorial n k
@[simp]
theorem ascFactorial_zero (n : ℕ) : n.ascFactorial 0 = 1 :=
rfl
theorem ascFactorial_succ {n k : ℕ} : n.ascFactorial k.succ = (n + k) * n.ascFactorial k :=
rfl
theorem zero_ascFactorial : ∀ (k : ℕ), (0 : ℕ).ascFactorial k.succ = 0
| 0 => by
rw [ascFactorial_succ, ascFactorial_zero, Nat.zero_add, Nat.zero_mul]
| (k+1) => by
rw [ascFactorial_succ, zero_ascFactorial k, Nat.mul_zero]
@[simp]
theorem one_ascFactorial : ∀ (k : ℕ), (1 : ℕ).ascFactorial k = k.factorial
| 0 => ascFactorial_zero 1
| (k+1) => by
rw [ascFactorial_succ, one_ascFactorial k, Nat.add_comm, factorial_succ]
theorem succ_ascFactorial (n : ℕ) :
∀ k, n * n.succ.ascFactorial k = (n + k) * n.ascFactorial k
| 0 => by rw [Nat.add_zero, ascFactorial_zero, ascFactorial_zero]
| k + 1 => by rw [ascFactorial, Nat.mul_left_comm, succ_ascFactorial n k, ascFactorial, succ_add,
← Nat.add_assoc]
/-- `(n + 1).ascFactorial k = (n + k) ! / n !` but without ℕ-division. See
`Nat.ascFactorial_eq_div` for the version with ℕ-division. -/
theorem factorial_mul_ascFactorial (n : ℕ) : ∀ k, n ! * (n + 1).ascFactorial k = (n + k)!
| 0 => by rw [ascFactorial_zero, Nat.add_zero, Nat.mul_one]
| k + 1 => by
rw [ascFactorial_succ, ← Nat.add_assoc, factorial_succ, Nat.mul_comm (n + 1 + k),
← Nat.mul_assoc, factorial_mul_ascFactorial n k, Nat.mul_comm, Nat.add_right_comm]
/-- `n.ascFactorial k = (n + k - 1)! / (n - 1)!` for `n > 0` but without ℕ-division. See
`Nat.ascFactorial_eq_div` for the version with ℕ-division. Consider using
`factorial_mul_ascFactorial` to avoid complications of ℕ-subtraction. -/
theorem factorial_mul_ascFactorial' (n k : ℕ) (h : 0 < n) :
(n - 1) ! * n.ascFactorial k = (n + k - 1)! := by
rw [Nat.sub_add_comm h, Nat.sub_one]
nth_rw 2 [Nat.eq_add_of_sub_eq h rfl]
rw [Nat.sub_one, factorial_mul_ascFactorial]
theorem ascFactorial_mul_ascFactorial (n l k : ℕ) :
n.ascFactorial l * (n + l).ascFactorial k = n.ascFactorial (l + k) := by
cases n with
| zero =>
cases l
· simp only [ascFactorial_zero, Nat.add_zero, Nat.one_mul, Nat.zero_add]
· simp only [Nat.add_right_comm, zero_ascFactorial, Nat.zero_add, Nat.zero_mul]
| succ n' =>
apply Nat.mul_left_cancel (factorial_pos n')
simp only [Nat.add_assoc, ← Nat.mul_assoc, factorial_mul_ascFactorial]
rw [Nat.add_comm 1 l, ← Nat.add_assoc, factorial_mul_ascFactorial, Nat.add_assoc]
/-- Avoid in favor of `Nat.factorial_mul_ascFactorial` if you can. ℕ-division isn't worth it. -/
theorem ascFactorial_eq_div (n k : ℕ) : (n + 1).ascFactorial k = (n + k)! / n ! :=
Nat.eq_div_of_mul_eq_right n.factorial_ne_zero (factorial_mul_ascFactorial _ _)
/-- Avoid in favor of `Nat.factorial_mul_ascFactorial'` if you can. ℕ-division isn't worth it. -/
theorem ascFactorial_eq_div' (n k : ℕ) (h : 0 < n) :
n.ascFactorial k = (n + k - 1)! / (n - 1) ! :=
Nat.eq_div_of_mul_eq_right (n - 1).factorial_ne_zero (factorial_mul_ascFactorial' _ _ h)
theorem ascFactorial_of_sub {n k : ℕ} :
(n - k) * (n - k + 1).ascFactorial k = (n - k).ascFactorial (k + 1) := by
rw [succ_ascFactorial, ascFactorial_succ]
theorem pow_succ_le_ascFactorial (n : ℕ) : ∀ k : ℕ, n ^ k ≤ n.ascFactorial k
| 0 => by rw [ascFactorial_zero, Nat.pow_zero]
| k + 1 => by
rw [Nat.pow_succ, Nat.mul_comm, ascFactorial_succ, ← succ_ascFactorial]
exact Nat.mul_le_mul (Nat.le_refl n)
(Nat.le_trans (Nat.pow_le_pow_left (le_succ n) k) (pow_succ_le_ascFactorial n.succ k))
theorem pow_lt_ascFactorial' (n k : ℕ) : (n + 1) ^ (k + 2) < (n + 1).ascFactorial (k + 2) := by
rw [Nat.pow_succ, ascFactorial, Nat.mul_comm]
exact Nat.mul_lt_mul_of_lt_of_le' (Nat.lt_add_of_pos_right k.succ_pos)
(pow_succ_le_ascFactorial n.succ _) (Nat.pow_pos n.succ_pos)
theorem pow_lt_ascFactorial (n : ℕ) : ∀ {k : ℕ}, 2 ≤ k → (n + 1) ^ k < (n + 1).ascFactorial k
| 0 => by rintro ⟨⟩
| 1 => by intro; contradiction
| k + 2 => fun _ => pow_lt_ascFactorial' n k
theorem ascFactorial_le_pow_add (n : ℕ) : ∀ k : ℕ, (n+1).ascFactorial k ≤ (n + k) ^ k
| 0 => by rw [ascFactorial_zero, Nat.pow_zero]
| k + 1 => by
rw [ascFactorial_succ, Nat.pow_succ, Nat.mul_comm, ← Nat.add_assoc, Nat.add_right_comm n 1 k]
exact Nat.mul_le_mul_right _
(Nat.le_trans (ascFactorial_le_pow_add _ k) (Nat.pow_le_pow_left (le_succ _) _))
theorem ascFactorial_lt_pow_add (n : ℕ) : ∀ {k : ℕ}, 2 ≤ k → (n + 1).ascFactorial k < (n + k) ^ k
| 0 => by rintro ⟨⟩
| 1 => by intro; contradiction
| k + 2 => fun _ => by
rw [Nat.pow_succ, Nat.mul_comm, ascFactorial_succ, succ_add_eq_add_succ n (k + 1)]
exact Nat.mul_lt_mul_of_le_of_lt (le_refl _) (Nat.lt_of_le_of_lt (ascFactorial_le_pow_add n _)
(Nat.pow_lt_pow_left (Nat.lt_succ_self _) k.succ_ne_zero)) (succ_pos _)
theorem ascFactorial_pos (n k : ℕ) : 0 < (n + 1).ascFactorial k :=
Nat.lt_of_lt_of_le (Nat.pow_pos n.succ_pos) (pow_succ_le_ascFactorial (n + 1) k)
end AscFactorial
section DescFactorial
/-- `n.descFactorial k = n! / (n - k)!` (as seen in `Nat.descFactorial_eq_div`), but
implemented recursively to allow for "quick" computation when using `norm_num`. This is closely
related to `descPochhammer`, but much less general. -/
def descFactorial (n : ℕ) : ℕ → ℕ
| 0 => 1
| k + 1 => (n - k) * descFactorial n k
@[simp]
theorem descFactorial_zero (n : ℕ) : n.descFactorial 0 = 1 :=
rfl
@[simp]
theorem descFactorial_succ (n k : ℕ) : n.descFactorial (k + 1) = (n - k) * n.descFactorial k :=
rfl
theorem zero_descFactorial_succ (k : ℕ) : (0 : ℕ).descFactorial (k + 1) = 0 := by
rw [descFactorial_succ, Nat.zero_sub, Nat.zero_mul]
theorem descFactorial_one (n : ℕ) : n.descFactorial 1 = n := by simp
theorem succ_descFactorial_succ (n : ℕ) :
∀ k : ℕ, (n + 1).descFactorial (k + 1) = (n + 1) * n.descFactorial k
| 0 => by rw [descFactorial_zero, descFactorial_one, Nat.mul_one]
| succ k => by
rw [descFactorial_succ, succ_descFactorial_succ _ k, descFactorial_succ, succ_sub_succ,
Nat.mul_left_comm]
theorem succ_descFactorial (n : ℕ) :
∀ k, (n + 1 - k) * (n + 1).descFactorial k = (n + 1) * n.descFactorial k
| 0 => by rw [Nat.sub_zero, descFactorial_zero, descFactorial_zero]
| k + 1 => by
rw [descFactorial, succ_descFactorial _ k, descFactorial_succ, succ_sub_succ, Nat.mul_left_comm]
theorem descFactorial_self : ∀ n : ℕ, n.descFactorial n = n !
| 0 => by rw [descFactorial_zero, factorial_zero]
| succ n => by rw [succ_descFactorial_succ, descFactorial_self n, factorial_succ]
@[simp]
theorem descFactorial_eq_zero_iff_lt {n : ℕ} : ∀ {k : ℕ}, n.descFactorial k = 0 ↔ n < k
| 0 => by simp only [descFactorial_zero, Nat.one_ne_zero, Nat.not_lt_zero]
| succ k => by
rw [descFactorial_succ, mul_eq_zero, descFactorial_eq_zero_iff_lt, Nat.lt_succ_iff,
Nat.sub_eq_zero_iff_le, Nat.lt_iff_le_and_ne, or_iff_left_iff_imp, and_imp]
exact fun h _ => h
alias ⟨_, descFactorial_of_lt⟩ := descFactorial_eq_zero_iff_lt
theorem add_descFactorial_eq_ascFactorial (n : ℕ) : ∀ k : ℕ,
(n + k).descFactorial k = (n + 1).ascFactorial k
| 0 => by rw [ascFactorial_zero, descFactorial_zero]
| succ k => by
rw [Nat.add_succ, succ_descFactorial_succ, ascFactorial_succ,
add_descFactorial_eq_ascFactorial _ k, Nat.add_right_comm]
theorem add_descFactorial_eq_ascFactorial' (n : ℕ) :
∀ k : ℕ, (n + k - 1).descFactorial k = n.ascFactorial k
| 0 => by rw [ascFactorial_zero, descFactorial_zero]
| succ k => by
rw [descFactorial_succ, ascFactorial_succ, ← succ_add_eq_add_succ,
add_descFactorial_eq_ascFactorial' _ k, ← succ_ascFactorial, succ_add_sub_one,
Nat.add_sub_cancel]
/-- `n.descFactorial k = n! / (n - k)!` but without ℕ-division. See `Nat.descFactorial_eq_div`
for the version using ℕ-division. -/
theorem factorial_mul_descFactorial : ∀ {n k : ℕ}, k ≤ n → (n - k)! * n.descFactorial k = n !
| n, 0 => fun _ => by rw [descFactorial_zero, Nat.mul_one, Nat.sub_zero]
| 0, succ k => fun h => by
exfalso
exact not_succ_le_zero k h
| succ n, succ k => fun h => by
rw [succ_descFactorial_succ, succ_sub_succ, ← Nat.mul_assoc, Nat.mul_comm (n - k)!,
Nat.mul_assoc, factorial_mul_descFactorial (Nat.succ_le_succ_iff.1 h), factorial_succ]
theorem descFactorial_mul_descFactorial {k m n : ℕ} (hkm : k ≤ m) :
(n - k).descFactorial (m - k) * n.descFactorial k = n.descFactorial m := by
by_cases hmn : m ≤ n
· apply Nat.mul_left_cancel (n - m).factorial_pos
rw [factorial_mul_descFactorial hmn, show n - m = (n - k) - (m - k) by omega, ← Nat.mul_assoc,
factorial_mul_descFactorial (show m - k ≤ n - k by omega),
factorial_mul_descFactorial (le_trans hkm hmn)]
· rw [descFactorial_eq_zero_iff_lt.mpr (show n < m by omega)]
by_cases hkn : k ≤ n
· rw [descFactorial_eq_zero_iff_lt.mpr (show n - k < m - k by omega), Nat.zero_mul]
· rw [descFactorial_eq_zero_iff_lt.mpr (show n < k by omega), Nat.mul_zero]
/-- Avoid in favor of `Nat.factorial_mul_descFactorial` if you can. ℕ-division isn't worth it. -/
theorem descFactorial_eq_div {n k : ℕ} (h : k ≤ n) : n.descFactorial k = n ! / (n - k)! := by
apply Nat.mul_left_cancel (n - k).factorial_pos
rw [factorial_mul_descFactorial h]
exact (Nat.mul_div_cancel' <| factorial_dvd_factorial <| Nat.sub_le n k).symm
theorem descFactorial_le (n : ℕ) {k m : ℕ} (h : k ≤ m) :
k.descFactorial n ≤ m.descFactorial n := by
| induction n with
| zero => rfl
| succ n ih =>
rw [descFactorial_succ, descFactorial_succ]
exact Nat.mul_le_mul (Nat.sub_le_sub_right h n) ih
theorem pow_sub_le_descFactorial (n : ℕ) : ∀ k : ℕ, (n + 1 - k) ^ k ≤ n.descFactorial k
| 0 => by rw [descFactorial_zero, Nat.pow_zero]
| Mathlib/Data/Nat/Factorial/Basic.lean | 397 | 404 |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir
-/
import Mathlib.Algebra.CharP.Defs
import Mathlib.Algebra.Order.CauSeq.BigOperators
import Mathlib.Algebra.Order.Star.Basic
import Mathlib.Data.Complex.BigOperators
import Mathlib.Data.Complex.Norm
import Mathlib.Data.Nat.Choose.Sum
/-!
# Exponential Function
This file contains the definitions of the real and complex exponential function.
## Main definitions
* `Complex.exp`: The complex exponential function, defined via its Taylor series
* `Real.exp`: The real exponential function, defined as the real part of the complex exponential
-/
open CauSeq Finset IsAbsoluteValue
open scoped ComplexConjugate
namespace Complex
theorem isCauSeq_norm_exp (z : ℂ) :
IsCauSeq abs fun n => ∑ m ∈ range n, ‖z ^ m / m.factorial‖ :=
let ⟨n, hn⟩ := exists_nat_gt ‖z‖
have hn0 : (0 : ℝ) < n := lt_of_le_of_lt (norm_nonneg _) hn
IsCauSeq.series_ratio_test n (‖z‖ / n) (div_nonneg (norm_nonneg _) (le_of_lt hn0))
(by rwa [div_lt_iff₀ hn0, one_mul]) fun m hm => by
rw [abs_norm, abs_norm, Nat.factorial_succ, pow_succ', mul_comm m.succ, Nat.cast_mul,
← div_div, mul_div_assoc, mul_div_right_comm, Complex.norm_mul, Complex.norm_div,
norm_natCast]
gcongr
exact le_trans hm (Nat.le_succ _)
@[deprecated (since := "2025-02-16")] alias isCauSeq_abs_exp := isCauSeq_norm_exp
noncomputable section
theorem isCauSeq_exp (z : ℂ) : IsCauSeq (‖·‖) fun n => ∑ m ∈ range n, z ^ m / m.factorial :=
(isCauSeq_norm_exp z).of_abv
/-- The Cauchy sequence consisting of partial sums of the Taylor series of
the complex exponential function -/
@[pp_nodot]
def exp' (z : ℂ) : CauSeq ℂ (‖·‖) :=
⟨fun n => ∑ m ∈ range n, z ^ m / m.factorial, isCauSeq_exp z⟩
/-- The complex exponential function, defined via its Taylor series -/
@[pp_nodot]
def exp (z : ℂ) : ℂ :=
CauSeq.lim (exp' z)
/-- scoped notation for the complex exponential function -/
scoped notation "cexp" => Complex.exp
end
end Complex
namespace Real
open Complex
noncomputable section
/-- The real exponential function, defined as the real part of the complex exponential -/
@[pp_nodot]
nonrec def exp (x : ℝ) : ℝ :=
(exp x).re
/-- scoped notation for the real exponential function -/
scoped notation "rexp" => Real.exp
end
end Real
namespace Complex
variable (x y : ℂ)
@[simp]
theorem exp_zero : exp 0 = 1 := by
rw [exp]
refine lim_eq_of_equiv_const fun ε ε0 => ⟨1, fun j hj => ?_⟩
convert (config := .unfoldSameFun) ε0 -- ε0 : ε > 0 but goal is _ < ε
rcases j with - | j
· exact absurd hj (not_le_of_gt zero_lt_one)
· dsimp [exp']
induction' j with j ih
· dsimp [exp']; simp [show Nat.succ 0 = 1 from rfl]
· rw [← ih (by simp [Nat.succ_le_succ])]
simp only [sum_range_succ, pow_succ]
simp
theorem exp_add : exp (x + y) = exp x * exp y := by
have hj : ∀ j : ℕ, (∑ m ∈ range j, (x + y) ^ m / m.factorial) =
∑ i ∈ range j, ∑ k ∈ range (i + 1), x ^ k / k.factorial *
(y ^ (i - k) / (i - k).factorial) := by
intro j
refine Finset.sum_congr rfl fun m _ => ?_
rw [add_pow, div_eq_mul_inv, sum_mul]
refine Finset.sum_congr rfl fun I hi => ?_
have h₁ : (m.choose I : ℂ) ≠ 0 :=
Nat.cast_ne_zero.2 (pos_iff_ne_zero.1 (Nat.choose_pos (Nat.le_of_lt_succ (mem_range.1 hi))))
have h₂ := Nat.choose_mul_factorial_mul_factorial (Nat.le_of_lt_succ <| Finset.mem_range.1 hi)
rw [← h₂, Nat.cast_mul, Nat.cast_mul, mul_inv, mul_inv]
simp only [mul_left_comm (m.choose I : ℂ), mul_assoc, mul_left_comm (m.choose I : ℂ)⁻¹,
mul_comm (m.choose I : ℂ)]
rw [inv_mul_cancel₀ h₁]
simp [div_eq_mul_inv, mul_comm, mul_assoc, mul_left_comm]
simp_rw [exp, exp', lim_mul_lim]
apply (lim_eq_lim_of_equiv _).symm
simp only [hj]
exact cauchy_product (isCauSeq_norm_exp x) (isCauSeq_exp y)
/-- the exponential function as a monoid hom from `Multiplicative ℂ` to `ℂ` -/
@[simps]
noncomputable def expMonoidHom : MonoidHom (Multiplicative ℂ) ℂ :=
{ toFun := fun z => exp z.toAdd,
map_one' := by simp,
map_mul' := by simp [exp_add] }
theorem exp_list_sum (l : List ℂ) : exp l.sum = (l.map exp).prod :=
map_list_prod (M := Multiplicative ℂ) expMonoidHom l
theorem exp_multiset_sum (s : Multiset ℂ) : exp s.sum = (s.map exp).prod :=
@MonoidHom.map_multiset_prod (Multiplicative ℂ) ℂ _ _ expMonoidHom s
theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℂ) :
exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) :=
map_prod (β := Multiplicative ℂ) expMonoidHom f s
lemma exp_nsmul (x : ℂ) (n : ℕ) : exp (n • x) = exp x ^ n :=
@MonoidHom.map_pow (Multiplicative ℂ) ℂ _ _ expMonoidHom _ _
theorem exp_nat_mul (x : ℂ) : ∀ n : ℕ, exp (n * x) = exp x ^ n
| 0 => by rw [Nat.cast_zero, zero_mul, exp_zero, pow_zero]
| Nat.succ n => by rw [pow_succ, Nat.cast_add_one, add_mul, exp_add, ← exp_nat_mul _ n, one_mul]
@[simp]
theorem exp_ne_zero : exp x ≠ 0 := fun h =>
zero_ne_one (α := ℂ) <| by rw [← exp_zero, ← add_neg_cancel x, exp_add, h]; simp
theorem exp_neg : exp (-x) = (exp x)⁻¹ := by
rw [← mul_right_inj' (exp_ne_zero x), ← exp_add]; simp [mul_inv_cancel₀ (exp_ne_zero x)]
theorem exp_sub : exp (x - y) = exp x / exp y := by
simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv]
theorem exp_int_mul (z : ℂ) (n : ℤ) : Complex.exp (n * z) = Complex.exp z ^ n := by
cases n
· simp [exp_nat_mul]
· simp [exp_add, add_mul, pow_add, exp_neg, exp_nat_mul]
@[simp]
theorem exp_conj : exp (conj x) = conj (exp x) := by
dsimp [exp]
rw [← lim_conj]
refine congr_arg CauSeq.lim (CauSeq.ext fun _ => ?_)
dsimp [exp', Function.comp_def, cauSeqConj]
rw [map_sum (starRingEnd _)]
refine sum_congr rfl fun n _ => ?_
rw [map_div₀, map_pow, ← ofReal_natCast, conj_ofReal]
@[simp]
theorem ofReal_exp_ofReal_re (x : ℝ) : ((exp x).re : ℂ) = exp x :=
conj_eq_iff_re.1 <| by rw [← exp_conj, conj_ofReal]
@[simp, norm_cast]
theorem ofReal_exp (x : ℝ) : (Real.exp x : ℂ) = exp x :=
ofReal_exp_ofReal_re _
@[simp]
theorem exp_ofReal_im (x : ℝ) : (exp x).im = 0 := by rw [← ofReal_exp_ofReal_re, ofReal_im]
theorem exp_ofReal_re (x : ℝ) : (exp x).re = Real.exp x :=
rfl
end Complex
namespace Real
open Complex
variable (x y : ℝ)
@[simp]
theorem exp_zero : exp 0 = 1 := by simp [Real.exp]
nonrec theorem exp_add : exp (x + y) = exp x * exp y := by simp [exp_add, exp]
/-- the exponential function as a monoid hom from `Multiplicative ℝ` to `ℝ` -/
@[simps]
noncomputable def expMonoidHom : MonoidHom (Multiplicative ℝ) ℝ :=
{ toFun := fun x => exp x.toAdd,
map_one' := by simp,
map_mul' := by simp [exp_add] }
theorem exp_list_sum (l : List ℝ) : exp l.sum = (l.map exp).prod :=
map_list_prod (M := Multiplicative ℝ) expMonoidHom l
theorem exp_multiset_sum (s : Multiset ℝ) : exp s.sum = (s.map exp).prod :=
@MonoidHom.map_multiset_prod (Multiplicative ℝ) ℝ _ _ expMonoidHom s
theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℝ) :
exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) :=
map_prod (β := Multiplicative ℝ) expMonoidHom f s
lemma exp_nsmul (x : ℝ) (n : ℕ) : exp (n • x) = exp x ^ n :=
@MonoidHom.map_pow (Multiplicative ℝ) ℝ _ _ expMonoidHom _ _
nonrec theorem exp_nat_mul (x : ℝ) (n : ℕ) : exp (n * x) = exp x ^ n :=
ofReal_injective (by simp [exp_nat_mul])
@[simp]
nonrec theorem exp_ne_zero : exp x ≠ 0 := fun h =>
exp_ne_zero x <| by rw [exp, ← ofReal_inj] at h; simp_all
nonrec theorem exp_neg : exp (-x) = (exp x)⁻¹ :=
ofReal_injective <| by simp [exp_neg]
theorem exp_sub : exp (x - y) = exp x / exp y := by
simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv]
open IsAbsoluteValue Nat
theorem sum_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) (n : ℕ) : ∑ i ∈ range n, x ^ i / i ! ≤ exp x :=
calc
∑ i ∈ range n, x ^ i / i ! ≤ lim (⟨_, isCauSeq_re (exp' x)⟩ : CauSeq ℝ abs) := by
refine le_lim (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩)
simp only [exp', const_apply, re_sum]
norm_cast
refine sum_le_sum_of_subset_of_nonneg (range_mono hj) fun _ _ _ ↦ ?_
positivity
_ = exp x := by rw [exp, Complex.exp, ← cauSeqRe, lim_re]
lemma pow_div_factorial_le_exp (hx : 0 ≤ x) (n : ℕ) : x ^ n / n ! ≤ exp x :=
calc
x ^ n / n ! ≤ ∑ k ∈ range (n + 1), x ^ k / k ! :=
single_le_sum (f := fun k ↦ x ^ k / k !) (fun k _ ↦ by positivity) (self_mem_range_succ n)
_ ≤ exp x := sum_le_exp_of_nonneg hx _
theorem quadratic_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : 1 + x + x ^ 2 / 2 ≤ exp x :=
calc
1 + x + x ^ 2 / 2 = ∑ i ∈ range 3, x ^ i / i ! := by
simp only [sum_range_succ, range_one, sum_singleton, _root_.pow_zero, factorial, cast_one,
ne_eq, one_ne_zero, not_false_eq_true, div_self, pow_one, mul_one, div_one, Nat.mul_one,
cast_succ, add_right_inj]
ring_nf
_ ≤ exp x := sum_le_exp_of_nonneg hx 3
private theorem add_one_lt_exp_of_pos {x : ℝ} (hx : 0 < x) : x + 1 < exp x :=
(by nlinarith : x + 1 < 1 + x + x ^ 2 / 2).trans_le (quadratic_le_exp_of_nonneg hx.le)
private theorem add_one_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : x + 1 ≤ exp x := by
rcases eq_or_lt_of_le hx with (rfl | h)
· simp
exact (add_one_lt_exp_of_pos h).le
theorem one_le_exp {x : ℝ} (hx : 0 ≤ x) : 1 ≤ exp x := by linarith [add_one_le_exp_of_nonneg hx]
@[bound]
theorem exp_pos (x : ℝ) : 0 < exp x :=
(le_total 0 x).elim (lt_of_lt_of_le zero_lt_one ∘ one_le_exp) fun h => by
rw [← neg_neg x, Real.exp_neg]
exact inv_pos.2 (lt_of_lt_of_le zero_lt_one (one_le_exp (neg_nonneg.2 h)))
@[bound]
lemma exp_nonneg (x : ℝ) : 0 ≤ exp x := x.exp_pos.le
@[simp]
theorem abs_exp (x : ℝ) : |exp x| = exp x :=
abs_of_pos (exp_pos _)
lemma exp_abs_le (x : ℝ) : exp |x| ≤ exp x + exp (-x) := by
cases le_total x 0 <;> simp [abs_of_nonpos, abs_of_nonneg, exp_nonneg, *]
@[mono]
theorem exp_strictMono : StrictMono exp := fun x y h => by
rw [← sub_add_cancel y x, Real.exp_add]
exact (lt_mul_iff_one_lt_left (exp_pos _)).2
(lt_of_lt_of_le (by linarith) (add_one_le_exp_of_nonneg (by linarith)))
@[gcongr]
theorem exp_lt_exp_of_lt {x y : ℝ} (h : x < y) : exp x < exp y := exp_strictMono h
@[mono]
theorem exp_monotone : Monotone exp :=
exp_strictMono.monotone
@[gcongr, bound]
theorem exp_le_exp_of_le {x y : ℝ} (h : x ≤ y) : exp x ≤ exp y := exp_monotone h
@[simp]
theorem exp_lt_exp {x y : ℝ} : exp x < exp y ↔ x < y :=
exp_strictMono.lt_iff_lt
@[simp]
theorem exp_le_exp {x y : ℝ} : exp x ≤ exp y ↔ x ≤ y :=
exp_strictMono.le_iff_le
theorem exp_injective : Function.Injective exp :=
exp_strictMono.injective
@[simp]
theorem exp_eq_exp {x y : ℝ} : exp x = exp y ↔ x = y :=
exp_injective.eq_iff
@[simp]
theorem exp_eq_one_iff : exp x = 1 ↔ x = 0 :=
exp_injective.eq_iff' exp_zero
@[simp]
theorem one_lt_exp_iff {x : ℝ} : 1 < exp x ↔ 0 < x := by rw [← exp_zero, exp_lt_exp]
@[bound] private alias ⟨_, Bound.one_lt_exp_of_pos⟩ := one_lt_exp_iff
@[simp]
theorem exp_lt_one_iff {x : ℝ} : exp x < 1 ↔ x < 0 := by rw [← exp_zero, exp_lt_exp]
@[simp]
theorem exp_le_one_iff {x : ℝ} : exp x ≤ 1 ↔ x ≤ 0 :=
exp_zero ▸ exp_le_exp
@[simp]
theorem one_le_exp_iff {x : ℝ} : 1 ≤ exp x ↔ 0 ≤ x :=
exp_zero ▸ exp_le_exp
end Real
namespace Complex
theorem sum_div_factorial_le {α : Type*} [Field α] [LinearOrder α] [IsStrictOrderedRing α]
(n j : ℕ) (hn : 0 < n) :
(∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) ≤ n.succ / (n.factorial * n) :=
calc
(∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) =
∑ m ∈ range (j - n), (1 / ((m + n).factorial : α)) := by
refine sum_nbij' (· - n) (· + n) ?_ ?_ ?_ ?_ ?_ <;>
simp +contextual [lt_tsub_iff_right, tsub_add_cancel_of_le]
_ ≤ ∑ m ∈ range (j - n), ((n.factorial : α) * (n.succ : α) ^ m)⁻¹ := by
simp_rw [one_div]
gcongr
rw [← Nat.cast_pow, ← Nat.cast_mul, Nat.cast_le, add_comm]
exact Nat.factorial_mul_pow_le_factorial
_ = (n.factorial : α)⁻¹ * ∑ m ∈ range (j - n), (n.succ : α)⁻¹ ^ m := by
simp [mul_inv, ← mul_sum, ← sum_mul, mul_comm, inv_pow]
_ = ((n.succ : α) - n.succ * (n.succ : α)⁻¹ ^ (j - n)) / (n.factorial * n) := by
have h₁ : (n.succ : α) ≠ 1 :=
@Nat.cast_one α _ ▸ mt Nat.cast_inj.1 (mt Nat.succ.inj (pos_iff_ne_zero.1 hn))
have h₂ : (n.succ : α) ≠ 0 := by positivity
have h₃ : (n.factorial * n : α) ≠ 0 := by positivity
have h₄ : (n.succ - 1 : α) = n := by simp
rw [geom_sum_inv h₁ h₂, eq_div_iff_mul_eq h₃, mul_comm _ (n.factorial * n : α),
← mul_assoc (n.factorial⁻¹ : α), ← mul_inv_rev, h₄, ← mul_assoc (n.factorial * n : α),
mul_comm (n : α) n.factorial, mul_inv_cancel₀ h₃, one_mul, mul_comm]
_ ≤ n.succ / (n.factorial * n : α) := by gcongr; apply sub_le_self; positivity
theorem exp_bound {x : ℂ} (hx : ‖x‖ ≤ 1) {n : ℕ} (hn : 0 < n) :
‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤
‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹) := by
rw [← lim_const (abv := norm) (∑ m ∈ range n, _), exp, sub_eq_add_neg,
← lim_neg, lim_add, ← lim_norm]
refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩)
simp_rw [← sub_eq_add_neg]
show
‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤
‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹)
rw [sum_range_sub_sum_range hj]
calc
‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖
= ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by
refine congr_arg norm (sum_congr rfl fun m hm => ?_)
rw [mem_filter, mem_range] at hm
rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2]
_ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ :=
IsAbsoluteValue.abv_sum norm ..
_ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (1 / m.factorial) := by
simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast]
gcongr
rw [Complex.norm_pow]
exact pow_le_one₀ (norm_nonneg _) hx
_ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (1 / m.factorial : ℝ) := by
simp [abs_mul, abv_pow abs, abs_div, ← mul_sum]
_ ≤ ‖x‖ ^ n * (n.succ * (n.factorial * n : ℝ)⁻¹) := by
gcongr
exact sum_div_factorial_le _ _ hn
theorem exp_bound' {x : ℂ} {n : ℕ} (hx : ‖x‖ / n.succ ≤ 1 / 2) :
‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n / n.factorial * 2 := by
rw [← lim_const (abv := norm) (∑ m ∈ range n, _),
exp, sub_eq_add_neg, ← lim_neg, lim_add, ← lim_norm]
refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩)
simp_rw [← sub_eq_add_neg]
show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤
‖x‖ ^ n / n.factorial * 2
let k := j - n
have hj : j = n + k := (add_tsub_cancel_of_le hj).symm
rw [hj, sum_range_add_sub_sum_range]
calc
‖∑ i ∈ range k, x ^ (n + i) / ((n + i).factorial : ℂ)‖ ≤
∑ i ∈ range k, ‖x ^ (n + i) / ((n + i).factorial : ℂ)‖ :=
IsAbsoluteValue.abv_sum _ _ _
_ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / (n + i).factorial := by
simp [norm_natCast, Complex.norm_pow]
_ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / ((n.factorial : ℝ) * (n.succ : ℝ) ^ i) := ?_
_ = ∑ i ∈ range k, ‖x‖ ^ n / n.factorial * (‖x‖ ^ i / (n.succ : ℝ) ^ i) := ?_
_ ≤ ‖x‖ ^ n / ↑n.factorial * 2 := ?_
· gcongr
exact mod_cast Nat.factorial_mul_pow_le_factorial
· refine Finset.sum_congr rfl fun _ _ => ?_
simp only [pow_add, div_eq_inv_mul, mul_inv, mul_left_comm, mul_assoc]
· rw [← mul_sum]
gcongr
simp_rw [← div_pow]
rw [geom_sum_eq, div_le_iff_of_neg]
· trans (-1 : ℝ)
· linarith
· simp only [neg_le_sub_iff_le_add, div_pow, Nat.cast_succ, le_add_iff_nonneg_left]
positivity
· linarith
· linarith
theorem norm_exp_sub_one_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1‖ ≤ 2 * ‖x‖ :=
calc
‖exp x - 1‖ = ‖exp x - ∑ m ∈ range 1, x ^ m / m.factorial‖ := by simp [sum_range_succ]
_ ≤ ‖x‖ ^ 1 * ((Nat.succ 1 : ℝ) * ((Nat.factorial 1) * (1 : ℕ) : ℝ)⁻¹) :=
(exp_bound hx (by decide))
_ = 2 * ‖x‖ := by simp [two_mul, mul_two, mul_add, mul_comm, add_mul, Nat.factorial]
theorem norm_exp_sub_one_sub_id_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1 - x‖ ≤ ‖x‖ ^ 2 :=
calc
‖exp x - 1 - x‖ = ‖exp x - ∑ m ∈ range 2, x ^ m / m.factorial‖ := by
simp [sub_eq_add_neg, sum_range_succ_comm, add_assoc, Nat.factorial]
_ ≤ ‖x‖ ^ 2 * ((Nat.succ 2 : ℝ) * (Nat.factorial 2 * (2 : ℕ) : ℝ)⁻¹) :=
(exp_bound hx (by decide))
_ ≤ ‖x‖ ^ 2 * 1 := by gcongr; norm_num [Nat.factorial]
_ = ‖x‖ ^ 2 := by rw [mul_one]
lemma norm_exp_sub_sum_le_exp_norm_sub_sum (x : ℂ) (n : ℕ) :
‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖
≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by
rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg,
← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm]
refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩)
simp_rw [← sub_eq_add_neg]
calc ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖
_ ≤ (∑ m ∈ range j, ‖x‖ ^ m / m.factorial) - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by
rw [sum_range_sub_sum_range hj, sum_range_sub_sum_range hj]
refine (IsAbsoluteValue.abv_sum norm ..).trans_eq ?_
congr with i
simp [Complex.norm_pow]
_ ≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by
gcongr
exact Real.sum_le_exp_of_nonneg (norm_nonneg _) _
lemma norm_exp_le_exp_norm (x : ℂ) : ‖exp x‖ ≤ Real.exp ‖x‖ := by
convert norm_exp_sub_sum_le_exp_norm_sub_sum x 0 using 1 <;> simp
lemma norm_exp_sub_sum_le_norm_mul_exp (x : ℂ) (n : ℕ) :
‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by
rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg,
← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm]
refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩)
simp_rw [← sub_eq_add_neg]
show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ _
rw [sum_range_sub_sum_range hj]
calc
‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖
= ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by
refine congr_arg norm (sum_congr rfl fun m hm => ?_)
rw [mem_filter, mem_range] at hm
rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2]
_ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ :=
IsAbsoluteValue.abv_sum norm ..
_ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (‖x‖ ^ (m - n) / (m - n).factorial) := by
simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast]
gcongr with i hi
· rw [Complex.norm_pow]
· simp
_ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (‖x‖ ^ (m - n) / (m - n).factorial) := by
rw [← mul_sum]
_ = ‖x‖ ^ n * ∑ m ∈ range (j - n), (‖x‖ ^ m / m.factorial) := by
congr 1
refine (sum_bij (fun m hm ↦ m + n) ?_ ?_ ?_ ?_).symm
· intro a ha
simp only [mem_filter, mem_range, le_add_iff_nonneg_left, zero_le, and_true]
simp only [mem_range] at ha
rwa [← lt_tsub_iff_right]
· intro a ha b hb hab
simpa using hab
· intro b hb
simp only [mem_range, exists_prop]
simp only [mem_filter, mem_range] at hb
refine ⟨b - n, ?_, ?_⟩
· rw [tsub_lt_tsub_iff_right hb.2]
exact hb.1
· rw [tsub_add_cancel_of_le hb.2]
· simp
_ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by
gcongr
refine Real.sum_le_exp_of_nonneg ?_ _
exact norm_nonneg _
@[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_le := norm_exp_sub_one_le
@[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_sub_id_le := norm_exp_sub_one_sub_id_le
@[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_exp_abs_sub_sum :=
norm_exp_sub_sum_le_exp_norm_sub_sum
@[deprecated (since := "2025-02-16")] alias abs_exp_le_exp_abs := norm_exp_le_exp_norm
@[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_abs_mul_exp :=
norm_exp_sub_sum_le_norm_mul_exp
end Complex
namespace Real
open Complex Finset
nonrec theorem exp_bound {x : ℝ} (hx : |x| ≤ 1) {n : ℕ} (hn : 0 < n) :
|exp x - ∑ m ∈ range n, x ^ m / m.factorial| ≤ |x| ^ n * (n.succ / (n.factorial * n)) := by
have hxc : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx
convert exp_bound hxc hn using 2 <;>
norm_cast
theorem exp_bound' {x : ℝ} (h1 : 0 ≤ x) (h2 : x ≤ 1) {n : ℕ} (hn : 0 < n) :
Real.exp x ≤ (∑ m ∈ Finset.range n, x ^ m / m.factorial) +
x ^ n * (n + 1) / (n.factorial * n) := by
have h3 : |x| = x := by simpa
have h4 : |x| ≤ 1 := by rwa [h3]
have h' := Real.exp_bound h4 hn
rw [h3] at h'
have h'' := (abs_sub_le_iff.1 h').1
have t := sub_le_iff_le_add'.1 h''
simpa [mul_div_assoc] using t
theorem abs_exp_sub_one_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1| ≤ 2 * |x| := by
have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx
exact_mod_cast Complex.norm_exp_sub_one_le (x := x) this
theorem abs_exp_sub_one_sub_id_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1 - x| ≤ x ^ 2 := by
rw [← sq_abs]
have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx
exact_mod_cast Complex.norm_exp_sub_one_sub_id_le this
/-- A finite initial segment of the exponential series, followed by an arbitrary tail.
For fixed `n` this is just a linear map wrt `r`, and each map is a simple linear function
of the previous (see `expNear_succ`), with `expNear n x r ⟶ exp x` as `n ⟶ ∞`,
for any `r`. -/
noncomputable def expNear (n : ℕ) (x r : ℝ) : ℝ :=
(∑ m ∈ range n, x ^ m / m.factorial) + x ^ n / n.factorial * r
@[simp]
theorem expNear_zero (x r) : expNear 0 x r = r := by simp [expNear]
@[simp]
theorem expNear_succ (n x r) : expNear (n + 1) x r = expNear n x (1 + x / (n + 1) * r) := by
simp [expNear, range_succ, mul_add, add_left_comm, add_assoc, pow_succ, div_eq_mul_inv,
mul_inv, Nat.factorial]
ac_rfl
theorem expNear_sub (n x r₁ r₂) : expNear n x r₁ -
expNear n x r₂ = x ^ n / n.factorial * (r₁ - r₂) := by
simp [expNear, mul_sub]
theorem exp_approx_end (n m : ℕ) (x : ℝ) (e₁ : n + 1 = m) (h : |x| ≤ 1) :
|exp x - expNear m x 0| ≤ |x| ^ m / m.factorial * ((m + 1) / m) := by
simp only [expNear, mul_zero, add_zero]
convert exp_bound (n := m) h ?_ using 1
· field_simp [mul_comm]
· omega
theorem exp_approx_succ {n} {x a₁ b₁ : ℝ} (m : ℕ) (e₁ : n + 1 = m) (a₂ b₂ : ℝ)
(e : |1 + x / m * a₂ - a₁| ≤ b₁ - |x| / m * b₂)
(h : |exp x - expNear m x a₂| ≤ |x| ^ m / m.factorial * b₂) :
|exp x - expNear n x a₁| ≤ |x| ^ n / n.factorial * b₁ := by
refine (abs_sub_le _ _ _).trans ((add_le_add_right h _).trans ?_)
subst e₁; rw [expNear_succ, expNear_sub, abs_mul]
convert mul_le_mul_of_nonneg_left (a := |x| ^ n / ↑(Nat.factorial n))
(le_sub_iff_add_le'.1 e) ?_ using 1
· simp [mul_add, pow_succ', div_eq_mul_inv, abs_mul, abs_inv, ← pow_abs, mul_inv, Nat.factorial]
ac_rfl
· simp [div_nonneg, abs_nonneg]
theorem exp_approx_end' {n} {x a b : ℝ} (m : ℕ) (e₁ : n + 1 = m) (rm : ℝ) (er : ↑m = rm)
(h : |x| ≤ 1) (e : |1 - a| ≤ b - |x| / rm * ((rm + 1) / rm)) :
|exp x - expNear n x a| ≤ |x| ^ n / n.factorial * b := by
subst er
exact exp_approx_succ _ e₁ _ _ (by simpa using e) (exp_approx_end _ _ _ e₁ h)
theorem exp_1_approx_succ_eq {n} {a₁ b₁ : ℝ} {m : ℕ} (en : n + 1 = m) {rm : ℝ} (er : ↑m = rm)
(h : |exp 1 - expNear m 1 ((a₁ - 1) * rm)| ≤ |1| ^ m / m.factorial * (b₁ * rm)) :
|exp 1 - expNear n 1 a₁| ≤ |1| ^ n / n.factorial * b₁ := by
subst er
refine exp_approx_succ _ en _ _ ?_ h
field_simp [show (m : ℝ) ≠ 0 by norm_cast; omega]
theorem exp_approx_start (x a b : ℝ) (h : |exp x - expNear 0 x a| ≤ |x| ^ 0 / Nat.factorial 0 * b) :
|exp x - a| ≤ b := by simpa using h
theorem exp_bound_div_one_sub_of_interval' {x : ℝ} (h1 : 0 < x) (h2 : x < 1) :
Real.exp x < 1 / (1 - x) := by
have H : 0 < 1 - (1 + x + x ^ 2) * (1 - x) := calc
0 < x ^ 3 := by positivity
_ = 1 - (1 + x + x ^ 2) * (1 - x) := by ring
calc
exp x ≤ _ := exp_bound' h1.le h2.le zero_lt_three
_ ≤ 1 + x + x ^ 2 := by
-- Porting note: was `norm_num [Finset.sum] <;> nlinarith`
-- This proof should be restored after the norm_num plugin for big operators is ported.
-- (It may also need the positivity extensions in https://github.com/leanprover-community/mathlib4/pull/3907.)
rw [show 3 = 1 + 1 + 1 from rfl]
repeat rw [Finset.sum_range_succ]
norm_num [Nat.factorial]
nlinarith
_ < 1 / (1 - x) := by rw [lt_div_iff₀] <;> nlinarith
theorem exp_bound_div_one_sub_of_interval {x : ℝ} (h1 : 0 ≤ x) (h2 : x < 1) :
Real.exp x ≤ 1 / (1 - x) := by
rcases eq_or_lt_of_le h1 with (rfl | h1)
· simp
· exact (exp_bound_div_one_sub_of_interval' h1 h2).le
theorem add_one_lt_exp {x : ℝ} (hx : x ≠ 0) : x + 1 < Real.exp x := by
obtain hx | hx := hx.symm.lt_or_lt
· exact add_one_lt_exp_of_pos hx
obtain h' | h' := le_or_lt 1 (-x)
· linarith [x.exp_pos]
have hx' : 0 < x + 1 := by linarith
simpa [add_comm, exp_neg, inv_lt_inv₀ (exp_pos _) hx']
using exp_bound_div_one_sub_of_interval' (neg_pos.2 hx) h'
theorem add_one_le_exp (x : ℝ) : x + 1 ≤ Real.exp x := by
obtain rfl | hx := eq_or_ne x 0
· simp
· exact (add_one_lt_exp hx).le
lemma one_sub_lt_exp_neg {x : ℝ} (hx : x ≠ 0) : 1 - x < exp (-x) :=
(sub_eq_neg_add _ _).trans_lt <| add_one_lt_exp <| neg_ne_zero.2 hx
lemma one_sub_le_exp_neg (x : ℝ) : 1 - x ≤ exp (-x) :=
(sub_eq_neg_add _ _).trans_le <| add_one_le_exp _
theorem one_sub_div_pow_le_exp_neg {n : ℕ} {t : ℝ} (ht' : t ≤ n) : (1 - t / n) ^ n ≤ exp (-t) := by
rcases eq_or_ne n 0 with (rfl | hn)
· simp
rwa [Nat.cast_zero] at ht'
calc
(1 - t / n) ^ n ≤ rexp (-(t / n)) ^ n := by
gcongr
· exact sub_nonneg.2 <| div_le_one_of_le₀ ht' n.cast_nonneg
· exact one_sub_le_exp_neg _
_ = rexp (-t) := by rw [← Real.exp_nat_mul, mul_neg, mul_comm, div_mul_cancel₀]; positivity
lemma le_inv_mul_exp (x : ℝ) {c : ℝ} (hc : 0 < c) : x ≤ c⁻¹ * exp (c * x) := by
rw [le_inv_mul_iff₀ hc]
calc c * x
_ ≤ c * x + 1 := le_add_of_nonneg_right zero_le_one
_ ≤ _ := Real.add_one_le_exp (c * x)
end Real
namespace Mathlib.Meta.Positivity
open Lean.Meta Qq
/-- Extension for the `positivity` tactic: `Real.exp` is always positive. -/
@[positivity Real.exp _]
def evalExp : PositivityExt where eval {u α} _ _ e := do
match u, α, e with
| 0, ~q(ℝ), ~q(Real.exp $a) =>
assertInstancesCommute
pure (.positive q(Real.exp_pos $a))
| _, _, _ => throwError "not Real.exp"
end Mathlib.Meta.Positivity
namespace Complex
@[simp]
theorem norm_exp_ofReal (x : ℝ) : ‖exp x‖ = Real.exp x := by
rw [← ofReal_exp]
exact Complex.norm_of_nonneg (le_of_lt (Real.exp_pos _))
@[deprecated (since := "2025-02-16")] alias abs_exp_ofReal := norm_exp_ofReal
end Complex
| Mathlib/Data/Complex/Exponential.lean | 1,615 | 1,619 | |
/-
Copyright (c) 2024 Josha Dekker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Josha Dekker
-/
import Mathlib.Probability.Notation
import Mathlib.Probability.CDF
import Mathlib.Analysis.SpecialFunctions.Gamma.Basic
/-! # Gamma distributions over ℝ
Define the gamma measure over the reals.
## Main definitions
* `gammaPDFReal`: the function `a r x ↦ r ^ a / (Gamma a) * x ^ (a-1) * exp (-(r * x))`
for `0 ≤ x` or `0` else, which is the probability density function of a gamma distribution with
shape `a` and rate `r` (when `ha : 0 < a ` and `hr : 0 < r`).
* `gammaPDF`: `ℝ≥0∞`-valued pdf,
`gammaPDF a r = ENNReal.ofReal (gammaPDFReal a r)`.
* `gammaMeasure`: a gamma measure on `ℝ`, parametrized by its shape `a` and rate `r`.
* `gammaCDFReal`: the CDF given by the definition of CDF in `ProbabilityTheory.CDF` applied to the
gamma measure.
-/
open scoped ENNReal NNReal
open MeasureTheory Real Set Filter Topology
/-- A Lebesgue Integral from -∞ to y can be expressed as the sum of one from -∞ to 0 and 0 to x -/
lemma lintegral_Iic_eq_lintegral_Iio_add_Icc {y z : ℝ} (f : ℝ → ℝ≥0∞) (hzy : z ≤ y) :
∫⁻ x in Iic y, f x = (∫⁻ x in Iio z, f x) + ∫⁻ x in Icc z y, f x := by
rw [← Iio_union_Icc_eq_Iic hzy, lintegral_union measurableSet_Icc]
simp_rw [Set.disjoint_iff_forall_ne, mem_Iio, mem_Icc]
intros
linarith
namespace ProbabilityTheory
section GammaPDF
/-- The pdf of the gamma distribution depending on its scale and rate -/
noncomputable
def gammaPDFReal (a r x : ℝ) : ℝ :=
if 0 ≤ x then r ^ a / (Gamma a) * x ^ (a-1) * exp (-(r * x)) else 0
/-- The pdf of the gamma distribution, as a function valued in `ℝ≥0∞` -/
noncomputable
def gammaPDF (a r x : ℝ) : ℝ≥0∞ :=
ENNReal.ofReal (gammaPDFReal a r x)
lemma gammaPDF_eq (a r x : ℝ) :
gammaPDF a r x =
ENNReal.ofReal (if 0 ≤ x then r ^ a / (Gamma a) * x ^ (a-1) * exp (-(r * x)) else 0) :=
rfl
lemma gammaPDF_of_neg {a r x : ℝ} (hx : x < 0) : gammaPDF a r x = 0 := by
simp only [gammaPDF_eq, if_neg (not_le.mpr hx), ENNReal.ofReal_zero]
lemma gammaPDF_of_nonneg {a r x : ℝ} (hx : 0 ≤ x) :
gammaPDF a r x = ENNReal.ofReal (r ^ a / (Gamma a) * x ^ (a-1) * exp (-(r * x))) := by
simp only [gammaPDF_eq, if_pos hx]
|
/-- The Lebesgue integral of the gamma pdf over nonpositive reals equals 0 -/
lemma lintegral_gammaPDF_of_nonpos {x a r : ℝ} (hx : x ≤ 0) :
∫⁻ y in Iio x, gammaPDF a r y = 0 := by
rw [setLIntegral_congr_fun (g := fun _ ↦ 0) measurableSet_Iio]
· rw [lintegral_zero, ← ENNReal.ofReal_zero]
· simp only [gammaPDF_eq, ENNReal.ofReal_eq_zero]
filter_upwards with a (_ : a < _)
| Mathlib/Probability/Distributions/Gamma.lean | 62 | 69 |
/-
Copyright (c) 2023 Amelia Livingston. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Amelia Livingston, Joël Riou
-/
import Mathlib.Algebra.Homology.ShortComplex.ModuleCat
import Mathlib.RepresentationTheory.GroupCohomology.Basic
import Mathlib.RepresentationTheory.Invariants
/-!
# The low-degree cohomology of a `k`-linear `G`-representation
Let `k` be a commutative ring and `G` a group. This file gives simple expressions for
the group cohomology of a `k`-linear `G`-representation `A` in degrees 0, 1 and 2.
In `RepresentationTheory.GroupCohomology.Basic`, we define the `n`th group cohomology of `A` to be
the cohomology of a complex `inhomogeneousCochains A`, whose objects are `(Fin n → G) → A`; this is
unnecessarily unwieldy in low degree. Moreover, cohomology of a complex is defined as an abstract
cokernel, whereas the definitions here are explicit quotients of cocycles by coboundaries.
We also show that when the representation on `A` is trivial, `H¹(G, A) ≃ Hom(G, A)`.
Given an additive or multiplicative abelian group `A` with an appropriate scalar action of `G`,
we provide support for turning a function `f : G → A` satisfying the 1-cocycle identity into an
element of the `oneCocycles` of the representation on `A` (or `Additive A`) corresponding to the
scalar action. We also do this for 1-coboundaries, 2-cocycles and 2-coboundaries. The
multiplicative case, starting with the section `IsMulCocycle`, just mirrors the additive case;
unfortunately `@[to_additive]` can't deal with scalar actions.
The file also contains an identification between the definitions in
`RepresentationTheory.GroupCohomology.Basic`, `groupCohomology.cocycles A n` and
`groupCohomology A n`, and the `nCocycles` and `Hn A` in this file, for `n = 0, 1, 2`.
## Main definitions
* `groupCohomology.H0 A`: the invariants `Aᴳ` of the `G`-representation on `A`.
* `groupCohomology.H1 A`: 1-cocycles (i.e. `Z¹(G, A) := Ker(d¹ : Fun(G, A) → Fun(G², A)`) modulo
1-coboundaries (i.e. `B¹(G, A) := Im(d⁰: A → Fun(G, A))`).
* `groupCohomology.H2 A`: 2-cocycles (i.e. `Z²(G, A) := Ker(d² : Fun(G², A) → Fun(G³, A)`) modulo
2-coboundaries (i.e. `B²(G, A) := Im(d¹: Fun(G, A) → Fun(G², A))`).
* `groupCohomology.H1LequivOfIsTrivial`: the isomorphism `H¹(G, A) ≃ Hom(G, A)` when the
representation on `A` is trivial.
* `groupCohomology.isoHn` for `n = 0, 1, 2`: an isomorphism
`groupCohomology A n ≅ groupCohomology.Hn A`.
## TODO
* The relationship between `H2` and group extensions
* The inflation-restriction exact sequence
* Nonabelian group cohomology
-/
universe v u
noncomputable section
open CategoryTheory Limits Representation
variable {k G : Type u} [CommRing k] [Group G] (A : Rep k G)
namespace groupCohomology
section Cochains
/-- The 0th object in the complex of inhomogeneous cochains of `A : Rep k G` is isomorphic
to `A` as a `k`-module. -/
def zeroCochainsLequiv : (inhomogeneousCochains A).X 0 ≃ₗ[k] A :=
LinearEquiv.funUnique (Fin 0 → G) k A
/-- The 1st object in the complex of inhomogeneous cochains of `A : Rep k G` is isomorphic
to `Fun(G, A)` as a `k`-module. -/
def oneCochainsLequiv : (inhomogeneousCochains A).X 1 ≃ₗ[k] G → A :=
LinearEquiv.funCongrLeft k A (Equiv.funUnique (Fin 1) G).symm
/-- The 2nd object in the complex of inhomogeneous cochains of `A : Rep k G` is isomorphic
to `Fun(G², A)` as a `k`-module. -/
def twoCochainsLequiv : (inhomogeneousCochains A).X 2 ≃ₗ[k] G × G → A :=
LinearEquiv.funCongrLeft k A <| (piFinTwoEquiv fun _ => G).symm
/-- The 3rd object in the complex of inhomogeneous cochains of `A : Rep k G` is isomorphic
to `Fun(G³, A)` as a `k`-module. -/
def threeCochainsLequiv : (inhomogeneousCochains A).X 3 ≃ₗ[k] G × G × G → A :=
LinearEquiv.funCongrLeft k A <| ((Fin.consEquiv _).symm.trans
((Equiv.refl G).prodCongr (piFinTwoEquiv fun _ => G))).symm
end Cochains
section Differentials
/-- The 0th differential in the complex of inhomogeneous cochains of `A : Rep k G`, as a
`k`-linear map `A → Fun(G, A)`. It sends `(a, g) ↦ ρ_A(g)(a) - a.` -/
@[simps]
def dZero : A →ₗ[k] G → A where
toFun m g := A.ρ g m - m
map_add' x y := funext fun g => by simp only [map_add, add_sub_add_comm]; rfl
map_smul' r x := funext fun g => by dsimp; rw [map_smul, smul_sub]
theorem dZero_ker_eq_invariants : LinearMap.ker (dZero A) = invariants A.ρ := by
ext x
simp only [LinearMap.mem_ker, mem_invariants, ← @sub_eq_zero _ _ _ x, funext_iff]
rfl
@[simp] theorem dZero_eq_zero [A.IsTrivial] : dZero A = 0 := by
ext
simp only [dZero_apply, isTrivial_apply, sub_self, LinearMap.zero_apply, Pi.zero_apply]
lemma dZero_comp_subtype : dZero A ∘ₗ A.ρ.invariants.subtype = 0 := by
ext ⟨x, hx⟩ g
replace hx := hx g
rw [← sub_eq_zero] at hx
exact hx
/-- The 1st differential in the complex of inhomogeneous cochains of `A : Rep k G`, as a
`k`-linear map `Fun(G, A) → Fun(G × G, A)`. It sends
`(f, (g₁, g₂)) ↦ ρ_A(g₁)(f(g₂)) - f(g₁g₂) + f(g₁).` -/
@[simps]
def dOne : (G → A) →ₗ[k] G × G → A where
toFun f g := A.ρ g.1 (f g.2) - f (g.1 * g.2) + f g.1
map_add' x y := funext fun g => by dsimp; rw [map_add, add_add_add_comm, add_sub_add_comm]
map_smul' r x := funext fun g => by dsimp; rw [map_smul, smul_add, smul_sub]
/-- The 2nd differential in the complex of inhomogeneous cochains of `A : Rep k G`, as a
`k`-linear map `Fun(G × G, A) → Fun(G × G × G, A)`. It sends
`(f, (g₁, g₂, g₃)) ↦ ρ_A(g₁)(f(g₂, g₃)) - f(g₁g₂, g₃) + f(g₁, g₂g₃) - f(g₁, g₂).` -/
@[simps]
def dTwo : (G × G → A) →ₗ[k] G × G × G → A where
toFun f g :=
A.ρ g.1 (f (g.2.1, g.2.2)) - f (g.1 * g.2.1, g.2.2) + f (g.1, g.2.1 * g.2.2) - f (g.1, g.2.1)
map_add' x y :=
funext fun g => by
dsimp
rw [map_add, add_sub_add_comm (A.ρ _ _), add_sub_assoc, add_sub_add_comm, add_add_add_comm,
add_sub_assoc, add_sub_assoc]
map_smul' r x := funext fun g => by dsimp; simp only [map_smul, smul_add, smul_sub]
/-- Let `C(G, A)` denote the complex of inhomogeneous cochains of `A : Rep k G`. This lemma
says `dZero` gives a simpler expression for the 0th differential: that is, the following
square commutes:
```
C⁰(G, A) ---d⁰---> C¹(G, A)
| |
| |
| |
v v
A ---- dZero ---> Fun(G, A)
```
where the vertical arrows are `zeroCochainsLequiv` and `oneCochainsLequiv` respectively.
-/
theorem dZero_comp_eq : dZero A ∘ₗ (zeroCochainsLequiv A) =
oneCochainsLequiv A ∘ₗ ((inhomogeneousCochains A).d 0 1).hom := by
ext x y
show A.ρ y (x default) - x default = _ + ({0} : Finset _).sum _
simp_rw [Fin.val_eq_zero, zero_add, pow_one, neg_smul, one_smul,
Finset.sum_singleton, sub_eq_add_neg]
rcongr i <;> exact Fin.elim0 i
/-- Let `C(G, A)` denote the complex of inhomogeneous cochains of `A : Rep k G`. This lemma
says `dOne` gives a simpler expression for the 1st differential: that is, the following
square commutes:
```
C¹(G, A) ---d¹-----> C²(G, A)
| |
| |
| |
v v
Fun(G, A) -dOne-> Fun(G × G, A)
```
where the vertical arrows are `oneCochainsLequiv` and `twoCochainsLequiv` respectively.
-/
theorem dOne_comp_eq : dOne A ∘ₗ oneCochainsLequiv A =
twoCochainsLequiv A ∘ₗ ((inhomogeneousCochains A).d 1 2).hom := by
ext x y
show A.ρ y.1 (x _) - x _ + x _ = _ + _
rw [Fin.sum_univ_two]
simp only [Fin.val_zero, zero_add, pow_one, neg_smul, one_smul, Fin.val_one,
Nat.one_add, neg_one_sq, sub_eq_add_neg, add_assoc]
rcongr i <;> rw [Subsingleton.elim i 0] <;> rfl
/-- Let `C(G, A)` denote the complex of inhomogeneous cochains of `A : Rep k G`. This lemma
says `dTwo` gives a simpler expression for the 2nd differential: that is, the following
square commutes:
```
C²(G, A) -------d²-----> C³(G, A)
| |
| |
| |
v v
Fun(G × G, A) --dTwo--> Fun(G × G × G, A)
```
where the vertical arrows are `twoCochainsLequiv` and `threeCochainsLequiv` respectively.
-/
theorem dTwo_comp_eq :
dTwo A ∘ₗ twoCochainsLequiv A =
threeCochainsLequiv A ∘ₗ ((inhomogeneousCochains A).d 2 3).hom := by
ext x y
show A.ρ y.1 (x _) - x _ + x _ - x _ = _ + _
dsimp
rw [Fin.sum_univ_three]
simp only [sub_eq_add_neg, add_assoc, Fin.val_zero, zero_add, pow_one, neg_smul,
one_smul, Fin.val_one, Fin.val_two, pow_succ' (-1 : k) 2, neg_sq, Nat.one_add, one_pow, mul_one]
rcongr i <;> fin_cases i <;> rfl
theorem dOne_comp_dZero : dOne A ∘ₗ dZero A = 0 := by
ext x g
simp only [LinearMap.coe_comp, Function.comp_apply, dOne_apply A, dZero_apply A, map_sub,
map_mul, Module.End.mul_apply, sub_sub_sub_cancel_left, sub_add_sub_cancel, sub_self]
rfl
theorem dTwo_comp_dOne : dTwo A ∘ₗ dOne A = 0 := by
show (ModuleCat.ofHom (dOne A) ≫ ModuleCat.ofHom (dTwo A)).hom = _
have h1 := congr_arg ModuleCat.ofHom (dOne_comp_eq A)
have h2 := congr_arg ModuleCat.ofHom (dTwo_comp_eq A)
simp only [ModuleCat.ofHom_comp, ModuleCat.ofHom_comp, ← LinearEquiv.toModuleIso_hom] at h1 h2
simp only [(Iso.eq_inv_comp _).2 h2, (Iso.eq_inv_comp _).2 h1, ModuleCat.ofHom_hom,
ModuleCat.hom_ofHom, Category.assoc, Iso.hom_inv_id_assoc, HomologicalComplex.d_comp_d_assoc,
zero_comp, comp_zero, ModuleCat.hom_zero]
open ShortComplex
/-- The (exact) short complex `A.ρ.invariants ⟶ A ⟶ (G → A)`. -/
def shortComplexH0 : ShortComplex (ModuleCat k) :=
moduleCatMk _ _ (dZero_comp_subtype A)
/-- The short complex `A --dZero--> Fun(G, A) --dOne--> Fun(G × G, A)`. -/
def shortComplexH1 : ShortComplex (ModuleCat k) :=
moduleCatMk (dZero A) (dOne A) (dOne_comp_dZero A)
/-- The short complex `Fun(G, A) --dOne--> Fun(G × G, A) --dTwo--> Fun(G × G × G, A)`. -/
def shortComplexH2 : ShortComplex (ModuleCat k) :=
moduleCatMk (dOne A) (dTwo A) (dTwo_comp_dOne A)
end Differentials
section Cocycles
/-- The 1-cocycles `Z¹(G, A)` of `A : Rep k G`, defined as the kernel of the map
`Fun(G, A) → Fun(G × G, A)` sending `(f, (g₁, g₂)) ↦ ρ_A(g₁)(f(g₂)) - f(g₁g₂) + f(g₁).` -/
def oneCocycles : Submodule k (G → A) := LinearMap.ker (dOne A)
/-- The 2-cocycles `Z²(G, A)` of `A : Rep k G`, defined as the kernel of the map
`Fun(G × G, A) → Fun(G × G × G, A)` sending
`(f, (g₁, g₂, g₃)) ↦ ρ_A(g₁)(f(g₂, g₃)) - f(g₁g₂, g₃) + f(g₁, g₂g₃) - f(g₁, g₂).` -/
def twoCocycles : Submodule k (G × G → A) := LinearMap.ker (dTwo A)
| variable {A}
instance : FunLike (oneCocycles A) G A := ⟨Subtype.val, Subtype.val_injective⟩
| Mathlib/RepresentationTheory/GroupCohomology/LowDegree.lean | 246 | 248 |
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Kenny Lau, Johan Commelin, Mario Carneiro, Kevin Buzzard,
Amelia Livingston, Yury Kudryashov
-/
import Mathlib.Algebra.Group.Hom.Defs
import Mathlib.Algebra.Group.Submonoid.Defs
import Mathlib.Algebra.Group.Subsemigroup.Basic
import Mathlib.Algebra.Group.Units.Defs
/-!
# Submonoids: `CompleteLattice` structure
This file defines a `CompleteLattice` structure on `Submonoid`s, define the closure of a set as the
minimal submonoid that includes this set, and prove a few results about extending properties from a
dense set (i.e. a set with `closure s = ⊤`) to the whole monoid, see `Submonoid.dense_induction` and
`MonoidHom.ofClosureEqTopLeft`/`MonoidHom.ofClosureEqTopRight`.
## Main definitions
For each of the following definitions in the `Submonoid` namespace, there is a corresponding
definition in the `AddSubmonoid` namespace.
* `Submonoid.copy` : copy of a submonoid with `carrier` replaced by a set that is equal but possibly
not definitionally equal to the carrier of the original `Submonoid`.
* `Submonoid.closure` : monoid closure of a set, i.e., the least submonoid that includes the set.
* `Submonoid.gi` : `closure : Set M → Submonoid M` and coercion `coe : Submonoid M → Set M`
form a `GaloisInsertion`;
* `MonoidHom.eqLocus`: the submonoid of elements `x : M` such that `f x = g x`;
* `MonoidHom.ofClosureEqTopRight`: if a map `f : M → N` between two monoids satisfies
`f 1 = 1` and `f (x * y) = f x * f y` for `y` from some dense set `s`, then `f` is a monoid
homomorphism. E.g., if `f : ℕ → M` satisfies `f 0 = 0` and `f (x + 1) = f x + f 1`, then `f` is
an additive monoid homomorphism.
## Implementation notes
Submonoid inclusion is denoted `≤` rather than `⊆`, although `∈` is defined as
membership of a submonoid's underlying set.
Note that `Submonoid M` does not actually require `Monoid M`, instead requiring only the weaker
`MulOneClass M`.
This file is designed to have very few dependencies. In particular, it should not use natural
numbers. `Submonoid` is implemented by extending `Subsemigroup` requiring `one_mem'`.
## Tags
submonoid, submonoids
-/
assert_not_exists MonoidWithZero
variable {M : Type*} {N : Type*}
variable {A : Type*}
section NonAssoc
variable [MulOneClass M] {s : Set M}
variable [AddZeroClass A] {t : Set A}
namespace Submonoid
variable (S : Submonoid M)
@[to_additive]
instance : InfSet (Submonoid M) :=
⟨fun s =>
{ carrier := ⋂ t ∈ s, ↑t
one_mem' := Set.mem_biInter fun i _ => i.one_mem
mul_mem' := fun hx hy =>
Set.mem_biInter fun i h =>
i.mul_mem (by apply Set.mem_iInter₂.1 hx i h) (by apply Set.mem_iInter₂.1 hy i h) }⟩
@[to_additive (attr := simp, norm_cast)]
theorem coe_sInf (S : Set (Submonoid M)) : ((sInf S : Submonoid M) : Set M) = ⋂ s ∈ S, ↑s :=
rfl
@[to_additive]
theorem mem_sInf {S : Set (Submonoid M)} {x : M} : x ∈ sInf S ↔ ∀ p ∈ S, x ∈ p :=
Set.mem_iInter₂
@[to_additive]
theorem mem_iInf {ι : Sort*} {S : ι → Submonoid M} {x : M} : (x ∈ ⨅ i, S i) ↔ ∀ i, x ∈ S i := by
simp only [iInf, mem_sInf, Set.forall_mem_range]
@[to_additive (attr := simp, norm_cast)]
theorem coe_iInf {ι : Sort*} {S : ι → Submonoid M} : (↑(⨅ i, S i) : Set M) = ⋂ i, S i := by
simp only [iInf, coe_sInf, Set.biInter_range]
/-- Submonoids of a monoid form a complete lattice. -/
@[to_additive "The `AddSubmonoid`s of an `AddMonoid` form a complete lattice."]
instance : CompleteLattice (Submonoid M) :=
{ (completeLatticeOfInf (Submonoid M)) fun _ =>
IsGLB.of_image (f := (SetLike.coe : Submonoid M → Set M))
(@fun S T => show (S : Set M) ≤ T ↔ S ≤ T from SetLike.coe_subset_coe)
isGLB_biInf with
le := (· ≤ ·)
lt := (· < ·)
bot := ⊥
bot_le := fun S _ hx => (mem_bot.1 hx).symm ▸ S.one_mem
top := ⊤
le_top := fun _ x _ => mem_top x
inf := (· ⊓ ·)
sInf := InfSet.sInf
le_inf := fun _ _ _ ha hb _ hx => ⟨ha hx, hb hx⟩
inf_le_left := fun _ _ _ => And.left
inf_le_right := fun _ _ _ => And.right }
/-- The `Submonoid` generated by a set. -/
@[to_additive "The `AddSubmonoid` generated by a set"]
def closure (s : Set M) : Submonoid M :=
sInf { S | s ⊆ S }
@[to_additive]
theorem mem_closure {x : M} : x ∈ closure s ↔ ∀ S : Submonoid M, s ⊆ S → x ∈ S :=
mem_sInf
/-- The submonoid generated by a set includes the set. -/
@[to_additive (attr := simp, aesop safe 20 apply (rule_sets := [SetLike]))
"The `AddSubmonoid` generated by a set includes the set."]
theorem subset_closure : s ⊆ closure s := fun _ hx => mem_closure.2 fun _ hS => hS hx
@[to_additive]
theorem not_mem_of_not_mem_closure {P : M} (hP : P ∉ closure s) : P ∉ s := fun h =>
hP (subset_closure h)
variable {S}
open Set
/-- A submonoid `S` includes `closure s` if and only if it includes `s`. -/
@[to_additive (attr := simp)
"An additive submonoid `S` includes `closure s` if and only if it includes `s`"]
theorem closure_le : closure s ≤ S ↔ s ⊆ S :=
⟨Subset.trans subset_closure, fun h => sInf_le h⟩
/-- Submonoid closure of a set is monotone in its argument: if `s ⊆ t`,
then `closure s ≤ closure t`. -/
@[to_additive (attr := gcongr)
"Additive submonoid closure of a set is monotone in its argument: if `s ⊆ t`,
then `closure s ≤ closure t`"]
theorem closure_mono ⦃s t : Set M⦄ (h : s ⊆ t) : closure s ≤ closure t :=
closure_le.2 <| Subset.trans h subset_closure
@[to_additive]
theorem closure_eq_of_le (h₁ : s ⊆ S) (h₂ : S ≤ closure s) : closure s = S :=
le_antisymm (closure_le.2 h₁) h₂
variable (S)
/-- An induction principle for closure membership. If `p` holds for `1` and all elements of `s`, and
is preserved under multiplication, then `p` holds for all elements of the closure of `s`. -/
@[to_additive (attr := elab_as_elim)
"An induction principle for additive closure membership. If `p` holds for `0` and all
elements of `s`, and is preserved under addition, then `p` holds for all elements of the
additive closure of `s`."]
theorem closure_induction {s : Set M} {motive : (x : M) → x ∈ closure s → Prop}
(mem : ∀ (x) (h : x ∈ s), motive x (subset_closure h)) (one : motive 1 (one_mem _))
(mul : ∀ x y hx hy, motive x hx → motive y hy → motive (x * y) (mul_mem hx hy)) {x}
(hx : x ∈ closure s) : motive x hx :=
let S : Submonoid M :=
{ carrier := { x | ∃ hx, motive x hx }
one_mem' := ⟨_, one⟩
mul_mem' := fun ⟨_, hpx⟩ ⟨_, hpy⟩ ↦ ⟨_, mul _ _ _ _ hpx hpy⟩ }
closure_le (S := S) |>.mpr (fun y hy ↦ ⟨subset_closure hy, mem y hy⟩) hx |>.elim fun _ ↦ id
/-- An induction principle for closure membership for predicates with two arguments. -/
@[to_additive (attr := elab_as_elim)
"An induction principle for additive closure membership for predicates with two arguments."]
theorem closure_induction₂ {motive : (x y : M) → x ∈ closure s → y ∈ closure s → Prop}
(mem : ∀ (x) (y) (hx : x ∈ s) (hy : y ∈ s), motive x y (subset_closure hx) (subset_closure hy))
(one_left : ∀ x hx, motive 1 x (one_mem _) hx) (one_right : ∀ x hx, motive x 1 hx (one_mem _))
(mul_left : ∀ x y z hx hy hz,
motive x z hx hz → motive y z hy hz → motive (x * y) z (mul_mem hx hy) hz)
(mul_right : ∀ x y z hx hy hz,
motive z x hz hx → motive z y hz hy → motive z (x * y) hz (mul_mem hx hy))
{x y : M} (hx : x ∈ closure s) (hy : y ∈ closure s) : motive x y hx hy := by
induction hy using closure_induction with
| mem z hz => induction hx using closure_induction with
| mem _ h => exact mem _ _ h hz
| one => exact one_left _ (subset_closure hz)
| mul _ _ _ _ h₁ h₂ => exact mul_left _ _ _ _ _ _ h₁ h₂
| one => exact one_right x hx
| mul _ _ _ _ h₁ h₂ => exact mul_right _ _ _ _ _ hx h₁ h₂
/-- If `s` is a dense set in a monoid `M`, `Submonoid.closure s = ⊤`, then in order to prove that
some predicate `p` holds for all `x : M` it suffices to verify `p x` for `x ∈ s`, verify `p 1`,
and verify that `p x` and `p y` imply `p (x * y)`. -/
@[to_additive (attr := elab_as_elim)
"If `s` is a dense set in an additive monoid `M`, `AddSubmonoid.closure s = ⊤`, then in
order to prove that some predicate `p` holds for all `x : M` it suffices to verify `p x` for
`x ∈ s`, verify `p 0`, and verify that `p x` and `p y` imply `p (x + y)`."]
theorem dense_induction {motive : M → Prop} (s : Set M) (closure : closure s = ⊤)
(mem : ∀ x ∈ s, motive x) (one : motive 1) (mul : ∀ x y, motive x → motive y → motive (x * y))
(x : M) : motive x := by
induction closure.symm ▸ mem_top x using closure_induction with
| mem _ h => exact mem _ h
| one => exact one
| mul _ _ _ _ h₁ h₂ => exact mul _ _ h₁ h₂
/- The argument `s : Set M` is explicit in `Submonoid.dense_induction` because the type of the
induction variable, namely `x : M`, does not reference `x`. Making `s` explicit allows the user
to apply the induction principle while deferring the proof of `closure s = ⊤` without creating
metavariables, as in the following example. -/
example {p : M → Prop} (s : Set M) (closure : closure s = ⊤) (mem : ∀ x ∈ s, p x)
(one : p 1) (mul : ∀ x y, p x → p y → p (x * y)) (x : M) : p x := by
induction x using dense_induction s with
| closure => exact closure
| mem x hx => exact mem x hx
| one => exact one
| mul _ _ h₁ h₂ => exact mul _ _ h₁ h₂
/-- The `Submonoid.closure` of a set is the union of `{1}` and its `Subsemigroup.closure`. -/
lemma closure_eq_one_union (s : Set M) :
closure s = {(1 : M)} ∪ (Subsemigroup.closure s : Set M) := by
apply le_antisymm
· intro x hx
induction hx using closure_induction with
| mem x hx => exact Or.inr <| Subsemigroup.subset_closure hx
| one => exact Or.inl <| by simp
| mul x hx y hy hx hy =>
simp only [singleton_union, mem_insert_iff, SetLike.mem_coe] at hx hy
obtain ⟨(rfl | hx), (rfl | hy)⟩ := And.intro hx hy
all_goals simp_all
exact Or.inr <| mul_mem hx hy
· rintro x (hx | hx)
· exact (show x = 1 by simpa using hx) ▸ one_mem (closure s)
· exact Subsemigroup.closure_le.mpr subset_closure hx
variable (M)
/-- `closure` forms a Galois insertion with the coercion to set. -/
@[to_additive "`closure` forms a Galois insertion with the coercion to set."]
protected def gi : GaloisInsertion (@closure M _) SetLike.coe where
choice s _ := closure s
gc _ _ := closure_le
le_l_u _ := subset_closure
choice_eq _ _ := rfl
variable {M}
/-- Closure of a submonoid `S` equals `S`. -/
@[to_additive (attr := simp) "Additive closure of an additive submonoid `S` equals `S`"]
theorem closure_eq : closure (S : Set M) = S :=
(Submonoid.gi M).l_u_eq S
@[to_additive (attr := simp)]
theorem closure_empty : closure (∅ : Set M) = ⊥ :=
(Submonoid.gi M).gc.l_bot
@[to_additive (attr := simp)]
theorem closure_univ : closure (univ : Set M) = ⊤ :=
@coe_top M _ ▸ closure_eq ⊤
@[to_additive]
theorem closure_union (s t : Set M) : closure (s ∪ t) = closure s ⊔ closure t :=
(Submonoid.gi M).gc.l_sup
@[to_additive]
theorem sup_eq_closure (N N' : Submonoid M) : N ⊔ N' = closure ((N : Set M) ∪ (N' : Set M)) := by
simp_rw [closure_union, closure_eq]
@[to_additive]
theorem closure_iUnion {ι} (s : ι → Set M) : closure (⋃ i, s i) = ⨆ i, closure (s i) :=
(Submonoid.gi M).gc.l_iSup
@[to_additive]
theorem closure_singleton_le_iff_mem (m : M) (p : Submonoid M) : closure {m} ≤ p ↔ m ∈ p := by
rw [closure_le, singleton_subset_iff, SetLike.mem_coe]
@[to_additive (attr := simp)]
theorem closure_insert_one (s : Set M) : closure (insert 1 s) = closure s := by
rw [insert_eq, closure_union, sup_eq_right, closure_singleton_le_iff_mem]
apply one_mem
@[to_additive]
theorem mem_iSup {ι : Sort*} (p : ι → Submonoid M) {m : M} :
(m ∈ ⨆ i, p i) ↔ ∀ N, (∀ i, p i ≤ N) → m ∈ N := by
rw [← closure_singleton_le_iff_mem, le_iSup_iff]
simp only [closure_singleton_le_iff_mem]
@[to_additive]
theorem iSup_eq_closure {ι : Sort*} (p : ι → Submonoid M) :
⨆ i, p i = Submonoid.closure (⋃ i, (p i : Set M)) := by
simp_rw [Submonoid.closure_iUnion, Submonoid.closure_eq]
@[to_additive]
theorem disjoint_def {p₁ p₂ : Submonoid M} :
Disjoint p₁ p₂ ↔ ∀ {x : M}, x ∈ p₁ → x ∈ p₂ → x = 1 := by
simp_rw [disjoint_iff_inf_le, SetLike.le_def, mem_inf, and_imp, mem_bot]
@[to_additive]
theorem disjoint_def' {p₁ p₂ : Submonoid M} :
Disjoint p₁ p₂ ↔ ∀ {x y : M}, x ∈ p₁ → y ∈ p₂ → x = y → x = 1 :=
disjoint_def.trans ⟨fun h _ _ hx hy hxy => h hx <| hxy.symm ▸ hy, fun h _ hx hx' => h hx hx' rfl⟩
variable {t : Set M}
@[to_additive (attr := simp)]
lemma closure_sdiff_eq_closure (hts : t ⊆ closure (s \ t)) : closure (s \ t) = closure s := by
refine (closure_mono Set.diff_subset).antisymm <| closure_le.mpr <| fun x hxs ↦ ?_
by_cases hxt : x ∈ t
· exact hts hxt
· rw [SetLike.mem_coe, Submonoid.mem_closure]
exact fun N hN ↦ hN <| Set.mem_diff_of_mem hxs hxt
@[to_additive (attr := simp)]
lemma closure_sdiff_singleton_one (s : Set M) : closure (s \ {1}) = closure s :=
closure_sdiff_eq_closure <| by simp [one_mem]
end Submonoid
namespace MonoidHom
variable [MulOneClass N]
open Submonoid
/-- If two monoid homomorphisms are equal on a set, then they are equal on its submonoid closure. -/
@[to_additive
"If two monoid homomorphisms are equal on a set, then they are equal on its submonoid
closure."]
theorem eqOn_closureM {f g : M →* N} {s : Set M} (h : Set.EqOn f g s) : Set.EqOn f g (closure s) :=
show closure s ≤ f.eqLocusM g from closure_le.2 h
@[to_additive]
theorem eq_of_eqOn_denseM {s : Set M} (hs : closure s = ⊤) {f g : M →* N} (h : s.EqOn f g) :
f = g :=
eq_of_eqOn_topM <| hs ▸ eqOn_closureM h
end MonoidHom
end NonAssoc
section Assoc
variable [Monoid M] [Monoid N] {s : Set M}
section IsUnit
/-- The submonoid consisting of the units of a monoid -/
@[to_additive "The additive submonoid consisting of the additive units of an additive monoid"]
def IsUnit.submonoid (M : Type*) [Monoid M] : Submonoid M where
carrier := setOf IsUnit
one_mem' := by simp only [isUnit_one, Set.mem_setOf_eq]
mul_mem' := by
intro a b ha hb
rw [Set.mem_setOf_eq] at *
exact IsUnit.mul ha hb
@[to_additive]
theorem IsUnit.mem_submonoid_iff {M : Type*} [Monoid M] (a : M) :
a ∈ IsUnit.submonoid M ↔ IsUnit a := by
change a ∈ setOf IsUnit ↔ IsUnit a
rw [Set.mem_setOf_eq]
end IsUnit
namespace MonoidHom
open Submonoid
/-- Let `s` be a subset of a monoid `M` such that the closure of `s` is the whole monoid.
Then `MonoidHom.ofClosureEqTopLeft` defines a monoid homomorphism from `M` asking for
a proof of `f (x * y) = f x * f y` only for `x ∈ s`. -/
@[to_additive
"Let `s` be a subset of an additive monoid `M` such that the closure of `s` is
the whole monoid. Then `AddMonoidHom.ofClosureEqTopLeft` defines an additive monoid
homomorphism from `M` asking for a proof of `f (x + y) = f x + f y` only for `x ∈ s`. "]
def ofClosureMEqTopLeft {M N} [Monoid M] [Monoid N] {s : Set M} (f : M → N) (hs : closure s = ⊤)
(h1 : f 1 = 1) (hmul : ∀ x ∈ s, ∀ (y), f (x * y) = f x * f y) :
M →* N where
toFun := f
map_one' := h1
map_mul' x :=
dense_induction (motive := _) _ hs hmul fun y => by rw [one_mul, h1, one_mul]
(fun a b ha hb y => by rw [mul_assoc, ha, ha, hb, mul_assoc]) x
@[to_additive (attr := simp, norm_cast)]
theorem coe_ofClosureMEqTopLeft (f : M → N) (hs : closure s = ⊤) (h1 hmul) :
⇑(ofClosureMEqTopLeft f hs h1 hmul) = f :=
rfl
/-- Let `s` be a subset of a monoid `M` such that the closure of `s` is the whole monoid.
Then `MonoidHom.ofClosureEqTopRight` defines a monoid homomorphism from `M` asking for
a proof of `f (x * y) = f x * f y` only for `y ∈ s`. -/
@[to_additive
"Let `s` be a subset of an additive monoid `M` such that the closure of `s` is
the whole monoid. Then `AddMonoidHom.ofClosureEqTopRight` defines an additive monoid
homomorphism from `M` asking for a proof of `f (x + y) = f x + f y` only for `y ∈ s`. "]
def ofClosureMEqTopRight {M N} [Monoid M] [Monoid N] {s : Set M} (f : M → N) (hs : closure s = ⊤)
(h1 : f 1 = 1) (hmul : ∀ (x), ∀ y ∈ s, f (x * y) = f x * f y) :
M →* N where
toFun := f
map_one' := h1
map_mul' x y :=
dense_induction _ hs (fun y hy x => hmul x y hy) (by simp [h1])
(fun y₁ y₂ (h₁ : ∀ _, f _ = f _ * f _) (h₂ : ∀ _, f _ = f _ * f _) x => by
simp [← mul_assoc, h₁, h₂]) y x
@[to_additive (attr := simp, norm_cast)]
theorem coe_ofClosureMEqTopRight (f : M → N) (hs : closure s = ⊤) (h1 hmul) :
⇑(ofClosureMEqTopRight f hs h1 hmul) = f :=
rfl
end MonoidHom
end Assoc
| Mathlib/Algebra/Group/Submonoid/Basic.lean | 561 | 562 | |
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Data.Set.Piecewise
import Mathlib.Logic.Equiv.Defs
import Mathlib.Tactic.Core
import Mathlib.Tactic.Attr.Core
/-!
# Partial equivalences
This files defines equivalences between subsets of given types.
An element `e` of `PartialEquiv α β` is made of two maps `e.toFun` and `e.invFun` respectively
from α to β and from β to α (just like equivs), which are inverse to each other on the subsets
`e.source` and `e.target` of respectively α and β.
They are designed in particular to define charts on manifolds.
The main functionality is `e.trans f`, which composes the two partial equivalences by restricting
the source and target to the maximal set where the composition makes sense.
As for equivs, we register a coercion to functions and use it in our simp normal form: we write
`e x` and `e.symm y` instead of `e.toFun x` and `e.invFun y`.
## Main definitions
* `Equiv.toPartialEquiv`: associating a partial equiv to an equiv, with source = target = univ
* `PartialEquiv.symm`: the inverse of a partial equivalence
* `PartialEquiv.trans`: the composition of two partial equivalences
* `PartialEquiv.refl`: the identity partial equivalence
* `PartialEquiv.ofSet`: the identity on a set `s`
* `EqOnSource`: equivalence relation describing the "right" notion of equality for partial
equivalences (see below in implementation notes)
## Implementation notes
There are at least three possible implementations of partial equivalences:
* equivs on subtypes
* pairs of functions taking values in `Option α` and `Option β`, equal to none where the partial
equivalence is not defined
* pairs of functions defined everywhere, keeping the source and target as additional data
Each of these implementations has pros and cons.
* When dealing with subtypes, one still need to define additional API for composition and
restriction of domains. Checking that one always belongs to the right subtype makes things very
tedious, and leads quickly to DTT hell (as the subtype `u ∩ v` is not the "same" as `v ∩ u`, for
instance).
* With option-valued functions, the composition is very neat (it is just the usual composition, and
the domain is restricted automatically). These are implemented in `PEquiv.lean`. For manifolds,
where one wants to discuss thoroughly the smoothness of the maps, this creates however a lot of
overhead as one would need to extend all classes of smoothness to option-valued maps.
* The `PartialEquiv` version as explained above is easier to use for manifolds. The drawback is that
there is extra useless data (the values of `toFun` and `invFun` outside of `source` and `target`).
In particular, the equality notion between partial equivs is not "the right one", i.e., coinciding
source and target and equality there. Moreover, there are no partial equivs in this sense between
an empty type and a nonempty type. Since empty types are not that useful, and since one almost never
needs to talk about equal partial equivs, this is not an issue in practice.
Still, we introduce an equivalence relation `EqOnSource` that captures this right notion of
equality, and show that many properties are invariant under this equivalence relation.
### Local coding conventions
If a lemma deals with the intersection of a set with either source or target of a `PartialEquiv`,
then it should use `e.source ∩ s` or `e.target ∩ t`, not `s ∩ e.source` or `t ∩ e.target`.
-/
open Lean Meta Elab Tactic
/-! Implementation of the `mfld_set_tac` tactic for working with the domains of partially-defined
functions (`PartialEquiv`, `PartialHomeomorph`, etc).
This is in a separate file from `Mathlib.Logic.Equiv.MfldSimpsAttr` because attributes need a new
file to become functional.
-/
/-- Common `@[simps]` configuration options used for manifold-related declarations. -/
def mfld_cfg : Simps.Config where
attrs := [`mfld_simps]
fullyApplied := false
namespace Tactic.MfldSetTac
/-- A very basic tactic to show that sets showing up in manifolds coincide or are included
in one another. -/
elab (name := mfldSetTac) "mfld_set_tac" : tactic => withMainContext do
let g ← getMainGoal
let goalTy := (← instantiateMVars (← g.getDecl).type).getAppFnArgs
match goalTy with
| (``Eq, #[_ty, _e₁, _e₂]) =>
evalTactic (← `(tactic| (
apply Set.ext; intro my_y
constructor <;>
· intro h_my_y
try simp only [*, mfld_simps] at h_my_y
try simp only [*, mfld_simps])))
| (``Subset, #[_ty, _inst, _e₁, _e₂]) =>
evalTactic (← `(tactic| (
intro my_y h_my_y
try simp only [*, mfld_simps] at h_my_y
try simp only [*, mfld_simps])))
| _ => throwError "goal should be an equality or an inclusion"
attribute [mfld_simps] and_true eq_self_iff_true Function.comp_apply
end Tactic.MfldSetTac
open Function Set
variable {α : Type*} {β : Type*} {γ : Type*} {δ : Type*}
/-- Local equivalence between subsets `source` and `target` of `α` and `β` respectively. The
(global) maps `toFun : α → β` and `invFun : β → α` map `source` to `target` and conversely, and are
inverse to each other there. The values of `toFun` outside of `source` and of `invFun` outside of
`target` are irrelevant. -/
structure PartialEquiv (α : Type*) (β : Type*) where
/-- The global function which has a partial inverse. Its value outside of the `source` subset is
irrelevant. -/
toFun : α → β
/-- The partial inverse to `toFun`. Its value outside of the `target` subset is irrelevant. -/
invFun : β → α
/-- The domain of the partial equivalence. -/
source : Set α
/-- The codomain of the partial equivalence. -/
target : Set β
/-- The proposition that elements of `source` are mapped to elements of `target`. -/
map_source' : ∀ ⦃x⦄, x ∈ source → toFun x ∈ target
/-- The proposition that elements of `target` are mapped to elements of `source`. -/
map_target' : ∀ ⦃x⦄, x ∈ target → invFun x ∈ source
/-- The proposition that `invFun` is a left-inverse of `toFun` on `source`. -/
left_inv' : ∀ ⦃x⦄, x ∈ source → invFun (toFun x) = x
/-- The proposition that `invFun` is a right-inverse of `toFun` on `target`. -/
right_inv' : ∀ ⦃x⦄, x ∈ target → toFun (invFun x) = x
attribute [coe] PartialEquiv.toFun
namespace PartialEquiv
variable (e : PartialEquiv α β) (e' : PartialEquiv β γ)
instance [Inhabited α] [Inhabited β] : Inhabited (PartialEquiv α β) :=
⟨⟨const α default, const β default, ∅, ∅, mapsTo_empty _ _, mapsTo_empty _ _, eqOn_empty _ _,
eqOn_empty _ _⟩⟩
/-- The inverse of a partial equivalence -/
@[symm]
protected def symm : PartialEquiv β α where
toFun := e.invFun
invFun := e.toFun
source := e.target
target := e.source
map_source' := e.map_target'
map_target' := e.map_source'
left_inv' := e.right_inv'
right_inv' := e.left_inv'
instance : CoeFun (PartialEquiv α β) fun _ => α → β :=
⟨PartialEquiv.toFun⟩
/-- See Note [custom simps projection] -/
def Simps.symm_apply (e : PartialEquiv α β) : β → α :=
e.symm
initialize_simps_projections PartialEquiv (toFun → apply, invFun → symm_apply)
theorem coe_mk (f : α → β) (g s t ml mr il ir) :
(PartialEquiv.mk f g s t ml mr il ir : α → β) = f := rfl
@[simp, mfld_simps]
theorem coe_symm_mk (f : α → β) (g s t ml mr il ir) :
((PartialEquiv.mk f g s t ml mr il ir).symm : β → α) = g :=
rfl
@[simp, mfld_simps]
theorem invFun_as_coe : e.invFun = e.symm :=
rfl
@[simp, mfld_simps]
theorem map_source {x : α} (h : x ∈ e.source) : e x ∈ e.target :=
e.map_source' h
/-- Variant of `e.map_source` and `map_source'`, stated for images of subsets of `source`. -/
lemma map_source'' : e '' e.source ⊆ e.target :=
fun _ ⟨_, hx, hex⟩ ↦ mem_of_eq_of_mem (id hex.symm) (e.map_source' hx)
@[simp, mfld_simps]
theorem map_target {x : β} (h : x ∈ e.target) : e.symm x ∈ e.source :=
e.map_target' h
@[simp, mfld_simps]
theorem left_inv {x : α} (h : x ∈ e.source) : e.symm (e x) = x :=
e.left_inv' h
@[simp, mfld_simps]
theorem right_inv {x : β} (h : x ∈ e.target) : e (e.symm x) = x :=
e.right_inv' h
theorem eq_symm_apply {x : α} {y : β} (hx : x ∈ e.source) (hy : y ∈ e.target) :
x = e.symm y ↔ e x = y :=
⟨fun h => by rw [← e.right_inv hy, h], fun h => by rw [← e.left_inv hx, h]⟩
protected theorem mapsTo : MapsTo e e.source e.target := fun _ => e.map_source
theorem symm_mapsTo : MapsTo e.symm e.target e.source :=
e.symm.mapsTo
protected theorem leftInvOn : LeftInvOn e.symm e e.source := fun _ => e.left_inv
protected theorem rightInvOn : RightInvOn e.symm e e.target := fun _ => e.right_inv
protected theorem invOn : InvOn e.symm e e.source e.target :=
⟨e.leftInvOn, e.rightInvOn⟩
protected theorem injOn : InjOn e e.source :=
e.leftInvOn.injOn
protected theorem bijOn : BijOn e e.source e.target :=
e.invOn.bijOn e.mapsTo e.symm_mapsTo
protected theorem surjOn : SurjOn e e.source e.target :=
e.bijOn.surjOn
/-- Interpret an `Equiv` as a `PartialEquiv` by restricting it to `s` in the domain
and to `t` in the codomain. -/
@[simps -fullyApplied]
def _root_.Equiv.toPartialEquivOfImageEq (e : α ≃ β) (s : Set α) (t : Set β) (h : e '' s = t) :
PartialEquiv α β where
toFun := e
invFun := e.symm
source := s
target := t
map_source' _ hx := h ▸ mem_image_of_mem _ hx
map_target' x hx := by
subst t
rcases hx with ⟨x, hx, rfl⟩
rwa [e.symm_apply_apply]
left_inv' x _ := e.symm_apply_apply x
right_inv' x _ := e.apply_symm_apply x
/-- Associate a `PartialEquiv` to an `Equiv`. -/
@[simps! (config := mfld_cfg)]
def _root_.Equiv.toPartialEquiv (e : α ≃ β) : PartialEquiv α β :=
e.toPartialEquivOfImageEq univ univ <| by rw [image_univ, e.surjective.range_eq]
instance inhabitedOfEmpty [IsEmpty α] [IsEmpty β] : Inhabited (PartialEquiv α β) :=
⟨((Equiv.equivEmpty α).trans (Equiv.equivEmpty β).symm).toPartialEquiv⟩
/-- Create a copy of a `PartialEquiv` providing better definitional equalities. -/
@[simps -fullyApplied]
def copy (e : PartialEquiv α β) (f : α → β) (hf : ⇑e = f) (g : β → α) (hg : ⇑e.symm = g) (s : Set α)
(hs : e.source = s) (t : Set β) (ht : e.target = t) :
PartialEquiv α β where
toFun := f
invFun := g
source := s
target := t
map_source' _ := ht ▸ hs ▸ hf ▸ e.map_source
map_target' _ := hs ▸ ht ▸ hg ▸ e.map_target
left_inv' _ := hs ▸ hf ▸ hg ▸ e.left_inv
right_inv' _ := ht ▸ hf ▸ hg ▸ e.right_inv
theorem copy_eq (e : PartialEquiv α β) (f : α → β) (hf : ⇑e = f) (g : β → α) (hg : ⇑e.symm = g)
(s : Set α) (hs : e.source = s) (t : Set β) (ht : e.target = t) :
e.copy f hf g hg s hs t ht = e := by
substs f g s t
cases e
rfl
/-- Associate to a `PartialEquiv` an `Equiv` between the source and the target. -/
protected def toEquiv : e.source ≃ e.target where
toFun x := ⟨e x, e.map_source x.mem⟩
invFun y := ⟨e.symm y, e.map_target y.mem⟩
left_inv := fun ⟨_, hx⟩ => Subtype.eq <| e.left_inv hx
right_inv := fun ⟨_, hy⟩ => Subtype.eq <| e.right_inv hy
@[simp, mfld_simps]
theorem symm_source : e.symm.source = e.target :=
rfl
@[simp, mfld_simps]
theorem symm_target : e.symm.target = e.source :=
rfl
@[simp, mfld_simps]
theorem symm_symm : e.symm.symm = e := rfl
theorem symm_bijective :
Function.Bijective (PartialEquiv.symm : PartialEquiv α β → PartialEquiv β α) :=
Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩
theorem image_source_eq_target : e '' e.source = e.target :=
e.bijOn.image_eq
theorem forall_mem_target {p : β → Prop} : (∀ y ∈ e.target, p y) ↔ ∀ x ∈ e.source, p (e x) := by
rw [← image_source_eq_target, forall_mem_image]
theorem exists_mem_target {p : β → Prop} : (∃ y ∈ e.target, p y) ↔ ∃ x ∈ e.source, p (e x) := by
rw [← image_source_eq_target, exists_mem_image]
/-- We say that `t : Set β` is an image of `s : Set α` under a partial equivalence if
any of the following equivalent conditions hold:
* `e '' (e.source ∩ s) = e.target ∩ t`;
* `e.source ∩ e ⁻¹ t = e.source ∩ s`;
* `∀ x ∈ e.source, e x ∈ t ↔ x ∈ s` (this one is used in the definition).
-/
def IsImage (s : Set α) (t : Set β) : Prop :=
∀ ⦃x⦄, x ∈ e.source → (e x ∈ t ↔ x ∈ s)
namespace IsImage
variable {e} {s : Set α} {t : Set β} {x : α}
theorem apply_mem_iff (h : e.IsImage s t) (hx : x ∈ e.source) : e x ∈ t ↔ x ∈ s :=
h hx
theorem symm_apply_mem_iff (h : e.IsImage s t) : ∀ ⦃y⦄, y ∈ e.target → (e.symm y ∈ s ↔ y ∈ t) :=
e.forall_mem_target.mpr fun x hx => by rw [e.left_inv hx, h hx]
protected theorem symm (h : e.IsImage s t) : e.symm.IsImage t s :=
h.symm_apply_mem_iff
@[simp]
theorem symm_iff : e.symm.IsImage t s ↔ e.IsImage s t :=
⟨fun h => h.symm, fun h => h.symm⟩
protected theorem mapsTo (h : e.IsImage s t) : MapsTo e (e.source ∩ s) (e.target ∩ t) :=
fun _ hx => ⟨e.mapsTo hx.1, (h hx.1).2 hx.2⟩
theorem symm_mapsTo (h : e.IsImage s t) : MapsTo e.symm (e.target ∩ t) (e.source ∩ s) :=
h.symm.mapsTo
/-- Restrict a `PartialEquiv` to a pair of corresponding sets. -/
@[simps -fullyApplied]
def restr (h : e.IsImage s t) : PartialEquiv α β where
toFun := e
invFun := e.symm
source := e.source ∩ s
target := e.target ∩ t
map_source' := h.mapsTo
map_target' := h.symm_mapsTo
left_inv' := e.leftInvOn.mono inter_subset_left
right_inv' := e.rightInvOn.mono inter_subset_left
theorem image_eq (h : e.IsImage s t) : e '' (e.source ∩ s) = e.target ∩ t :=
h.restr.image_source_eq_target
theorem symm_image_eq (h : e.IsImage s t) : e.symm '' (e.target ∩ t) = e.source ∩ s :=
h.symm.image_eq
theorem iff_preimage_eq : e.IsImage s t ↔ e.source ∩ e ⁻¹' t = e.source ∩ s := by
simp only [IsImage, Set.ext_iff, mem_inter_iff, mem_preimage, and_congr_right_iff]
alias ⟨preimage_eq, of_preimage_eq⟩ := iff_preimage_eq
theorem iff_symm_preimage_eq : e.IsImage s t ↔ e.target ∩ e.symm ⁻¹' s = e.target ∩ t :=
symm_iff.symm.trans iff_preimage_eq
alias ⟨symm_preimage_eq, of_symm_preimage_eq⟩ := iff_symm_preimage_eq
theorem of_image_eq (h : e '' (e.source ∩ s) = e.target ∩ t) : e.IsImage s t :=
of_symm_preimage_eq <| Eq.trans (of_symm_preimage_eq rfl).image_eq.symm h
theorem of_symm_image_eq (h : e.symm '' (e.target ∩ t) = e.source ∩ s) : e.IsImage s t :=
of_preimage_eq <| Eq.trans (iff_preimage_eq.2 rfl).symm_image_eq.symm h
protected theorem compl (h : e.IsImage s t) : e.IsImage sᶜ tᶜ := fun _ hx => not_congr (h hx)
protected theorem inter {s' t'} (h : e.IsImage s t) (h' : e.IsImage s' t') :
e.IsImage (s ∩ s') (t ∩ t') := fun _ hx => and_congr (h hx) (h' hx)
protected theorem union {s' t'} (h : e.IsImage s t) (h' : e.IsImage s' t') :
e.IsImage (s ∪ s') (t ∪ t') := fun _ hx => or_congr (h hx) (h' hx)
protected theorem diff {s' t'} (h : e.IsImage s t) (h' : e.IsImage s' t') :
e.IsImage (s \ s') (t \ t') :=
h.inter h'.compl
theorem leftInvOn_piecewise {e' : PartialEquiv α β} [∀ i, Decidable (i ∈ s)]
[∀ i, Decidable (i ∈ t)] (h : e.IsImage s t) (h' : e'.IsImage s t) :
LeftInvOn (t.piecewise e.symm e'.symm) (s.piecewise e e') (s.ite e.source e'.source) := by
rintro x (⟨he, hs⟩ | ⟨he, hs : x ∉ s⟩)
· rw [piecewise_eq_of_mem _ _ _ hs, piecewise_eq_of_mem _ _ _ ((h he).2 hs), e.left_inv he]
· rw [piecewise_eq_of_not_mem _ _ _ hs, piecewise_eq_of_not_mem _ _ _ ((h'.compl he).2 hs),
e'.left_inv he]
theorem inter_eq_of_inter_eq_of_eqOn {e' : PartialEquiv α β} (h : e.IsImage s t)
(h' : e'.IsImage s t) (hs : e.source ∩ s = e'.source ∩ s) (heq : EqOn e e' (e.source ∩ s)) :
e.target ∩ t = e'.target ∩ t := by rw [← h.image_eq, ← h'.image_eq, ← hs, heq.image_eq]
theorem symm_eq_on_of_inter_eq_of_eqOn {e' : PartialEquiv α β} (h : e.IsImage s t)
(hs : e.source ∩ s = e'.source ∩ s) (heq : EqOn e e' (e.source ∩ s)) :
EqOn e.symm e'.symm (e.target ∩ t) := by
rw [← h.image_eq]
rintro y ⟨x, hx, rfl⟩
have hx' := hx; rw [hs] at hx'
rw [e.left_inv hx.1, heq hx, e'.left_inv hx'.1]
end IsImage
theorem isImage_source_target : e.IsImage e.source e.target := fun x hx => by simp [hx]
theorem isImage_source_target_of_disjoint (e' : PartialEquiv α β) (hs : Disjoint e.source e'.source)
(ht : Disjoint e.target e'.target) : e.IsImage e'.source e'.target :=
IsImage.of_image_eq <| by rw [hs.inter_eq, ht.inter_eq, image_empty]
theorem image_source_inter_eq' (s : Set α) : e '' (e.source ∩ s) = e.target ∩ e.symm ⁻¹' s := by
rw [inter_comm, e.leftInvOn.image_inter', image_source_eq_target, inter_comm]
theorem image_source_inter_eq (s : Set α) :
e '' (e.source ∩ s) = e.target ∩ e.symm ⁻¹' (e.source ∩ s) := by
rw [inter_comm, e.leftInvOn.image_inter, image_source_eq_target, inter_comm]
theorem image_eq_target_inter_inv_preimage {s : Set α} (h : s ⊆ e.source) :
e '' s = e.target ∩ e.symm ⁻¹' s := by
rw [← e.image_source_inter_eq', inter_eq_self_of_subset_right h]
theorem symm_image_eq_source_inter_preimage {s : Set β} (h : s ⊆ e.target) :
e.symm '' s = e.source ∩ e ⁻¹' s :=
e.symm.image_eq_target_inter_inv_preimage h
theorem symm_image_target_inter_eq (s : Set β) :
e.symm '' (e.target ∩ s) = e.source ∩ e ⁻¹' (e.target ∩ s) :=
e.symm.image_source_inter_eq _
theorem symm_image_target_inter_eq' (s : Set β) : e.symm '' (e.target ∩ s) = e.source ∩ e ⁻¹' s :=
e.symm.image_source_inter_eq' _
theorem source_inter_preimage_inv_preimage (s : Set α) :
e.source ∩ e ⁻¹' (e.symm ⁻¹' s) = e.source ∩ s :=
Set.ext fun x => and_congr_right_iff.2 fun hx =>
by simp only [mem_preimage, e.left_inv hx]
theorem source_inter_preimage_target_inter (s : Set β) :
e.source ∩ e ⁻¹' (e.target ∩ s) = e.source ∩ e ⁻¹' s :=
ext fun _ => ⟨fun hx => ⟨hx.1, hx.2.2⟩, fun hx => ⟨hx.1, e.map_source hx.1, hx.2⟩⟩
theorem target_inter_inv_preimage_preimage (s : Set β) :
e.target ∩ e.symm ⁻¹' (e ⁻¹' s) = e.target ∩ s :=
e.symm.source_inter_preimage_inv_preimage _
theorem symm_image_image_of_subset_source {s : Set α} (h : s ⊆ e.source) : e.symm '' (e '' s) = s :=
(e.leftInvOn.mono h).image_image
theorem image_symm_image_of_subset_target {s : Set β} (h : s ⊆ e.target) : e '' (e.symm '' s) = s :=
e.symm.symm_image_image_of_subset_source h
theorem source_subset_preimage_target : e.source ⊆ e ⁻¹' e.target :=
e.mapsTo
theorem symm_image_target_eq_source : e.symm '' e.target = e.source :=
e.symm.image_source_eq_target
theorem target_subset_preimage_source : e.target ⊆ e.symm ⁻¹' e.source :=
e.symm_mapsTo
/-- Two partial equivs that have the same `source`, same `toFun` and same `invFun`, coincide. -/
@[ext]
protected theorem ext {e e' : PartialEquiv α β} (h : ∀ x, e x = e' x)
(hsymm : ∀ x, e.symm x = e'.symm x) (hs : e.source = e'.source) : e = e' := by
have A : (e : α → β) = e' := by
ext x
exact h x
have B : (e.symm : β → α) = e'.symm := by
ext x
exact hsymm x
have I : e '' e.source = e.target := e.image_source_eq_target
have I' : e' '' e'.source = e'.target := e'.image_source_eq_target
rw [A, hs, I'] at I
cases e; cases e'
simp_all
/-- Restricting a partial equivalence to `e.source ∩ s` -/
protected def restr (s : Set α) : PartialEquiv α β :=
(@IsImage.of_symm_preimage_eq α β e s (e.symm ⁻¹' s) rfl).restr
@[simp, mfld_simps]
theorem restr_coe (s : Set α) : (e.restr s : α → β) = e :=
rfl
@[simp, mfld_simps]
theorem restr_coe_symm (s : Set α) : ((e.restr s).symm : β → α) = e.symm :=
rfl
@[simp, mfld_simps]
theorem restr_source (s : Set α) : (e.restr s).source = e.source ∩ s :=
rfl
theorem source_restr_subset_source (s : Set α) : (e.restr s).source ⊆ e.source := inter_subset_left
@[simp, mfld_simps]
theorem restr_target (s : Set α) : (e.restr s).target = e.target ∩ e.symm ⁻¹' s :=
rfl
theorem restr_eq_of_source_subset {e : PartialEquiv α β} {s : Set α} (h : e.source ⊆ s) :
e.restr s = e :=
PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) (by simp [inter_eq_self_of_subset_left h])
@[simp, mfld_simps]
theorem restr_univ {e : PartialEquiv α β} : e.restr univ = e :=
restr_eq_of_source_subset (subset_univ _)
/-- The identity partial equiv -/
protected def refl (α : Type*) : PartialEquiv α α :=
(Equiv.refl α).toPartialEquiv
@[simp, mfld_simps]
theorem refl_source : (PartialEquiv.refl α).source = univ :=
rfl
@[simp, mfld_simps]
theorem refl_target : (PartialEquiv.refl α).target = univ :=
rfl
@[simp, mfld_simps]
theorem refl_coe : (PartialEquiv.refl α : α → α) = id :=
rfl
@[simp, mfld_simps]
theorem refl_symm : (PartialEquiv.refl α).symm = PartialEquiv.refl α :=
rfl
@[mfld_simps]
theorem refl_restr_source (s : Set α) : ((PartialEquiv.refl α).restr s).source = s := by simp
@[mfld_simps]
theorem refl_restr_target (s : Set α) : ((PartialEquiv.refl α).restr s).target = s := by simp
/-- The identity partial equivalence on a set `s` -/
def ofSet (s : Set α) : PartialEquiv α α where
toFun := id
invFun := id
source := s
target := s
map_source' _ hx := hx
map_target' _ hx := hx
left_inv' _ _ := rfl
right_inv' _ _ := rfl
@[simp, mfld_simps]
theorem ofSet_source (s : Set α) : (PartialEquiv.ofSet s).source = s :=
rfl
@[simp, mfld_simps]
theorem ofSet_target (s : Set α) : (PartialEquiv.ofSet s).target = s :=
rfl
@[simp, mfld_simps]
theorem ofSet_coe (s : Set α) : (PartialEquiv.ofSet s : α → α) = id :=
rfl
@[simp, mfld_simps]
theorem ofSet_symm (s : Set α) : (PartialEquiv.ofSet s).symm = PartialEquiv.ofSet s :=
rfl
/-- `Function.const` as a `PartialEquiv`.
It consists of two constant maps in opposite directions. -/
@[simps]
def single (a : α) (b : β) : PartialEquiv α β where
toFun := Function.const α b
invFun := Function.const β a
source := {a}
target := {b}
map_source' _ _ := rfl
map_target' _ _ := rfl
left_inv' a' ha' := by rw [eq_of_mem_singleton ha', const_apply]
right_inv' b' hb' := by rw [eq_of_mem_singleton hb', const_apply]
/-- Composing two partial equivs if the target of the first coincides with the source of the
second. -/
@[simps]
protected def trans' (e' : PartialEquiv β γ) (h : e.target = e'.source) : PartialEquiv α γ where
toFun := e' ∘ e
invFun := e.symm ∘ e'.symm
source := e.source
target := e'.target
map_source' x hx := by simp [← h, hx]
map_target' y hy := by simp [h, hy]
left_inv' x hx := by simp [hx, ← h]
right_inv' y hy := by simp [hy, h]
/-- Composing two partial equivs, by restricting to the maximal domain where their composition
is well defined.
Within the `Manifold` namespace, there is the notation `e ≫ f` for this.
-/
@[trans]
protected def trans : PartialEquiv α γ :=
PartialEquiv.trans' (e.symm.restr e'.source).symm (e'.restr e.target) (inter_comm _ _)
@[simp, mfld_simps]
theorem coe_trans : (e.trans e' : α → γ) = e' ∘ e :=
rfl
@[simp, mfld_simps]
theorem coe_trans_symm : ((e.trans e').symm : γ → α) = e.symm ∘ e'.symm :=
rfl
theorem trans_apply {x : α} : (e.trans e') x = e' (e x) :=
rfl
theorem trans_symm_eq_symm_trans_symm : (e.trans e').symm = e'.symm.trans e.symm := by
cases e; cases e'; rfl
@[simp, mfld_simps]
theorem trans_source : (e.trans e').source = e.source ∩ e ⁻¹' e'.source :=
rfl
theorem trans_source' : (e.trans e').source = e.source ∩ e ⁻¹' (e.target ∩ e'.source) := by
mfld_set_tac
theorem trans_source'' : (e.trans e').source = e.symm '' (e.target ∩ e'.source) := by
rw [e.trans_source', e.symm_image_target_inter_eq]
theorem image_trans_source : e '' (e.trans e').source = e.target ∩ e'.source :=
(e.symm.restr e'.source).symm.image_source_eq_target
@[simp, mfld_simps]
theorem trans_target : (e.trans e').target = e'.target ∩ e'.symm ⁻¹' e.target :=
rfl
theorem trans_target' : (e.trans e').target = e'.target ∩ e'.symm ⁻¹' (e'.source ∩ e.target) :=
trans_source' e'.symm e.symm
theorem trans_target'' : (e.trans e').target = e' '' (e'.source ∩ e.target) :=
trans_source'' e'.symm e.symm
theorem inv_image_trans_target : e'.symm '' (e.trans e').target = e'.source ∩ e.target :=
image_trans_source e'.symm e.symm
theorem trans_assoc (e'' : PartialEquiv γ δ) : (e.trans e').trans e'' = e.trans (e'.trans e'') :=
PartialEquiv.ext (fun _ => rfl) (fun _ => rfl)
(by simp [trans_source, @preimage_comp α β γ, inter_assoc])
@[simp, mfld_simps]
theorem trans_refl : e.trans (PartialEquiv.refl β) = e :=
PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) (by simp [trans_source])
@[simp, mfld_simps]
theorem refl_trans : (PartialEquiv.refl α).trans e = e :=
PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) (by simp [trans_source, preimage_id])
theorem trans_ofSet (s : Set β) : e.trans (ofSet s) = e.restr (e ⁻¹' s) :=
PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) rfl
theorem trans_refl_restr (s : Set β) :
e.trans ((PartialEquiv.refl β).restr s) = e.restr (e ⁻¹' s) :=
PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) (by simp [trans_source])
theorem trans_refl_restr' (s : Set β) :
e.trans ((PartialEquiv.refl β).restr s) = e.restr (e.source ∩ e ⁻¹' s) :=
PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) <| by
simp only [trans_source, restr_source, refl_source, univ_inter]
rw [← inter_assoc, inter_self]
theorem restr_trans (s : Set α) : (e.restr s).trans e' = (e.trans e').restr s :=
PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) <| by
simp [trans_source, inter_comm, inter_assoc]
/-- A lemma commonly useful when `e` and `e'` are charts of a manifold. -/
theorem mem_symm_trans_source {e' : PartialEquiv α γ} {x : α} (he : x ∈ e.source)
(he' : x ∈ e'.source) : e x ∈ (e.symm.trans e').source :=
⟨e.mapsTo he, by rwa [mem_preimage, PartialEquiv.symm_symm, e.left_inv he]⟩
/-- `EqOnSource e e'` means that `e` and `e'` have the same source, and coincide there. Then `e`
and `e'` should really be considered the same partial equiv. -/
def EqOnSource (e e' : PartialEquiv α β) : Prop :=
e.source = e'.source ∧ e.source.EqOn e e'
/-- `EqOnSource` is an equivalence relation. This instance provides the `≈` notation between two
`PartialEquiv`s. -/
instance eqOnSourceSetoid : Setoid (PartialEquiv α β) where
r := EqOnSource
iseqv := by constructor <;> simp only [Equivalence, EqOnSource, EqOn] <;> aesop
theorem eqOnSource_refl : e ≈ e :=
Setoid.refl _
/-- Two equivalent partial equivs have the same source. -/
theorem EqOnSource.source_eq {e e' : PartialEquiv α β} (h : e ≈ e') : e.source = e'.source :=
h.1
/-- Two equivalent partial equivs coincide on the source. -/
theorem EqOnSource.eqOn {e e' : PartialEquiv α β} (h : e ≈ e') : e.source.EqOn e e' :=
h.2
/-- Two equivalent partial equivs have the same target. -/
theorem EqOnSource.target_eq {e e' : PartialEquiv α β} (h : e ≈ e') : e.target = e'.target := by
simp only [← image_source_eq_target, ← source_eq h, h.2.image_eq]
/-- If two partial equivs are equivalent, so are their inverses. -/
theorem EqOnSource.symm' {e e' : PartialEquiv α β} (h : e ≈ e') : e.symm ≈ e'.symm := by
refine ⟨target_eq h, eqOn_of_leftInvOn_of_rightInvOn e.leftInvOn ?_ ?_⟩ <;>
simp only [symm_source, target_eq h, source_eq h, e'.symm_mapsTo]
exact e'.rightInvOn.congr_right e'.symm_mapsTo (source_eq h ▸ h.eqOn.symm)
/-- Two equivalent partial equivs have coinciding inverses on the target. -/
theorem EqOnSource.symm_eqOn {e e' : PartialEquiv α β} (h : e ≈ e') :
EqOn e.symm e'.symm e.target :=
-- Porting note: `h.symm'` dot notation doesn't work anymore because `h` is not recognised as
-- `PartialEquiv.EqOnSource` for some reason.
eqOn (symm' h)
/-- Composition of partial equivs respects equivalence. -/
theorem EqOnSource.trans' {e e' : PartialEquiv α β} {f f' : PartialEquiv β γ} (he : e ≈ e')
(hf : f ≈ f') : e.trans f ≈ e'.trans f' := by
constructor
· rw [trans_source'', trans_source'', ← target_eq he, ← hf.1]
exact (he.symm'.eqOn.mono inter_subset_left).image_eq
· intro x hx
rw [trans_source] at hx
simp [Function.comp_apply, PartialEquiv.coe_trans, (he.2 hx.1).symm, hf.2 hx.2]
/-- Restriction of partial equivs respects equivalence. -/
theorem EqOnSource.restr {e e' : PartialEquiv α β} (he : e ≈ e') (s : Set α) :
e.restr s ≈ e'.restr s := by
constructor
· simp [he.1]
· intro x hx
simp only [mem_inter_iff, restr_source] at hx
exact he.2 hx.1
/-- Preimages are respected by equivalence. -/
theorem EqOnSource.source_inter_preimage_eq {e e' : PartialEquiv α β} (he : e ≈ e') (s : Set β) :
e.source ∩ e ⁻¹' s = e'.source ∩ e' ⁻¹' s := by rw [he.eqOn.inter_preimage_eq, source_eq he]
/-- Composition of a partial equivalence and its inverse is equivalent to
the restriction of the identity to the source. -/
theorem self_trans_symm : e.trans e.symm ≈ ofSet e.source := by
have A : (e.trans e.symm).source = e.source := by mfld_set_tac
refine ⟨by rw [A, ofSet_source], fun x hx => ?_⟩
rw [A] at hx
simp only [hx, mfld_simps]
/-- Composition of the inverse of a partial equivalence and this partial equivalence is equivalent
to the restriction of the identity to the target. -/
theorem symm_trans_self : e.symm.trans e ≈ ofSet e.target :=
self_trans_symm e.symm
/-- Two equivalent partial equivs are equal when the source and target are `univ`. -/
theorem eq_of_eqOnSource_univ (e e' : PartialEquiv α β) (h : e ≈ e') (s : e.source = univ)
(t : e.target = univ) : e = e' := by
refine PartialEquiv.ext (fun x => ?_) (fun x => ?_) h.1
· apply h.2
rw [s]
exact mem_univ _
· apply h.symm'.2
rw [symm_source, t]
exact mem_univ _
section Prod
/-- The product of two partial equivalences, as a partial equivalence on the product. -/
def prod (e : PartialEquiv α β) (e' : PartialEquiv γ δ) : PartialEquiv (α × γ) (β × δ) where
| source := e.source ×ˢ e'.source
target := e.target ×ˢ e'.target
| Mathlib/Logic/Equiv/PartialEquiv.lean | 755 | 756 |
/-
Copyright (c) 2024 Michael Stoll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Michael Stoll
-/
import Mathlib.NumberTheory.DirichletCharacter.Bounds
import Mathlib.NumberTheory.LSeries.Convolution
import Mathlib.NumberTheory.LSeries.Deriv
import Mathlib.NumberTheory.LSeries.RiemannZeta
import Mathlib.NumberTheory.SumPrimeReciprocals
import Mathlib.NumberTheory.VonMangoldt
/-!
# L-series of Dirichlet characters and arithmetic functions
We collect some results on L-series of specific (arithmetic) functions, for example,
the Möbius function `μ` or the von Mangoldt function `Λ`. In particular, we show that
`L ↗Λ` is the negative of the logarithmic derivative of the Riemann zeta function
on `re s > 1`; see `LSeries_vonMangoldt_eq_deriv_riemannZeta_div`.
We also prove some general results on L-series associated to Dirichlet characters
(i.e., Dirichlet L-series). For example, we show that the abscissa of absolute convergence
equals `1` (see `DirichletCharacter.absicssaOfAbsConv`) and that the L-series does not
vanish on the open half-plane `re s > 1` (see `DirichletCharacter.LSeries_ne_zero_of_one_lt_re`).
We deduce results on the Riemann zeta function (which is `L 1` or `L ↗ζ` on `re s > 1`)
as special cases.
## Tags
Dirichlet L-series, Möbius function, von Mangoldt function, Riemann zeta function
-/
open scoped LSeries.notation
/-- `δ` is the function underlying the arithmetic function `1`. -/
lemma ArithmeticFunction.one_eq_delta : ↗(1 : ArithmeticFunction ℂ) = δ := by
ext
simp [one_apply, LSeries.delta]
section Moebius
/-!
### The L-series of the Möbius function
We show that `L μ s` converges absolutely if and only if `re s > 1`.
-/
namespace ArithmeticFunction
open LSeries Nat Complex
lemma not_LSeriesSummable_moebius_at_one : ¬ LSeriesSummable ↗μ 1 := by
refine fun h ↦ not_summable_one_div_on_primes <| summable_ofReal.mp <| .of_neg ?_
refine (h.indicator {n | n.Prime}).congr fun n ↦ ?_
by_cases hn : n.Prime
· simp [hn, hn.ne_zero, moebius_apply_prime hn, push_cast, neg_div]
· simp [hn]
/-- The L-series of the Möbius function converges absolutely at `s` if and only if `re s > 1`. -/
lemma LSeriesSummable_moebius_iff {s : ℂ} : LSeriesSummable ↗μ s ↔ 1 < s.re := by
refine ⟨fun H ↦ ?_, LSeriesSummable_of_bounded_of_one_lt_re (m := 1) fun n _ ↦ ?_⟩
· by_contra! h
exact not_LSeriesSummable_moebius_at_one <| LSeriesSummable.of_re_le_re (by simpa) H
· norm_cast
exact abs_moebius_le_one
/-- The abscissa of absolute convergence of the L-series of the Möbius function is `1`. -/
lemma abscissaOfAbsConv_moebius : abscissaOfAbsConv ↗μ = 1 := by
simpa [abscissaOfAbsConv, LSeriesSummable_moebius_iff, Set.Ioi_def, EReal.image_coe_Ioi]
using csInf_Ioo <| EReal.coe_lt_top 1
end ArithmeticFunction
end Moebius
/-!
### L-series of Dirichlet characters
-/
open Nat
open scoped ArithmeticFunction.zeta in
lemma ArithmeticFunction.const_one_eq_zeta {R : Type*} [AddMonoidWithOne R] {n : ℕ} (hn : n ≠ 0) :
(1 : ℕ → R) n = (ζ ·) n := by
simp [hn]
lemma LSeries.one_convolution_eq_zeta_convolution {R : Type*} [Semiring R] (f : ℕ → R) :
(1 : ℕ → R) ⍟ f = ((ArithmeticFunction.zeta ·) : ℕ → R) ⍟ f :=
convolution_congr ArithmeticFunction.const_one_eq_zeta fun _ ↦ rfl
lemma LSeries.convolution_one_eq_convolution_zeta {R : Type*} [Semiring R] (f : ℕ → R) :
f ⍟ (1 : ℕ → R) = f ⍟ ((ArithmeticFunction.zeta ·) : ℕ → R) :=
convolution_congr (fun _ ↦ rfl) ArithmeticFunction.const_one_eq_zeta
/-- `χ₁` is (local) notation for the (necessarily trivial) Dirichlet character modulo `1`. -/
local notation (name := Dchar_one) "χ₁" => (1 : DirichletCharacter ℂ 1)
namespace DirichletCharacter
open ArithmeticFunction in
/-- The arithmetic function associated to a Dirichlet character is multiplicative. -/
lemma isMultiplicative_toArithmeticFunction {N : ℕ} {R : Type*} [CommMonoidWithZero R]
(χ : DirichletCharacter R N) :
(toArithmeticFunction (χ ·)).IsMultiplicative := by
refine IsMultiplicative.iff_ne_zero.mpr ⟨?_, fun {m} {n} hm hn _ ↦ ?_⟩
· simp [toArithmeticFunction]
| · simp [toArithmeticFunction, hm, hn]
lemma apply_eq_toArithmeticFunction_apply {N : ℕ} {R : Type*} [CommMonoidWithZero R]
(χ : DirichletCharacter R N) {n : ℕ} (hn : n ≠ 0) :
χ n = toArithmeticFunction (χ ·) n := by
simp [toArithmeticFunction, hn]
open LSeries Nat Complex
| Mathlib/NumberTheory/LSeries/Dirichlet.lean | 110 | 118 |
/-
Copyright (c) 2022 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa, Yuyang Zhao
-/
import Mathlib.Algebra.Order.GroupWithZero.Unbundled.Basic
import Mathlib.Algebra.Order.GroupWithZero.Unbundled.Defs
import Mathlib.Tactic.Linter.DeprecatedModule
deprecated_module (since := "2025-04-13")
| Mathlib/Algebra/Order/GroupWithZero/Unbundled.lean | 752 | 753 | |
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Yury Kudryashov, Sébastien Gouëzel, Rémy Degenne
-/
import Mathlib.MeasureTheory.Integral.Bochner.Basic
import Mathlib.MeasureTheory.Integral.Bochner.L1
import Mathlib.MeasureTheory.Integral.Bochner.VitaliCaratheodory
deprecated_module (since := "2025-04-13")
| Mathlib/MeasureTheory/Integral/Bochner.lean | 1,930 | 1,933 | |
/-
Copyright (c) 2019 Gabriel Ebner. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Gabriel Ebner, Anatole Dedecker, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.Deriv.Basic
import Mathlib.Analysis.Calculus.FDeriv.Mul
import Mathlib.Analysis.Calculus.FDeriv.Add
/-!
# Derivative of `f x * g x`
In this file we prove formulas for `(f x * g x)'` and `(f x • g x)'`.
For a more detailed overview of one-dimensional derivatives in mathlib, see the module docstring of
`Analysis/Calculus/Deriv/Basic`.
## Keywords
derivative, multiplication
-/
universe u v w
noncomputable section
open scoped Topology Filter ENNReal
open Filter Asymptotics Set
open ContinuousLinearMap (smulRight smulRight_one_eq_iff)
variable {𝕜 : Type u} [NontriviallyNormedField 𝕜]
variable {F : Type v} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
variable {E : Type w} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
variable {G : Type*} [NormedAddCommGroup G] [NormedSpace 𝕜 G]
variable {f : 𝕜 → F}
variable {f' : F}
variable {x : 𝕜}
variable {s : Set 𝕜}
variable {L : Filter 𝕜}
/-! ### Derivative of bilinear maps -/
namespace ContinuousLinearMap
variable {B : E →L[𝕜] F →L[𝕜] G} {u : 𝕜 → E} {v : 𝕜 → F} {u' : E} {v' : F}
theorem hasDerivWithinAt_of_bilinear
(hu : HasDerivWithinAt u u' s x) (hv : HasDerivWithinAt v v' s x) :
HasDerivWithinAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) s x := by
simpa using (B.hasFDerivWithinAt_of_bilinear
hu.hasFDerivWithinAt hv.hasFDerivWithinAt).hasDerivWithinAt
theorem hasDerivAt_of_bilinear (hu : HasDerivAt u u' x) (hv : HasDerivAt v v' x) :
HasDerivAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) x := by
simpa using (B.hasFDerivAt_of_bilinear hu.hasFDerivAt hv.hasFDerivAt).hasDerivAt
theorem hasStrictDerivAt_of_bilinear (hu : HasStrictDerivAt u u' x) (hv : HasStrictDerivAt v v' x) :
HasStrictDerivAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) x := by
simpa using
(B.hasStrictFDerivAt_of_bilinear hu.hasStrictFDerivAt hv.hasStrictFDerivAt).hasStrictDerivAt
theorem derivWithin_of_bilinear
(hu : DifferentiableWithinAt 𝕜 u s x) (hv : DifferentiableWithinAt 𝕜 v s x) :
derivWithin (fun y => B (u y) (v y)) s x =
B (u x) (derivWithin v s x) + B (derivWithin u s x) (v x) := by
by_cases hsx : UniqueDiffWithinAt 𝕜 s x
· exact (B.hasDerivWithinAt_of_bilinear hu.hasDerivWithinAt hv.hasDerivWithinAt).derivWithin hsx
· simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx]
theorem deriv_of_bilinear (hu : DifferentiableAt 𝕜 u x) (hv : DifferentiableAt 𝕜 v x) :
deriv (fun y => B (u y) (v y)) x = B (u x) (deriv v x) + B (deriv u x) (v x) :=
(B.hasDerivAt_of_bilinear hu.hasDerivAt hv.hasDerivAt).deriv
end ContinuousLinearMap
section SMul
/-! ### Derivative of the multiplication of a scalar function and a vector function -/
variable {𝕜' : Type*} [NontriviallyNormedField 𝕜'] [NormedAlgebra 𝕜 𝕜'] [NormedSpace 𝕜' F]
[IsScalarTower 𝕜 𝕜' F] {c : 𝕜 → 𝕜'} {c' : 𝕜'}
theorem HasDerivWithinAt.smul (hc : HasDerivWithinAt c c' s x) (hf : HasDerivWithinAt f f' s x) :
HasDerivWithinAt (fun y => c y • f y) (c x • f' + c' • f x) s x := by
simpa using (HasFDerivWithinAt.smul hc hf).hasDerivWithinAt
theorem HasDerivAt.smul (hc : HasDerivAt c c' x) (hf : HasDerivAt f f' x) :
HasDerivAt (fun y => c y • f y) (c x • f' + c' • f x) x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.smul hf
nonrec theorem HasStrictDerivAt.smul (hc : HasStrictDerivAt c c' x) (hf : HasStrictDerivAt f f' x) :
HasStrictDerivAt (fun y => c y • f y) (c x • f' + c' • f x) x := by
simpa using (hc.smul hf).hasStrictDerivAt
theorem derivWithin_smul (hc : DifferentiableWithinAt 𝕜 c s x)
(hf : DifferentiableWithinAt 𝕜 f s x) :
derivWithin (fun y => c y • f y) s x = c x • derivWithin f s x + derivWithin c s x • f x := by
by_cases hsx : UniqueDiffWithinAt 𝕜 s x
· exact (hc.hasDerivWithinAt.smul hf.hasDerivWithinAt).derivWithin hsx
· simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx]
theorem deriv_smul (hc : DifferentiableAt 𝕜 c x) (hf : DifferentiableAt 𝕜 f x) :
deriv (fun y => c y • f y) x = c x • deriv f x + deriv c x • f x :=
(hc.hasDerivAt.smul hf.hasDerivAt).deriv
theorem HasStrictDerivAt.smul_const (hc : HasStrictDerivAt c c' x) (f : F) :
HasStrictDerivAt (fun y => c y • f) (c' • f) x := by
have := hc.smul (hasStrictDerivAt_const x f)
rwa [smul_zero, zero_add] at this
theorem HasDerivWithinAt.smul_const (hc : HasDerivWithinAt c c' s x) (f : F) :
HasDerivWithinAt (fun y => c y • f) (c' • f) s x := by
have := hc.smul (hasDerivWithinAt_const x s f)
rwa [smul_zero, zero_add] at this
theorem HasDerivAt.smul_const (hc : HasDerivAt c c' x) (f : F) :
HasDerivAt (fun y => c y • f) (c' • f) x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.smul_const f
theorem derivWithin_smul_const (hc : DifferentiableWithinAt 𝕜 c s x) (f : F) :
derivWithin (fun y => c y • f) s x = derivWithin c s x • f := by
by_cases hsx : UniqueDiffWithinAt 𝕜 s x
· exact (hc.hasDerivWithinAt.smul_const f).derivWithin hsx
· simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx]
theorem deriv_smul_const (hc : DifferentiableAt 𝕜 c x) (f : F) :
deriv (fun y => c y • f) x = deriv c x • f :=
(hc.hasDerivAt.smul_const f).deriv
end SMul
section ConstSMul
variable {R : Type*} [Semiring R] [Module R F] [SMulCommClass 𝕜 R F] [ContinuousConstSMul R F]
nonrec theorem HasStrictDerivAt.const_smul (c : R) (hf : HasStrictDerivAt f f' x) :
HasStrictDerivAt (fun y => c • f y) (c • f') x := by
simpa using (hf.const_smul c).hasStrictDerivAt
nonrec theorem HasDerivAtFilter.const_smul (c : R) (hf : HasDerivAtFilter f f' x L) :
HasDerivAtFilter (fun y => c • f y) (c • f') x L := by
simpa using (hf.const_smul c).hasDerivAtFilter
nonrec theorem HasDerivWithinAt.const_smul (c : R) (hf : HasDerivWithinAt f f' s x) :
HasDerivWithinAt (fun y => c • f y) (c • f') s x :=
hf.const_smul c
nonrec theorem HasDerivAt.const_smul (c : R) (hf : HasDerivAt f f' x) :
HasDerivAt (fun y => c • f y) (c • f') x :=
hf.const_smul c
theorem derivWithin_const_smul (c : R) (hf : DifferentiableWithinAt 𝕜 f s x) :
derivWithin (fun y => c • f y) s x = c • derivWithin f s x := by
by_cases hsx : UniqueDiffWithinAt 𝕜 s x
· exact (hf.hasDerivWithinAt.const_smul c).derivWithin hsx
· simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx]
theorem deriv_const_smul (c : R) (hf : DifferentiableAt 𝕜 f x) :
deriv (fun y => c • f y) x = c • deriv f x :=
(hf.hasDerivAt.const_smul c).deriv
/-- A variant of `deriv_const_smul` without differentiability assumption when the scalar
multiplication is by field elements. -/
lemma deriv_const_smul' {f : 𝕜 → F} {x : 𝕜} {R : Type*} [Field R] [Module R F] [SMulCommClass 𝕜 R F]
[ContinuousConstSMul R F] (c : R) :
deriv (fun y ↦ c • f y) x = c • deriv f x := by
by_cases hf : DifferentiableAt 𝕜 f x
· exact deriv_const_smul c hf
· rcases eq_or_ne c 0 with rfl | hc
· simp only [zero_smul, deriv_const']
· have H : ¬DifferentiableAt 𝕜 (fun y ↦ c • f y) x := by
contrapose! hf
conv => enter [2, y]; rw [← inv_smul_smul₀ hc (f y)]
exact DifferentiableAt.const_smul hf c⁻¹
rw [deriv_zero_of_not_differentiableAt hf, deriv_zero_of_not_differentiableAt H, smul_zero]
end ConstSMul
section Mul
/-! ### Derivative of the multiplication of two functions -/
variable {𝕜' 𝔸 : Type*} [NormedField 𝕜'] [NormedRing 𝔸] [NormedAlgebra 𝕜 𝕜'] [NormedAlgebra 𝕜 𝔸]
{c d : 𝕜 → 𝔸} {c' d' : 𝔸} {u v : 𝕜 → 𝕜'}
theorem HasDerivWithinAt.mul (hc : HasDerivWithinAt c c' s x) (hd : HasDerivWithinAt d d' s x) :
HasDerivWithinAt (fun y => c y * d y) (c' * d x + c x * d') s x := by
have := (HasFDerivWithinAt.mul' hc hd).hasDerivWithinAt
rwa [ContinuousLinearMap.add_apply, ContinuousLinearMap.smul_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.smulRight_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.one_apply, one_smul, one_smul,
add_comm] at this
theorem HasDerivAt.mul (hc : HasDerivAt c c' x) (hd : HasDerivAt d d' x) :
HasDerivAt (fun y => c y * d y) (c' * d x + c x * d') x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.mul hd
theorem HasStrictDerivAt.mul (hc : HasStrictDerivAt c c' x) (hd : HasStrictDerivAt d d' x) :
HasStrictDerivAt (fun y => c y * d y) (c' * d x + c x * d') x := by
have := (HasStrictFDerivAt.mul' hc hd).hasStrictDerivAt
rwa [ContinuousLinearMap.add_apply, ContinuousLinearMap.smul_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.smulRight_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.one_apply, one_smul, one_smul,
add_comm] at this
theorem derivWithin_mul (hc : DifferentiableWithinAt 𝕜 c s x)
(hd : DifferentiableWithinAt 𝕜 d s x) :
derivWithin (fun y => c y * d y) s x = derivWithin c s x * d x + c x * derivWithin d s x := by
by_cases hsx : UniqueDiffWithinAt 𝕜 s x
· exact (hc.hasDerivWithinAt.mul hd.hasDerivWithinAt).derivWithin hsx
· simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx]
@[simp]
theorem deriv_mul (hc : DifferentiableAt 𝕜 c x) (hd : DifferentiableAt 𝕜 d x) :
deriv (fun y => c y * d y) x = deriv c x * d x + c x * deriv d x :=
(hc.hasDerivAt.mul hd.hasDerivAt).deriv
theorem HasDerivWithinAt.mul_const (hc : HasDerivWithinAt c c' s x) (d : 𝔸) :
HasDerivWithinAt (fun y => c y * d) (c' * d) s x := by
convert hc.mul (hasDerivWithinAt_const x s d) using 1
rw [mul_zero, add_zero]
theorem HasDerivAt.mul_const (hc : HasDerivAt c c' x) (d : 𝔸) :
HasDerivAt (fun y => c y * d) (c' * d) x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.mul_const d
theorem hasDerivAt_mul_const (c : 𝕜) : HasDerivAt (fun x => x * c) c x := by
simpa only [one_mul] using (hasDerivAt_id' x).mul_const c
theorem HasStrictDerivAt.mul_const (hc : HasStrictDerivAt c c' x) (d : 𝔸) :
HasStrictDerivAt (fun y => c y * d) (c' * d) x := by
convert hc.mul (hasStrictDerivAt_const x d) using 1
rw [mul_zero, add_zero]
theorem derivWithin_mul_const (hc : DifferentiableWithinAt 𝕜 c s x) (d : 𝔸) :
derivWithin (fun y => c y * d) s x = derivWithin c s x * d := by
by_cases hsx : UniqueDiffWithinAt 𝕜 s x
· exact (hc.hasDerivWithinAt.mul_const d).derivWithin hsx
· simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx]
lemma derivWithin_mul_const_field (u : 𝕜') :
derivWithin (fun y => v y * u) s x = derivWithin v s x * u := by
by_cases hv : DifferentiableWithinAt 𝕜 v s x
· rw [derivWithin_mul_const hv u]
by_cases hu : u = 0
· simp [hu]
rw [derivWithin_zero_of_not_differentiableWithinAt hv, zero_mul,
derivWithin_zero_of_not_differentiableWithinAt]
have : v = fun x ↦ (v x * u) * u⁻¹ := by ext; simp [hu]
exact fun h_diff ↦ hv <| this ▸ h_diff.mul_const _
theorem deriv_mul_const (hc : DifferentiableAt 𝕜 c x) (d : 𝔸) :
deriv (fun y => c y * d) x = deriv c x * d :=
(hc.hasDerivAt.mul_const d).deriv
theorem deriv_mul_const_field (v : 𝕜') : deriv (fun y => u y * v) x = deriv u x * v := by
by_cases hu : DifferentiableAt 𝕜 u x
· exact deriv_mul_const hu v
· rw [deriv_zero_of_not_differentiableAt hu, zero_mul]
rcases eq_or_ne v 0 with (rfl | hd)
· simp only [mul_zero, deriv_const]
· refine deriv_zero_of_not_differentiableAt (mt (fun H => ?_) hu)
simpa only [mul_inv_cancel_right₀ hd] using H.mul_const v⁻¹
@[simp]
theorem deriv_mul_const_field' (v : 𝕜') : (deriv fun x => u x * v) = fun x => deriv u x * v :=
funext fun _ => deriv_mul_const_field v
theorem HasDerivWithinAt.const_mul (c : 𝔸) (hd : HasDerivWithinAt d d' s x) :
HasDerivWithinAt (fun y => c * d y) (c * d') s x := by
convert (hasDerivWithinAt_const x s c).mul hd using 1
rw [zero_mul, zero_add]
theorem HasDerivAt.const_mul (c : 𝔸) (hd : HasDerivAt d d' x) :
HasDerivAt (fun y => c * d y) (c * d') x := by
rw [← hasDerivWithinAt_univ] at *
exact hd.const_mul c
theorem HasStrictDerivAt.const_mul (c : 𝔸) (hd : HasStrictDerivAt d d' x) :
HasStrictDerivAt (fun y => c * d y) (c * d') x := by
convert (hasStrictDerivAt_const _ _).mul hd using 1
rw [zero_mul, zero_add]
theorem derivWithin_const_mul (c : 𝔸) (hd : DifferentiableWithinAt 𝕜 d s x) :
derivWithin (fun y => c * d y) s x = c * derivWithin d s x := by
by_cases hsx : UniqueDiffWithinAt 𝕜 s x
| · exact (hd.hasDerivWithinAt.const_mul c).derivWithin hsx
· simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx]
lemma derivWithin_const_mul_field (u : 𝕜') :
| Mathlib/Analysis/Calculus/Deriv/Mul.lean | 295 | 298 |
/-
Copyright (c) 2019 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, François Dupuis
-/
import Mathlib.Analysis.Convex.Basic
import Mathlib.Order.Filter.Extr
import Mathlib.Tactic.NormNum
/-!
# Convex and concave functions
This file defines convex and concave functions in vector spaces and proves the finite Jensen
inequality. The integral version can be found in `Analysis.Convex.Integral`.
A function `f : E → β` is `ConvexOn` a set `s` if `s` is itself a convex set, and for any two
points `x y ∈ s`, the segment joining `(x, f x)` to `(y, f y)` is above the graph of `f`.
Equivalently, `ConvexOn 𝕜 f s` means that the epigraph `{p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2}` is
a convex set.
## Main declarations
* `ConvexOn 𝕜 s f`: The function `f` is convex on `s` with scalars `𝕜`.
* `ConcaveOn 𝕜 s f`: The function `f` is concave on `s` with scalars `𝕜`.
* `StrictConvexOn 𝕜 s f`: The function `f` is strictly convex on `s` with scalars `𝕜`.
* `StrictConcaveOn 𝕜 s f`: The function `f` is strictly concave on `s` with scalars `𝕜`.
-/
open LinearMap Set Convex Pointwise
variable {𝕜 E F α β ι : Type*}
section OrderedSemiring
variable [Semiring 𝕜] [PartialOrder 𝕜]
section AddCommMonoid
variable [AddCommMonoid E] [AddCommMonoid F]
section OrderedAddCommMonoid
variable [AddCommMonoid α] [PartialOrder α] [AddCommMonoid β] [PartialOrder β]
section SMul
variable (𝕜) [SMul 𝕜 E] [SMul 𝕜 α] [SMul 𝕜 β] (s : Set E) (f : E → β) {g : β → α}
/-- Convexity of functions -/
def ConvexOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 ≤ a → 0 ≤ b → a + b = 1 →
f (a • x + b • y) ≤ a • f x + b • f y
/-- Concavity of functions -/
def ConcaveOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 ≤ a → 0 ≤ b → a + b = 1 →
a • f x + b • f y ≤ f (a • x + b • y)
/-- Strict convexity of functions -/
def StrictConvexOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x ≠ y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
f (a • x + b • y) < a • f x + b • f y
/-- Strict concavity of functions -/
def StrictConcaveOn : Prop :=
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x ≠ y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y < f (a • x + b • y)
variable {𝕜 s f}
open OrderDual (toDual ofDual)
theorem ConvexOn.dual (hf : ConvexOn 𝕜 s f) : ConcaveOn 𝕜 s (toDual ∘ f) := hf
theorem ConcaveOn.dual (hf : ConcaveOn 𝕜 s f) : ConvexOn 𝕜 s (toDual ∘ f) := hf
theorem StrictConvexOn.dual (hf : StrictConvexOn 𝕜 s f) : StrictConcaveOn 𝕜 s (toDual ∘ f) := hf
theorem StrictConcaveOn.dual (hf : StrictConcaveOn 𝕜 s f) : StrictConvexOn 𝕜 s (toDual ∘ f) := hf
theorem convexOn_id {s : Set β} (hs : Convex 𝕜 s) : ConvexOn 𝕜 s _root_.id :=
⟨hs, by
intros
rfl⟩
theorem concaveOn_id {s : Set β} (hs : Convex 𝕜 s) : ConcaveOn 𝕜 s _root_.id :=
⟨hs, by
intros
rfl⟩
section congr
variable {g : E → β}
theorem ConvexOn.congr (hf : ConvexOn 𝕜 s f) (hfg : EqOn f g s) : ConvexOn 𝕜 s g :=
⟨hf.1, fun x hx y hy a b ha hb hab => by
simpa only [← hfg hx, ← hfg hy, ← hfg (hf.1 hx hy ha hb hab)] using hf.2 hx hy ha hb hab⟩
theorem ConcaveOn.congr (hf : ConcaveOn 𝕜 s f) (hfg : EqOn f g s) : ConcaveOn 𝕜 s g :=
⟨hf.1, fun x hx y hy a b ha hb hab => by
simpa only [← hfg hx, ← hfg hy, ← hfg (hf.1 hx hy ha hb hab)] using hf.2 hx hy ha hb hab⟩
theorem StrictConvexOn.congr (hf : StrictConvexOn 𝕜 s f) (hfg : EqOn f g s) :
StrictConvexOn 𝕜 s g :=
⟨hf.1, fun x hx y hy hxy a b ha hb hab => by
simpa only [← hfg hx, ← hfg hy, ← hfg (hf.1 hx hy ha.le hb.le hab)] using
hf.2 hx hy hxy ha hb hab⟩
theorem StrictConcaveOn.congr (hf : StrictConcaveOn 𝕜 s f) (hfg : EqOn f g s) :
StrictConcaveOn 𝕜 s g :=
⟨hf.1, fun x hx y hy hxy a b ha hb hab => by
simpa only [← hfg hx, ← hfg hy, ← hfg (hf.1 hx hy ha.le hb.le hab)] using
hf.2 hx hy hxy ha hb hab⟩
end congr
theorem ConvexOn.subset {t : Set E} (hf : ConvexOn 𝕜 t f) (hst : s ⊆ t) (hs : Convex 𝕜 s) :
ConvexOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
theorem ConcaveOn.subset {t : Set E} (hf : ConcaveOn 𝕜 t f) (hst : s ⊆ t) (hs : Convex 𝕜 s) :
ConcaveOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
theorem StrictConvexOn.subset {t : Set E} (hf : StrictConvexOn 𝕜 t f) (hst : s ⊆ t)
(hs : Convex 𝕜 s) : StrictConvexOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
theorem StrictConcaveOn.subset {t : Set E} (hf : StrictConcaveOn 𝕜 t f) (hst : s ⊆ t)
(hs : Convex 𝕜 s) : StrictConcaveOn 𝕜 s f :=
⟨hs, fun _ hx _ hy => hf.2 (hst hx) (hst hy)⟩
theorem ConvexOn.comp (hg : ConvexOn 𝕜 (f '' s) g) (hf : ConvexOn 𝕜 s f)
(hg' : MonotoneOn g (f '' s)) : ConvexOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy _ _ ha hb hab =>
(hg' (mem_image_of_mem f <| hf.1 hx hy ha hb hab)
(hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab) <|
hf.2 hx hy ha hb hab).trans <|
hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab⟩
theorem ConcaveOn.comp (hg : ConcaveOn 𝕜 (f '' s) g) (hf : ConcaveOn 𝕜 s f)
(hg' : MonotoneOn g (f '' s)) : ConcaveOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy _ _ ha hb hab =>
(hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab).trans <|
hg' (hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha hb hab)
(mem_image_of_mem f <| hf.1 hx hy ha hb hab) <|
hf.2 hx hy ha hb hab⟩
theorem ConvexOn.comp_concaveOn (hg : ConvexOn 𝕜 (f '' s) g) (hf : ConcaveOn 𝕜 s f)
(hg' : AntitoneOn g (f '' s)) : ConvexOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg'
theorem ConcaveOn.comp_convexOn (hg : ConcaveOn 𝕜 (f '' s) g) (hf : ConvexOn 𝕜 s f)
(hg' : AntitoneOn g (f '' s)) : ConcaveOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg'
theorem StrictConvexOn.comp (hg : StrictConvexOn 𝕜 (f '' s) g) (hf : StrictConvexOn 𝕜 s f)
(hg' : StrictMonoOn g (f '' s)) (hf' : s.InjOn f) : StrictConvexOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy hxy _ _ ha hb hab =>
(hg' (mem_image_of_mem f <| hf.1 hx hy ha.le hb.le hab)
(hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha.le hb.le hab) <|
hf.2 hx hy hxy ha hb hab).trans <|
hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) (mt (hf' hx hy) hxy) ha hb hab⟩
theorem StrictConcaveOn.comp (hg : StrictConcaveOn 𝕜 (f '' s) g) (hf : StrictConcaveOn 𝕜 s f)
(hg' : StrictMonoOn g (f '' s)) (hf' : s.InjOn f) : StrictConcaveOn 𝕜 s (g ∘ f) :=
⟨hf.1, fun _ hx _ hy hxy _ _ ha hb hab =>
(hg.2 (mem_image_of_mem f hx) (mem_image_of_mem f hy) (mt (hf' hx hy) hxy) ha hb hab).trans <|
hg' (hg.1 (mem_image_of_mem f hx) (mem_image_of_mem f hy) ha.le hb.le hab)
(mem_image_of_mem f <| hf.1 hx hy ha.le hb.le hab) <|
hf.2 hx hy hxy ha hb hab⟩
theorem StrictConvexOn.comp_strictConcaveOn (hg : StrictConvexOn 𝕜 (f '' s) g)
(hf : StrictConcaveOn 𝕜 s f) (hg' : StrictAntiOn g (f '' s)) (hf' : s.InjOn f) :
StrictConvexOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg' hf'
theorem StrictConcaveOn.comp_strictConvexOn (hg : StrictConcaveOn 𝕜 (f '' s) g)
(hf : StrictConvexOn 𝕜 s f) (hg' : StrictAntiOn g (f '' s)) (hf' : s.InjOn f) :
StrictConcaveOn 𝕜 s (g ∘ f) :=
hg.dual.comp hf hg' hf'
end SMul
section DistribMulAction
variable [IsOrderedAddMonoid β] [SMul 𝕜 E] [DistribMulAction 𝕜 β] {s : Set E} {f g : E → β}
theorem ConvexOn.add (hf : ConvexOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) : ConvexOn 𝕜 s (f + g) :=
⟨hf.1, fun x hx y hy a b ha hb hab =>
calc
f (a • x + b • y) + g (a • x + b • y) ≤ a • f x + b • f y + (a • g x + b • g y) :=
add_le_add (hf.2 hx hy ha hb hab) (hg.2 hx hy ha hb hab)
_ = a • (f x + g x) + b • (f y + g y) := by rw [smul_add, smul_add, add_add_add_comm]
⟩
theorem ConcaveOn.add (hf : ConcaveOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) : ConcaveOn 𝕜 s (f + g) :=
hf.dual.add hg
end DistribMulAction
section Module
variable [SMul 𝕜 E] [Module 𝕜 β] {s : Set E} {f : E → β}
theorem convexOn_const (c : β) (hs : Convex 𝕜 s) : ConvexOn 𝕜 s fun _ : E => c :=
⟨hs, fun _ _ _ _ _ _ _ _ hab => (Convex.combo_self hab c).ge⟩
theorem concaveOn_const (c : β) (hs : Convex 𝕜 s) : ConcaveOn 𝕜 s fun _ => c :=
convexOn_const (β := βᵒᵈ) _ hs
theorem ConvexOn.add_const [IsOrderedAddMonoid β] (hf : ConvexOn 𝕜 s f) (b : β) :
ConvexOn 𝕜 s (f + fun _ => b) :=
hf.add (convexOn_const _ hf.1)
theorem ConcaveOn.add_const [IsOrderedAddMonoid β] (hf : ConcaveOn 𝕜 s f) (b : β) :
ConcaveOn 𝕜 s (f + fun _ => b) :=
hf.add (concaveOn_const _ hf.1)
theorem convexOn_of_convex_epigraph (h : Convex 𝕜 { p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2 }) :
ConvexOn 𝕜 s f :=
⟨fun x hx y hy a b ha hb hab => (@h (x, f x) ⟨hx, le_rfl⟩ (y, f y) ⟨hy, le_rfl⟩ a b ha hb hab).1,
fun x hx y hy a b ha hb hab => (@h (x, f x) ⟨hx, le_rfl⟩ (y, f y) ⟨hy, le_rfl⟩ a b ha hb hab).2⟩
theorem concaveOn_of_convex_hypograph (h : Convex 𝕜 { p : E × β | p.1 ∈ s ∧ p.2 ≤ f p.1 }) :
ConcaveOn 𝕜 s f :=
convexOn_of_convex_epigraph (β := βᵒᵈ) h
end Module
section OrderedSMul
variable [IsOrderedAddMonoid β] [SMul 𝕜 E] [Module 𝕜 β] [OrderedSMul 𝕜 β] {s : Set E} {f : E → β}
theorem ConvexOn.convex_le (hf : ConvexOn 𝕜 s f) (r : β) : Convex 𝕜 ({ x ∈ s | f x ≤ r }) :=
fun x hx y hy a b ha hb hab =>
⟨hf.1 hx.1 hy.1 ha hb hab,
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx.1 hy.1 ha hb hab
_ ≤ a • r + b • r := by
gcongr
· exact hx.2
· exact hy.2
_ = r := Convex.combo_self hab r
⟩
theorem ConcaveOn.convex_ge (hf : ConcaveOn 𝕜 s f) (r : β) : Convex 𝕜 ({ x ∈ s | r ≤ f x }) :=
hf.dual.convex_le r
theorem ConvexOn.convex_epigraph (hf : ConvexOn 𝕜 s f) :
Convex 𝕜 { p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2 } := by
rintro ⟨x, r⟩ ⟨hx, hr⟩ ⟨y, t⟩ ⟨hy, ht⟩ a b ha hb hab
refine ⟨hf.1 hx hy ha hb hab, ?_⟩
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx hy ha hb hab
_ ≤ a • r + b • t := by gcongr
theorem ConcaveOn.convex_hypograph (hf : ConcaveOn 𝕜 s f) :
Convex 𝕜 { p : E × β | p.1 ∈ s ∧ p.2 ≤ f p.1 } :=
hf.dual.convex_epigraph
theorem convexOn_iff_convex_epigraph :
ConvexOn 𝕜 s f ↔ Convex 𝕜 { p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2 } :=
⟨ConvexOn.convex_epigraph, convexOn_of_convex_epigraph⟩
theorem concaveOn_iff_convex_hypograph :
ConcaveOn 𝕜 s f ↔ Convex 𝕜 { p : E × β | p.1 ∈ s ∧ p.2 ≤ f p.1 } :=
convexOn_iff_convex_epigraph (β := βᵒᵈ)
end OrderedSMul
section Module
variable [Module 𝕜 E] [SMul 𝕜 β] {s : Set E} {f : E → β}
/-- Right translation preserves convexity. -/
theorem ConvexOn.translate_right (hf : ConvexOn 𝕜 s f) (c : E) :
ConvexOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => c + z) :=
⟨hf.1.translate_preimage_right _, fun x hx y hy a b ha hb hab =>
calc
f (c + (a • x + b • y)) = f (a • (c + x) + b • (c + y)) := by
rw [smul_add, smul_add, add_add_add_comm, Convex.combo_self hab]
_ ≤ a • f (c + x) + b • f (c + y) := hf.2 hx hy ha hb hab
⟩
/-- Right translation preserves concavity. -/
theorem ConcaveOn.translate_right (hf : ConcaveOn 𝕜 s f) (c : E) :
ConcaveOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => c + z) :=
hf.dual.translate_right _
/-- Left translation preserves convexity. -/
theorem ConvexOn.translate_left (hf : ConvexOn 𝕜 s f) (c : E) :
ConvexOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => z + c) := by
simpa only [add_comm c] using hf.translate_right c
/-- Left translation preserves concavity. -/
theorem ConcaveOn.translate_left (hf : ConcaveOn 𝕜 s f) (c : E) :
ConcaveOn 𝕜 ((fun z => c + z) ⁻¹' s) (f ∘ fun z => z + c) :=
hf.dual.translate_left _
end Module
section Module
variable [Module 𝕜 E] [Module 𝕜 β]
theorem convexOn_iff_forall_pos {s : Set E} {f : E → β} :
ConvexOn 𝕜 s f ↔ Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b →
a + b = 1 → f (a • x + b • y) ≤ a • f x + b • f y := by
refine and_congr_right'
⟨fun h x hx y hy a b ha hb hab => h hx hy ha.le hb.le hab, fun h x hx y hy a b ha hb hab => ?_⟩
obtain rfl | ha' := ha.eq_or_lt
· rw [zero_add] at hab
subst b
simp_rw [zero_smul, zero_add, one_smul, le_rfl]
obtain rfl | hb' := hb.eq_or_lt
· rw [add_zero] at hab
subst a
simp_rw [zero_smul, add_zero, one_smul, le_rfl]
exact h hx hy ha' hb' hab
theorem concaveOn_iff_forall_pos {s : Set E} {f : E → β} :
ConcaveOn 𝕜 s f ↔
Convex 𝕜 s ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y ≤ f (a • x + b • y) :=
convexOn_iff_forall_pos (β := βᵒᵈ)
theorem convexOn_iff_pairwise_pos {s : Set E} {f : E → β} :
ConvexOn 𝕜 s f ↔
Convex 𝕜 s ∧
s.Pairwise fun x y =>
∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 → f (a • x + b • y) ≤ a • f x + b • f y := by
rw [convexOn_iff_forall_pos]
refine
and_congr_right'
⟨fun h x hx y hy _ a b ha hb hab => h hx hy ha hb hab, fun h x hx y hy a b ha hb hab => ?_⟩
obtain rfl | hxy := eq_or_ne x y
· rw [Convex.combo_self hab, Convex.combo_self hab]
exact h hx hy hxy ha hb hab
theorem concaveOn_iff_pairwise_pos {s : Set E} {f : E → β} :
ConcaveOn 𝕜 s f ↔
Convex 𝕜 s ∧
s.Pairwise fun x y =>
∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 → a • f x + b • f y ≤ f (a • x + b • y) :=
convexOn_iff_pairwise_pos (β := βᵒᵈ)
/-- A linear map is convex. -/
theorem LinearMap.convexOn (f : E →ₗ[𝕜] β) {s : Set E} (hs : Convex 𝕜 s) : ConvexOn 𝕜 s f :=
⟨hs, fun _ _ _ _ _ _ _ _ _ => by rw [f.map_add, f.map_smul, f.map_smul]⟩
/-- A linear map is concave. -/
theorem LinearMap.concaveOn (f : E →ₗ[𝕜] β) {s : Set E} (hs : Convex 𝕜 s) : ConcaveOn 𝕜 s f :=
⟨hs, fun _ _ _ _ _ _ _ _ _ => by rw [f.map_add, f.map_smul, f.map_smul]⟩
theorem StrictConvexOn.convexOn {s : Set E} {f : E → β} (hf : StrictConvexOn 𝕜 s f) :
ConvexOn 𝕜 s f :=
convexOn_iff_pairwise_pos.mpr
⟨hf.1, fun _ hx _ hy hxy _ _ ha hb hab => (hf.2 hx hy hxy ha hb hab).le⟩
theorem StrictConcaveOn.concaveOn {s : Set E} {f : E → β} (hf : StrictConcaveOn 𝕜 s f) :
ConcaveOn 𝕜 s f :=
hf.dual.convexOn
section OrderedSMul
variable [IsOrderedAddMonoid β] [OrderedSMul 𝕜 β] {s : Set E} {f : E → β}
theorem StrictConvexOn.convex_lt (hf : StrictConvexOn 𝕜 s f) (r : β) :
Convex 𝕜 ({ x ∈ s | f x < r }) :=
convex_iff_pairwise_pos.2 fun x hx y hy hxy a b ha hb hab =>
⟨hf.1 hx.1 hy.1 ha.le hb.le hab,
calc
f (a • x + b • y) < a • f x + b • f y := hf.2 hx.1 hy.1 hxy ha hb hab
_ ≤ a • r + b • r := by
gcongr
· exact hx.2.le
· exact hy.2.le
_ = r := Convex.combo_self hab r
⟩
theorem StrictConcaveOn.convex_gt (hf : StrictConcaveOn 𝕜 s f) (r : β) :
Convex 𝕜 ({ x ∈ s | r < f x }) :=
hf.dual.convex_lt r
end OrderedSMul
section LinearOrder
variable [LinearOrder E] {s : Set E} {f : E → β}
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is convex, it suffices to
verify the inequality `f (a • x + b • y) ≤ a • f x + b • f y` only for `x < y` and positive `a`,
`b`. The main use case is `E = 𝕜` however one can apply it, e.g., to `𝕜^n` with lexicographic order.
-/
theorem LinearOrder.convexOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
f (a • x + b • y) ≤ a • f x + b • f y) :
ConvexOn 𝕜 s f := by
refine convexOn_iff_pairwise_pos.2 ⟨hs, fun x hx y hy hxy a b ha hb hab => ?_⟩
wlog h : x < y
· rw [add_comm (a • x), add_comm (a • f x)]
rw [add_comm] at hab
exact this hs hf y hy x hx hxy.symm b a hb ha hab (hxy.lt_or_lt.resolve_left h)
exact hf hx hy h ha hb hab
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is concave it suffices to
verify the inequality `a • f x + b • f y ≤ f (a • x + b • y)` for `x < y` and positive `a`, `b`. The
main use case is `E = ℝ` however one can apply it, e.g., to `ℝ^n` with lexicographic order. -/
theorem LinearOrder.concaveOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y ≤ f (a • x + b • y)) :
ConcaveOn 𝕜 s f :=
LinearOrder.convexOn_of_lt (β := βᵒᵈ) hs hf
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is strictly convex, it suffices
to verify the inequality `f (a • x + b • y) < a • f x + b • f y` for `x < y` and positive `a`, `b`.
The main use case is `E = 𝕜` however one can apply it, e.g., to `𝕜^n` with lexicographic order. -/
theorem LinearOrder.strictConvexOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
f (a • x + b • y) < a • f x + b • f y) :
StrictConvexOn 𝕜 s f := by
refine ⟨hs, fun x hx y hy hxy a b ha hb hab => ?_⟩
wlog h : x < y
· rw [add_comm (a • x), add_comm (a • f x)]
rw [add_comm] at hab
exact this hs hf y hy x hx hxy.symm b a hb ha hab (hxy.lt_or_lt.resolve_left h)
exact hf hx hy h ha hb hab
/-- For a function on a convex set in a linearly ordered space (where the order and the algebraic
structures aren't necessarily compatible), in order to prove that it is strictly concave it suffices
to verify the inequality `a • f x + b • f y < f (a • x + b • y)` for `x < y` and positive `a`, `b`.
The main use case is `E = 𝕜` however one can apply it, e.g., to `𝕜^n` with lexicographic order. -/
theorem LinearOrder.strictConcaveOn_of_lt (hs : Convex 𝕜 s)
(hf : ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → x < y → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 →
a • f x + b • f y < f (a • x + b • y)) :
StrictConcaveOn 𝕜 s f :=
LinearOrder.strictConvexOn_of_lt (β := βᵒᵈ) hs hf
end LinearOrder
end Module
section Module
variable [Module 𝕜 E] [Module 𝕜 F] [SMul 𝕜 β]
/-- If `g` is convex on `s`, so is `(f ∘ g)` on `f ⁻¹' s` for a linear `f`. -/
theorem ConvexOn.comp_linearMap {f : F → β} {s : Set F} (hf : ConvexOn 𝕜 s f) (g : E →ₗ[𝕜] F) :
ConvexOn 𝕜 (g ⁻¹' s) (f ∘ g) :=
⟨hf.1.linear_preimage _, fun x hx y hy a b ha hb hab =>
calc
f (g (a • x + b • y)) = f (a • g x + b • g y) := by rw [g.map_add, g.map_smul, g.map_smul]
_ ≤ a • f (g x) + b • f (g y) := hf.2 hx hy ha hb hab⟩
/-- If `g` is concave on `s`, so is `(g ∘ f)` on `f ⁻¹' s` for a linear `f`. -/
theorem ConcaveOn.comp_linearMap {f : F → β} {s : Set F} (hf : ConcaveOn 𝕜 s f) (g : E →ₗ[𝕜] F) :
ConcaveOn 𝕜 (g ⁻¹' s) (f ∘ g) :=
hf.dual.comp_linearMap g
end Module
end OrderedAddCommMonoid
section OrderedCancelAddCommMonoid
variable [AddCommMonoid β] [PartialOrder β] [IsOrderedCancelAddMonoid β]
section DistribMulAction
variable [SMul 𝕜 E] [DistribMulAction 𝕜 β] {s : Set E} {f g : E → β}
theorem StrictConvexOn.add_convexOn (hf : StrictConvexOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f + g) :=
⟨hf.1, fun x hx y hy hxy a b ha hb hab =>
calc
f (a • x + b • y) + g (a • x + b • y) < a • f x + b • f y + (a • g x + b • g y) :=
add_lt_add_of_lt_of_le (hf.2 hx hy hxy ha hb hab) (hg.2 hx hy ha.le hb.le hab)
_ = a • (f x + g x) + b • (f y + g y) := by rw [smul_add, smul_add, add_add_add_comm]⟩
theorem ConvexOn.add_strictConvexOn (hf : ConvexOn 𝕜 s f) (hg : StrictConvexOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f + g) :=
add_comm g f ▸ hg.add_convexOn hf
theorem StrictConvexOn.add (hf : StrictConvexOn 𝕜 s f) (hg : StrictConvexOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f + g) :=
⟨hf.1, fun x hx y hy hxy a b ha hb hab =>
calc
f (a • x + b • y) + g (a • x + b • y) < a • f x + b • f y + (a • g x + b • g y) :=
add_lt_add (hf.2 hx hy hxy ha hb hab) (hg.2 hx hy hxy ha hb hab)
_ = a • (f x + g x) + b • (f y + g y) := by rw [smul_add, smul_add, add_add_add_comm]⟩
theorem StrictConcaveOn.add_concaveOn (hf : StrictConcaveOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) :
StrictConcaveOn 𝕜 s (f + g) :=
hf.dual.add_convexOn hg.dual
theorem ConcaveOn.add_strictConcaveOn (hf : ConcaveOn 𝕜 s f) (hg : StrictConcaveOn 𝕜 s g) :
StrictConcaveOn 𝕜 s (f + g) :=
hf.dual.add_strictConvexOn hg.dual
theorem StrictConcaveOn.add (hf : StrictConcaveOn 𝕜 s f) (hg : StrictConcaveOn 𝕜 s g) :
StrictConcaveOn 𝕜 s (f + g) :=
hf.dual.add hg
theorem StrictConvexOn.add_const {γ : Type*} {f : E → γ}
[AddCommMonoid γ] [PartialOrder γ] [IsOrderedCancelAddMonoid γ]
[Module 𝕜 γ] (hf : StrictConvexOn 𝕜 s f) (b : γ) : StrictConvexOn 𝕜 s (f + fun _ => b) :=
hf.add_convexOn (convexOn_const _ hf.1)
theorem StrictConcaveOn.add_const {γ : Type*} {f : E → γ}
[AddCommMonoid γ] [PartialOrder γ] [IsOrderedCancelAddMonoid γ]
[Module 𝕜 γ] (hf : StrictConcaveOn 𝕜 s f) (b : γ) : StrictConcaveOn 𝕜 s (f + fun _ => b) :=
hf.add_concaveOn (concaveOn_const _ hf.1)
end DistribMulAction
section Module
variable [Module 𝕜 E] [Module 𝕜 β] [OrderedSMul 𝕜 β] {s : Set E} {f : E → β}
theorem ConvexOn.convex_lt (hf : ConvexOn 𝕜 s f) (r : β) : Convex 𝕜 ({ x ∈ s | f x < r }) :=
convex_iff_forall_pos.2 fun x hx y hy a b ha hb hab =>
⟨hf.1 hx.1 hy.1 ha.le hb.le hab,
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx.1 hy.1 ha.le hb.le hab
_ < a • r + b • r :=
(add_lt_add_of_lt_of_le (smul_lt_smul_of_pos_left hx.2 ha)
(smul_le_smul_of_nonneg_left hy.2.le hb.le))
_ = r := Convex.combo_self hab _⟩
theorem ConcaveOn.convex_gt (hf : ConcaveOn 𝕜 s f) (r : β) : Convex 𝕜 ({ x ∈ s | r < f x }) :=
hf.dual.convex_lt r
theorem ConvexOn.openSegment_subset_strict_epigraph (hf : ConvexOn 𝕜 s f) (p q : E × β)
(hp : p.1 ∈ s ∧ f p.1 < p.2) (hq : q.1 ∈ s ∧ f q.1 ≤ q.2) :
openSegment 𝕜 p q ⊆ { p : E × β | p.1 ∈ s ∧ f p.1 < p.2 } := by
rintro _ ⟨a, b, ha, hb, hab, rfl⟩
refine ⟨hf.1 hp.1 hq.1 ha.le hb.le hab, ?_⟩
calc
f (a • p.1 + b • q.1) ≤ a • f p.1 + b • f q.1 := hf.2 hp.1 hq.1 ha.le hb.le hab
_ < a • p.2 + b • q.2 := add_lt_add_of_lt_of_le
(smul_lt_smul_of_pos_left hp.2 ha) (smul_le_smul_of_nonneg_left hq.2 hb.le)
theorem ConcaveOn.openSegment_subset_strict_hypograph (hf : ConcaveOn 𝕜 s f) (p q : E × β)
(hp : p.1 ∈ s ∧ p.2 < f p.1) (hq : q.1 ∈ s ∧ q.2 ≤ f q.1) :
openSegment 𝕜 p q ⊆ { p : E × β | p.1 ∈ s ∧ p.2 < f p.1 } :=
hf.dual.openSegment_subset_strict_epigraph p q hp hq
theorem ConvexOn.convex_strict_epigraph [ZeroLEOneClass 𝕜] (hf : ConvexOn 𝕜 s f) :
Convex 𝕜 { p : E × β | p.1 ∈ s ∧ f p.1 < p.2 } :=
convex_iff_openSegment_subset.mpr fun p hp q hq =>
hf.openSegment_subset_strict_epigraph p q hp ⟨hq.1, hq.2.le⟩
theorem ConcaveOn.convex_strict_hypograph [ZeroLEOneClass 𝕜] (hf : ConcaveOn 𝕜 s f) :
Convex 𝕜 { p : E × β | p.1 ∈ s ∧ p.2 < f p.1 } :=
hf.dual.convex_strict_epigraph
end Module
end OrderedCancelAddCommMonoid
section LinearOrderedAddCommMonoid
variable [AddCommMonoid β] [LinearOrder β] [IsOrderedAddMonoid β]
[SMul 𝕜 E] [Module 𝕜 β] [OrderedSMul 𝕜 β] {s : Set E}
{f g : E → β}
/-- The pointwise maximum of convex functions is convex. -/
theorem ConvexOn.sup (hf : ConvexOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) : ConvexOn 𝕜 s (f ⊔ g) := by
refine ⟨hf.left, fun x hx y hy a b ha hb hab => sup_le ?_ ?_⟩
· calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.right hx hy ha hb hab
_ ≤ a • (f x ⊔ g x) + b • (f y ⊔ g y) := by gcongr <;> apply le_sup_left
· calc
g (a • x + b • y) ≤ a • g x + b • g y := hg.right hx hy ha hb hab
_ ≤ a • (f x ⊔ g x) + b • (f y ⊔ g y) := by gcongr <;> apply le_sup_right
/-- The pointwise minimum of concave functions is concave. -/
theorem ConcaveOn.inf (hf : ConcaveOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) : ConcaveOn 𝕜 s (f ⊓ g) :=
hf.dual.sup hg
/-- The pointwise maximum of strictly convex functions is strictly convex. -/
theorem StrictConvexOn.sup (hf : StrictConvexOn 𝕜 s f) (hg : StrictConvexOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f ⊔ g) :=
⟨hf.left, fun x hx y hy hxy a b ha hb hab =>
max_lt
(calc
f (a • x + b • y) < a • f x + b • f y := hf.2 hx hy hxy ha hb hab
_ ≤ a • (f x ⊔ g x) + b • (f y ⊔ g y) := by gcongr <;> apply le_sup_left)
(calc
g (a • x + b • y) < a • g x + b • g y := hg.2 hx hy hxy ha hb hab
_ ≤ a • (f x ⊔ g x) + b • (f y ⊔ g y) := by gcongr <;> apply le_sup_right)⟩
/-- The pointwise minimum of strictly concave functions is strictly concave. -/
theorem StrictConcaveOn.inf (hf : StrictConcaveOn 𝕜 s f) (hg : StrictConcaveOn 𝕜 s g) :
StrictConcaveOn 𝕜 s (f ⊓ g) :=
hf.dual.sup hg
/-- A convex function on a segment is upper-bounded by the max of its endpoints. -/
theorem ConvexOn.le_on_segment' (hf : ConvexOn 𝕜 s f) {x y : E} (hx : x ∈ s) (hy : y ∈ s) {a b : 𝕜}
(ha : 0 ≤ a) (hb : 0 ≤ b) (hab : a + b = 1) : f (a • x + b • y) ≤ max (f x) (f y) :=
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx hy ha hb hab
_ ≤ a • max (f x) (f y) + b • max (f x) (f y) := by
gcongr
· apply le_max_left
· apply le_max_right
_ = max (f x) (f y) := Convex.combo_self hab _
/-- A concave function on a segment is lower-bounded by the min of its endpoints. -/
theorem ConcaveOn.ge_on_segment' (hf : ConcaveOn 𝕜 s f) {x y : E} (hx : x ∈ s) (hy : y ∈ s)
{a b : 𝕜} (ha : 0 ≤ a) (hb : 0 ≤ b) (hab : a + b = 1) : min (f x) (f y) ≤ f (a • x + b • y) :=
hf.dual.le_on_segment' hx hy ha hb hab
/-- A convex function on a segment is upper-bounded by the max of its endpoints. -/
theorem ConvexOn.le_on_segment (hf : ConvexOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ [x -[𝕜] y]) : f z ≤ max (f x) (f y) :=
let ⟨_, _, ha, hb, hab, hz⟩ := hz
hz ▸ hf.le_on_segment' hx hy ha hb hab
/-- A concave function on a segment is lower-bounded by the min of its endpoints. -/
theorem ConcaveOn.ge_on_segment (hf : ConcaveOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ [x -[𝕜] y]) : min (f x) (f y) ≤ f z :=
hf.dual.le_on_segment hx hy hz
/-- A strictly convex function on an open segment is strictly upper-bounded by the max of its
endpoints. -/
theorem StrictConvexOn.lt_on_open_segment' (hf : StrictConvexOn 𝕜 s f) {x y : E} (hx : x ∈ s)
(hy : y ∈ s) (hxy : x ≠ y) {a b : 𝕜} (ha : 0 < a) (hb : 0 < b) (hab : a + b = 1) :
f (a • x + b • y) < max (f x) (f y) :=
calc
f (a • x + b • y) < a • f x + b • f y := hf.2 hx hy hxy ha hb hab
_ ≤ a • max (f x) (f y) + b • max (f x) (f y) := by
gcongr
· apply le_max_left
· apply le_max_right
_ = max (f x) (f y) := Convex.combo_self hab _
/-- A strictly concave function on an open segment is strictly lower-bounded by the min of its
endpoints. -/
theorem StrictConcaveOn.lt_on_open_segment' (hf : StrictConcaveOn 𝕜 s f) {x y : E} (hx : x ∈ s)
(hy : y ∈ s) (hxy : x ≠ y) {a b : 𝕜} (ha : 0 < a) (hb : 0 < b) (hab : a + b = 1) :
min (f x) (f y) < f (a • x + b • y) :=
hf.dual.lt_on_open_segment' hx hy hxy ha hb hab
/-- A strictly convex function on an open segment is strictly upper-bounded by the max of its
endpoints. -/
theorem StrictConvexOn.lt_on_openSegment (hf : StrictConvexOn 𝕜 s f) {x y z : E} (hx : x ∈ s)
(hy : y ∈ s) (hxy : x ≠ y) (hz : z ∈ openSegment 𝕜 x y) : f z < max (f x) (f y) :=
let ⟨_, _, ha, hb, hab, hz⟩ := hz
hz ▸ hf.lt_on_open_segment' hx hy hxy ha hb hab
/-- A strictly concave function on an open segment is strictly lower-bounded by the min of its
endpoints. -/
theorem StrictConcaveOn.lt_on_openSegment (hf : StrictConcaveOn 𝕜 s f) {x y z : E} (hx : x ∈ s)
(hy : y ∈ s) (hxy : x ≠ y) (hz : z ∈ openSegment 𝕜 x y) : min (f x) (f y) < f z :=
hf.dual.lt_on_openSegment hx hy hxy hz
end LinearOrderedAddCommMonoid
section LinearOrderedCancelAddCommMonoid
variable [AddCommMonoid β] [LinearOrder β] [IsOrderedCancelAddMonoid β]
section OrderedSMul
variable [SMul 𝕜 E] [Module 𝕜 β] [OrderedSMul 𝕜 β] {s : Set E} {f g : E → β}
theorem ConvexOn.le_left_of_right_le' (hf : ConvexOn 𝕜 s f) {x y : E} (hx : x ∈ s) (hy : y ∈ s)
{a b : 𝕜} (ha : 0 < a) (hb : 0 ≤ b) (hab : a + b = 1) (hfy : f y ≤ f (a • x + b • y)) :
f (a • x + b • y) ≤ f x :=
le_of_not_lt fun h ↦ lt_irrefl (f (a • x + b • y)) <|
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx hy ha.le hb hab
_ < a • f (a • x + b • y) + b • f (a • x + b • y) := add_lt_add_of_lt_of_le
(smul_lt_smul_of_pos_left h ha) (smul_le_smul_of_nonneg_left hfy hb)
_ = f (a • x + b • y) := Convex.combo_self hab _
theorem ConcaveOn.left_le_of_le_right' (hf : ConcaveOn 𝕜 s f) {x y : E} (hx : x ∈ s) (hy : y ∈ s)
{a b : 𝕜} (ha : 0 < a) (hb : 0 ≤ b) (hab : a + b = 1) (hfy : f (a • x + b • y) ≤ f y) :
f x ≤ f (a • x + b • y) :=
hf.dual.le_left_of_right_le' hx hy ha hb hab hfy
theorem ConvexOn.le_right_of_left_le' (hf : ConvexOn 𝕜 s f) {x y : E} {a b : 𝕜} (hx : x ∈ s)
(hy : y ∈ s) (ha : 0 ≤ a) (hb : 0 < b) (hab : a + b = 1) (hfx : f x ≤ f (a • x + b • y)) :
f (a • x + b • y) ≤ f y := by
rw [add_comm] at hab hfx ⊢
exact hf.le_left_of_right_le' hy hx hb ha hab hfx
theorem ConcaveOn.right_le_of_le_left' (hf : ConcaveOn 𝕜 s f) {x y : E} {a b : 𝕜} (hx : x ∈ s)
(hy : y ∈ s) (ha : 0 ≤ a) (hb : 0 < b) (hab : a + b = 1) (hfx : f (a • x + b • y) ≤ f x) :
f y ≤ f (a • x + b • y) :=
hf.dual.le_right_of_left_le' hx hy ha hb hab hfx
theorem ConvexOn.le_left_of_right_le (hf : ConvexOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ openSegment 𝕜 x y) (hyz : f y ≤ f z) : f z ≤ f x := by
obtain ⟨a, b, ha, hb, hab, rfl⟩ := hz
exact hf.le_left_of_right_le' hx hy ha hb.le hab hyz
theorem ConcaveOn.left_le_of_le_right (hf : ConcaveOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ openSegment 𝕜 x y) (hyz : f z ≤ f y) : f x ≤ f z :=
hf.dual.le_left_of_right_le hx hy hz hyz
theorem ConvexOn.le_right_of_left_le (hf : ConvexOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ openSegment 𝕜 x y) (hxz : f x ≤ f z) : f z ≤ f y := by
obtain ⟨a, b, ha, hb, hab, rfl⟩ := hz
exact hf.le_right_of_left_le' hx hy ha.le hb hab hxz
theorem ConcaveOn.right_le_of_le_left (hf : ConcaveOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ openSegment 𝕜 x y) (hxz : f z ≤ f x) : f y ≤ f z :=
hf.dual.le_right_of_left_le hx hy hz hxz
end OrderedSMul
section Module
variable [Module 𝕜 E] [Module 𝕜 β] [OrderedSMul 𝕜 β] {s : Set E} {f g : E → β}
/- The following lemmas don't require `Module 𝕜 E` if you add the hypothesis `x ≠ y`. At the time of
the writing, we decided the resulting lemmas wouldn't be useful. Feel free to reintroduce them. -/
theorem ConvexOn.lt_left_of_right_lt' (hf : ConvexOn 𝕜 s f) {x y : E} (hx : x ∈ s) (hy : y ∈ s)
{a b : 𝕜} (ha : 0 < a) (hb : 0 < b) (hab : a + b = 1) (hfy : f y < f (a • x + b • y)) :
f (a • x + b • y) < f x :=
not_le.1 fun h ↦ lt_irrefl (f (a • x + b • y)) <|
calc
f (a • x + b • y) ≤ a • f x + b • f y := hf.2 hx hy ha.le hb.le hab
_ < a • f (a • x + b • y) + b • f (a • x + b • y) := add_lt_add_of_le_of_lt
(smul_le_smul_of_nonneg_left h ha.le) (smul_lt_smul_of_pos_left hfy hb)
_ = f (a • x + b • y) := Convex.combo_self hab _
theorem ConcaveOn.left_lt_of_lt_right' (hf : ConcaveOn 𝕜 s f) {x y : E} (hx : x ∈ s) (hy : y ∈ s)
{a b : 𝕜} (ha : 0 < a) (hb : 0 < b) (hab : a + b = 1) (hfy : f (a • x + b • y) < f y) :
f x < f (a • x + b • y) :=
hf.dual.lt_left_of_right_lt' hx hy ha hb hab hfy
theorem ConvexOn.lt_right_of_left_lt' (hf : ConvexOn 𝕜 s f) {x y : E} {a b : 𝕜} (hx : x ∈ s)
(hy : y ∈ s) (ha : 0 < a) (hb : 0 < b) (hab : a + b = 1) (hfx : f x < f (a • x + b • y)) :
f (a • x + b • y) < f y := by
rw [add_comm] at hab hfx ⊢
exact hf.lt_left_of_right_lt' hy hx hb ha hab hfx
theorem ConcaveOn.lt_right_of_left_lt' (hf : ConcaveOn 𝕜 s f) {x y : E} {a b : 𝕜} (hx : x ∈ s)
(hy : y ∈ s) (ha : 0 < a) (hb : 0 < b) (hab : a + b = 1) (hfx : f (a • x + b • y) < f x) :
f y < f (a • x + b • y) :=
hf.dual.lt_right_of_left_lt' hx hy ha hb hab hfx
theorem ConvexOn.lt_left_of_right_lt (hf : ConvexOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ openSegment 𝕜 x y) (hyz : f y < f z) : f z < f x := by
obtain ⟨a, b, ha, hb, hab, rfl⟩ := hz
exact hf.lt_left_of_right_lt' hx hy ha hb hab hyz
theorem ConcaveOn.left_lt_of_lt_right (hf : ConcaveOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ openSegment 𝕜 x y) (hyz : f z < f y) : f x < f z :=
hf.dual.lt_left_of_right_lt hx hy hz hyz
theorem ConvexOn.lt_right_of_left_lt (hf : ConvexOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ openSegment 𝕜 x y) (hxz : f x < f z) : f z < f y := by
obtain ⟨a, b, ha, hb, hab, rfl⟩ := hz
exact hf.lt_right_of_left_lt' hx hy ha hb hab hxz
theorem ConcaveOn.lt_right_of_left_lt (hf : ConcaveOn 𝕜 s f) {x y z : E} (hx : x ∈ s) (hy : y ∈ s)
(hz : z ∈ openSegment 𝕜 x y) (hxz : f z < f x) : f y < f z :=
hf.dual.lt_right_of_left_lt hx hy hz hxz
end Module
end LinearOrderedCancelAddCommMonoid
section OrderedAddCommGroup
variable [AddCommGroup β] [PartialOrder β] [IsOrderedAddMonoid β] [SMul 𝕜 E] [Module 𝕜 β]
{s : Set E} {f g : E → β}
/-- A function `-f` is convex iff `f` is concave. -/
@[simp]
theorem neg_convexOn_iff : ConvexOn 𝕜 s (-f) ↔ ConcaveOn 𝕜 s f := by
constructor
· rintro ⟨hconv, h⟩
refine ⟨hconv, fun x hx y hy a b ha hb hab => ?_⟩
simp? [neg_apply, neg_le, add_comm] at h says
simp only [Pi.neg_apply, smul_neg, le_add_neg_iff_add_le, add_comm,
add_neg_le_iff_le_add] at h
exact h hx hy ha hb hab
· rintro ⟨hconv, h⟩
refine ⟨hconv, fun x hx y hy a b ha hb hab => ?_⟩
rw [← neg_le_neg_iff]
simp_rw [neg_add, Pi.neg_apply, smul_neg, neg_neg]
exact h hx hy ha hb hab
/-- A function `-f` is concave iff `f` is convex. -/
@[simp]
theorem neg_concaveOn_iff : ConcaveOn 𝕜 s (-f) ↔ ConvexOn 𝕜 s f := by
rw [← neg_convexOn_iff, neg_neg f]
/-- A function `-f` is strictly convex iff `f` is strictly concave. -/
@[simp]
theorem neg_strictConvexOn_iff : StrictConvexOn 𝕜 s (-f) ↔ StrictConcaveOn 𝕜 s f := by
constructor
· rintro ⟨hconv, h⟩
refine ⟨hconv, fun x hx y hy hxy a b ha hb hab => ?_⟩
simp only [ne_eq, Pi.neg_apply, smul_neg, lt_add_neg_iff_add_lt, add_comm,
add_neg_lt_iff_lt_add] at h
exact h hx hy hxy ha hb hab
· rintro ⟨hconv, h⟩
refine ⟨hconv, fun x hx y hy hxy a b ha hb hab => ?_⟩
rw [← neg_lt_neg_iff]
simp_rw [neg_add, Pi.neg_apply, smul_neg, neg_neg]
exact h hx hy hxy ha hb hab
/-- A function `-f` is strictly concave iff `f` is strictly convex. -/
@[simp]
theorem neg_strictConcaveOn_iff : StrictConcaveOn 𝕜 s (-f) ↔ StrictConvexOn 𝕜 s f := by
rw [← neg_strictConvexOn_iff, neg_neg f]
alias ⟨_, ConcaveOn.neg⟩ := neg_convexOn_iff
alias ⟨_, ConvexOn.neg⟩ := neg_concaveOn_iff
alias ⟨_, StrictConcaveOn.neg⟩ := neg_strictConvexOn_iff
alias ⟨_, StrictConvexOn.neg⟩ := neg_strictConcaveOn_iff
theorem ConvexOn.sub (hf : ConvexOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) : ConvexOn 𝕜 s (f - g) :=
(sub_eq_add_neg f g).symm ▸ hf.add hg.neg
theorem ConcaveOn.sub (hf : ConcaveOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) : ConcaveOn 𝕜 s (f - g) :=
(sub_eq_add_neg f g).symm ▸ hf.add hg.neg
theorem StrictConvexOn.sub (hf : StrictConvexOn 𝕜 s f) (hg : StrictConcaveOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f - g) :=
(sub_eq_add_neg f g).symm ▸ hf.add hg.neg
theorem StrictConcaveOn.sub (hf : StrictConcaveOn 𝕜 s f) (hg : StrictConvexOn 𝕜 s g) :
StrictConcaveOn 𝕜 s (f - g) :=
(sub_eq_add_neg f g).symm ▸ hf.add hg.neg
theorem ConvexOn.sub_strictConcaveOn (hf : ConvexOn 𝕜 s f) (hg : StrictConcaveOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f - g) :=
(sub_eq_add_neg f g).symm ▸ hf.add_strictConvexOn hg.neg
theorem ConcaveOn.sub_strictConvexOn (hf : ConcaveOn 𝕜 s f) (hg : StrictConvexOn 𝕜 s g) :
StrictConcaveOn 𝕜 s (f - g) :=
(sub_eq_add_neg f g).symm ▸ hf.add_strictConcaveOn hg.neg
theorem StrictConvexOn.sub_concaveOn (hf : StrictConvexOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) :
StrictConvexOn 𝕜 s (f - g) :=
(sub_eq_add_neg f g).symm ▸ hf.add_convexOn hg.neg
theorem StrictConcaveOn.sub_convexOn (hf : StrictConcaveOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) :
StrictConcaveOn 𝕜 s (f - g) :=
| (sub_eq_add_neg f g).symm ▸ hf.add_concaveOn hg.neg
| Mathlib/Analysis/Convex/Function.lean | 854 | 855 |
/-
Copyright (c) 2019 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca, Johan Commelin
-/
import Mathlib.Algebra.Polynomial.FieldDivision
import Mathlib.Algebra.Polynomial.Lifts
import Mathlib.FieldTheory.Minpoly.Basic
import Mathlib.RingTheory.Algebraic.Integral
import Mathlib.RingTheory.LocalRing.Basic
/-!
# Minimal polynomials on an algebra over a field
This file specializes the theory of minpoly to the setting of field extensions
and derives some well-known properties, amongst which the fact that minimal polynomials
are irreducible, and uniquely determined by their defining property.
-/
open Polynomial Set Function minpoly
namespace minpoly
variable {A B : Type*}
variable (A) [Field A]
section Ring
variable [Ring B] [Algebra A B] (x : B)
/-- If an element `x` is a root of a nonzero polynomial `p`, then the degree of `p` is at least the
degree of the minimal polynomial of `x`. See also `minpoly.IsIntegrallyClosed.degree_le_of_ne_zero`
which relaxes the assumptions on `A` in exchange for stronger assumptions on `B`. -/
theorem degree_le_of_ne_zero {p : A[X]} (pnz : p ≠ 0) (hp : Polynomial.aeval x p = 0) :
degree (minpoly A x) ≤ degree p :=
calc
degree (minpoly A x) ≤ degree (p * C (leadingCoeff p)⁻¹) :=
min A x (monic_mul_leadingCoeff_inv pnz) (by simp [hp])
_ = degree p := degree_mul_leadingCoeff_inv p pnz
theorem ne_zero_of_finite (e : B) [FiniteDimensional A B] : minpoly A e ≠ 0 :=
minpoly.ne_zero <| .of_finite A _
/-- The minimal polynomial of an element `x` is uniquely characterized by its defining property:
if there is another monic polynomial of minimal degree that has `x` as a root, then this polynomial
is equal to the minimal polynomial of `x`. See also `minpoly.IsIntegrallyClosed.Minpoly.unique`
which relaxes the assumptions on `A` in exchange for stronger assumptions on `B`. -/
theorem unique {p : A[X]} (pmonic : p.Monic) (hp : Polynomial.aeval x p = 0)
(pmin : ∀ q : A[X], q.Monic → Polynomial.aeval x q = 0 → degree p ≤ degree q) :
p = minpoly A x := by
have hx : IsIntegral A x := ⟨p, pmonic, hp⟩
symm; apply eq_of_sub_eq_zero
by_contra hnz
apply degree_le_of_ne_zero A x hnz (by simp [hp]) |>.not_lt
apply degree_sub_lt _ (minpoly.ne_zero hx)
· rw [(monic hx).leadingCoeff, pmonic.leadingCoeff]
· exact le_antisymm (min A x pmonic hp) (pmin (minpoly A x) (monic hx) (aeval A x))
/-- If an element `x` is a root of a polynomial `p`, then the minimal polynomial of `x` divides `p`.
See also `minpoly.isIntegrallyClosed_dvd` which relaxes the assumptions on `A` in exchange for
stronger assumptions on `B`. -/
theorem dvd {p : A[X]} (hp : Polynomial.aeval x p = 0) : minpoly A x ∣ p := by
by_cases hp0 : p = 0
· simp only [hp0, dvd_zero]
have hx : IsIntegral A x := IsAlgebraic.isIntegral ⟨p, hp0, hp⟩
rw [← modByMonic_eq_zero_iff_dvd (monic hx)]
by_contra hnz
apply degree_le_of_ne_zero A x hnz
((aeval_modByMonic_eq_self_of_root (monic hx) (aeval _ _)).trans hp) |>.not_lt
exact degree_modByMonic_lt _ (monic hx)
variable {A x} in
lemma dvd_iff {p : A[X]} : minpoly A x ∣ p ↔ Polynomial.aeval x p = 0 :=
⟨fun ⟨q, hq⟩ ↦ by rw [hq, map_mul, aeval, zero_mul], minpoly.dvd A x⟩
theorem isRadical [IsReduced B] : IsRadical (minpoly A x) := fun n p dvd ↦ by
rw [dvd_iff] at dvd ⊢; rw [map_pow] at dvd; exact IsReduced.eq_zero _ ⟨n, dvd⟩
theorem dvd_map_of_isScalarTower (A K : Type*) {R : Type*} [CommRing A] [Field K] [Ring R]
[Algebra A K] [Algebra A R] [Algebra K R] [IsScalarTower A K R] (x : R) :
minpoly K x ∣ (minpoly A x).map (algebraMap A K) := by
refine minpoly.dvd K x ?_
rw [aeval_map_algebraMap, minpoly.aeval]
theorem dvd_map_of_isScalarTower' (R : Type*) {S : Type*} (K L : Type*) [CommRing R]
[CommRing S] [Field K] [Ring L] [Algebra R S] [Algebra R K] [Algebra S L] [Algebra K L]
[Algebra R L] [IsScalarTower R K L] [IsScalarTower R S L] (s : S) :
minpoly K (algebraMap S L s) ∣ map (algebraMap R K) (minpoly R s) := by
apply minpoly.dvd K (algebraMap S L s)
rw [← map_aeval_eq_aeval_map, minpoly.aeval, map_zero]
rw [← IsScalarTower.algebraMap_eq, ← IsScalarTower.algebraMap_eq]
/-- If `y` is a conjugate of `x` over a field `K`, then it is a conjugate over a subring `R`. -/
theorem aeval_of_isScalarTower (R : Type*) {K T U : Type*} [CommRing R] [Field K] [CommRing T]
[Algebra R K] [Algebra K T] [Algebra R T] [IsScalarTower R K T] [CommSemiring U] [Algebra K U]
[Algebra R U] [IsScalarTower R K U] (x : T) (y : U)
(hy : Polynomial.aeval y (minpoly K x) = 0) : Polynomial.aeval y (minpoly R x) = 0 :=
aeval_map_algebraMap K y (minpoly R x) ▸
eval₂_eq_zero_of_dvd_of_eval₂_eq_zero (algebraMap K U) y
(minpoly.dvd_map_of_isScalarTower R K x) hy
/-- If a subfield `F` of `E` contains all the coefficients of `minpoly E a`, then
`minpoly F a` maps to `minpoly E a` via `algebraMap F E`. -/
theorem map_algebraMap {F E A : Type*} [Field F] [Field E] [CommRing A]
[Algebra F E] [Algebra E A] [Algebra F A] [IsScalarTower F E A]
{a : A} (ha : IsIntegral F a) (h : minpoly E a ∈ lifts (algebraMap F E)) :
(minpoly F a).map (algebraMap F E) = minpoly E a := by
refine eq_of_monic_of_dvd_of_natDegree_le (minpoly.monic ha.tower_top)
((algebraMap F E).injective.monic_map_iff.mp <| minpoly.monic ha)
(minpoly.dvd E a (by simp)) ?_
obtain ⟨g, hg, hgdeg, hgmon⟩ := lifts_and_natDegree_eq_and_monic h (minpoly.monic ha.tower_top)
rw [natDegree_map, ← hgdeg]
refine natDegree_le_of_dvd (minpoly.dvd F a ?_) hgmon.ne_zero
rw [← aeval_map_algebraMap A, IsScalarTower.algebraMap_eq F E A, ← coe_mapRingHom,
← mapRingHom_comp, RingHom.comp_apply, coe_mapRingHom, coe_mapRingHom, hg,
aeval_map_algebraMap, minpoly.aeval]
/-- See also `minpoly.ker_eval` which relaxes the assumptions on `A` in exchange for
stronger assumptions on `B`. -/
@[simp]
lemma ker_aeval_eq_span_minpoly :
RingHom.ker (Polynomial.aeval x) = A[X] ∙ minpoly A x := by
ext p
simp_rw [RingHom.mem_ker, ← minpoly.dvd_iff, Submodule.mem_span_singleton,
dvd_iff_exists_eq_mul_left, smul_eq_mul, eq_comm (a := p)]
variable {A x}
theorem eq_of_irreducible_of_monic [Nontrivial B] {p : A[X]} (hp1 : Irreducible p)
(hp2 : Polynomial.aeval x p = 0) (hp3 : p.Monic) : p = minpoly A x :=
let ⟨_, hq⟩ := dvd A x hp2
eq_of_monic_of_associated hp3 (monic ⟨p, ⟨hp3, hp2⟩⟩) <|
mul_one (minpoly A x) ▸ hq.symm ▸ Associated.mul_left _
(associated_one_iff_isUnit.2 <| (hp1.isUnit_or_isUnit hq).resolve_left <| not_isUnit A x)
theorem eq_iff_aeval_eq_zero [Nontrivial B] {p : A[X]} (irr : Irreducible p) (monic : p.Monic) :
p = minpoly A x ↔ Polynomial.aeval x p = 0 :=
⟨(· ▸ aeval A x), (eq_of_irreducible_of_monic irr · monic)⟩
|
theorem eq_iff_aeval_minpoly_eq_zero [IsDomain B] {C} [Ring C] [Algebra A C] [Nontrivial C]
{b : B} (h : IsIntegral A b) {c : C} :
minpoly A b = minpoly A c ↔ Polynomial.aeval c (minpoly A b) = 0 :=
eq_iff_aeval_eq_zero (irreducible h) (monic h)
theorem eq_of_irreducible [Nontrivial B] {p : A[X]} (hp1 : Irreducible p)
(hp2 : Polynomial.aeval x p = 0) : p * C p.leadingCoeff⁻¹ = minpoly A x := by
have : p.leadingCoeff ≠ 0 := leadingCoeff_ne_zero.mpr hp1.ne_zero
apply eq_of_irreducible_of_monic
· exact Associated.irreducible ⟨⟨C p.leadingCoeff⁻¹, C p.leadingCoeff,
by rwa [← C_mul, inv_mul_cancel₀, C_1], by rwa [← C_mul, mul_inv_cancel₀, C_1]⟩, rfl⟩ hp1
| Mathlib/FieldTheory/Minpoly/Field.lean | 141 | 152 |
/-
Copyright (c) 2022 Praneeth Kolichala. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Praneeth Kolichala
-/
import Mathlib.AlgebraicTopology.FundamentalGroupoid.InducedMaps
import Mathlib.Topology.Homotopy.Contractible
import Mathlib.CategoryTheory.PUnit
import Mathlib.AlgebraicTopology.FundamentalGroupoid.PUnit
/-!
# Simply connected spaces
This file defines simply connected spaces.
A topological space is simply connected if its fundamental groupoid is equivalent to `Unit`.
## Main theorems
- `simply_connected_iff_unique_homotopic` - A space is simply connected if and only if it is
nonempty and there is a unique path up to homotopy between any two points
- `SimplyConnectedSpace.ofContractible` - A contractible space is simply connected
-/
universe u
noncomputable section
open CategoryTheory
open ContinuousMap
open scoped ContinuousMap
/-- A simply connected space is one whose fundamental groupoid is equivalent to `Discrete Unit` -/
@[mk_iff simply_connected_def]
class SimplyConnectedSpace (X : Type*) [TopologicalSpace X] : Prop where
equiv_unit : Nonempty (FundamentalGroupoid X ≌ Discrete Unit)
theorem simply_connected_iff_unique_homotopic (X : Type*) [TopologicalSpace X] :
SimplyConnectedSpace X ↔
Nonempty X ∧ ∀ x y : X, Nonempty (Unique (Path.Homotopic.Quotient x y)) := by
simp only [simply_connected_def, equiv_punit_iff_unique,
| FundamentalGroupoid.nonempty_iff X, and_congr_right_iff, Nonempty.forall]
intros
exact ⟨fun h _ _ => h _ _, fun h _ _ => h _ _⟩
namespace SimplyConnectedSpace
variable {X : Type*} [TopologicalSpace X] [SimplyConnectedSpace X]
| Mathlib/AlgebraicTopology/FundamentalGroupoid/SimplyConnected.lean | 42 | 48 |
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura, Jeremy Avigad, Minchao Wu, Mario Carneiro
-/
import Mathlib.Data.Finset.Attach
import Mathlib.Data.Finset.Disjoint
import Mathlib.Data.Finset.Erase
import Mathlib.Data.Finset.Filter
import Mathlib.Data.Finset.Range
import Mathlib.Data.Finset.SDiff
import Mathlib.Data.Multiset.Basic
import Mathlib.Logic.Equiv.Set
import Mathlib.Order.Directed
import Mathlib.Order.Interval.Set.Defs
import Mathlib.Data.Set.SymmDiff
/-!
# Basic lemmas on finite sets
This file contains lemmas on the interaction of various definitions on the `Finset` type.
For an explanation of `Finset` design decisions, please see `Mathlib/Data/Finset/Defs.lean`.
## Main declarations
### Main definitions
* `Finset.choose`: Given a proof `h` of existence and uniqueness of a certain element
satisfying a predicate, `choose s h` returns the element of `s` satisfying that predicate.
### Equivalences between finsets
* The `Mathlib/Logic/Equiv/Defs.lean` file describes a general type of equivalence, so look in there
for any lemmas. There is some API for rewriting sums and products from `s` to `t` given that
`s ≃ t`.
TODO: examples
## Tags
finite sets, finset
-/
-- Assert that we define `Finset` without the material on `List.sublists`.
-- Note that we cannot use `List.sublists` itself as that is defined very early.
assert_not_exists List.sublistsLen Multiset.powerset CompleteLattice Monoid
open Multiset Subtype Function
universe u
variable {α : Type*} {β : Type*} {γ : Type*}
namespace Finset
-- TODO: these should be global attributes, but this will require fixing other files
attribute [local trans] Subset.trans Superset.trans
set_option linter.deprecated false in
@[deprecated "Deprecated without replacement." (since := "2025-02-07")]
theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Finset α} (hx : x ∈ s) :
SizeOf.sizeOf x < SizeOf.sizeOf s := by
cases s
dsimp [SizeOf.sizeOf, SizeOf.sizeOf, Multiset.sizeOf]
rw [Nat.add_comm]
refine lt_trans ?_ (Nat.lt_succ_self _)
exact Multiset.sizeOf_lt_sizeOf_of_mem hx
/-! ### Lattice structure -/
section Lattice
variable [DecidableEq α] {s s₁ s₂ t t₁ t₂ u v : Finset α} {a b : α}
/-! #### union -/
@[simp]
theorem disjUnion_eq_union (s t h) : @disjUnion α s t h = s ∪ t :=
ext fun a => by simp
@[simp]
theorem disjoint_union_left : Disjoint (s ∪ t) u ↔ Disjoint s u ∧ Disjoint t u := by
simp only [disjoint_left, mem_union, or_imp, forall_and]
@[simp]
theorem disjoint_union_right : Disjoint s (t ∪ u) ↔ Disjoint s t ∧ Disjoint s u := by
simp only [disjoint_right, mem_union, or_imp, forall_and]
/-! #### inter -/
theorem not_disjoint_iff_nonempty_inter : ¬Disjoint s t ↔ (s ∩ t).Nonempty :=
not_disjoint_iff.trans <| by simp [Finset.Nonempty]
alias ⟨_, Nonempty.not_disjoint⟩ := not_disjoint_iff_nonempty_inter
theorem disjoint_or_nonempty_inter (s t : Finset α) : Disjoint s t ∨ (s ∩ t).Nonempty := by
rw [← not_disjoint_iff_nonempty_inter]
exact em _
omit [DecidableEq α] in
theorem disjoint_of_subset_iff_left_eq_empty (h : s ⊆ t) :
Disjoint s t ↔ s = ∅ :=
disjoint_of_le_iff_left_eq_bot h
lemma pairwiseDisjoint_iff {ι : Type*} {s : Set ι} {f : ι → Finset α} :
s.PairwiseDisjoint f ↔ ∀ ⦃i⦄, i ∈ s → ∀ ⦃j⦄, j ∈ s → (f i ∩ f j).Nonempty → i = j := by
simp [Set.PairwiseDisjoint, Set.Pairwise, Function.onFun, not_imp_comm (a := _ = _),
not_disjoint_iff_nonempty_inter]
end Lattice
instance isDirected_le : IsDirected (Finset α) (· ≤ ·) := by classical infer_instance
instance isDirected_subset : IsDirected (Finset α) (· ⊆ ·) := isDirected_le
/-! ### erase -/
section Erase
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
@[simp]
theorem erase_empty (a : α) : erase ∅ a = ∅ :=
rfl
protected lemma Nontrivial.erase_nonempty (hs : s.Nontrivial) : (s.erase a).Nonempty :=
(hs.exists_ne a).imp <| by aesop
@[simp] lemma erase_nonempty (ha : a ∈ s) : (s.erase a).Nonempty ↔ s.Nontrivial := by
simp only [Finset.Nonempty, mem_erase, and_comm (b := _ ∈ _)]
refine ⟨?_, fun hs ↦ hs.exists_ne a⟩
rintro ⟨b, hb, hba⟩
exact ⟨_, hb, _, ha, hba⟩
@[simp]
theorem erase_singleton (a : α) : ({a} : Finset α).erase a = ∅ := by
ext x
simp
@[simp]
theorem erase_insert_eq_erase (s : Finset α) (a : α) : (insert a s).erase a = s.erase a :=
ext fun x => by
simp +contextual only [mem_erase, mem_insert, and_congr_right_iff,
false_or, iff_self, imp_true_iff]
theorem erase_insert {a : α} {s : Finset α} (h : a ∉ s) : erase (insert a s) a = s := by
rw [erase_insert_eq_erase, erase_eq_of_not_mem h]
theorem erase_insert_of_ne {a b : α} {s : Finset α} (h : a ≠ b) :
erase (insert a s) b = insert a (erase s b) :=
ext fun x => by
have : x ≠ b ∧ x = a ↔ x = a := and_iff_right_of_imp fun hx => hx.symm ▸ h
simp only [mem_erase, mem_insert, and_or_left, this]
theorem erase_cons_of_ne {a b : α} {s : Finset α} (ha : a ∉ s) (hb : a ≠ b) :
erase (cons a s ha) b = cons a (erase s b) fun h => ha <| erase_subset _ _ h := by
simp only [cons_eq_insert, erase_insert_of_ne hb]
@[simp] theorem insert_erase (h : a ∈ s) : insert a (erase s a) = s :=
ext fun x => by
simp only [mem_insert, mem_erase, or_and_left, dec_em, true_and]
apply or_iff_right_of_imp
rintro rfl
exact h
lemma erase_eq_iff_eq_insert (hs : a ∈ s) (ht : a ∉ t) : erase s a = t ↔ s = insert a t := by
aesop
lemma insert_erase_invOn :
Set.InvOn (insert a) (fun s ↦ erase s a) {s : Finset α | a ∈ s} {s : Finset α | a ∉ s} :=
⟨fun _s ↦ insert_erase, fun _s ↦ erase_insert⟩
theorem erase_ssubset {a : α} {s : Finset α} (h : a ∈ s) : s.erase a ⊂ s :=
calc
s.erase a ⊂ insert a (s.erase a) := ssubset_insert <| not_mem_erase _ _
_ = _ := insert_erase h
theorem ssubset_iff_exists_subset_erase {s t : Finset α} : s ⊂ t ↔ ∃ a ∈ t, s ⊆ t.erase a := by
refine ⟨fun h => ?_, fun ⟨a, ha, h⟩ => ssubset_of_subset_of_ssubset h <| erase_ssubset ha⟩
obtain ⟨a, ht, hs⟩ := not_subset.1 h.2
exact ⟨a, ht, subset_erase.2 ⟨h.1, hs⟩⟩
theorem erase_ssubset_insert (s : Finset α) (a : α) : s.erase a ⊂ insert a s :=
ssubset_iff_exists_subset_erase.2
⟨a, mem_insert_self _ _, erase_subset_erase _ <| subset_insert _ _⟩
theorem erase_cons {s : Finset α} {a : α} (h : a ∉ s) : (s.cons a h).erase a = s := by
rw [cons_eq_insert, erase_insert_eq_erase, erase_eq_of_not_mem h]
theorem subset_insert_iff {a : α} {s t : Finset α} : s ⊆ insert a t ↔ erase s a ⊆ t := by
simp only [subset_iff, or_iff_not_imp_left, mem_erase, mem_insert, and_imp]
exact forall_congr' fun x => forall_swap
theorem erase_insert_subset (a : α) (s : Finset α) : erase (insert a s) a ⊆ s :=
subset_insert_iff.1 <| Subset.rfl
theorem insert_erase_subset (a : α) (s : Finset α) : s ⊆ insert a (erase s a) :=
subset_insert_iff.2 <| Subset.rfl
theorem subset_insert_iff_of_not_mem (h : a ∉ s) : s ⊆ insert a t ↔ s ⊆ t := by
rw [subset_insert_iff, erase_eq_of_not_mem h]
theorem erase_subset_iff_of_mem (h : a ∈ t) : s.erase a ⊆ t ↔ s ⊆ t := by
rw [← subset_insert_iff, insert_eq_of_mem h]
theorem erase_injOn' (a : α) : { s : Finset α | a ∈ s }.InjOn fun s => erase s a :=
fun s hs t ht (h : s.erase a = _) => by rw [← insert_erase hs, ← insert_erase ht, h]
end Erase
lemma Nontrivial.exists_cons_eq {s : Finset α} (hs : s.Nontrivial) :
∃ t a ha b hb hab, (cons b t hb).cons a (mem_cons.not.2 <| not_or_intro hab ha) = s := by
classical
obtain ⟨a, ha, b, hb, hab⟩ := hs
have : b ∈ s.erase a := mem_erase.2 ⟨hab.symm, hb⟩
refine ⟨(s.erase a).erase b, a, ?_, b, ?_, ?_, ?_⟩ <;>
simp [insert_erase this, insert_erase ha, *]
/-! ### sdiff -/
section Sdiff
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
lemma erase_sdiff_erase (hab : a ≠ b) (hb : b ∈ s) : s.erase a \ s.erase b = {b} := by
ext; aesop
-- TODO: Do we want to delete this lemma and `Finset.disjUnion_singleton`,
-- or instead add `Finset.union_singleton`/`Finset.singleton_union`?
theorem sdiff_singleton_eq_erase (a : α) (s : Finset α) : s \ {a} = erase s a := by
ext
rw [mem_erase, mem_sdiff, mem_singleton, and_comm]
-- This lemma matches `Finset.insert_eq` in functionality.
theorem erase_eq (s : Finset α) (a : α) : s.erase a = s \ {a} :=
(sdiff_singleton_eq_erase _ _).symm
theorem disjoint_erase_comm : Disjoint (s.erase a) t ↔ Disjoint s (t.erase a) := by
simp_rw [erase_eq, disjoint_sdiff_comm]
lemma disjoint_insert_erase (ha : a ∉ t) : Disjoint (s.erase a) (insert a t) ↔ Disjoint s t := by
rw [disjoint_erase_comm, erase_insert ha]
lemma disjoint_erase_insert (ha : a ∉ s) : Disjoint (insert a s) (t.erase a) ↔ Disjoint s t := by
rw [← disjoint_erase_comm, erase_insert ha]
theorem disjoint_of_erase_left (ha : a ∉ t) (hst : Disjoint (s.erase a) t) : Disjoint s t := by
rw [← erase_insert ha, ← disjoint_erase_comm, disjoint_insert_right]
exact ⟨not_mem_erase _ _, hst⟩
theorem disjoint_of_erase_right (ha : a ∉ s) (hst : Disjoint s (t.erase a)) : Disjoint s t := by
rw [← erase_insert ha, disjoint_erase_comm, disjoint_insert_left]
exact ⟨not_mem_erase _ _, hst⟩
theorem inter_erase (a : α) (s t : Finset α) : s ∩ t.erase a = (s ∩ t).erase a := by
simp only [erase_eq, inter_sdiff_assoc]
@[simp]
theorem erase_inter (a : α) (s t : Finset α) : s.erase a ∩ t = (s ∩ t).erase a := by
simpa only [inter_comm t] using inter_erase a t s
theorem erase_sdiff_comm (s t : Finset α) (a : α) : s.erase a \ t = (s \ t).erase a := by
simp_rw [erase_eq, sdiff_right_comm]
theorem erase_inter_comm (s t : Finset α) (a : α) : s.erase a ∩ t = s ∩ t.erase a := by
rw [erase_inter, inter_erase]
theorem erase_union_distrib (s t : Finset α) (a : α) : (s ∪ t).erase a = s.erase a ∪ t.erase a := by
simp_rw [erase_eq, union_sdiff_distrib]
theorem insert_inter_distrib (s t : Finset α) (a : α) :
insert a (s ∩ t) = insert a s ∩ insert a t := by simp_rw [insert_eq, union_inter_distrib_left]
theorem erase_sdiff_distrib (s t : Finset α) (a : α) : (s \ t).erase a = s.erase a \ t.erase a := by
simp_rw [erase_eq, sdiff_sdiff, sup_sdiff_eq_sup le_rfl, sup_comm]
theorem erase_union_of_mem (ha : a ∈ t) (s : Finset α) : s.erase a ∪ t = s ∪ t := by
rw [← insert_erase (mem_union_right s ha), erase_union_distrib, ← union_insert, insert_erase ha]
theorem union_erase_of_mem (ha : a ∈ s) (t : Finset α) : s ∪ t.erase a = s ∪ t := by
rw [← insert_erase (mem_union_left t ha), erase_union_distrib, ← insert_union, insert_erase ha]
theorem sdiff_union_erase_cancel (hts : t ⊆ s) (ha : a ∈ t) : s \ t ∪ t.erase a = s.erase a := by
simp_rw [erase_eq, sdiff_union_sdiff_cancel hts (singleton_subset_iff.2 ha)]
theorem sdiff_insert (s t : Finset α) (x : α) : s \ insert x t = (s \ t).erase x := by
simp_rw [← sdiff_singleton_eq_erase, insert_eq, sdiff_sdiff_left', sdiff_union_distrib,
inter_comm]
theorem sdiff_insert_insert_of_mem_of_not_mem {s t : Finset α} {x : α} (hxs : x ∈ s) (hxt : x ∉ t) :
insert x (s \ insert x t) = s \ t := by
rw [sdiff_insert, insert_erase (mem_sdiff.mpr ⟨hxs, hxt⟩)]
theorem sdiff_erase (h : a ∈ s) : s \ t.erase a = insert a (s \ t) := by
rw [← sdiff_singleton_eq_erase, sdiff_sdiff_eq_sdiff_union (singleton_subset_iff.2 h), insert_eq,
union_comm]
theorem sdiff_erase_self (ha : a ∈ s) : s \ s.erase a = {a} := by
rw [sdiff_erase ha, Finset.sdiff_self, insert_empty_eq]
theorem erase_eq_empty_iff (s : Finset α) (a : α) : s.erase a = ∅ ↔ s = ∅ ∨ s = {a} := by
rw [← sdiff_singleton_eq_erase, sdiff_eq_empty_iff_subset, subset_singleton_iff]
--TODO@Yaël: Kill lemmas duplicate with `BooleanAlgebra`
theorem sdiff_disjoint : Disjoint (t \ s) s :=
disjoint_left.2 fun _a ha => (mem_sdiff.1 ha).2
theorem disjoint_sdiff : Disjoint s (t \ s) :=
sdiff_disjoint.symm
theorem disjoint_sdiff_inter (s t : Finset α) : Disjoint (s \ t) (s ∩ t) :=
disjoint_of_subset_right inter_subset_right sdiff_disjoint
end Sdiff
/-! ### attach -/
@[simp]
theorem attach_empty : attach (∅ : Finset α) = ∅ :=
rfl
@[simp]
theorem attach_nonempty_iff {s : Finset α} : s.attach.Nonempty ↔ s.Nonempty := by
simp [Finset.Nonempty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
protected alias ⟨_, Nonempty.attach⟩ := attach_nonempty_iff
@[simp]
theorem attach_eq_empty_iff {s : Finset α} : s.attach = ∅ ↔ s = ∅ := by
simp [eq_empty_iff_forall_not_mem]
/-! ### filter -/
section Filter
variable (p q : α → Prop) [DecidablePred p] [DecidablePred q] {s t : Finset α}
theorem filter_singleton (a : α) : filter p {a} = if p a then {a} else ∅ := by
classical
ext x
simp only [mem_singleton, forall_eq, mem_filter]
split_ifs with h <;> by_cases h' : x = a <;> simp [h, h']
theorem filter_cons_of_pos (a : α) (s : Finset α) (ha : a ∉ s) (hp : p a) :
filter p (cons a s ha) = cons a (filter p s) ((mem_of_mem_filter _).mt ha) :=
eq_of_veq <| Multiset.filter_cons_of_pos s.val hp
theorem filter_cons_of_neg (a : α) (s : Finset α) (ha : a ∉ s) (hp : ¬p a) :
filter p (cons a s ha) = filter p s :=
eq_of_veq <| Multiset.filter_cons_of_neg s.val hp
theorem disjoint_filter {s : Finset α} {p q : α → Prop} [DecidablePred p] [DecidablePred q] :
Disjoint (s.filter p) (s.filter q) ↔ ∀ x ∈ s, p x → ¬q x := by
constructor <;> simp +contextual [disjoint_left]
theorem disjoint_filter_filter' (s t : Finset α)
{p q : α → Prop} [DecidablePred p] [DecidablePred q] (h : Disjoint p q) :
Disjoint (s.filter p) (t.filter q) := by
simp_rw [disjoint_left, mem_filter]
rintro a ⟨_, hp⟩ ⟨_, hq⟩
rw [Pi.disjoint_iff] at h
simpa [hp, hq] using h a
theorem disjoint_filter_filter_neg (s t : Finset α) (p : α → Prop)
[DecidablePred p] [∀ x, Decidable (¬p x)] :
Disjoint (s.filter p) (t.filter fun a => ¬p a) :=
disjoint_filter_filter' s t disjoint_compl_right
theorem filter_disj_union (s : Finset α) (t : Finset α) (h : Disjoint s t) :
filter p (disjUnion s t h) = (filter p s).disjUnion (filter p t) (disjoint_filter_filter h) :=
eq_of_veq <| Multiset.filter_add _ _ _
theorem filter_cons {a : α} (s : Finset α) (ha : a ∉ s) :
filter p (cons a s ha) =
if p a then cons a (filter p s) ((mem_of_mem_filter _).mt ha) else filter p s := by
split_ifs with h
· rw [filter_cons_of_pos _ _ _ ha h]
· rw [filter_cons_of_neg _ _ _ ha h]
section
variable [DecidableEq α]
theorem filter_union (s₁ s₂ : Finset α) : (s₁ ∪ s₂).filter p = s₁.filter p ∪ s₂.filter p :=
ext fun _ => by simp only [mem_filter, mem_union, or_and_right]
theorem filter_union_right (s : Finset α) : s.filter p ∪ s.filter q = s.filter fun x => p x ∨ q x :=
ext fun x => by simp [mem_filter, mem_union, ← and_or_left]
theorem filter_mem_eq_inter {s t : Finset α} [∀ i, Decidable (i ∈ t)] :
(s.filter fun i => i ∈ t) = s ∩ t :=
ext fun i => by simp [mem_filter, mem_inter]
theorem filter_inter_distrib (s t : Finset α) : (s ∩ t).filter p = s.filter p ∩ t.filter p := by
ext
simp [mem_filter, mem_inter, and_assoc]
theorem filter_inter (s t : Finset α) : filter p s ∩ t = filter p (s ∩ t) := by
ext
simp only [mem_inter, mem_filter, and_right_comm]
theorem inter_filter (s t : Finset α) : s ∩ filter p t = filter p (s ∩ t) := by
rw [inter_comm, filter_inter, inter_comm]
theorem filter_insert (a : α) (s : Finset α) :
filter p (insert a s) = if p a then insert a (filter p s) else filter p s := by
ext x
split_ifs with h <;> by_cases h' : x = a <;> simp [h, h']
theorem filter_erase (a : α) (s : Finset α) : filter p (erase s a) = erase (filter p s) a := by
ext x
simp only [and_assoc, mem_filter, iff_self, mem_erase]
theorem filter_or (s : Finset α) : (s.filter fun a => p a ∨ q a) = s.filter p ∪ s.filter q :=
ext fun _ => by simp [mem_filter, mem_union, and_or_left]
theorem filter_and (s : Finset α) : (s.filter fun a => p a ∧ q a) = s.filter p ∩ s.filter q :=
ext fun _ => by simp [mem_filter, mem_inter, and_comm, and_left_comm, and_self_iff, and_assoc]
theorem filter_not (s : Finset α) : (s.filter fun a => ¬p a) = s \ s.filter p :=
ext fun a => by
simp only [Bool.decide_coe, Bool.not_eq_true', mem_filter, and_comm, mem_sdiff, not_and_or,
Bool.not_eq_true, and_or_left, and_not_self, or_false]
lemma filter_and_not (s : Finset α) (p q : α → Prop) [DecidablePred p] [DecidablePred q] :
s.filter (fun a ↦ p a ∧ ¬ q a) = s.filter p \ s.filter q := by
rw [filter_and, filter_not, ← inter_sdiff_assoc, inter_eq_left.2 (filter_subset _ _)]
theorem sdiff_eq_filter (s₁ s₂ : Finset α) : s₁ \ s₂ = filter (· ∉ s₂) s₁ :=
ext fun _ => by simp [mem_sdiff, mem_filter]
theorem subset_union_elim {s : Finset α} {t₁ t₂ : Set α} (h : ↑s ⊆ t₁ ∪ t₂) :
∃ s₁ s₂ : Finset α, s₁ ∪ s₂ = s ∧ ↑s₁ ⊆ t₁ ∧ ↑s₂ ⊆ t₂ \ t₁ := by
classical
refine ⟨s.filter (· ∈ t₁), s.filter (· ∉ t₁), ?_, ?_, ?_⟩
· simp [filter_union_right, em]
· intro x
simp
· intro x
simp only [not_not, coe_filter, Set.mem_setOf_eq, Set.mem_diff, and_imp]
intro hx hx₂
exact ⟨Or.resolve_left (h hx) hx₂, hx₂⟩
-- This is not a good simp lemma, as it would prevent `Finset.mem_filter` from firing
-- on, e.g. `x ∈ s.filter (Eq b)`.
/-- After filtering out everything that does not equal a given value, at most that value remains.
This is equivalent to `filter_eq'` with the equality the other way.
-/
theorem filter_eq [DecidableEq β] (s : Finset β) (b : β) :
s.filter (Eq b) = ite (b ∈ s) {b} ∅ := by
split_ifs with h
· ext
simp only [mem_filter, mem_singleton, decide_eq_true_eq]
refine ⟨fun h => h.2.symm, ?_⟩
rintro rfl
exact ⟨h, rfl⟩
· ext
simp only [mem_filter, not_and, iff_false, not_mem_empty, decide_eq_true_eq]
rintro m rfl
exact h m
/-- After filtering out everything that does not equal a given value, at most that value remains.
This is equivalent to `filter_eq` with the equality the other way.
-/
theorem filter_eq' [DecidableEq β] (s : Finset β) (b : β) :
(s.filter fun a => a = b) = ite (b ∈ s) {b} ∅ :=
_root_.trans (filter_congr fun _ _ => by simp_rw [@eq_comm _ b]) (filter_eq s b)
theorem filter_ne [DecidableEq β] (s : Finset β) (b : β) :
(s.filter fun a => b ≠ a) = s.erase b := by
ext
simp only [mem_filter, mem_erase, Ne, decide_not, Bool.not_eq_true', decide_eq_false_iff_not]
tauto
theorem filter_ne' [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => a ≠ b) = s.erase b :=
_root_.trans (filter_congr fun _ _ => by simp_rw [@ne_comm _ b]) (filter_ne s b)
theorem filter_union_filter_of_codisjoint (s : Finset α) (h : Codisjoint p q) :
s.filter p ∪ s.filter q = s :=
(filter_or _ _ _).symm.trans <| filter_true_of_mem fun x _ => h.top_le x trivial
theorem filter_union_filter_neg_eq [∀ x, Decidable (¬p x)] (s : Finset α) :
(s.filter p ∪ s.filter fun a => ¬p a) = s :=
filter_union_filter_of_codisjoint _ _ _ <| @codisjoint_hnot_right _ _ p
end
end Filter
/-! ### range -/
section Range
open Nat
variable {n m l : ℕ}
@[simp]
theorem range_filter_eq {n m : ℕ} : (range n).filter (· = m) = if m < n then {m} else ∅ := by
convert filter_eq (range n) m using 2
· ext
rw [eq_comm]
· simp
end Range
end Finset
/-! ### dedup on list and multiset -/
namespace Multiset
variable [DecidableEq α] {s t : Multiset α}
@[simp]
theorem toFinset_add (s t : Multiset α) : toFinset (s + t) = toFinset s ∪ toFinset t :=
Finset.ext <| by simp
@[simp]
theorem toFinset_inter (s t : Multiset α) : toFinset (s ∩ t) = toFinset s ∩ toFinset t :=
Finset.ext <| by simp
@[simp]
theorem toFinset_union (s t : Multiset α) : (s ∪ t).toFinset = s.toFinset ∪ t.toFinset := by
ext; simp
@[simp]
theorem toFinset_eq_empty {m : Multiset α} : m.toFinset = ∅ ↔ m = 0 :=
Finset.val_inj.symm.trans Multiset.dedup_eq_zero
@[simp]
theorem toFinset_nonempty : s.toFinset.Nonempty ↔ s ≠ 0 := by
simp only [toFinset_eq_empty, Ne, Finset.nonempty_iff_ne_empty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
protected alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty
@[simp]
theorem toFinset_filter (s : Multiset α) (p : α → Prop) [DecidablePred p] :
Multiset.toFinset (s.filter p) = s.toFinset.filter p := by
ext; simp
end Multiset
namespace List
variable [DecidableEq α] {l l' : List α} {a : α} {f : α → β}
{s : Finset α} {t : Set β} {t' : Finset β}
@[simp]
theorem toFinset_union (l l' : List α) : (l ∪ l').toFinset = l.toFinset ∪ l'.toFinset := by
ext
simp
@[simp]
theorem toFinset_inter (l l' : List α) : (l ∩ l').toFinset = l.toFinset ∩ l'.toFinset := by
ext
simp
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty_iff
@[simp]
theorem toFinset_filter (s : List α) (p : α → Bool) :
(s.filter p).toFinset = s.toFinset.filter (p ·) := by
ext; simp [List.mem_filter]
end List
namespace Finset
section ToList
@[simp]
theorem toList_eq_nil {s : Finset α} : s.toList = [] ↔ s = ∅ :=
Multiset.toList_eq_nil.trans val_eq_zero
theorem empty_toList {s : Finset α} : s.toList.isEmpty ↔ s = ∅ := by simp
@[simp]
theorem toList_empty : (∅ : Finset α).toList = [] :=
toList_eq_nil.mpr rfl
theorem Nonempty.toList_ne_nil {s : Finset α} (hs : s.Nonempty) : s.toList ≠ [] :=
mt toList_eq_nil.mp hs.ne_empty
theorem Nonempty.not_empty_toList {s : Finset α} (hs : s.Nonempty) : ¬s.toList.isEmpty :=
mt empty_toList.mp hs.ne_empty
end ToList
/-! ### choose -/
section Choose
variable (p : α → Prop) [DecidablePred p] (l : Finset α)
/-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of
`l` satisfying `p` this unique element, as an element of the corresponding subtype. -/
def chooseX (hp : ∃! a, a ∈ l ∧ p a) : { a // a ∈ l ∧ p a } :=
Multiset.chooseX p l.val hp
/-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of
`l` satisfying `p` this unique element, as an element of the ambient type. -/
def choose (hp : ∃! a, a ∈ l ∧ p a) : α :=
chooseX p l hp
theorem choose_spec (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l ∧ p (choose p l hp) :=
(chooseX p l hp).property
theorem choose_mem (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l :=
(choose_spec _ _ _).1
theorem choose_property (hp : ∃! a, a ∈ l ∧ p a) : p (choose p l hp) :=
(choose_spec _ _ _).2
end Choose
end Finset
namespace Equiv
variable [DecidableEq α] {s t : Finset α}
open Finset
/-- The disjoint union of finsets is a sum -/
def Finset.union (s t : Finset α) (h : Disjoint s t) :
s ⊕ t ≃ (s ∪ t : Finset α) :=
Equiv.setCongr (coe_union _ _) |>.trans (Equiv.Set.union (disjoint_coe.mpr h)) |>.symm
@[simp]
theorem Finset.union_symm_inl (h : Disjoint s t) (x : s) :
Equiv.Finset.union s t h (Sum.inl x) = ⟨x, Finset.mem_union.mpr <| Or.inl x.2⟩ :=
rfl
@[simp]
theorem Finset.union_symm_inr (h : Disjoint s t) (y : t) :
Equiv.Finset.union s t h (Sum.inr y) = ⟨y, Finset.mem_union.mpr <| Or.inr y.2⟩ :=
rfl
/-- The type of dependent functions on the disjoint union of finsets `s ∪ t` is equivalent to the
type of pairs of functions on `s` and on `t`. This is similar to `Equiv.sumPiEquivProdPi`. -/
def piFinsetUnion {ι} [DecidableEq ι] (α : ι → Type*) {s t : Finset ι} (h : Disjoint s t) :
((∀ i : s, α i) × ∀ i : t, α i) ≃ ∀ i : (s ∪ t : Finset ι), α i :=
let e := Equiv.Finset.union s t h
sumPiEquivProdPi (fun b ↦ α (e b)) |>.symm.trans (.piCongrLeft (fun i : ↥(s ∪ t) ↦ α i) e)
/-- A finset is equivalent to its coercion as a set. -/
def _root_.Finset.equivToSet (s : Finset α) : s ≃ s.toSet where
toFun a := ⟨a.1, mem_coe.2 a.2⟩
invFun a := ⟨a.1, mem_coe.1 a.2⟩
left_inv := fun _ ↦ rfl
right_inv := fun _ ↦ rfl
end Equiv
namespace Multiset
variable [DecidableEq α]
@[simp]
lemma toFinset_replicate (n : ℕ) (a : α) :
(replicate n a).toFinset = if n = 0 then ∅ else {a} := by
ext x
simp only [mem_toFinset, Finset.mem_singleton, mem_replicate]
split_ifs with hn <;> simp [hn]
end Multiset
| Mathlib/Data/Finset/Basic.lean | 1,680 | 1,681 | |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Kevin Buzzard, Yury Kudryashov, Frédéric Dupuis,
Heather Macbeth
-/
import Mathlib.Algebra.Module.Submodule.Range
/-! ### Linear equivalences involving submodules -/
open Function
variable {R : Type*} {R₁ : Type*} {R₂ : Type*} {R₃ : Type*}
variable {M : Type*} {M₁ : Type*} {M₂ : Type*} {M₃ : Type*}
variable {N : Type*}
namespace LinearEquiv
section AddCommMonoid
section
variable [Semiring R] [Semiring R₂] [Semiring R₃]
variable [AddCommMonoid M] [AddCommMonoid M₂] [AddCommMonoid M₃]
variable {module_M : Module R M} {module_M₂ : Module R₂ M₂} {module_M₃ : Module R₃ M₃}
variable {σ₁₂ : R →+* R₂} {σ₂₁ : R₂ →+* R}
variable {σ₂₃ : R₂ →+* R₃} {σ₁₃ : R →+* R₃} [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃]
variable {σ₃₂ : R₃ →+* R₂}
variable {re₁₂ : RingHomInvPair σ₁₂ σ₂₁} {re₂₁ : RingHomInvPair σ₂₁ σ₁₂}
variable {re₂₃ : RingHomInvPair σ₂₃ σ₃₂} {re₃₂ : RingHomInvPair σ₃₂ σ₂₃}
variable (f : M →ₛₗ[σ₁₂] M₂) (g : M₂ →ₛₗ[σ₂₁] M) (e : M ≃ₛₗ[σ₁₂] M₂) (h : M₂ →ₛₗ[σ₂₃] M₃)
variable (p q : Submodule R M)
/-- Linear equivalence between two equal submodules. -/
def ofEq (h : p = q) : p ≃ₗ[R] q :=
{ Equiv.setCongr (congr_arg _ h) with
map_smul' := fun _ _ => rfl
map_add' := fun _ _ => rfl }
variable {p q}
@[simp]
theorem coe_ofEq_apply (h : p = q) (x : p) : (ofEq p q h x : M) = x :=
rfl
@[simp]
theorem ofEq_symm (h : p = q) : (ofEq p q h).symm = ofEq q p h.symm :=
rfl
@[simp]
theorem ofEq_rfl : ofEq p p rfl = LinearEquiv.refl R p := by ext; rfl
/-- A linear equivalence which maps a submodule of one module onto another, restricts to a linear
equivalence of the two submodules. -/
def ofSubmodules (p : Submodule R M) (q : Submodule R₂ M₂) (h : p.map (e : M →ₛₗ[σ₁₂] M₂) = q) :
p ≃ₛₗ[σ₁₂] q :=
(e.submoduleMap p).trans (LinearEquiv.ofEq _ _ h)
@[simp]
theorem ofSubmodules_apply {p : Submodule R M} {q : Submodule R₂ M₂} (h : p.map ↑e = q) (x : p) :
↑(e.ofSubmodules p q h x) = e x :=
rfl
@[simp]
theorem ofSubmodules_symm_apply {p : Submodule R M} {q : Submodule R₂ M₂} (h : p.map ↑e = q)
(x : q) : ↑((e.ofSubmodules p q h).symm x) = e.symm x :=
rfl
/-- A linear equivalence of two modules restricts to a linear equivalence from the preimage of any
submodule to that submodule.
This is `LinearEquiv.ofSubmodule` but with `comap` on the left instead of `map` on the right. -/
def ofSubmodule' [Module R M] [Module R₂ M₂] (f : M ≃ₛₗ[σ₁₂] M₂) (U : Submodule R₂ M₂) :
U.comap (f : M →ₛₗ[σ₁₂] M₂) ≃ₛₗ[σ₁₂] U :=
(f.symm.ofSubmodules _ _ f.symm.map_eq_comap).symm
theorem ofSubmodule'_toLinearMap [Module R M] [Module R₂ M₂] (f : M ≃ₛₗ[σ₁₂] M₂)
(U : Submodule R₂ M₂) :
(f.ofSubmodule' U).toLinearMap = (f.toLinearMap.domRestrict _).codRestrict _ Subtype.prop := by
ext
rfl
@[simp]
theorem ofSubmodule'_apply [Module R M] [Module R₂ M₂] (f : M ≃ₛₗ[σ₁₂] M₂) (U : Submodule R₂ M₂)
(x : U.comap (f : M →ₛₗ[σ₁₂] M₂)) : (f.ofSubmodule' U x : M₂) = f (x : M) :=
rfl
@[simp]
theorem ofSubmodule'_symm_apply [Module R M] [Module R₂ M₂] (f : M ≃ₛₗ[σ₁₂] M₂)
(U : Submodule R₂ M₂) (x : U) : ((f.ofSubmodule' U).symm x : M) = f.symm (x : M₂) :=
rfl
variable (p)
/-- The top submodule of `M` is linearly equivalent to `M`. -/
def ofTop (h : p = ⊤) : p ≃ₗ[R] M :=
{ p.subtype with
invFun := fun x => ⟨x, h.symm ▸ trivial⟩
left_inv := fun _ => rfl
right_inv := fun _ => rfl }
@[simp]
theorem ofTop_apply {h} (x : p) : ofTop p h x = x :=
rfl
@[simp]
theorem coe_ofTop_symm_apply {h} (x : M) : ((ofTop p h).symm x : M) = x :=
rfl
theorem ofTop_symm_apply {h} (x : M) : (ofTop p h).symm x = ⟨x, h.symm ▸ trivial⟩ :=
rfl
@[simp]
protected theorem range : LinearMap.range (e : M →ₛₗ[σ₁₂] M₂) = ⊤ :=
LinearMap.range_eq_top.2 e.toEquiv.surjective
@[simp]
protected theorem _root_.LinearEquivClass.range [Module R M] [Module R₂ M₂] {F : Type*}
[EquivLike F M M₂] [SemilinearEquivClass F σ₁₂ M M₂] (e : F) : LinearMap.range e = ⊤ :=
LinearMap.range_eq_top.2 (EquivLike.surjective e)
theorem eq_bot_of_equiv [Module R₂ M₂] (e : p ≃ₛₗ[σ₁₂] (⊥ : Submodule R₂ M₂)) : p = ⊥ := by
refine bot_unique (SetLike.le_def.2 fun b hb => (Submodule.mem_bot R).2 ?_)
rw [← p.mk_eq_zero hb, ← e.map_eq_zero_iff]
apply Submodule.eq_zero_of_bot_submodule
@[simp]
theorem range_comp [RingHomSurjective σ₂₃] [RingHomSurjective σ₁₃] :
LinearMap.range (h.comp (e : M →ₛₗ[σ₁₂] M₂) : M →ₛₗ[σ₁₃] M₃) = LinearMap.range h :=
LinearMap.range_comp_of_range_eq_top _ e.range
variable {f g}
/-- A linear map `f : M →ₗ[R] M₂` with a left-inverse `g : M₂ →ₗ[R] M` defines a linear
equivalence between `M` and `f.range`.
This is a computable alternative to `LinearEquiv.ofInjective`, and a bidirectional version of
`LinearMap.rangeRestrict`. -/
def ofLeftInverse [RingHomInvPair σ₁₂ σ₂₁] [RingHomInvPair σ₂₁ σ₁₂] {g : M₂ → M}
(h : Function.LeftInverse g f) : M ≃ₛₗ[σ₁₂] (LinearMap.range f) :=
| { LinearMap.rangeRestrict f with
toFun := LinearMap.rangeRestrict f
invFun := g ∘ (LinearMap.range f).subtype
left_inv := h
| Mathlib/Algebra/Module/Submodule/Equiv.lean | 141 | 144 |
/-
Copyright (c) 2020 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Yury Kudryashov
-/
import Mathlib.MeasureTheory.Integral.Bochner.ContinuousLinearMap
import Mathlib.MeasureTheory.Integral.Bochner.FundThmCalculus
import Mathlib.MeasureTheory.Integral.Bochner.Set
deprecated_module (since := "2025-04-15")
| Mathlib/MeasureTheory/Integral/SetIntegral.lean | 169 | 173 | |
/-
Copyright (c) 2024 Brendan Murphy. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Brendan Murphy
-/
import Mathlib.RingTheory.Regular.IsSMulRegular
import Mathlib.RingTheory.Artinian.Module
import Mathlib.RingTheory.Nakayama
import Mathlib.Algebra.Equiv.TransferInstance
import Mathlib.RingTheory.LocalRing.MaximalIdeal.Basic
import Mathlib.RingTheory.Noetherian.Basic
/-!
# Regular sequences and weakly regular sequences
The notion of a regular sequence is fundamental in commutative algebra.
Properties of regular sequences encode information about singularities of a
ring and regularity of a sequence can be tested homologically.
However the notion of a regular sequence is only really sensible for Noetherian local rings.
TODO: Koszul regular sequences, H_1-regular sequences, quasi-regular sequences, depth.
## Tags
module, regular element, regular sequence, commutative algebra
-/
universe u v
open scoped Pointwise
variable {R S M M₂ M₃ M₄ : Type*}
namespace Ideal
variable [Semiring R] [Semiring S]
/-- The ideal generated by a list of elements. -/
abbrev ofList (rs : List R) := span { r | r ∈ rs }
@[simp] lemma ofList_nil : (ofList [] : Ideal R) = ⊥ :=
have : { r | r ∈ [] } = ∅ := Set.eq_empty_of_forall_not_mem (fun _ => List.not_mem_nil)
Eq.trans (congrArg span this) span_empty
@[simp] lemma ofList_append (rs₁ rs₂ : List R) :
ofList (rs₁ ++ rs₂) = ofList rs₁ ⊔ ofList rs₂ :=
have : { r | r ∈ rs₁ ++ rs₂ } = _ := Set.ext (fun _ => List.mem_append)
Eq.trans (congrArg span this) (span_union _ _)
lemma ofList_singleton (r : R) : ofList [r] = span {r} :=
congrArg span (Set.ext fun _ => List.mem_singleton)
@[simp] lemma ofList_cons (r : R) (rs : List R) :
ofList (r::rs) = span {r} ⊔ ofList rs :=
Eq.trans (ofList_append [r] rs) (congrArg (· ⊔ _) (ofList_singleton r))
@[simp] lemma map_ofList (f : R →+* S) (rs : List R) :
map f (ofList rs) = ofList (rs.map f) :=
Eq.trans (map_span f { r | r ∈ rs }) <| congrArg span <|
Set.ext (fun _ => List.mem_map.symm)
lemma ofList_cons_smul {R} [CommSemiring R] (r : R) (rs : List R) {M}
[AddCommMonoid M] [Module R M] (N : Submodule R M) :
ofList (r :: rs) • N = r • N ⊔ ofList rs • N := by
rw [ofList_cons, Submodule.sup_smul, Submodule.ideal_span_singleton_smul]
end Ideal
namespace Submodule
lemma smul_top_le_comap_smul_top [Semiring R] [AddCommMonoid M]
[AddCommMonoid M₂] [Module R M] [Module R M₂] (I : Ideal R)
(f : M →ₗ[R] M₂) : I • ⊤ ≤ comap f (I • ⊤) :=
map_le_iff_le_comap.mp <| le_of_eq_of_le (map_smul'' _ _ _) <|
smul_mono_right _ le_top
variable (M) [CommRing R] [AddCommGroup M] [AddCommGroup M₂]
[Module R M] [Module R M₂] (r : R) (rs : List R)
/-- The equivalence between M ⧸ (r₀, r₁, …, rₙ)M and (M ⧸ r₀M) ⧸ (r₁, …, rₙ) (M ⧸ r₀M). -/
def quotOfListConsSMulTopEquivQuotSMulTopInner :
(M ⧸ (Ideal.ofList (r :: rs) • ⊤ : Submodule R M)) ≃ₗ[R]
QuotSMulTop r M ⧸ (Ideal.ofList rs • ⊤ : Submodule R (QuotSMulTop r M)) :=
quotEquivOfEq _ _ (Ideal.ofList_cons_smul r rs ⊤) ≪≫ₗ
(quotientQuotientEquivQuotientSup (r • ⊤) (Ideal.ofList rs • ⊤)).symm ≪≫ₗ
quotEquivOfEq _ _ (by rw [map_smul'', map_top, range_mkQ])
/-- The equivalence between M ⧸ (r₀, r₁, …, rₙ)M and (M ⧸ (r₁, …, rₙ)) ⧸ r₀ (M ⧸ (r₁, …, rₙ)). -/
def quotOfListConsSMulTopEquivQuotSMulTopOuter :
(M ⧸ (Ideal.ofList (r :: rs) • ⊤ : Submodule R M)) ≃ₗ[R]
QuotSMulTop r (M ⧸ (Ideal.ofList rs • ⊤ : Submodule R M)) :=
quotEquivOfEq _ _ (Eq.trans (Ideal.ofList_cons_smul r rs ⊤) (sup_comm _ _)) ≪≫ₗ
(quotientQuotientEquivQuotientSup (Ideal.ofList rs • ⊤) (r • ⊤)).symm ≪≫ₗ
quotEquivOfEq _ _ (by rw [map_pointwise_smul, map_top, range_mkQ])
variable {M}
lemma quotOfListConsSMulTopEquivQuotSMulTopInner_naturality (f : M →ₗ[R] M₂) :
(quotOfListConsSMulTopEquivQuotSMulTopInner M₂ r rs).toLinearMap ∘ₗ
mapQ _ _ _ (smul_top_le_comap_smul_top (Ideal.ofList (r :: rs)) f) =
mapQ _ _ _ (smul_top_le_comap_smul_top _ (QuotSMulTop.map r f)) ∘ₗ
(quotOfListConsSMulTopEquivQuotSMulTopInner M r rs).toLinearMap :=
quot_hom_ext _ _ _ fun _ => rfl
lemma top_eq_ofList_cons_smul_iff :
(⊤ : Submodule R M) = Ideal.ofList (r :: rs) • ⊤ ↔
(⊤ : Submodule R (QuotSMulTop r M)) = Ideal.ofList rs • ⊤ := by
conv => congr <;> rw [eq_comm, ← subsingleton_quotient_iff_eq_top]
exact (quotOfListConsSMulTopEquivQuotSMulTopInner M r rs).toEquiv.subsingleton_congr
end Submodule
namespace RingTheory.Sequence
open scoped TensorProduct List
open Function Submodule QuotSMulTop
variable (S M)
section Definitions
/-
In theory, regularity of `rs : List α` on `M` makes sense as soon as
`[Monoid α]`, `[AddCommGroup M]`, and `[DistribMulAction α M]`.
Instead of `Ideal.ofList (rs.take i) • (⊤ : Submodule R M)` we use
`⨆ (j : Fin i), rs[j] • (⊤ : AddSubgroup M)`.
However it's not clear that this is a useful generalization.
If we add the assumption `[SMulCommClass α α M]` this is essentially the same
as focusing on the commutative ring case, by passing to the monoid ring
`ℤ[abelianization of α]`.
-/
variable [CommRing R] [AddCommGroup M] [Module R M]
open Ideal
/-- A sequence `[r₁, …, rₙ]` is weakly regular on `M` iff `rᵢ` is regular on
`M⧸(r₁, …, rᵢ₋₁)M` for all `1 ≤ i ≤ n`. -/
@[mk_iff]
structure IsWeaklyRegular (rs : List R) : Prop where
regular_mod_prev : ∀ i (h : i < rs.length),
IsSMulRegular (M ⧸ (ofList (rs.take i) • ⊤ : Submodule R M)) rs[i]
lemma isWeaklyRegular_iff_Fin (rs : List R) :
IsWeaklyRegular M rs ↔ ∀ (i : Fin rs.length),
IsSMulRegular (M ⧸ (ofList (rs.take i) • ⊤ : Submodule R M)) rs[i] :=
Iff.trans (isWeaklyRegular_iff M rs) (Iff.symm Fin.forall_iff)
/-- A weakly regular sequence `rs` on `M` is regular if also `M/rsM ≠ 0`. -/
@[mk_iff]
structure IsRegular (rs : List R) : Prop extends IsWeaklyRegular M rs where
top_ne_smul : (⊤ : Submodule R M) ≠ Ideal.ofList rs • ⊤
end Definitions
section Congr
variable {S M} [CommRing R] [CommRing S] [AddCommGroup M] [AddCommGroup M₂]
[Module R M] [Module S M₂]
{σ : R →+* S} {σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
open DistribMulAction AddSubgroup in
private lemma _root_.AddHom.map_smul_top_toAddSubgroup_of_surjective
{f : M →+ M₂} {as : List R} {bs : List S} (hf : Function.Surjective f)
(h : List.Forall₂ (fun r s => ∀ x, f (r • x) = s • f x) as bs) :
(Ideal.ofList as • ⊤ : Submodule R M).toAddSubgroup.map f =
(Ideal.ofList bs • ⊤ : Submodule S M₂).toAddSubgroup := by
induction h with
| nil =>
convert AddSubgroup.map_bot f using 1 <;>
rw [Ideal.ofList_nil, bot_smul, bot_toAddSubgroup]
| @cons r s _ _ h _ ih =>
conv => congr <;> rw [Ideal.ofList_cons, sup_smul, sup_toAddSubgroup,
ideal_span_singleton_smul, pointwise_smul_toAddSubgroup,
top_toAddSubgroup, pointwise_smul_def]
apply DFunLike.ext (f.comp (toAddMonoidEnd R M r))
((toAddMonoidEnd S M₂ s).comp f) at h
rw [AddSubgroup.map_sup, ih, map_map, h, ← map_map,
map_top_of_surjective f hf]
lemma _root_.AddEquiv.isWeaklyRegular_congr {e : M ≃+ M₂} {as bs}
(h : List.Forall₂ (fun (r : R) (s : S) => ∀ x, e (r • x) = s • e x) as bs) :
IsWeaklyRegular M as ↔ IsWeaklyRegular M₂ bs := by
conv => congr <;> rw [isWeaklyRegular_iff_Fin]
let e' i : (M ⧸ (Ideal.ofList (as.take i) • ⊤ : Submodule R M)) ≃+
M₂ ⧸ (Ideal.ofList (bs.take i) • ⊤ : Submodule S M₂) :=
QuotientAddGroup.congr _ _ e <|
AddHom.map_smul_top_toAddSubgroup_of_surjective e.surjective <|
List.forall₂_take i h
refine (finCongr h.length_eq).forall_congr @fun _ => (e' _).isSMulRegular_congr ?_
exact (mkQ_surjective _).forall.mpr fun _ => congrArg (mkQ _) (h.get _ _ _)
lemma _root_.LinearEquiv.isWeaklyRegular_congr' (e : M ≃ₛₗ[σ] M₂) (rs : List R) :
IsWeaklyRegular M rs ↔ IsWeaklyRegular M₂ (rs.map σ) :=
e.toAddEquiv.isWeaklyRegular_congr <| List.forall₂_map_right_iff.mpr <|
List.forall₂_same.mpr fun r _ x => e.map_smul' r x
lemma _root_.LinearEquiv.isWeaklyRegular_congr [Module R M₂] (e : M ≃ₗ[R] M₂) (rs : List R) :
IsWeaklyRegular M rs ↔ IsWeaklyRegular M₂ rs :=
Iff.trans (e.isWeaklyRegular_congr' rs) <| iff_of_eq <| congrArg _ rs.map_id
lemma _root_.AddEquiv.isRegular_congr {e : M ≃+ M₂} {as bs}
(h : List.Forall₂ (fun (r : R) (s : S) => ∀ x, e (r • x) = s • e x) as bs) :
IsRegular M as ↔ IsRegular M₂ bs := by
conv => congr <;> rw [isRegular_iff, ne_eq, eq_comm,
← subsingleton_quotient_iff_eq_top]
let e' := QuotientAddGroup.congr _ _ e <|
AddHom.map_smul_top_toAddSubgroup_of_surjective e.surjective h
exact and_congr (e.isWeaklyRegular_congr h) e'.subsingleton_congr.not
lemma _root_.LinearEquiv.isRegular_congr' (e : M ≃ₛₗ[σ] M₂) (rs : List R) :
IsRegular M rs ↔ IsRegular M₂ (rs.map σ) :=
e.toAddEquiv.isRegular_congr <| List.forall₂_map_right_iff.mpr <|
List.forall₂_same.mpr fun r _ x => e.map_smul' r x
lemma _root_.LinearEquiv.isRegular_congr [Module R M₂] (e : M ≃ₗ[R] M₂) (rs : List R) :
IsRegular M rs ↔ IsRegular M₂ rs :=
Iff.trans (e.isRegular_congr' rs) <| iff_of_eq <| congrArg _ rs.map_id
end Congr
lemma isWeaklyRegular_map_algebraMap_iff [CommRing R] [CommRing S]
[Algebra R S] [AddCommGroup M] [Module R M] [Module S M]
[IsScalarTower R S M] (rs : List R) :
IsWeaklyRegular M (rs.map (algebraMap R S)) ↔ IsWeaklyRegular M rs :=
(AddEquiv.refl M).isWeaklyRegular_congr <| List.forall₂_map_left_iff.mpr <|
List.forall₂_same.mpr fun r _ => algebraMap_smul S r
variable [CommRing R] [AddCommGroup M] [AddCommGroup M₂] [AddCommGroup M₃]
[AddCommGroup M₄] [Module R M] [Module R M₂] [Module R M₃] [Module R M₄]
@[simp]
lemma isWeaklyRegular_cons_iff (r : R) (rs : List R) :
IsWeaklyRegular M (r :: rs) ↔
IsSMulRegular M r ∧ IsWeaklyRegular (QuotSMulTop r M) rs :=
have := Eq.trans (congrArg (· • ⊤) Ideal.ofList_nil) (bot_smul ⊤)
let e i := quotOfListConsSMulTopEquivQuotSMulTopInner M r (rs.take i)
Iff.trans (isWeaklyRegular_iff_Fin _ _) <| Iff.trans Fin.forall_iff_succ <|
and_congr ((quotEquivOfEqBot _ this).isSMulRegular_congr r) <|
Iff.trans (forall_congr' fun i => (e i).isSMulRegular_congr (rs.get i))
(isWeaklyRegular_iff_Fin _ _).symm
lemma isWeaklyRegular_cons_iff' (r : R) (rs : List R) :
IsWeaklyRegular M (r :: rs) ↔
IsSMulRegular M r ∧
IsWeaklyRegular (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r}))) :=
Iff.trans (isWeaklyRegular_cons_iff M r rs) <| and_congr_right' <|
Iff.symm <| isWeaklyRegular_map_algebraMap_iff (R ⧸ Ideal.span {r}) _ rs
@[simp]
lemma isRegular_cons_iff (r : R) (rs : List R) :
IsRegular M (r :: rs) ↔
IsSMulRegular M r ∧ IsRegular (QuotSMulTop r M) rs := by
rw [isRegular_iff, isRegular_iff, isWeaklyRegular_cons_iff M r rs,
ne_eq, top_eq_ofList_cons_smul_iff, and_assoc]
lemma isRegular_cons_iff' (r : R) (rs : List R) :
IsRegular M (r :: rs) ↔
IsSMulRegular M r ∧ IsRegular (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r}))) := by
conv => congr <;> rw [isRegular_iff, ne_eq]
rw [isWeaklyRegular_cons_iff', ← restrictScalars_inj R (R ⧸ _),
← Ideal.map_ofList, ← Ideal.Quotient.algebraMap_eq, Ideal.smul_restrictScalars,
restrictScalars_top, top_eq_ofList_cons_smul_iff, and_assoc]
variable {M}
namespace IsWeaklyRegular
variable (R M) in
@[simp] lemma nil : IsWeaklyRegular M ([] : List R) :=
.mk (False.elim <| Nat.not_lt_zero · ·)
lemma cons {r : R} {rs : List R} (h1 : IsSMulRegular M r)
(h2 : IsWeaklyRegular (QuotSMulTop r M) rs) : IsWeaklyRegular M (r :: rs) :=
(isWeaklyRegular_cons_iff M r rs).mpr ⟨h1, h2⟩
lemma cons' {r : R} {rs : List R} (h1 : IsSMulRegular M r)
(h2 : IsWeaklyRegular (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r})))) :
IsWeaklyRegular M (r :: rs) :=
(isWeaklyRegular_cons_iff' M r rs).mpr ⟨h1, h2⟩
/-- Weakly regular sequences can be inductively characterized by:
* The empty sequence is weakly regular on any module.
* If `r` is regular on `M` and `rs` is a weakly regular sequence on `M⧸rM` then
the sequence obtained from `rs` by prepending `r` is weakly regular on `M`.
This is the induction principle produced by the inductive definition above.
The motive will usually be valued in `Prop`, but `Sort*` works too. -/
@[induction_eliminator]
def recIterModByRegular
{motive : (M : Type v) → [AddCommGroup M] → [Module R M] → (rs : List R) →
IsWeaklyRegular M rs → Sort*}
(nil : (M : Type v) → [AddCommGroup M] → [Module R M] → motive M [] (nil R M))
(cons : {M : Type v} → [AddCommGroup M] → [Module R M] → (r : R) →
(rs : List R) → (h1 : IsSMulRegular M r) →
(h2 : IsWeaklyRegular (QuotSMulTop r M) rs) →
(ih : motive (QuotSMulTop r M) rs h2) → motive M (r :: rs) (cons h1 h2)) :
{M : Type v} → [AddCommGroup M] → [Module R M] → {rs : List R} →
(h : IsWeaklyRegular M rs) → motive M rs h
| M, _, _, [], _ => nil M
| M, _, _, r :: rs, h =>
let ⟨h1, h2⟩ := (isWeaklyRegular_cons_iff M r rs).mp h
cons r rs h1 h2 (recIterModByRegular nil cons h2)
/-- A simplified version of `IsWeaklyRegular.recIterModByRegular` where the
motive is not allowed to depend on the proof of `IsWeaklyRegular`. -/
def ndrecIterModByRegular
{motive : (M : Type v) → [AddCommGroup M] → [Module R M] → (rs : List R) → Sort*}
(nil : (M : Type v) → [AddCommGroup M] → [Module R M] → motive M [])
(cons : {M : Type v} → [AddCommGroup M] → [Module R M] → (r : R) →
(rs : List R) → IsSMulRegular M r → IsWeaklyRegular (QuotSMulTop r M) rs →
motive (QuotSMulTop r M) rs → motive M (r :: rs))
{M} [AddCommGroup M] [Module R M] {rs} :
IsWeaklyRegular M rs → motive M rs :=
recIterModByRegular (motive := fun M _ _ rs _ => motive M rs) nil cons
/-- An alternate induction principle from `IsWeaklyRegular.recIterModByRegular`
where we mod out by successive elements in both the module and the base ring.
This is useful for propagating certain properties of the initial `M`, e.g.
faithfulness or freeness, throughout the induction. -/
def recIterModByRegularWithRing
{motive : (R : Type u) → [CommRing R] → (M : Type v) → [AddCommGroup M] →
[Module R M] → (rs : List R) → IsWeaklyRegular M rs → Sort*}
(nil : (R : Type u) → [CommRing R] → (M : Type v) → [AddCommGroup M] →
[Module R M] → motive R M [] (nil R M))
(cons : {R : Type u} → [CommRing R] → {M : Type v} → [AddCommGroup M] →
[Module R M] → (r : R) → (rs : List R) → (h1 : IsSMulRegular M r) →
(h2 : IsWeaklyRegular (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r})))) →
(ih : motive (R ⧸ Ideal.span {r}) (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r}))) h2) →
motive R M (r :: rs) (cons' h1 h2)) :
{R : Type u} → [CommRing R] → {M : Type v} → [AddCommGroup M] →
[Module R M] → {rs : List R} → (h : IsWeaklyRegular M rs) → motive R M rs h
| R, _, M, _, _, [], _ => nil R M
| _, _, M, _, _, r :: rs, h =>
let ⟨h1, h2⟩ := (isWeaklyRegular_cons_iff' M r rs).mp h
cons r rs h1 h2 (recIterModByRegularWithRing nil cons h2)
termination_by _ _ _ _ _ rs => List.length rs
/-- A simplified version of `IsWeaklyRegular.recIterModByRegularWithRing` where
the motive is not allowed to depend on the proof of `IsWeaklyRegular`. -/
def ndrecWithRing
{motive : (R : Type u) → [CommRing R] → (M : Type v) →
[AddCommGroup M] → [Module R M] → (rs : List R) → Sort*}
(nil : (R : Type u) → [CommRing R] → (M : Type v) →
[AddCommGroup M] → [Module R M] → motive R M [])
(cons : {R : Type u} → [CommRing R] → {M : Type v} → [AddCommGroup M] →
[Module R M] → (r : R) → (rs : List R) → IsSMulRegular M r →
IsWeaklyRegular (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r}))) →
motive (R ⧸ Ideal.span {r}) (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r}))) → motive R M (r :: rs))
{R} [CommRing R] {M} [AddCommGroup M] [Module R M] {rs} :
IsWeaklyRegular M rs → motive R M rs :=
recIterModByRegularWithRing (motive := fun R _ M _ _ rs _ => motive R M rs)
nil cons
end IsWeaklyRegular
section
variable (M)
lemma isWeaklyRegular_singleton_iff (r : R) :
IsWeaklyRegular M [r] ↔ IsSMulRegular M r :=
Iff.trans (isWeaklyRegular_cons_iff M r []) (and_iff_left (.nil R _))
lemma isWeaklyRegular_append_iff (rs₁ rs₂ : List R) :
IsWeaklyRegular M (rs₁ ++ rs₂) ↔
IsWeaklyRegular M rs₁ ∧
IsWeaklyRegular (M ⧸ (Ideal.ofList rs₁ • ⊤ : Submodule R M)) rs₂ := by
induction rs₁ generalizing M with
| nil =>
refine Iff.symm <| Iff.trans (and_iff_right (.nil R M)) ?_
refine (quotEquivOfEqBot _ ?_).isWeaklyRegular_congr rs₂
rw [Ideal.ofList_nil, bot_smul]
| cons r rs₁ ih =>
let e := quotOfListConsSMulTopEquivQuotSMulTopInner M r rs₁
rw [List.cons_append, isWeaklyRegular_cons_iff, isWeaklyRegular_cons_iff,
ih, ← and_assoc, ← e.isWeaklyRegular_congr rs₂]
lemma isWeaklyRegular_append_iff' (rs₁ rs₂ : List R) :
IsWeaklyRegular M (rs₁ ++ rs₂) ↔
IsWeaklyRegular M rs₁ ∧
IsWeaklyRegular (M ⧸ (Ideal.ofList rs₁ • ⊤ : Submodule R M))
(rs₂.map (Ideal.Quotient.mk (Ideal.ofList rs₁))) :=
Iff.trans (isWeaklyRegular_append_iff M rs₁ rs₂) <| and_congr_right' <|
Iff.symm <| isWeaklyRegular_map_algebraMap_iff (R ⧸ Ideal.ofList rs₁) _ rs₂
end
namespace IsRegular
variable (R M) in
lemma nil [Nontrivial M] : IsRegular M ([] : List R) where
toIsWeaklyRegular := IsWeaklyRegular.nil R M
top_ne_smul h := by
rw [Ideal.ofList_nil, bot_smul, eq_comm, subsingleton_iff_bot_eq_top] at h
exact not_subsingleton M ((Submodule.subsingleton_iff _).mp h)
lemma cons {r : R} {rs : List R} (h1 : IsSMulRegular M r)
(h2 : IsRegular (QuotSMulTop r M) rs) : IsRegular M (r :: rs) :=
(isRegular_cons_iff M r rs).mpr ⟨h1, h2⟩
lemma cons' {r : R} {rs : List R} (h1 : IsSMulRegular M r)
(h2 : IsRegular (QuotSMulTop r M) (rs.map (Ideal.Quotient.mk (Ideal.span {r})))) :
IsRegular M (r :: rs) :=
(isRegular_cons_iff' M r rs).mpr ⟨h1, h2⟩
/-- Regular sequences can be inductively characterized by:
* The empty sequence is regular on any nonzero module.
* If `r` is regular on `M` and `rs` is a regular sequence on `M⧸rM` then the
sequence obtained from `rs` by prepending `r` is regular on `M`.
This is the induction principle produced by the inductive definition above.
The motive will usually be valued in `Prop`, but `Sort*` works too. -/
@[induction_eliminator]
def recIterModByRegular
{motive : (M : Type v) → [AddCommGroup M] → [Module R M] → (rs : List R) →
IsRegular M rs → Sort*}
(nil : (M : Type v) → [AddCommGroup M] → [Module R M] → [Nontrivial M] →
motive M [] (nil R M))
(cons : {M : Type v} → [AddCommGroup M] → [Module R M] → (r : R) →
(rs : List R) → (h1 : IsSMulRegular M r) → (h2 : IsRegular (QuotSMulTop r M) rs) →
(ih : motive (QuotSMulTop r M) rs h2) → motive M (r :: rs) (cons h1 h2))
{M} [AddCommGroup M] [Module R M] {rs} (h : IsRegular M rs) : motive M rs h :=
h.toIsWeaklyRegular.recIterModByRegular
(motive := fun N _ _ rs' h' => ∀ h'', motive N rs' ⟨h', h''⟩)
(fun N _ _ h' =>
haveI := (nontrivial_iff R).mp (nontrivial_of_ne _ _ h'); nil N)
(fun r rs' h1 h2 h3 h4 =>
have ⟨h5, h6⟩ := (isRegular_cons_iff _ _ _).mp ⟨h2.cons h1, h4⟩
cons r rs' h5 h6 (h3 h6.top_ne_smul))
h.top_ne_smul
/-- A simplified version of `IsRegular.recIterModByRegular` where the motive is
not allowed to depend on the proof of `IsRegular`. -/
def ndrecIterModByRegular
{motive : (M : Type v) → [AddCommGroup M] → [Module R M] → (rs : List R) → Sort*}
(nil : (M : Type v) → [AddCommGroup M] → [Module R M] → [Nontrivial M] → motive M [])
(cons : {M : Type v} → [AddCommGroup M] → [Module R M] → (r : R) →
(rs : List R) → IsSMulRegular M r → IsRegular (QuotSMulTop r M) rs →
motive (QuotSMulTop r M) rs → motive M (r :: rs))
{M} [AddCommGroup M] [Module R M] {rs} : IsRegular M rs → motive M rs :=
recIterModByRegular (motive := fun M _ _ rs _ => motive M rs) nil cons
/-- An alternate induction principle from `IsRegular.recIterModByRegular` where
we mod out by successive elements in both the module and the base ring. This is
useful for propagating certain properties of the initial `M`, e.g. faithfulness
or freeness, throughout the induction. -/
def recIterModByRegularWithRing
{motive : (R : Type u) → [CommRing R] → (M : Type v) → [AddCommGroup M] →
[Module R M] → (rs : List R) → IsRegular M rs → Sort*}
(nil : (R : Type u) → [CommRing R] → (M : Type v) → [AddCommGroup M] →
[Module R M] → [Nontrivial M] → motive R M [] (nil R M))
(cons : {R : Type u} → [CommRing R] → {M : Type v} → [AddCommGroup M] →
[Module R M] → (r : R) → (rs : List R) → (h1 : IsSMulRegular M r) →
(h2 : IsRegular (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r})))) →
(ih : motive (R ⧸ Ideal.span {r}) (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r}))) h2) →
motive R M (r :: rs) (cons' h1 h2))
{R} [CommRing R] {M} [AddCommGroup M] [Module R M] {rs}
(h : IsRegular M rs) : motive R M rs h :=
h.toIsWeaklyRegular.recIterModByRegularWithRing
(motive := fun R _ N _ _ rs' h' => ∀ h'', motive R N rs' ⟨h', h''⟩)
(fun R _ N _ _ h' =>
haveI := (nontrivial_iff R).mp (nontrivial_of_ne _ _ h'); nil R N)
(fun r rs' h1 h2 h3 h4 =>
have ⟨h5, h6⟩ := (isRegular_cons_iff' _ _ _).mp ⟨h2.cons' h1, h4⟩
cons r rs' h5 h6 <| h3 h6.top_ne_smul)
h.top_ne_smul
/-- A simplified version of `IsRegular.recIterModByRegularWithRing` where the
motive is not allowed to depend on the proof of `IsRegular`. -/
def ndrecIterModByRegularWithRing
{motive : (R : Type u) → [CommRing R] → (M : Type v) →
[AddCommGroup M] → [Module R M] → (rs : List R) → Sort*}
(nil : (R : Type u) → [CommRing R] → (M : Type v) →
[AddCommGroup M] → [Module R M] → [Nontrivial M] → motive R M [])
(cons : {R : Type u} → [CommRing R] → {M : Type v} →
[AddCommGroup M] → [Module R M] → (r : R) → (rs : List R) →
IsSMulRegular M r →
IsRegular (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r}))) →
motive (R ⧸ Ideal.span {r}) (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r}))) →
motive R M (r :: rs))
{R} [CommRing R] {M} [AddCommGroup M] [Module R M] {rs} :
IsRegular M rs → motive R M rs :=
recIterModByRegularWithRing (motive := fun R _ M _ _ rs _ => motive R M rs)
nil cons
lemma quot_ofList_smul_nontrivial {rs : List R} (h : IsRegular M rs)
(N : Submodule R M) : Nontrivial (M ⧸ Ideal.ofList rs • N) :=
Submodule.Quotient.nontrivial_of_lt_top _ <|
lt_of_le_of_lt (smul_mono_right _ le_top) h.top_ne_smul.symm.lt_top
lemma nontrivial {rs : List R} (h : IsRegular M rs) : Nontrivial M :=
haveI := quot_ofList_smul_nontrivial h ⊤
(mkQ_surjective (Ideal.ofList rs • ⊤ : Submodule R M)).nontrivial
end IsRegular
lemma isRegular_iff_isWeaklyRegular_of_subset_jacobson_annihilator
[Nontrivial M] [Module.Finite R M] {rs : List R}
(h : ∀ r ∈ rs, r ∈ Ideal.jacobson (Module.annihilator R M)) :
IsRegular M rs ↔ IsWeaklyRegular M rs :=
Iff.trans (isRegular_iff M rs) <| and_iff_left <|
top_ne_ideal_smul_of_le_jacobson_annihilator <| Ideal.span_le.mpr h
lemma _root_.IsLocalRing.isRegular_iff_isWeaklyRegular_of_subset_maximalIdeal
[IsLocalRing R] [Nontrivial M] [Module.Finite R M] {rs : List R}
(h : ∀ r ∈ rs, r ∈ IsLocalRing.maximalIdeal R) :
IsRegular M rs ↔ IsWeaklyRegular M rs :=
have H h' := bot_ne_top.symm <| annihilator_eq_top_iff.mp <|
Eq.trans annihilator_top h'
isRegular_iff_isWeaklyRegular_of_subset_jacobson_annihilator fun r hr =>
IsLocalRing.jacobson_eq_maximalIdeal (Module.annihilator R M) H ▸ h r hr
open IsWeaklyRegular IsArtinian in
lemma eq_nil_of_isRegular_on_artinian [IsArtinian R M] :
{rs : List R} → IsRegular M rs → rs = []
| [], _ => rfl
| r :: rs, h => by
rw [isRegular_iff, ne_comm, ← lt_top_iff_ne_top, Ideal.ofList_cons,
sup_smul, ideal_span_singleton_smul, isWeaklyRegular_cons_iff] at h
refine absurd ?_ (ne_of_lt (lt_of_le_of_lt le_sup_left h.right))
exact Eq.trans (Submodule.map_top _) <| LinearMap.range_eq_top.mpr <|
| surjective_of_injective_endomorphism (LinearMap.lsmul R M r) h.left.left
lemma IsWeaklyRegular.isWeaklyRegular_lTensor [Module.Flat R M₂]
{rs : List R} (h : IsWeaklyRegular M rs) :
IsWeaklyRegular (M₂ ⊗[R] M) rs := by
induction h with
| nil N => exact nil R (M₂ ⊗[R] N)
| @cons N _ _ r rs' h1 _ ih =>
| Mathlib/RingTheory/Regular/RegularSequence.lean | 533 | 540 |
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Sébastien Gouëzel, Frédéric Dupuis
-/
import Mathlib.Algebra.BigOperators.Field
import Mathlib.Analysis.Complex.Basic
import Mathlib.Analysis.InnerProductSpace.Defs
import Mathlib.GroupTheory.MonoidLocalization.Basic
/-!
# Properties of inner product spaces
This file proves many basic properties of inner product spaces (real or complex).
## Main results
- `inner_mul_inner_self_le`: the Cauchy-Schwartz inequality (one of many variants).
- `norm_inner_eq_norm_iff`: the equality criteion in the Cauchy-Schwartz inequality (also in many
variants).
- `inner_eq_sum_norm_sq_div_four`: the polarization identity.
## Tags
inner product space, Hilbert space, norm
-/
noncomputable section
open RCLike Real Filter Topology ComplexConjugate Finsupp
open LinearMap (BilinForm)
variable {𝕜 E F : Type*} [RCLike 𝕜]
section BasicProperties_Seminormed
open scoped InnerProductSpace
variable [SeminormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [SeminormedAddCommGroup F] [InnerProductSpace ℝ F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
local postfix:90 "†" => starRingEnd _
export InnerProductSpace (norm_sq_eq_re_inner)
@[simp]
theorem inner_conj_symm (x y : E) : ⟪y, x⟫† = ⟪x, y⟫ :=
InnerProductSpace.conj_inner_symm _ _
theorem real_inner_comm (x y : F) : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ :=
@inner_conj_symm ℝ _ _ _ _ x y
theorem inner_eq_zero_symm {x y : E} : ⟪x, y⟫ = 0 ↔ ⟪y, x⟫ = 0 := by
rw [← inner_conj_symm]
exact star_eq_zero
@[simp]
theorem inner_self_im (x : E) : im ⟪x, x⟫ = 0 := by rw [← @ofReal_inj 𝕜, im_eq_conj_sub]; simp
theorem inner_add_left (x y z : E) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
InnerProductSpace.add_left _ _ _
theorem inner_add_right (x y z : E) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]
simp only [inner_conj_symm]
theorem inner_re_symm (x y : E) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
theorem inner_im_symm (x y : E) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
section Algebra
variable {𝕝 : Type*} [CommSemiring 𝕝] [StarRing 𝕝] [Algebra 𝕝 𝕜] [Module 𝕝 E]
[IsScalarTower 𝕝 𝕜 E] [StarModule 𝕝 𝕜]
/-- See `inner_smul_left` for the common special when `𝕜 = 𝕝`. -/
lemma inner_smul_left_eq_star_smul (x y : E) (r : 𝕝) : ⟪r • x, y⟫ = r† • ⟪x, y⟫ := by
rw [← algebraMap_smul 𝕜 r, InnerProductSpace.smul_left, starRingEnd_apply, starRingEnd_apply,
← algebraMap_star_comm, ← smul_eq_mul, algebraMap_smul]
/-- Special case of `inner_smul_left_eq_star_smul` when the acting ring has a trivial star
(eg `ℕ`, `ℤ`, `ℚ≥0`, `ℚ`, `ℝ`). -/
lemma inner_smul_left_eq_smul [TrivialStar 𝕝] (x y : E) (r : 𝕝) : ⟪r • x, y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_left_eq_star_smul, starRingEnd_apply, star_trivial]
/-- See `inner_smul_right` for the common special when `𝕜 = 𝕝`. -/
lemma inner_smul_right_eq_smul (x y : E) (r : 𝕝) : ⟪x, r • y⟫ = r • ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left_eq_star_smul, starRingEnd_apply, starRingEnd_apply,
star_smul, star_star, ← starRingEnd_apply, inner_conj_symm]
end Algebra
/-- See `inner_smul_left_eq_star_smul` for the case of a general algebra action. -/
theorem inner_smul_left (x y : E) (r : 𝕜) : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
inner_smul_left_eq_star_smul ..
theorem real_inner_smul_left (x y : F) (r : ℝ) : ⟪r • x, y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_left _ _ _
theorem inner_smul_real_left (x y : E) (r : ℝ) : ⟪(r : 𝕜) • x, y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_left, conj_ofReal, Algebra.smul_def]
/-- See `inner_smul_right_eq_smul` for the case of a general algebra action. -/
theorem inner_smul_right (x y : E) (r : 𝕜) : ⟪x, r • y⟫ = r * ⟪x, y⟫ :=
inner_smul_right_eq_smul ..
theorem real_inner_smul_right (x y : F) (r : ℝ) : ⟪x, r • y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_right _ _ _
theorem inner_smul_real_right (x y : E) (r : ℝ) : ⟪x, (r : 𝕜) • y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_right, Algebra.smul_def]
/-- The inner product as a sesquilinear form.
Note that in the case `𝕜 = ℝ` this is a bilinear form. -/
@[simps!]
def sesqFormOfInner : E →ₗ[𝕜] E →ₗ⋆[𝕜] 𝕜 :=
LinearMap.mk₂'ₛₗ (RingHom.id 𝕜) (starRingEnd _) (fun x y => ⟪y, x⟫)
(fun _x _y _z => inner_add_right _ _ _) (fun _r _x _y => inner_smul_right _ _ _)
(fun _x _y _z => inner_add_left _ _ _) fun _r _x _y => inner_smul_left _ _ _
/-- The real inner product as a bilinear form.
Note that unlike `sesqFormOfInner`, this does not reverse the order of the arguments. -/
@[simps!]
def bilinFormOfRealInner : BilinForm ℝ F := sesqFormOfInner.flip
/-- An inner product with a sum on the left. -/
theorem sum_inner {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪∑ i ∈ s, f i, x⟫ = ∑ i ∈ s, ⟪f i, x⟫ :=
map_sum (sesqFormOfInner (𝕜 := 𝕜) (E := E) x) _ _
/-- An inner product with a sum on the right. -/
theorem inner_sum {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪x, ∑ i ∈ s, f i⟫ = ∑ i ∈ s, ⟪x, f i⟫ :=
map_sum (LinearMap.flip sesqFormOfInner x) _ _
/-- An inner product with a sum on the left, `Finsupp` version. -/
protected theorem Finsupp.sum_inner {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪l.sum fun (i : ι) (a : 𝕜) => a • v i, x⟫ = l.sum fun (i : ι) (a : 𝕜) => conj a • ⟪v i, x⟫ := by
convert sum_inner (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_left, Finsupp.sum, smul_eq_mul]
/-- An inner product with a sum on the right, `Finsupp` version. -/
protected theorem Finsupp.inner_sum {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪x, l.sum fun (i : ι) (a : 𝕜) => a • v i⟫ = l.sum fun (i : ι) (a : 𝕜) => a • ⟪x, v i⟫ := by
convert inner_sum (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_right, Finsupp.sum, smul_eq_mul]
protected theorem DFinsupp.sum_inner {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪l.sum f, x⟫ = l.sum fun i a => ⟪f i a, x⟫ := by
simp +contextual only [DFinsupp.sum, sum_inner, smul_eq_mul]
protected theorem DFinsupp.inner_sum {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪x, l.sum f⟫ = l.sum fun i a => ⟪x, f i a⟫ := by
simp +contextual only [DFinsupp.sum, inner_sum, smul_eq_mul]
@[simp]
theorem inner_zero_left (x : E) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : E), inner_smul_left, RingHom.map_zero, zero_mul]
theorem inner_re_zero_left (x : E) : re ⟪0, x⟫ = 0 := by
simp only [inner_zero_left, AddMonoidHom.map_zero]
@[simp]
theorem inner_zero_right (x : E) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left, RingHom.map_zero]
theorem inner_re_zero_right (x : E) : re ⟪x, 0⟫ = 0 := by
simp only [inner_zero_right, AddMonoidHom.map_zero]
theorem inner_self_nonneg {x : E} : 0 ≤ re ⟪x, x⟫ :=
PreInnerProductSpace.toCore.re_inner_nonneg x
theorem real_inner_self_nonneg {x : F} : 0 ≤ ⟪x, x⟫_ℝ :=
@inner_self_nonneg ℝ F _ _ _ x
@[simp]
theorem inner_self_ofReal_re (x : E) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ :=
((RCLike.is_real_TFAE (⟪x, x⟫ : 𝕜)).out 2 3).2 (inner_self_im (𝕜 := 𝕜) x)
theorem inner_self_eq_norm_sq_to_K (x : E) : ⟪x, x⟫ = (‖x‖ : 𝕜) ^ 2 := by
rw [← inner_self_ofReal_re, ← norm_sq_eq_re_inner, ofReal_pow]
theorem inner_self_re_eq_norm (x : E) : re ⟪x, x⟫ = ‖⟪x, x⟫‖ := by
conv_rhs => rw [← inner_self_ofReal_re]
symm
exact norm_of_nonneg inner_self_nonneg
theorem inner_self_ofReal_norm (x : E) : (‖⟪x, x⟫‖ : 𝕜) = ⟪x, x⟫ := by
rw [← inner_self_re_eq_norm]
exact inner_self_ofReal_re _
theorem real_inner_self_abs (x : F) : |⟪x, x⟫_ℝ| = ⟪x, x⟫_ℝ :=
@inner_self_ofReal_norm ℝ F _ _ _ x
theorem norm_inner_symm (x y : E) : ‖⟪x, y⟫‖ = ‖⟪y, x⟫‖ := by rw [← inner_conj_symm, norm_conj]
@[simp]
theorem inner_neg_left (x y : E) : ⟪-x, y⟫ = -⟪x, y⟫ := by
rw [← neg_one_smul 𝕜 x, inner_smul_left]
simp
@[simp]
theorem inner_neg_right (x y : E) : ⟪x, -y⟫ = -⟪x, y⟫ := by
rw [← inner_conj_symm, inner_neg_left]; simp only [RingHom.map_neg, inner_conj_symm]
theorem inner_neg_neg (x y : E) : ⟪-x, -y⟫ = ⟪x, y⟫ := by simp
theorem inner_self_conj (x : E) : ⟪x, x⟫† = ⟪x, x⟫ := inner_conj_symm _ _
theorem inner_sub_left (x y z : E) : ⟪x - y, z⟫ = ⟪x, z⟫ - ⟪y, z⟫ := by
simp [sub_eq_add_neg, inner_add_left]
theorem inner_sub_right (x y z : E) : ⟪x, y - z⟫ = ⟪x, y⟫ - ⟪x, z⟫ := by
simp [sub_eq_add_neg, inner_add_right]
theorem inner_mul_symm_re_eq_norm (x y : E) : re (⟪x, y⟫ * ⟪y, x⟫) = ‖⟪x, y⟫ * ⟪y, x⟫‖ := by
rw [← inner_conj_symm, mul_comm]
exact re_eq_norm_of_mul_conj (inner y x)
/-- Expand `⟪x + y, x + y⟫` -/
theorem inner_add_add_self (x y : E) : ⟪x + y, x + y⟫ = ⟪x, x⟫ + ⟪x, y⟫ + ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_add_left, inner_add_right]; ring
/-- Expand `⟪x + y, x + y⟫_ℝ` -/
theorem real_inner_add_add_self (x y : F) :
⟪x + y, x + y⟫_ℝ = ⟪x, x⟫_ℝ + 2 * ⟪x, y⟫_ℝ + ⟪y, y⟫_ℝ := by
have : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ := by rw [← inner_conj_symm]; rfl
simp only [inner_add_add_self, this, add_left_inj]
ring
-- Expand `⟪x - y, x - y⟫`
theorem inner_sub_sub_self (x y : E) : ⟪x - y, x - y⟫ = ⟪x, x⟫ - ⟪x, y⟫ - ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_sub_left, inner_sub_right]; ring
/-- Expand `⟪x - y, x - y⟫_ℝ` -/
theorem real_inner_sub_sub_self (x y : F) :
⟪x - y, x - y⟫_ℝ = ⟪x, x⟫_ℝ - 2 * ⟪x, y⟫_ℝ + ⟪y, y⟫_ℝ := by
have : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ := by rw [← inner_conj_symm]; rfl
simp only [inner_sub_sub_self, this, add_left_inj]
ring
/-- Parallelogram law -/
theorem parallelogram_law {x y : E} : ⟪x + y, x + y⟫ + ⟪x - y, x - y⟫ = 2 * (⟪x, x⟫ + ⟪y, y⟫) := by
simp only [inner_add_add_self, inner_sub_sub_self]
ring
/-- **Cauchy–Schwarz inequality**. -/
theorem inner_mul_inner_self_le (x y : E) : ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ :=
letI cd : PreInnerProductSpace.Core 𝕜 E := PreInnerProductSpace.toCore
InnerProductSpace.Core.inner_mul_inner_self_le x y
/-- Cauchy–Schwarz inequality for real inner products. -/
theorem real_inner_mul_inner_self_le (x y : F) : ⟪x, y⟫_ℝ * ⟪x, y⟫_ℝ ≤ ⟪x, x⟫_ℝ * ⟪y, y⟫_ℝ :=
calc
⟪x, y⟫_ℝ * ⟪x, y⟫_ℝ ≤ ‖⟪x, y⟫_ℝ‖ * ‖⟪y, x⟫_ℝ‖ := by
rw [real_inner_comm y, ← norm_mul]
exact le_abs_self _
_ ≤ ⟪x, x⟫_ℝ * ⟪y, y⟫_ℝ := @inner_mul_inner_self_le ℝ _ _ _ _ x y
end BasicProperties_Seminormed
section BasicProperties
variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [NormedAddCommGroup F] [InnerProductSpace ℝ F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
export InnerProductSpace (norm_sq_eq_re_inner)
@[simp]
theorem inner_self_eq_zero {x : E} : ⟪x, x⟫ = 0 ↔ x = 0 := by
rw [inner_self_eq_norm_sq_to_K, sq_eq_zero_iff, ofReal_eq_zero, norm_eq_zero]
theorem inner_self_ne_zero {x : E} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
variable (𝕜)
theorem ext_inner_left {x y : E} (h : ∀ v, ⟪v, x⟫ = ⟪v, y⟫) : x = y := by
rw [← sub_eq_zero, ← @inner_self_eq_zero 𝕜, inner_sub_right, sub_eq_zero, h (x - y)]
theorem ext_inner_right {x y : E} (h : ∀ v, ⟪x, v⟫ = ⟪y, v⟫) : x = y := by
rw [← sub_eq_zero, ← @inner_self_eq_zero 𝕜, inner_sub_left, sub_eq_zero, h (x - y)]
variable {𝕜}
@[simp]
theorem re_inner_self_nonpos {x : E} : re ⟪x, x⟫ ≤ 0 ↔ x = 0 := by
rw [← norm_sq_eq_re_inner, (sq_nonneg _).le_iff_eq, sq_eq_zero_iff, norm_eq_zero]
@[simp]
lemma re_inner_self_pos {x : E} : 0 < re ⟪x, x⟫ ↔ x ≠ 0 := by
simpa [-re_inner_self_nonpos] using re_inner_self_nonpos (𝕜 := 𝕜) (x := x).not
@[deprecated (since := "2025-04-22")] alias inner_self_nonpos := re_inner_self_nonpos
@[deprecated (since := "2025-04-22")] alias inner_self_pos := re_inner_self_pos
open scoped InnerProductSpace in
theorem real_inner_self_nonpos {x : F} : ⟪x, x⟫_ℝ ≤ 0 ↔ x = 0 := re_inner_self_nonpos (𝕜 := ℝ)
open scoped InnerProductSpace in
theorem real_inner_self_pos {x : F} : 0 < ⟪x, x⟫_ℝ ↔ x ≠ 0 := re_inner_self_pos (𝕜 := ℝ)
/-- A family of vectors is linearly independent if they are nonzero
and orthogonal. -/
theorem linearIndependent_of_ne_zero_of_inner_eq_zero {ι : Type*} {v : ι → E} (hz : ∀ i, v i ≠ 0)
(ho : Pairwise fun i j => ⟪v i, v j⟫ = 0) : LinearIndependent 𝕜 v := by
rw [linearIndependent_iff']
intro s g hg i hi
have h' : g i * inner (v i) (v i) = inner (v i) (∑ j ∈ s, g j • v j) := by
rw [inner_sum]
symm
convert Finset.sum_eq_single (M := 𝕜) i ?_ ?_
· rw [inner_smul_right]
· intro j _hj hji
rw [inner_smul_right, ho hji.symm, mul_zero]
· exact fun h => False.elim (h hi)
simpa [hg, hz] using h'
end BasicProperties
section Norm_Seminormed
open scoped InnerProductSpace
variable [SeminormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [SeminormedAddCommGroup F] [InnerProductSpace ℝ F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
local notation "IK" => @RCLike.I 𝕜 _
theorem norm_eq_sqrt_re_inner (x : E) : ‖x‖ = √(re ⟪x, x⟫) :=
calc
‖x‖ = √(‖x‖ ^ 2) := (sqrt_sq (norm_nonneg _)).symm
_ = √(re ⟪x, x⟫) := congr_arg _ (norm_sq_eq_re_inner _)
@[deprecated (since := "2025-04-22")] alias norm_eq_sqrt_inner := norm_eq_sqrt_re_inner
theorem norm_eq_sqrt_real_inner (x : F) : ‖x‖ = √⟪x, x⟫_ℝ :=
@norm_eq_sqrt_re_inner ℝ _ _ _ _ x
theorem inner_self_eq_norm_mul_norm (x : E) : re ⟪x, x⟫ = ‖x‖ * ‖x‖ := by
rw [@norm_eq_sqrt_re_inner 𝕜, ← sqrt_mul inner_self_nonneg (re ⟪x, x⟫),
sqrt_mul_self inner_self_nonneg]
theorem inner_self_eq_norm_sq (x : E) : re ⟪x, x⟫ = ‖x‖ ^ 2 := by
rw [pow_two, inner_self_eq_norm_mul_norm]
theorem real_inner_self_eq_norm_mul_norm (x : F) : ⟪x, x⟫_ℝ = ‖x‖ * ‖x‖ := by
have h := @inner_self_eq_norm_mul_norm ℝ F _ _ _ x
simpa using h
theorem real_inner_self_eq_norm_sq (x : F) : ⟪x, x⟫_ℝ = ‖x‖ ^ 2 := by
rw [pow_two, real_inner_self_eq_norm_mul_norm]
/-- Expand the square -/
theorem norm_add_sq (x y : E) : ‖x + y‖ ^ 2 = ‖x‖ ^ 2 + 2 * re ⟪x, y⟫ + ‖y‖ ^ 2 := by
repeat' rw [sq (M := ℝ), ← @inner_self_eq_norm_mul_norm 𝕜]
rw [inner_add_add_self, two_mul]
simp only [add_assoc, add_left_inj, add_right_inj, AddMonoidHom.map_add]
rw [← inner_conj_symm, conj_re]
alias norm_add_pow_two := norm_add_sq
/-- Expand the square -/
theorem norm_add_sq_real (x y : F) : ‖x + y‖ ^ 2 = ‖x‖ ^ 2 + 2 * ⟪x, y⟫_ℝ + ‖y‖ ^ 2 := by
have h := @norm_add_sq ℝ _ _ _ _ x y
simpa using h
alias norm_add_pow_two_real := norm_add_sq_real
/-- Expand the square -/
theorem norm_add_mul_self (x y : E) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + 2 * re ⟪x, y⟫ + ‖y‖ * ‖y‖ := by
repeat' rw [← sq (M := ℝ)]
exact norm_add_sq _ _
/-- Expand the square -/
theorem norm_add_mul_self_real (x y : F) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + 2 * ⟪x, y⟫_ℝ + ‖y‖ * ‖y‖ := by
have h := @norm_add_mul_self ℝ _ _ _ _ x y
simpa using h
/-- Expand the square -/
theorem norm_sub_sq (x y : E) : ‖x - y‖ ^ 2 = ‖x‖ ^ 2 - 2 * re ⟪x, y⟫ + ‖y‖ ^ 2 := by
rw [sub_eq_add_neg, @norm_add_sq 𝕜 _ _ _ _ x (-y), norm_neg, inner_neg_right, map_neg, mul_neg,
sub_eq_add_neg]
alias norm_sub_pow_two := norm_sub_sq
/-- Expand the square -/
theorem norm_sub_sq_real (x y : F) : ‖x - y‖ ^ 2 = ‖x‖ ^ 2 - 2 * ⟪x, y⟫_ℝ + ‖y‖ ^ 2 :=
@norm_sub_sq ℝ _ _ _ _ _ _
alias norm_sub_pow_two_real := norm_sub_sq_real
/-- Expand the square -/
theorem norm_sub_mul_self (x y : E) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ - 2 * re ⟪x, y⟫ + ‖y‖ * ‖y‖ := by
repeat' rw [← sq (M := ℝ)]
exact norm_sub_sq _ _
/-- Expand the square -/
theorem norm_sub_mul_self_real (x y : F) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ - 2 * ⟪x, y⟫_ℝ + ‖y‖ * ‖y‖ := by
have h := @norm_sub_mul_self ℝ _ _ _ _ x y
simpa using h
/-- Cauchy–Schwarz inequality with norm -/
theorem norm_inner_le_norm (x y : E) : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ := by
rw [norm_eq_sqrt_re_inner (𝕜 := 𝕜) x, norm_eq_sqrt_re_inner (𝕜 := 𝕜) y]
letI : PreInnerProductSpace.Core 𝕜 E := PreInnerProductSpace.toCore
exact InnerProductSpace.Core.norm_inner_le_norm x y
theorem nnnorm_inner_le_nnnorm (x y : E) : ‖⟪x, y⟫‖₊ ≤ ‖x‖₊ * ‖y‖₊ :=
norm_inner_le_norm x y
theorem re_inner_le_norm (x y : E) : re ⟪x, y⟫ ≤ ‖x‖ * ‖y‖ :=
le_trans (re_le_norm (inner x y)) (norm_inner_le_norm x y)
/-- Cauchy–Schwarz inequality with norm -/
theorem abs_real_inner_le_norm (x y : F) : |⟪x, y⟫_ℝ| ≤ ‖x‖ * ‖y‖ :=
(Real.norm_eq_abs _).ge.trans (norm_inner_le_norm x y)
/-- Cauchy–Schwarz inequality with norm -/
theorem real_inner_le_norm (x y : F) : ⟪x, y⟫_ℝ ≤ ‖x‖ * ‖y‖ :=
le_trans (le_abs_self _) (abs_real_inner_le_norm _ _)
lemma inner_eq_zero_of_left {x : E} (y : E) (h : ‖x‖ = 0) : ⟪x, y⟫_𝕜 = 0 := by
rw [← norm_eq_zero]
refine le_antisymm ?_ (by positivity)
exact norm_inner_le_norm _ _ |>.trans <| by simp [h]
lemma inner_eq_zero_of_right (x : E) {y : E} (h : ‖y‖ = 0) : ⟪x, y⟫_𝕜 = 0 := by
rw [inner_eq_zero_symm, inner_eq_zero_of_left _ h]
variable (𝕜)
include 𝕜 in
theorem parallelogram_law_with_norm (x y : E) :
‖x + y‖ * ‖x + y‖ + ‖x - y‖ * ‖x - y‖ = 2 * (‖x‖ * ‖x‖ + ‖y‖ * ‖y‖) := by
simp only [← @inner_self_eq_norm_mul_norm 𝕜]
rw [← re.map_add, parallelogram_law, two_mul, two_mul]
simp only [re.map_add]
include 𝕜 in
theorem parallelogram_law_with_nnnorm (x y : E) :
‖x + y‖₊ * ‖x + y‖₊ + ‖x - y‖₊ * ‖x - y‖₊ = 2 * (‖x‖₊ * ‖x‖₊ + ‖y‖₊ * ‖y‖₊) :=
Subtype.ext <| parallelogram_law_with_norm 𝕜 x y
variable {𝕜}
/-- Polarization identity: The real part of the inner product, in terms of the norm. -/
theorem re_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two (x y : E) :
re ⟪x, y⟫ = (‖x + y‖ * ‖x + y‖ - ‖x‖ * ‖x‖ - ‖y‖ * ‖y‖) / 2 := by
rw [@norm_add_mul_self 𝕜]
ring
/-- Polarization identity: The real part of the inner product, in terms of the norm. -/
theorem re_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two (x y : E) :
re ⟪x, y⟫ = (‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ - ‖x - y‖ * ‖x - y‖) / 2 := by
rw [@norm_sub_mul_self 𝕜]
ring
/-- Polarization identity: The real part of the inner product, in terms of the norm. -/
theorem re_inner_eq_norm_add_mul_self_sub_norm_sub_mul_self_div_four (x y : E) :
re ⟪x, y⟫ = (‖x + y‖ * ‖x + y‖ - ‖x - y‖ * ‖x - y‖) / 4 := by
rw [@norm_add_mul_self 𝕜, @norm_sub_mul_self 𝕜]
ring
/-- Polarization identity: The imaginary part of the inner product, in terms of the norm. -/
theorem im_inner_eq_norm_sub_i_smul_mul_self_sub_norm_add_i_smul_mul_self_div_four (x y : E) :
im ⟪x, y⟫ = (‖x - IK • y‖ * ‖x - IK • y‖ - ‖x + IK • y‖ * ‖x + IK • y‖) / 4 := by
simp only [@norm_add_mul_self 𝕜, @norm_sub_mul_self 𝕜, inner_smul_right, I_mul_re]
ring
/-- Polarization identity: The inner product, in terms of the norm. -/
theorem inner_eq_sum_norm_sq_div_four (x y : E) :
⟪x, y⟫ = ((‖x + y‖ : 𝕜) ^ 2 - (‖x - y‖ : 𝕜) ^ 2 +
((‖x - IK • y‖ : 𝕜) ^ 2 - (‖x + IK • y‖ : 𝕜) ^ 2) * IK) / 4 := by
rw [← re_add_im ⟪x, y⟫, re_inner_eq_norm_add_mul_self_sub_norm_sub_mul_self_div_four,
im_inner_eq_norm_sub_i_smul_mul_self_sub_norm_add_i_smul_mul_self_div_four]
push_cast
simp only [sq, ← mul_div_right_comm, ← add_div]
/-- Polarization identity: The real inner product, in terms of the norm. -/
theorem real_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two (x y : F) :
⟪x, y⟫_ℝ = (‖x + y‖ * ‖x + y‖ - ‖x‖ * ‖x‖ - ‖y‖ * ‖y‖) / 2 :=
re_to_real.symm.trans <|
re_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two x y
/-- Polarization identity: The real inner product, in terms of the norm. -/
theorem real_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two (x y : F) :
⟪x, y⟫_ℝ = (‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ - ‖x - y‖ * ‖x - y‖) / 2 :=
re_to_real.symm.trans <|
re_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two x y
/-- Pythagorean theorem, if-and-only-if vector inner product form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero (x y : F) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ ↔ ⟪x, y⟫_ℝ = 0 := by
rw [@norm_add_mul_self ℝ, add_right_cancel_iff, add_eq_left, mul_eq_zero]
norm_num
/-- Pythagorean theorem, if-and-if vector inner product form using square roots. -/
theorem norm_add_eq_sqrt_iff_real_inner_eq_zero {x y : F} :
‖x + y‖ = √(‖x‖ * ‖x‖ + ‖y‖ * ‖y‖) ↔ ⟪x, y⟫_ℝ = 0 := by
rw [← norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero, eq_comm, sqrt_eq_iff_mul_self_eq,
eq_comm] <;> positivity
/-- Pythagorean theorem, vector inner product form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero (x y : E) (h : ⟪x, y⟫ = 0) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ := by
rw [@norm_add_mul_self 𝕜, add_right_cancel_iff, add_eq_left, mul_eq_zero]
apply Or.inr
simp only [h, zero_re']
/-- Pythagorean theorem, vector inner product form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq_real {x y : F} (h : ⟪x, y⟫_ℝ = 0) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ :=
(norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero x y).2 h
/-- Pythagorean theorem, subtracting vectors, if-and-only-if vector
inner product form. -/
theorem norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero (x y : F) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ ↔ ⟪x, y⟫_ℝ = 0 := by
rw [@norm_sub_mul_self ℝ, add_right_cancel_iff, sub_eq_add_neg, add_eq_left, neg_eq_zero,
mul_eq_zero]
norm_num
/-- Pythagorean theorem, subtracting vectors, if-and-if vector inner product form using square
roots. -/
theorem norm_sub_eq_sqrt_iff_real_inner_eq_zero {x y : F} :
‖x - y‖ = √(‖x‖ * ‖x‖ + ‖y‖ * ‖y‖) ↔ ⟪x, y⟫_ℝ = 0 := by
rw [← norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero, eq_comm, sqrt_eq_iff_mul_self_eq,
eq_comm] <;> positivity
/-- Pythagorean theorem, subtracting vectors, vector inner product
form. -/
theorem norm_sub_sq_eq_norm_sq_add_norm_sq_real {x y : F} (h : ⟪x, y⟫_ℝ = 0) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ :=
(norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero x y).2 h
/-- The sum and difference of two vectors are orthogonal if and only
if they have the same norm. -/
theorem real_inner_add_sub_eq_zero_iff (x y : F) : ⟪x + y, x - y⟫_ℝ = 0 ↔ ‖x‖ = ‖y‖ := by
conv_rhs => rw [← mul_self_inj_of_nonneg (norm_nonneg _) (norm_nonneg _)]
simp only [← @inner_self_eq_norm_mul_norm ℝ, inner_add_left, inner_sub_right, real_inner_comm y x,
sub_eq_zero, re_to_real]
constructor
· intro h
rw [add_comm] at h
linarith
· intro h
linarith
/-- Given two orthogonal vectors, their sum and difference have equal norms. -/
theorem norm_sub_eq_norm_add {v w : E} (h : ⟪v, w⟫ = 0) : ‖w - v‖ = ‖w + v‖ := by
rw [← mul_self_inj_of_nonneg (norm_nonneg _) (norm_nonneg _)]
simp only [h, ← @inner_self_eq_norm_mul_norm 𝕜, sub_neg_eq_add, sub_zero, map_sub, zero_re',
zero_sub, add_zero, map_add, inner_add_right, inner_sub_left, inner_sub_right, inner_re_symm,
zero_add]
/-- The real inner product of two vectors, divided by the product of their
norms, has absolute value at most 1. -/
theorem abs_real_inner_div_norm_mul_norm_le_one (x y : F) : |⟪x, y⟫_ℝ / (‖x‖ * ‖y‖)| ≤ 1 := by
rw [abs_div, abs_mul, abs_norm, abs_norm]
exact div_le_one_of_le₀ (abs_real_inner_le_norm x y) (by positivity)
/-- The inner product of a vector with a multiple of itself. -/
theorem real_inner_smul_self_left (x : F) (r : ℝ) : ⟪r • x, x⟫_ℝ = r * (‖x‖ * ‖x‖) := by
rw [real_inner_smul_left, ← real_inner_self_eq_norm_mul_norm]
/-- The inner product of a vector with a multiple of itself. -/
theorem real_inner_smul_self_right (x : F) (r : ℝ) : ⟪x, r • x⟫_ℝ = r * (‖x‖ * ‖x‖) := by
rw [inner_smul_right, ← real_inner_self_eq_norm_mul_norm]
/-- The inner product of two weighted sums, where the weights in each
sum add to 0, in terms of the norms of pairwise differences. -/
theorem inner_sum_smul_sum_smul_of_sum_eq_zero {ι₁ : Type*} {s₁ : Finset ι₁} {w₁ : ι₁ → ℝ}
(v₁ : ι₁ → F) (h₁ : ∑ i ∈ s₁, w₁ i = 0) {ι₂ : Type*} {s₂ : Finset ι₂} {w₂ : ι₂ → ℝ}
(v₂ : ι₂ → F) (h₂ : ∑ i ∈ s₂, w₂ i = 0) :
⟪∑ i₁ ∈ s₁, w₁ i₁ • v₁ i₁, ∑ i₂ ∈ s₂, w₂ i₂ • v₂ i₂⟫_ℝ =
(-∑ i₁ ∈ s₁, ∑ i₂ ∈ s₂, w₁ i₁ * w₂ i₂ * (‖v₁ i₁ - v₂ i₂‖ * ‖v₁ i₁ - v₂ i₂‖)) / 2 := by
simp_rw [sum_inner, inner_sum, real_inner_smul_left, real_inner_smul_right,
real_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two, ← div_sub_div_same,
← div_add_div_same, mul_sub_left_distrib, left_distrib, Finset.sum_sub_distrib,
Finset.sum_add_distrib, ← Finset.mul_sum, ← Finset.sum_mul, h₁, h₂, zero_mul,
mul_zero, Finset.sum_const_zero, zero_add, zero_sub, Finset.mul_sum, neg_div,
Finset.sum_div, mul_div_assoc, mul_assoc]
end Norm_Seminormed
section Norm
open scoped InnerProductSpace
variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [NormedAddCommGroup F] [InnerProductSpace ℝ F]
variable {ι : Type*}
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
/-- Formula for the distance between the images of two nonzero points under an inversion with center
zero. See also `EuclideanGeometry.dist_inversion_inversion` for inversions around a general
point. -/
theorem dist_div_norm_sq_smul {x y : F} (hx : x ≠ 0) (hy : y ≠ 0) (R : ℝ) :
dist ((R / ‖x‖) ^ 2 • x) ((R / ‖y‖) ^ 2 • y) = R ^ 2 / (‖x‖ * ‖y‖) * dist x y :=
calc
dist ((R / ‖x‖) ^ 2 • x) ((R / ‖y‖) ^ 2 • y) =
√(‖(R / ‖x‖) ^ 2 • x - (R / ‖y‖) ^ 2 • y‖ ^ 2) := by
rw [dist_eq_norm, sqrt_sq (norm_nonneg _)]
_ = √((R ^ 2 / (‖x‖ * ‖y‖)) ^ 2 * ‖x - y‖ ^ 2) :=
congr_arg sqrt <| by
field_simp [sq, norm_sub_mul_self_real, norm_smul, real_inner_smul_left, inner_smul_right,
Real.norm_of_nonneg (mul_self_nonneg _)]
ring
_ = R ^ 2 / (‖x‖ * ‖y‖) * dist x y := by
rw [sqrt_mul, sqrt_sq, sqrt_sq, dist_eq_norm] <;> positivity
/-- The inner product of a nonzero vector with a nonzero multiple of
itself, divided by the product of their norms, has absolute value
1. -/
theorem norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul {x : E} {r : 𝕜} (hx : x ≠ 0)
(hr : r ≠ 0) : ‖⟪x, r • x⟫‖ / (‖x‖ * ‖r • x‖) = 1 := by
have hx' : ‖x‖ ≠ 0 := by simp [hx]
have hr' : ‖r‖ ≠ 0 := by simp [hr]
rw [inner_smul_right, norm_mul, ← inner_self_re_eq_norm, inner_self_eq_norm_mul_norm, norm_smul]
rw [← mul_assoc, ← div_div, mul_div_cancel_right₀ _ hx', ← div_div, mul_comm,
mul_div_cancel_right₀ _ hr', div_self hx']
/-- The inner product of a nonzero vector with a nonzero multiple of
itself, divided by the product of their norms, has absolute value
1. -/
theorem abs_real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul {x : F} {r : ℝ}
(hx : x ≠ 0) (hr : r ≠ 0) : |⟪x, r • x⟫_ℝ| / (‖x‖ * ‖r • x‖) = 1 :=
norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul hx hr
/-- The inner product of a nonzero vector with a positive multiple of
itself, divided by the product of their norms, has value 1. -/
theorem real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_pos_mul {x : F} {r : ℝ} (hx : x ≠ 0)
(hr : 0 < r) : ⟪x, r • x⟫_ℝ / (‖x‖ * ‖r • x‖) = 1 := by
rw [real_inner_smul_self_right, norm_smul, Real.norm_eq_abs, ← mul_assoc ‖x‖, mul_comm _ |r|,
mul_assoc, abs_of_nonneg hr.le, div_self]
exact mul_ne_zero hr.ne' (mul_self_ne_zero.2 (norm_ne_zero_iff.2 hx))
/-- The inner product of a nonzero vector with a negative multiple of
itself, divided by the product of their norms, has value -1. -/
theorem real_inner_div_norm_mul_norm_eq_neg_one_of_ne_zero_of_neg_mul {x : F} {r : ℝ} (hx : x ≠ 0)
(hr : r < 0) : ⟪x, r • x⟫_ℝ / (‖x‖ * ‖r • x‖) = -1 := by
rw [real_inner_smul_self_right, norm_smul, Real.norm_eq_abs, ← mul_assoc ‖x‖, mul_comm _ |r|,
mul_assoc, abs_of_neg hr, neg_mul, div_neg_eq_neg_div, div_self]
exact mul_ne_zero hr.ne (mul_self_ne_zero.2 (norm_ne_zero_iff.2 hx))
theorem norm_inner_eq_norm_tfae (x y : E) :
List.TFAE [‖⟪x, y⟫‖ = ‖x‖ * ‖y‖,
x = 0 ∨ y = (⟪x, y⟫ / ⟪x, x⟫) • x,
x = 0 ∨ ∃ r : 𝕜, y = r • x,
x = 0 ∨ y ∈ 𝕜 ∙ x] := by
tfae_have 1 → 2 := by
refine fun h => or_iff_not_imp_left.2 fun hx₀ => ?_
have : ‖x‖ ^ 2 ≠ 0 := pow_ne_zero _ (norm_ne_zero_iff.2 hx₀)
rw [← sq_eq_sq₀, mul_pow, ← mul_right_inj' this, eq_comm, ← sub_eq_zero, ← mul_sub] at h <;>
try positivity
simp only [@norm_sq_eq_re_inner 𝕜] at h
letI : InnerProductSpace.Core 𝕜 E := InnerProductSpace.toCore
erw [← InnerProductSpace.Core.cauchy_schwarz_aux (𝕜 := 𝕜) (F := E)] at h
rw [InnerProductSpace.Core.normSq_eq_zero, sub_eq_zero] at h
rw [div_eq_inv_mul, mul_smul, h, inv_smul_smul₀]
rwa [inner_self_ne_zero]
tfae_have 2 → 3 := fun h => h.imp_right fun h' => ⟨_, h'⟩
tfae_have 3 → 1 := by
rintro (rfl | ⟨r, rfl⟩) <;>
simp [inner_smul_right, norm_smul, inner_self_eq_norm_sq_to_K, inner_self_eq_norm_mul_norm,
sq, mul_left_comm]
tfae_have 3 ↔ 4 := by simp only [Submodule.mem_span_singleton, eq_comm]
tfae_finish
/-- If the inner product of two vectors is equal to the product of their norms, then the two vectors
are multiples of each other. One form of the equality case for Cauchy-Schwarz.
Compare `inner_eq_norm_mul_iff`, which takes the stronger hypothesis `⟪x, y⟫ = ‖x‖ * ‖y‖`. -/
theorem norm_inner_eq_norm_iff {x y : E} (hx₀ : x ≠ 0) (hy₀ : y ≠ 0) :
‖⟪x, y⟫‖ = ‖x‖ * ‖y‖ ↔ ∃ r : 𝕜, r ≠ 0 ∧ y = r • x :=
calc
‖⟪x, y⟫‖ = ‖x‖ * ‖y‖ ↔ x = 0 ∨ ∃ r : 𝕜, y = r • x :=
(@norm_inner_eq_norm_tfae 𝕜 _ _ _ _ x y).out 0 2
_ ↔ ∃ r : 𝕜, y = r • x := or_iff_right hx₀
_ ↔ ∃ r : 𝕜, r ≠ 0 ∧ y = r • x :=
⟨fun ⟨r, h⟩ => ⟨r, fun hr₀ => hy₀ <| h.symm ▸ smul_eq_zero.2 <| Or.inl hr₀, h⟩,
fun ⟨r, _hr₀, h⟩ => ⟨r, h⟩⟩
/-- The inner product of two vectors, divided by the product of their
norms, has absolute value 1 if and only if they are nonzero and one is
a multiple of the other. One form of equality case for Cauchy-Schwarz. -/
theorem norm_inner_div_norm_mul_norm_eq_one_iff (x y : E) :
‖⟪x, y⟫ / (‖x‖ * ‖y‖)‖ = 1 ↔ x ≠ 0 ∧ ∃ r : 𝕜, r ≠ 0 ∧ y = r • x := by
constructor
· intro h
have hx₀ : x ≠ 0 := fun h₀ => by simp [h₀] at h
have hy₀ : y ≠ 0 := fun h₀ => by simp [h₀] at h
refine ⟨hx₀, (norm_inner_eq_norm_iff hx₀ hy₀).1 <| eq_of_div_eq_one ?_⟩
simpa using h
· rintro ⟨hx, ⟨r, ⟨hr, rfl⟩⟩⟩
simp only [norm_div, norm_mul, norm_ofReal, abs_norm]
exact norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul hx hr
/-- The inner product of two vectors, divided by the product of their
norms, has absolute value 1 if and only if they are nonzero and one is
a multiple of the other. One form of equality case for Cauchy-Schwarz. -/
theorem abs_real_inner_div_norm_mul_norm_eq_one_iff (x y : F) :
|⟪x, y⟫_ℝ / (‖x‖ * ‖y‖)| = 1 ↔ x ≠ 0 ∧ ∃ r : ℝ, r ≠ 0 ∧ y = r • x :=
@norm_inner_div_norm_mul_norm_eq_one_iff ℝ F _ _ _ x y
theorem inner_eq_norm_mul_iff_div {x y : E} (h₀ : x ≠ 0) :
⟪x, y⟫ = (‖x‖ : 𝕜) * ‖y‖ ↔ (‖y‖ / ‖x‖ : 𝕜) • x = y := by
have h₀' := h₀
rw [← norm_ne_zero_iff, Ne, ← @ofReal_eq_zero 𝕜] at h₀'
constructor <;> intro h
· have : x = 0 ∨ y = (⟪x, y⟫ / ⟪x, x⟫ : 𝕜) • x :=
((@norm_inner_eq_norm_tfae 𝕜 _ _ _ _ x y).out 0 1).1 (by simp [h])
rw [this.resolve_left h₀, h]
simp [norm_smul, inner_self_ofReal_norm, mul_div_cancel_right₀ _ h₀']
· conv_lhs => rw [← h, inner_smul_right, inner_self_eq_norm_sq_to_K]
field_simp [sq, mul_left_comm]
/-- If the inner product of two vectors is equal to the product of their norms (i.e.,
`⟪x, y⟫ = ‖x‖ * ‖y‖`), then the two vectors are nonnegative real multiples of each other. One form
of the equality case for Cauchy-Schwarz.
Compare `norm_inner_eq_norm_iff`, which takes the weaker hypothesis `abs ⟪x, y⟫ = ‖x‖ * ‖y‖`. -/
theorem inner_eq_norm_mul_iff {x y : E} :
⟪x, y⟫ = (‖x‖ : 𝕜) * ‖y‖ ↔ (‖y‖ : 𝕜) • x = (‖x‖ : 𝕜) • y := by
rcases eq_or_ne x 0 with (rfl | h₀)
· simp
· rw [inner_eq_norm_mul_iff_div h₀, div_eq_inv_mul, mul_smul, inv_smul_eq_iff₀]
rwa [Ne, ofReal_eq_zero, norm_eq_zero]
/-- If the inner product of two vectors is equal to the product of their norms (i.e.,
`⟪x, y⟫ = ‖x‖ * ‖y‖`), then the two vectors are nonnegative real multiples of each other. One form
of the equality case for Cauchy-Schwarz.
Compare `norm_inner_eq_norm_iff`, which takes the weaker hypothesis `abs ⟪x, y⟫ = ‖x‖ * ‖y‖`. -/
theorem inner_eq_norm_mul_iff_real {x y : F} : ⟪x, y⟫_ℝ = ‖x‖ * ‖y‖ ↔ ‖y‖ • x = ‖x‖ • y :=
inner_eq_norm_mul_iff
/-- The inner product of two vectors, divided by the product of their
norms, has value 1 if and only if they are nonzero and one is
a positive multiple of the other. -/
theorem real_inner_div_norm_mul_norm_eq_one_iff (x y : F) :
⟪x, y⟫_ℝ / (‖x‖ * ‖y‖) = 1 ↔ x ≠ 0 ∧ ∃ r : ℝ, 0 < r ∧ y = r • x := by
constructor
· intro h
have hx₀ : x ≠ 0 := fun h₀ => by simp [h₀] at h
have hy₀ : y ≠ 0 := fun h₀ => by simp [h₀] at h
refine ⟨hx₀, ‖y‖ / ‖x‖, div_pos (norm_pos_iff.2 hy₀) (norm_pos_iff.2 hx₀), ?_⟩
exact ((inner_eq_norm_mul_iff_div hx₀).1 (eq_of_div_eq_one h)).symm
· rintro ⟨hx, ⟨r, ⟨hr, rfl⟩⟩⟩
exact real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_pos_mul hx hr
/-- The inner product of two vectors, divided by the product of their
norms, has value -1 if and only if they are nonzero and one is
a negative multiple of the other. -/
theorem real_inner_div_norm_mul_norm_eq_neg_one_iff (x y : F) :
⟪x, y⟫_ℝ / (‖x‖ * ‖y‖) = -1 ↔ x ≠ 0 ∧ ∃ r : ℝ, r < 0 ∧ y = r • x := by
rw [← neg_eq_iff_eq_neg, ← neg_div, ← inner_neg_right, ← norm_neg y,
real_inner_div_norm_mul_norm_eq_one_iff, (@neg_surjective ℝ _).exists]
refine Iff.rfl.and (exists_congr fun r => ?_)
rw [neg_pos, neg_smul, neg_inj]
/-- If the inner product of two unit vectors is `1`, then the two vectors are equal. One form of
the equality case for Cauchy-Schwarz. -/
theorem inner_eq_one_iff_of_norm_one {x y : E} (hx : ‖x‖ = 1) (hy : ‖y‖ = 1) :
⟪x, y⟫ = 1 ↔ x = y := by
convert inner_eq_norm_mul_iff (𝕜 := 𝕜) (E := E) using 2 <;> simp [hx, hy]
theorem inner_lt_norm_mul_iff_real {x y : F} : ⟪x, y⟫_ℝ < ‖x‖ * ‖y‖ ↔ ‖y‖ • x ≠ ‖x‖ • y :=
calc
⟪x, y⟫_ℝ < ‖x‖ * ‖y‖ ↔ ⟪x, y⟫_ℝ ≠ ‖x‖ * ‖y‖ :=
⟨ne_of_lt, lt_of_le_of_ne (real_inner_le_norm _ _)⟩
_ ↔ ‖y‖ • x ≠ ‖x‖ • y := not_congr inner_eq_norm_mul_iff_real
/-- If the inner product of two unit vectors is strictly less than `1`, then the two vectors are
distinct. One form of the equality case for Cauchy-Schwarz. -/
theorem inner_lt_one_iff_real_of_norm_one {x y : F} (hx : ‖x‖ = 1) (hy : ‖y‖ = 1) :
⟪x, y⟫_ℝ < 1 ↔ x ≠ y := by convert inner_lt_norm_mul_iff_real (F := F) <;> simp [hx, hy]
/-- The sphere of radius `r = ‖y‖` is tangent to the plane `⟪x, y⟫ = ‖y‖ ^ 2` at `x = y`. -/
theorem eq_of_norm_le_re_inner_eq_norm_sq {x y : E} (hle : ‖x‖ ≤ ‖y‖) (h : re ⟪x, y⟫ = ‖y‖ ^ 2) :
x = y := by
suffices H : re ⟪x - y, x - y⟫ ≤ 0 by rwa [re_inner_self_nonpos, sub_eq_zero] at H
have H₁ : ‖x‖ ^ 2 ≤ ‖y‖ ^ 2 := by gcongr
have H₂ : re ⟪y, x⟫ = ‖y‖ ^ 2 := by rwa [← inner_conj_symm, conj_re]
simpa [inner_sub_left, inner_sub_right, ← norm_sq_eq_re_inner, h, H₂] using H₁
end Norm
section RCLike
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
/-- A field `𝕜` satisfying `RCLike` is itself a `𝕜`-inner product space. -/
instance RCLike.innerProductSpace : InnerProductSpace 𝕜 𝕜 where
inner x y := y * conj x
norm_sq_eq_re_inner x := by simp only [inner, mul_conj, ← ofReal_pow, ofReal_re]
conj_inner_symm x y := by simp only [mul_comm, map_mul, starRingEnd_self_apply]
add_left x y z := by simp only [mul_add, map_add]
smul_left x y z := by simp only [mul_comm (conj z), mul_assoc, smul_eq_mul, map_mul]
@[simp]
theorem RCLike.inner_apply (x y : 𝕜) : ⟪x, y⟫ = y * conj x :=
rfl
/-- A version of `RCLike.inner_apply` that swaps the order of multiplication. -/
theorem RCLike.inner_apply' (x y : 𝕜) : ⟪x, y⟫ = conj x * y := mul_comm _ _
end RCLike
section RCLikeToReal
open scoped InnerProductSpace
variable {G : Type*}
variable (𝕜 E)
variable [SeminormedAddCommGroup E] [InnerProductSpace 𝕜 E]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
/-- A general inner product implies a real inner product. This is not registered as an instance
since `𝕜` does not appear in the return type `Inner ℝ E`. -/
def Inner.rclikeToReal : Inner ℝ E where inner x y := re ⟪x, y⟫
/-- A general inner product space structure implies a real inner product structure.
This is not registered as an instance since
* `𝕜` does not appear in the return type `InnerProductSpace ℝ E`,
* It is likely to create instance diamonds, as it builds upon the diamond-prone
`NormedSpace.restrictScalars`.
However, it can be used in a proof to obtain a real inner product space structure from a given
`𝕜`-inner product space structure. -/
-- See note [reducible non instances]
abbrev InnerProductSpace.rclikeToReal : InnerProductSpace ℝ E :=
{ Inner.rclikeToReal 𝕜 E,
NormedSpace.restrictScalars ℝ 𝕜
E with
norm_sq_eq_re_inner := norm_sq_eq_re_inner
conj_inner_symm := fun _ _ => inner_re_symm _ _
add_left := fun x y z => by
change re ⟪x + y, z⟫ = re ⟪x, z⟫ + re ⟪y, z⟫
simp only [inner_add_left, map_add]
smul_left := fun x y r => by
change re ⟪(r : 𝕜) • x, y⟫ = r * re ⟪x, y⟫
simp only [inner_smul_left, conj_ofReal, re_ofReal_mul] }
variable {E}
theorem real_inner_eq_re_inner (x y : E) :
@Inner.inner ℝ E (Inner.rclikeToReal 𝕜 E) x y = re ⟪x, y⟫ :=
rfl
theorem real_inner_I_smul_self (x : E) :
@Inner.inner ℝ E (Inner.rclikeToReal 𝕜 E) x ((I : 𝕜) • x) = 0 := by
simp [real_inner_eq_re_inner 𝕜, inner_smul_right]
/-- A complex inner product implies a real inner product. This cannot be an instance since it
creates a diamond with `PiLp.innerProductSpace` because `re (sum i, inner (x i) (y i))` and
`sum i, re (inner (x i) (y i))` are not defeq. -/
def InnerProductSpace.complexToReal [SeminormedAddCommGroup G] [InnerProductSpace ℂ G] :
InnerProductSpace ℝ G :=
InnerProductSpace.rclikeToReal ℂ G
instance : InnerProductSpace ℝ ℂ := InnerProductSpace.complexToReal
@[simp]
protected theorem Complex.inner (w z : ℂ) : ⟪w, z⟫_ℝ = (z * conj w).re :=
rfl
end RCLikeToReal
/-- An `RCLike` field is a real inner product space. -/
noncomputable instance RCLike.toInnerProductSpaceReal : InnerProductSpace ℝ 𝕜 where
__ := Inner.rclikeToReal 𝕜 𝕜
norm_sq_eq_re_inner := norm_sq_eq_re_inner
conj_inner_symm x y := inner_re_symm ..
add_left x y z :=
show re (_ * _) = re (_ * _) + re (_ * _) by simp only [map_add, mul_re, conj_re, conj_im]; ring
smul_left x y r :=
show re (_ * _) = _ * re (_ * _) by
simp only [mul_re, conj_re, conj_im, conj_trivial, smul_re, smul_im]; ring
-- The instance above does not create diamonds for concrete `𝕜`:
example : (innerProductSpace : InnerProductSpace ℝ ℝ) = RCLike.toInnerProductSpaceReal := rfl
example :
(instInnerProductSpaceRealComplex : InnerProductSpace ℝ ℂ) = RCLike.toInnerProductSpaceReal := rfl
| Mathlib/Analysis/InnerProductSpace/Basic.lean | 1,921 | 1,930 | |
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.ShortComplex.QuasiIso
import Mathlib.CategoryTheory.Limits.Preserves.Finite
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Kernels
/-!
# Functors which preserves homology
If `F : C ⥤ D` is a functor between categories with zero morphisms, we shall
say that `F` preserves homology when `F` preserves both kernels and cokernels.
This typeclass is named `[F.PreservesHomology]`, and is automatically
satisfied when `F` preserves both finite limits and finite colimits.
If `S : ShortComplex C` and `[F.PreservesHomology]`, then there is an
isomorphism `S.mapHomologyIso F : (S.map F).homology ≅ F.obj S.homology`, which
is part of the natural isomorphism `homologyFunctorIso F` between the functors
`F.mapShortComplex ⋙ homologyFunctor D` and `homologyFunctor C ⋙ F`.
-/
namespace CategoryTheory
open Category Limits
variable {C D : Type*} [Category C] [Category D] [HasZeroMorphisms C] [HasZeroMorphisms D]
namespace Functor
variable (F : C ⥤ D)
/-- A functor preserves homology when it preserves both kernels and cokernels. -/
class PreservesHomology (F : C ⥤ D) [PreservesZeroMorphisms F] : Prop where
/-- the functor preserves kernels -/
preservesKernels ⦃X Y : C⦄ (f : X ⟶ Y) : PreservesLimit (parallelPair f 0) F := by
infer_instance
/-- the functor preserves cokernels -/
preservesCokernels ⦃X Y : C⦄ (f : X ⟶ Y) : PreservesColimit (parallelPair f 0) F := by
infer_instance
variable [PreservesZeroMorphisms F]
/-- A functor which preserves homology preserves kernels. -/
lemma PreservesHomology.preservesKernel [F.PreservesHomology] {X Y : C} (f : X ⟶ Y) :
PreservesLimit (parallelPair f 0) F :=
PreservesHomology.preservesKernels _
/-- A functor which preserves homology preserves cokernels. -/
lemma PreservesHomology.preservesCokernel [F.PreservesHomology] {X Y : C} (f : X ⟶ Y) :
PreservesColimit (parallelPair f 0) F :=
PreservesHomology.preservesCokernels _
noncomputable instance preservesHomologyOfExact
[PreservesFiniteLimits F] [PreservesFiniteColimits F] :
F.PreservesHomology where
end Functor
namespace ShortComplex
variable {S S₁ S₂ : ShortComplex C}
namespace LeftHomologyData
variable (h : S.LeftHomologyData) (F : C ⥤ D)
/-- A left homology data `h` of a short complex `S` is preserved by a functor `F` is
`F` preserves the kernel of `S.g : S.X₂ ⟶ S.X₃` and the cokernel of `h.f' : S.X₁ ⟶ h.K`. -/
class IsPreservedBy [F.PreservesZeroMorphisms] : Prop where
/-- the functor preserves the kernel of `S.g : S.X₂ ⟶ S.X₃`. -/
g : PreservesLimit (parallelPair S.g 0) F
/-- the functor preserves the cokernel of `h.f' : S.X₁ ⟶ h.K`. -/
f' : PreservesColimit (parallelPair h.f' 0) F
variable [F.PreservesZeroMorphisms]
noncomputable instance isPreservedBy_of_preservesHomology [F.PreservesHomology] :
h.IsPreservedBy F where
g := Functor.PreservesHomology.preservesKernel _ _
f' := Functor.PreservesHomology.preservesCokernel _ _
variable [h.IsPreservedBy F]
include h in
/-- When a left homology data is preserved by a functor `F`, this functor
preserves the kernel of `S.g : S.X₂ ⟶ S.X₃`. -/
lemma IsPreservedBy.hg : PreservesLimit (parallelPair S.g 0) F :=
@IsPreservedBy.g _ _ _ _ _ _ _ h F _ _
/-- When a left homology data `h` is preserved by a functor `F`, this functor
preserves the cokernel of `h.f' : S.X₁ ⟶ h.K`. -/
lemma IsPreservedBy.hf' : PreservesColimit (parallelPair h.f' 0) F := IsPreservedBy.f'
/-- When a left homology data `h` of a short complex `S` is preserved by a functor `F`,
this is the induced left homology data `h.map F` for the short complex `S.map F`. -/
@[simps]
noncomputable def map : (S.map F).LeftHomologyData := by
have := IsPreservedBy.hg h F
have := IsPreservedBy.hf' h F
have wi : F.map h.i ≫ F.map S.g = 0 := by rw [← F.map_comp, h.wi, F.map_zero]
have hi := KernelFork.mapIsLimit _ h.hi F
let f' : F.obj S.X₁ ⟶ F.obj h.K := hi.lift (KernelFork.ofι (S.map F).f (S.map F).zero)
have hf' : f' = F.map h.f' := Fork.IsLimit.hom_ext hi (by
rw [Fork.IsLimit.lift_ι hi]
simp only [KernelFork.map_ι, Fork.ι_ofι, map_f, ← F.map_comp, f'_i])
have wπ : f' ≫ F.map h.π = 0 := by rw [hf', ← F.map_comp, f'_π, F.map_zero]
have hπ : IsColimit (CokernelCofork.ofπ (F.map h.π) wπ) := by
let e : parallelPair f' 0 ≅ parallelPair (F.map h.f') 0 :=
parallelPair.ext (Iso.refl _) (Iso.refl _) (by simpa using hf') (by simp)
refine IsColimit.precomposeInvEquiv e _
(IsColimit.ofIsoColimit (CokernelCofork.mapIsColimit _ h.hπ' F) ?_)
exact Cofork.ext (Iso.refl _) (by simp [e])
exact
{ K := F.obj h.K
H := F.obj h.H
i := F.map h.i
π := F.map h.π
wi := wi
hi := hi
wπ := wπ
hπ := hπ }
@[simp]
lemma map_f' : (h.map F).f' = F.map h.f' := by
rw [← cancel_mono (h.map F).i, f'_i, map_f, map_i, ← F.map_comp, f'_i]
end LeftHomologyData
/-- Given a left homology map data `ψ : LeftHomologyMapData φ h₁ h₂` such that
both left homology data `h₁` and `h₂` are preserved by a functor `F`, this is
the induced left homology map data for the morphism `F.mapShortComplex.map φ`. -/
@[simps]
def LeftHomologyMapData.map {φ : S₁ ⟶ S₂} {h₁ : S₁.LeftHomologyData}
{h₂ : S₂.LeftHomologyData} (ψ : LeftHomologyMapData φ h₁ h₂) (F : C ⥤ D)
[F.PreservesZeroMorphisms] [h₁.IsPreservedBy F] [h₂.IsPreservedBy F] :
LeftHomologyMapData (F.mapShortComplex.map φ) (h₁.map F) (h₂.map F) where
φK := F.map ψ.φK
φH := F.map ψ.φH
commi := by simpa only [F.map_comp] using F.congr_map ψ.commi
commf' := by simpa only [LeftHomologyData.map_f', F.map_comp] using F.congr_map ψ.commf'
commπ := by simpa only [F.map_comp] using F.congr_map ψ.commπ
namespace RightHomologyData
variable (h : S.RightHomologyData) (F : C ⥤ D)
/-- A right homology data `h` of a short complex `S` is preserved by a functor `F` is
`F` preserves the cokernel of `S.f : S.X₁ ⟶ S.X₂` and the kernel of `h.g' : h.Q ⟶ S.X₃`. -/
class IsPreservedBy [F.PreservesZeroMorphisms] : Prop where
/-- the functor preserves the cokernel of `S.f : S.X₁ ⟶ S.X₂`. -/
f : PreservesColimit (parallelPair S.f 0) F
/-- the functor preserves the kernel of `h.g' : h.Q ⟶ S.X₃`. -/
g' : PreservesLimit (parallelPair h.g' 0) F
variable [F.PreservesZeroMorphisms]
noncomputable instance isPreservedBy_of_preservesHomology [F.PreservesHomology] :
h.IsPreservedBy F where
f := Functor.PreservesHomology.preservesCokernel F _
g' := Functor.PreservesHomology.preservesKernel F _
variable [h.IsPreservedBy F]
include h in
/-- When a right homology data is preserved by a functor `F`, this functor
preserves the cokernel of `S.f : S.X₁ ⟶ S.X₂`. -/
lemma IsPreservedBy.hf : PreservesColimit (parallelPair S.f 0) F :=
@IsPreservedBy.f _ _ _ _ _ _ _ h F _ _
/-- When a right homology data `h` is preserved by a functor `F`, this functor
preserves the kernel of `h.g' : h.Q ⟶ S.X₃`. -/
lemma IsPreservedBy.hg' : PreservesLimit (parallelPair h.g' 0) F :=
@IsPreservedBy.g' _ _ _ _ _ _ _ h F _ _
/-- When a right homology data `h` of a short complex `S` is preserved by a functor `F`,
this is the induced right homology data `h.map F` for the short complex `S.map F`. -/
@[simps]
noncomputable def map : (S.map F).RightHomologyData := by
have := IsPreservedBy.hf h F
have := IsPreservedBy.hg' h F
have wp : F.map S.f ≫ F.map h.p = 0 := by rw [← F.map_comp, h.wp, F.map_zero]
have hp := CokernelCofork.mapIsColimit _ h.hp F
let g' : F.obj h.Q ⟶ F.obj S.X₃ := hp.desc (CokernelCofork.ofπ (S.map F).g (S.map F).zero)
have hg' : g' = F.map h.g' := by
apply Cofork.IsColimit.hom_ext hp
rw [Cofork.IsColimit.π_desc hp]
simp only [Cofork.π_ofπ, CokernelCofork.map_π, map_g, ← F.map_comp, p_g']
have wι : F.map h.ι ≫ g' = 0 := by rw [hg', ← F.map_comp, ι_g', F.map_zero]
have hι : IsLimit (KernelFork.ofι (F.map h.ι) wι) := by
let e : parallelPair g' 0 ≅ parallelPair (F.map h.g') 0 :=
parallelPair.ext (Iso.refl _) (Iso.refl _) (by simpa using hg') (by simp)
refine IsLimit.postcomposeHomEquiv e _
(IsLimit.ofIsoLimit (KernelFork.mapIsLimit _ h.hι' F) ?_)
exact Fork.ext (Iso.refl _) (by simp [e])
exact
{ Q := F.obj h.Q
H := F.obj h.H
p := F.map h.p
ι := F.map h.ι
wp := wp
hp := hp
wι := wι
hι := hι }
@[simp]
lemma map_g' : (h.map F).g' = F.map h.g' := by
rw [← cancel_epi (h.map F).p, p_g', map_g, map_p, ← F.map_comp, p_g']
end RightHomologyData
/-- Given a right homology map data `ψ : RightHomologyMapData φ h₁ h₂` such that
both right homology data `h₁` and `h₂` are preserved by a functor `F`, this is
the induced right homology map data for the morphism `F.mapShortComplex.map φ`. -/
@[simps]
def RightHomologyMapData.map {φ : S₁ ⟶ S₂} {h₁ : S₁.RightHomologyData}
{h₂ : S₂.RightHomologyData} (ψ : RightHomologyMapData φ h₁ h₂) (F : C ⥤ D)
[F.PreservesZeroMorphisms] [h₁.IsPreservedBy F] [h₂.IsPreservedBy F] :
RightHomologyMapData (F.mapShortComplex.map φ) (h₁.map F) (h₂.map F) where
φQ := F.map ψ.φQ
φH := F.map ψ.φH
commp := by simpa only [F.map_comp] using F.congr_map ψ.commp
commg' := by simpa only [RightHomologyData.map_g', F.map_comp] using F.congr_map ψ.commg'
commι := by simpa only [F.map_comp] using F.congr_map ψ.commι
/-- When a homology data `h` of a short complex `S` is such that both `h.left` and
`h.right` are preserved by a functor `F`, this is the induced homology data
`h.map F` for the short complex `S.map F`. -/
@[simps]
noncomputable def HomologyData.map (h : S.HomologyData) (F : C ⥤ D) [F.PreservesZeroMorphisms]
[h.left.IsPreservedBy F] [h.right.IsPreservedBy F] :
(S.map F).HomologyData where
left := h.left.map F
right := h.right.map F
iso := F.mapIso h.iso
comm := by simpa only [F.map_comp] using F.congr_map h.comm
/-- Given a homology map data `ψ : HomologyMapData φ h₁ h₂` such that
`h₁.left`, `h₁.right`, `h₂.left` and `h₂.right` are all preserved by a functor `F`, this is
the induced homology map data for the morphism `F.mapShortComplex.map φ`. -/
@[simps]
def HomologyMapData.map {φ : S₁ ⟶ S₂} {h₁ : S₁.HomologyData} {h₂ : S₂.HomologyData}
(ψ : HomologyMapData φ h₁ h₂) (F : C ⥤ D) [F.PreservesZeroMorphisms]
[h₁.left.IsPreservedBy F] [h₁.right.IsPreservedBy F]
[h₂.left.IsPreservedBy F] [h₂.right.IsPreservedBy F] :
HomologyMapData (F.mapShortComplex.map φ) (h₁.map F) (h₂.map F) where
left := ψ.left.map F
right := ψ.right.map F
end ShortComplex
namespace Functor
variable (F : C ⥤ D) [PreservesZeroMorphisms F] (S : ShortComplex C) {S₁ S₂ : ShortComplex C}
/-- A functor preserves the left homology of a short complex `S` if it preserves all the
left homology data of `S`. -/
class PreservesLeftHomologyOf : Prop where
/-- the functor preserves all the left homology data of the short complex -/
isPreservedBy : ∀ (h : S.LeftHomologyData), h.IsPreservedBy F
/-- A functor preserves the right homology of a short complex `S` if it preserves all the
right homology data of `S`. -/
class PreservesRightHomologyOf : Prop where
/-- the functor preserves all the right homology data of the short complex -/
isPreservedBy : ∀ (h : S.RightHomologyData), h.IsPreservedBy F
instance PreservesHomology.preservesLeftHomologyOf [F.PreservesHomology] :
F.PreservesLeftHomologyOf S := ⟨inferInstance⟩
instance PreservesHomology.preservesRightHomologyOf [F.PreservesHomology] :
F.PreservesRightHomologyOf S := ⟨inferInstance⟩
variable {S}
/-- If a functor preserves a certain left homology data of a short complex `S`, then it
preserves the left homology of `S`. -/
lemma PreservesLeftHomologyOf.mk' (h : S.LeftHomologyData) [h.IsPreservedBy F] :
F.PreservesLeftHomologyOf S where
isPreservedBy h' :=
{ g := ShortComplex.LeftHomologyData.IsPreservedBy.hg h F
f' := by
have := ShortComplex.LeftHomologyData.IsPreservedBy.hf' h F
let e : parallelPair h.f' 0 ≅ parallelPair h'.f' 0 :=
parallelPair.ext (Iso.refl _) (ShortComplex.cyclesMapIso' (Iso.refl S) h h')
(by simp) (by simp)
exact preservesColimit_of_iso_diagram F e }
/-- If a functor preserves a certain right homology data of a short complex `S`, then it
preserves the right homology of `S`. -/
lemma PreservesRightHomologyOf.mk' (h : S.RightHomologyData) [h.IsPreservedBy F] :
F.PreservesRightHomologyOf S where
isPreservedBy h' :=
{ f := ShortComplex.RightHomologyData.IsPreservedBy.hf h F
g' := by
have := ShortComplex.RightHomologyData.IsPreservedBy.hg' h F
let e : parallelPair h.g' 0 ≅ parallelPair h'.g' 0 :=
parallelPair.ext (ShortComplex.opcyclesMapIso' (Iso.refl S) h h') (Iso.refl _)
(by simp) (by simp)
exact preservesLimit_of_iso_diagram F e }
end Functor
namespace ShortComplex
variable {S : ShortComplex C} (h₁ : S.LeftHomologyData) (h₂ : S.RightHomologyData)
(F : C ⥤ D) [F.PreservesZeroMorphisms]
instance LeftHomologyData.isPreservedBy_of_preserves [F.PreservesLeftHomologyOf S] :
h₁.IsPreservedBy F :=
Functor.PreservesLeftHomologyOf.isPreservedBy _
instance RightHomologyData.isPreservedBy_of_preserves [F.PreservesRightHomologyOf S] :
h₂.IsPreservedBy F :=
Functor.PreservesRightHomologyOf.isPreservedBy _
variable (S)
instance hasLeftHomology_of_preserves [S.HasLeftHomology] [F.PreservesLeftHomologyOf S] :
(S.map F).HasLeftHomology :=
HasLeftHomology.mk' (S.leftHomologyData.map F)
instance hasLeftHomology_of_preserves' [S.HasLeftHomology] [F.PreservesLeftHomologyOf S] :
(F.mapShortComplex.obj S).HasLeftHomology := by
dsimp; infer_instance
instance hasRightHomology_of_preserves [S.HasRightHomology] [F.PreservesRightHomologyOf S] :
(S.map F).HasRightHomology :=
HasRightHomology.mk' (S.rightHomologyData.map F)
instance hasRightHomology_of_preserves' [S.HasRightHomology] [F.PreservesRightHomologyOf S] :
(F.mapShortComplex.obj S).HasRightHomology := by
dsimp; infer_instance
instance hasHomology_of_preserves [S.HasHomology] [F.PreservesLeftHomologyOf S]
[F.PreservesRightHomologyOf S] :
(S.map F).HasHomology :=
HasHomology.mk' (S.homologyData.map F)
instance hasHomology_of_preserves' [S.HasHomology] [F.PreservesLeftHomologyOf S]
[F.PreservesRightHomologyOf S] :
(F.mapShortComplex.obj S).HasHomology := by
dsimp; infer_instance
section
variable
(hl : S.LeftHomologyData) (hr : S.RightHomologyData)
{S₁ S₂ : ShortComplex C} (φ : S₁ ⟶ S₂)
(hl₁ : S₁.LeftHomologyData) (hr₁ : S₁.RightHomologyData)
(hl₂ : S₂.LeftHomologyData) (hr₂ : S₂.RightHomologyData)
(h₁ : S₁.HomologyData) (h₂ : S₂.HomologyData)
(F : C ⥤ D) [F.PreservesZeroMorphisms]
namespace LeftHomologyData
variable [hl₁.IsPreservedBy F] [hl₂.IsPreservedBy F]
lemma map_cyclesMap' : F.map (ShortComplex.cyclesMap' φ hl₁ hl₂) =
ShortComplex.cyclesMap' (F.mapShortComplex.map φ) (hl₁.map F) (hl₂.map F) := by
have γ : ShortComplex.LeftHomologyMapData φ hl₁ hl₂ := default
rw [γ.cyclesMap'_eq, (γ.map F).cyclesMap'_eq, ShortComplex.LeftHomologyMapData.map_φK]
lemma map_leftHomologyMap' : F.map (ShortComplex.leftHomologyMap' φ hl₁ hl₂) =
ShortComplex.leftHomologyMap' (F.mapShortComplex.map φ) (hl₁.map F) (hl₂.map F) := by
have γ : ShortComplex.LeftHomologyMapData φ hl₁ hl₂ := default
rw [γ.leftHomologyMap'_eq, (γ.map F).leftHomologyMap'_eq,
ShortComplex.LeftHomologyMapData.map_φH]
end LeftHomologyData
namespace RightHomologyData
variable [hr₁.IsPreservedBy F] [hr₂.IsPreservedBy F]
lemma map_opcyclesMap' : F.map (ShortComplex.opcyclesMap' φ hr₁ hr₂) =
ShortComplex.opcyclesMap' (F.mapShortComplex.map φ) (hr₁.map F) (hr₂.map F) := by
have γ : ShortComplex.RightHomologyMapData φ hr₁ hr₂ := default
rw [γ.opcyclesMap'_eq, (γ.map F).opcyclesMap'_eq, ShortComplex.RightHomologyMapData.map_φQ]
lemma map_rightHomologyMap' : F.map (ShortComplex.rightHomologyMap' φ hr₁ hr₂) =
ShortComplex.rightHomologyMap' (F.mapShortComplex.map φ) (hr₁.map F) (hr₂.map F) := by
have γ : ShortComplex.RightHomologyMapData φ hr₁ hr₂ := default
rw [γ.rightHomologyMap'_eq, (γ.map F).rightHomologyMap'_eq,
ShortComplex.RightHomologyMapData.map_φH]
end RightHomologyData
lemma HomologyData.map_homologyMap'
[h₁.left.IsPreservedBy F] [h₁.right.IsPreservedBy F]
[h₂.left.IsPreservedBy F] [h₂.right.IsPreservedBy F] :
F.map (ShortComplex.homologyMap' φ h₁ h₂) =
ShortComplex.homologyMap' (F.mapShortComplex.map φ) (h₁.map F) (h₂.map F) :=
LeftHomologyData.map_leftHomologyMap' _ _ _ _
/-- When a functor `F` preserves the left homology of a short complex `S`, this is the
canonical isomorphism `(S.map F).cycles ≅ F.obj S.cycles`. -/
noncomputable def mapCyclesIso [S.HasLeftHomology] [F.PreservesLeftHomologyOf S] :
(S.map F).cycles ≅ F.obj S.cycles :=
(S.leftHomologyData.map F).cyclesIso
@[reassoc (attr := simp)]
lemma mapCyclesIso_hom_iCycles [S.HasLeftHomology] [F.PreservesLeftHomologyOf S] :
(S.mapCyclesIso F).hom ≫ F.map S.iCycles = (S.map F).iCycles := by
apply LeftHomologyData.cyclesIso_hom_comp_i
/-- When a functor `F` preserves the left homology of a short complex `S`, this is the
canonical isomorphism `(S.map F).leftHomology ≅ F.obj S.leftHomology`. -/
noncomputable def mapLeftHomologyIso [S.HasLeftHomology] [F.PreservesLeftHomologyOf S] :
(S.map F).leftHomology ≅ F.obj S.leftHomology :=
(S.leftHomologyData.map F).leftHomologyIso
/-- When a functor `F` preserves the right homology of a short complex `S`, this is the
canonical isomorphism `(S.map F).opcycles ≅ F.obj S.opcycles`. -/
noncomputable def mapOpcyclesIso [S.HasRightHomology] [F.PreservesRightHomologyOf S] :
(S.map F).opcycles ≅ F.obj S.opcycles :=
(S.rightHomologyData.map F).opcyclesIso
/-- When a functor `F` preserves the right homology of a short complex `S`, this is the
canonical isomorphism `(S.map F).rightHomology ≅ F.obj S.rightHomology`. -/
noncomputable def mapRightHomologyIso [S.HasRightHomology] [F.PreservesRightHomologyOf S] :
(S.map F).rightHomology ≅ F.obj S.rightHomology :=
(S.rightHomologyData.map F).rightHomologyIso
/-- When a functor `F` preserves the left homology of a short complex `S`, this is the
canonical isomorphism `(S.map F).homology ≅ F.obj S.homology`. -/
noncomputable def mapHomologyIso [S.HasHomology] [(S.map F).HasHomology]
[F.PreservesLeftHomologyOf S] :
(S.map F).homology ≅ F.obj S.homology :=
(S.homologyData.left.map F).homologyIso
/-- When a functor `F` preserves the right homology of a short complex `S`, this is the
canonical isomorphism `(S.map F).homology ≅ F.obj S.homology`. -/
noncomputable def mapHomologyIso' [S.HasHomology] [(S.map F).HasHomology]
[F.PreservesRightHomologyOf S] :
(S.map F).homology ≅ F.obj S.homology :=
(S.homologyData.right.map F).homologyIso ≪≫ F.mapIso S.homologyData.right.homologyIso.symm
variable {S}
lemma LeftHomologyData.mapCyclesIso_eq [S.HasLeftHomology]
[F.PreservesLeftHomologyOf S] :
S.mapCyclesIso F = (hl.map F).cyclesIso ≪≫ F.mapIso hl.cyclesIso.symm := by
ext
dsimp [mapCyclesIso, cyclesIso]
simp only [map_cyclesMap', ← cyclesMap'_comp, Functor.map_id, comp_id,
Functor.mapShortComplex_obj]
lemma LeftHomologyData.mapLeftHomologyIso_eq [S.HasLeftHomology]
[F.PreservesLeftHomologyOf S] :
S.mapLeftHomologyIso F = (hl.map F).leftHomologyIso ≪≫ F.mapIso hl.leftHomologyIso.symm := by
ext
dsimp [mapLeftHomologyIso, leftHomologyIso]
simp only [map_leftHomologyMap', ← leftHomologyMap'_comp, Functor.map_id, comp_id,
Functor.mapShortComplex_obj]
lemma RightHomologyData.mapOpcyclesIso_eq [S.HasRightHomology]
[F.PreservesRightHomologyOf S] :
S.mapOpcyclesIso F = (hr.map F).opcyclesIso ≪≫ F.mapIso hr.opcyclesIso.symm := by
ext
dsimp [mapOpcyclesIso, opcyclesIso]
simp only [map_opcyclesMap', ← opcyclesMap'_comp, Functor.map_id, comp_id,
Functor.mapShortComplex_obj]
lemma RightHomologyData.mapRightHomologyIso_eq [S.HasRightHomology]
[F.PreservesRightHomologyOf S] :
S.mapRightHomologyIso F = (hr.map F).rightHomologyIso ≪≫
F.mapIso hr.rightHomologyIso.symm := by
ext
dsimp [mapRightHomologyIso, rightHomologyIso]
simp only [map_rightHomologyMap', ← rightHomologyMap'_comp, Functor.map_id, comp_id,
Functor.mapShortComplex_obj]
lemma LeftHomologyData.mapHomologyIso_eq [S.HasHomology]
[(S.map F).HasHomology] [F.PreservesLeftHomologyOf S] :
S.mapHomologyIso F = (hl.map F).homologyIso ≪≫ F.mapIso hl.homologyIso.symm := by
ext
dsimp only [mapHomologyIso, homologyIso, ShortComplex.leftHomologyIso,
leftHomologyMapIso', leftHomologyIso, Functor.mapIso,
Iso.symm, Iso.trans, Iso.refl]
simp only [F.map_comp, map_leftHomologyMap', ← leftHomologyMap'_comp, comp_id,
Functor.map_id, Functor.mapShortComplex_obj]
lemma RightHomologyData.mapHomologyIso'_eq [S.HasHomology]
[(S.map F).HasHomology] [F.PreservesRightHomologyOf S] :
S.mapHomologyIso' F = (hr.map F).homologyIso ≪≫ F.mapIso hr.homologyIso.symm := by
ext
dsimp only [Iso.trans, Iso.symm, Iso.refl, Functor.mapIso, mapHomologyIso', homologyIso,
rightHomologyIso, rightHomologyMapIso', ShortComplex.rightHomologyIso]
simp only [assoc, F.map_comp, map_rightHomologyMap', ← rightHomologyMap'_comp_assoc]
@[reassoc]
lemma mapCyclesIso_hom_naturality [S₁.HasLeftHomology] [S₂.HasLeftHomology]
[F.PreservesLeftHomologyOf S₁] [F.PreservesLeftHomologyOf S₂] :
cyclesMap (F.mapShortComplex.map φ) ≫ (S₂.mapCyclesIso F).hom =
(S₁.mapCyclesIso F).hom ≫ F.map (cyclesMap φ) := by
dsimp only [cyclesMap, mapCyclesIso, LeftHomologyData.cyclesIso, cyclesMapIso', Iso.refl]
simp only [LeftHomologyData.map_cyclesMap', Functor.mapShortComplex_obj, ← cyclesMap'_comp,
comp_id, id_comp]
@[reassoc]
lemma mapCyclesIso_inv_naturality [S₁.HasLeftHomology] [S₂.HasLeftHomology]
[F.PreservesLeftHomologyOf S₁] [F.PreservesLeftHomologyOf S₂] :
F.map (cyclesMap φ) ≫ (S₂.mapCyclesIso F).inv =
(S₁.mapCyclesIso F).inv ≫ cyclesMap (F.mapShortComplex.map φ) := by
rw [← cancel_epi (S₁.mapCyclesIso F).hom, ← mapCyclesIso_hom_naturality_assoc,
Iso.hom_inv_id, comp_id, Iso.hom_inv_id_assoc]
@[reassoc]
lemma mapLeftHomologyIso_hom_naturality [S₁.HasLeftHomology] [S₂.HasLeftHomology]
[F.PreservesLeftHomologyOf S₁] [F.PreservesLeftHomologyOf S₂] :
leftHomologyMap (F.mapShortComplex.map φ) ≫ (S₂.mapLeftHomologyIso F).hom =
(S₁.mapLeftHomologyIso F).hom ≫ F.map (leftHomologyMap φ) := by
dsimp only [leftHomologyMap, mapLeftHomologyIso, LeftHomologyData.leftHomologyIso,
leftHomologyMapIso', Iso.refl]
simp only [LeftHomologyData.map_leftHomologyMap', Functor.mapShortComplex_obj,
← leftHomologyMap'_comp, comp_id, id_comp]
@[reassoc]
lemma mapLeftHomologyIso_inv_naturality [S₁.HasLeftHomology] [S₂.HasLeftHomology]
[F.PreservesLeftHomologyOf S₁] [F.PreservesLeftHomologyOf S₂] :
F.map (leftHomologyMap φ) ≫ (S₂.mapLeftHomologyIso F).inv =
(S₁.mapLeftHomologyIso F).inv ≫ leftHomologyMap (F.mapShortComplex.map φ) := by
rw [← cancel_epi (S₁.mapLeftHomologyIso F).hom, ← mapLeftHomologyIso_hom_naturality_assoc,
Iso.hom_inv_id, comp_id, Iso.hom_inv_id_assoc]
@[reassoc]
lemma mapOpcyclesIso_hom_naturality [S₁.HasRightHomology] [S₂.HasRightHomology]
[F.PreservesRightHomologyOf S₁] [F.PreservesRightHomologyOf S₂] :
opcyclesMap (F.mapShortComplex.map φ) ≫ (S₂.mapOpcyclesIso F).hom =
(S₁.mapOpcyclesIso F).hom ≫ F.map (opcyclesMap φ) := by
dsimp only [opcyclesMap, mapOpcyclesIso, RightHomologyData.opcyclesIso,
opcyclesMapIso', Iso.refl]
simp only [RightHomologyData.map_opcyclesMap', Functor.mapShortComplex_obj, ← opcyclesMap'_comp,
comp_id, id_comp]
@[reassoc]
lemma mapOpcyclesIso_inv_naturality [S₁.HasRightHomology] [S₂.HasRightHomology]
[F.PreservesRightHomologyOf S₁] [F.PreservesRightHomologyOf S₂] :
F.map (opcyclesMap φ) ≫ (S₂.mapOpcyclesIso F).inv =
(S₁.mapOpcyclesIso F).inv ≫ opcyclesMap (F.mapShortComplex.map φ) := by
rw [← cancel_epi (S₁.mapOpcyclesIso F).hom, ← mapOpcyclesIso_hom_naturality_assoc,
Iso.hom_inv_id, comp_id, Iso.hom_inv_id_assoc]
@[reassoc]
lemma mapRightHomologyIso_hom_naturality [S₁.HasRightHomology] [S₂.HasRightHomology]
[F.PreservesRightHomologyOf S₁] [F.PreservesRightHomologyOf S₂] :
rightHomologyMap (F.mapShortComplex.map φ) ≫ (S₂.mapRightHomologyIso F).hom =
(S₁.mapRightHomologyIso F).hom ≫ F.map (rightHomologyMap φ) := by
dsimp only [rightHomologyMap, mapRightHomologyIso, RightHomologyData.rightHomologyIso,
rightHomologyMapIso', Iso.refl]
simp only [RightHomologyData.map_rightHomologyMap', Functor.mapShortComplex_obj,
← rightHomologyMap'_comp, comp_id, id_comp]
@[reassoc]
lemma mapRightHomologyIso_inv_naturality [S₁.HasRightHomology] [S₂.HasRightHomology]
[F.PreservesRightHomologyOf S₁] [F.PreservesRightHomologyOf S₂] :
F.map (rightHomologyMap φ) ≫ (S₂.mapRightHomologyIso F).inv =
(S₁.mapRightHomologyIso F).inv ≫ rightHomologyMap (F.mapShortComplex.map φ) := by
rw [← cancel_epi (S₁.mapRightHomologyIso F).hom, ← mapRightHomologyIso_hom_naturality_assoc,
Iso.hom_inv_id, comp_id, Iso.hom_inv_id_assoc]
@[reassoc]
lemma mapHomologyIso_hom_naturality [S₁.HasHomology] [S₂.HasHomology]
[(S₁.map F).HasHomology] [(S₂.map F).HasHomology]
[F.PreservesLeftHomologyOf S₁] [F.PreservesLeftHomologyOf S₂] :
@homologyMap _ _ _ (S₁.map F) (S₂.map F) (F.mapShortComplex.map φ) _ _ ≫
(S₂.mapHomologyIso F).hom = (S₁.mapHomologyIso F).hom ≫ F.map (homologyMap φ) := by
dsimp only [homologyMap, homologyMap', mapHomologyIso, LeftHomologyData.homologyIso,
LeftHomologyData.leftHomologyIso, leftHomologyMapIso', leftHomologyIso,
Iso.symm, Iso.trans, Iso.refl]
simp only [LeftHomologyData.map_leftHomologyMap', ← leftHomologyMap'_comp, comp_id, id_comp]
@[reassoc]
lemma mapHomologyIso_inv_naturality [S₁.HasHomology] [S₂.HasHomology]
[(S₁.map F).HasHomology] [(S₂.map F).HasHomology]
[F.PreservesLeftHomologyOf S₁] [F.PreservesLeftHomologyOf S₂] :
F.map (homologyMap φ) ≫ (S₂.mapHomologyIso F).inv =
(S₁.mapHomologyIso F).inv ≫
@homologyMap _ _ _ (S₁.map F) (S₂.map F) (F.mapShortComplex.map φ) _ _ := by
rw [← cancel_epi (S₁.mapHomologyIso F).hom, ← mapHomologyIso_hom_naturality_assoc,
Iso.hom_inv_id, comp_id, Iso.hom_inv_id_assoc]
@[reassoc]
lemma mapHomologyIso'_hom_naturality [S₁.HasHomology] [S₂.HasHomology]
[(S₁.map F).HasHomology] [(S₂.map F).HasHomology]
[F.PreservesRightHomologyOf S₁] [F.PreservesRightHomologyOf S₂] :
@homologyMap _ _ _ (S₁.map F) (S₂.map F) (F.mapShortComplex.map φ) _ _ ≫
(S₂.mapHomologyIso' F).hom = (S₁.mapHomologyIso' F).hom ≫ F.map (homologyMap φ) := by
dsimp only [Iso.trans, Iso.symm, Functor.mapIso, mapHomologyIso']
simp only [← RightHomologyData.rightHomologyIso_hom_naturality_assoc _
((homologyData S₁).right.map F) ((homologyData S₂).right.map F), assoc,
← RightHomologyData.map_rightHomologyMap', ← F.map_comp,
RightHomologyData.rightHomologyIso_inv_naturality _
(homologyData S₁).right (homologyData S₂).right]
@[reassoc]
lemma mapHomologyIso'_inv_naturality [S₁.HasHomology] [S₂.HasHomology]
[(S₁.map F).HasHomology] [(S₂.map F).HasHomology]
[F.PreservesRightHomologyOf S₁] [F.PreservesRightHomologyOf S₂] :
F.map (homologyMap φ) ≫ (S₂.mapHomologyIso' F).inv = (S₁.mapHomologyIso' F).inv ≫
@homologyMap _ _ _ (S₁.map F) (S₂.map F) (F.mapShortComplex.map φ) _ _ := by
rw [← cancel_epi (S₁.mapHomologyIso' F).hom, ← mapHomologyIso'_hom_naturality_assoc,
Iso.hom_inv_id, comp_id, Iso.hom_inv_id_assoc]
variable (S)
lemma mapHomologyIso'_eq_mapHomologyIso [S.HasHomology] [F.PreservesLeftHomologyOf S]
[F.PreservesRightHomologyOf S] :
S.mapHomologyIso' F = S.mapHomologyIso F := by
ext
rw [S.homologyData.left.mapHomologyIso_eq F, S.homologyData.right.mapHomologyIso'_eq F]
dsimp only [Iso.trans, Iso.symm, Iso.refl, Functor.mapIso, RightHomologyData.homologyIso,
rightHomologyIso, RightHomologyData.rightHomologyIso, LeftHomologyData.homologyIso,
leftHomologyIso, LeftHomologyData.leftHomologyIso]
simp only [RightHomologyData.map_H, rightHomologyMapIso'_inv, rightHomologyMapIso'_hom, assoc,
Functor.map_comp, RightHomologyData.map_rightHomologyMap', Functor.mapShortComplex_obj,
Functor.map_id, LeftHomologyData.map_H, leftHomologyMapIso'_inv, leftHomologyMapIso'_hom,
LeftHomologyData.map_leftHomologyMap', ← rightHomologyMap'_comp_assoc, ← leftHomologyMap'_comp,
← leftHomologyMap'_comp_assoc, id_comp]
have γ : HomologyMapData (𝟙 (S.map F)) (map S F).homologyData (S.homologyData.map F) := default
have eq := γ.comm
rw [← γ.left.leftHomologyMap'_eq, ← γ.right.rightHomologyMap'_eq] at eq
dsimp at eq
simp only [← reassoc_of% eq, ← F.map_comp, Iso.hom_inv_id, F.map_id, comp_id]
end
section
variable {S}
{F G : C ⥤ D} [F.PreservesZeroMorphisms] [G.PreservesZeroMorphisms]
[F.PreservesLeftHomologyOf S] [G.PreservesLeftHomologyOf S]
[F.PreservesRightHomologyOf S] [G.PreservesRightHomologyOf S]
/-- Given a natural transformation `τ : F ⟶ G` between functors `C ⥤ D` which preserve
the left homology of a short complex `S`, and a left homology data for `S`,
this is the left homology map data for the morphism `S.mapNatTrans τ`
obtained by evaluating `τ`. -/
@[simps]
def LeftHomologyMapData.natTransApp (h : LeftHomologyData S) (τ : F ⟶ G) :
LeftHomologyMapData (S.mapNatTrans τ) (h.map F) (h.map G) where
φK := τ.app h.K
φH := τ.app h.H
/-- Given a natural transformation `τ : F ⟶ G` between functors `C ⥤ D` which preserve
the right homology of a short complex `S`, and a right homology data for `S`,
this is the right homology map data for the morphism `S.mapNatTrans τ`
obtained by evaluating `τ`. -/
@[simps]
def RightHomologyMapData.natTransApp (h : RightHomologyData S) (τ : F ⟶ G) :
RightHomologyMapData (S.mapNatTrans τ) (h.map F) (h.map G) where
φQ := τ.app h.Q
φH := τ.app h.H
/-- Given a natural transformation `τ : F ⟶ G` between functors `C ⥤ D` which preserve
the homology of a short complex `S`, and a homology data for `S`,
this is the homology map data for the morphism `S.mapNatTrans τ`
obtained by evaluating `τ`. -/
@[simps]
def HomologyMapData.natTransApp (h : HomologyData S) (τ : F ⟶ G) :
HomologyMapData (S.mapNatTrans τ) (h.map F) (h.map G) where
left := LeftHomologyMapData.natTransApp h.left τ
right := RightHomologyMapData.natTransApp h.right τ
variable (S)
lemma homologyMap_mapNatTrans [S.HasHomology] (τ : F ⟶ G) :
homologyMap (S.mapNatTrans τ) =
(S.mapHomologyIso F).hom ≫ τ.app S.homology ≫ (S.mapHomologyIso G).inv :=
(LeftHomologyMapData.natTransApp S.homologyData.left τ).homologyMap_eq
end
section
variable [HasKernels C] [HasCokernels C] [HasKernels D] [HasCokernels D]
/-- The natural isomorphism
`F.mapShortComplex ⋙ cyclesFunctor D ≅ cyclesFunctor C ⋙ F`
for a functor `F : C ⥤ D` which preserves homology. -/
noncomputable def cyclesFunctorIso [F.PreservesHomology] :
F.mapShortComplex ⋙ ShortComplex.cyclesFunctor D ≅
ShortComplex.cyclesFunctor C ⋙ F :=
NatIso.ofComponents (fun S => S.mapCyclesIso F)
(fun f => ShortComplex.mapCyclesIso_hom_naturality f F)
/-- The natural isomorphism
`F.mapShortComplex ⋙ leftHomologyFunctor D ≅ leftHomologyFunctor C ⋙ F`
for a functor `F : C ⥤ D` which preserves homology. -/
noncomputable def leftHomologyFunctorIso [F.PreservesHomology] :
F.mapShortComplex ⋙ ShortComplex.leftHomologyFunctor D ≅
ShortComplex.leftHomologyFunctor C ⋙ F :=
NatIso.ofComponents (fun S => S.mapLeftHomologyIso F)
(fun f => ShortComplex.mapLeftHomologyIso_hom_naturality f F)
/-- The natural isomorphism
`F.mapShortComplex ⋙ opcyclesFunctor D ≅ opcyclesFunctor C ⋙ F`
for a functor `F : C ⥤ D` which preserves homology. -/
noncomputable def opcyclesFunctorIso [F.PreservesHomology] :
F.mapShortComplex ⋙ ShortComplex.opcyclesFunctor D ≅
ShortComplex.opcyclesFunctor C ⋙ F :=
NatIso.ofComponents (fun S => S.mapOpcyclesIso F)
(fun f => ShortComplex.mapOpcyclesIso_hom_naturality f F)
/-- The natural isomorphism
`F.mapShortComplex ⋙ rightHomologyFunctor D ≅ rightHomologyFunctor C ⋙ F`
for a functor `F : C ⥤ D` which preserves homology. -/
noncomputable def rightHomologyFunctorIso [F.PreservesHomology] :
F.mapShortComplex ⋙ ShortComplex.rightHomologyFunctor D ≅
ShortComplex.rightHomologyFunctor C ⋙ F :=
NatIso.ofComponents (fun S => S.mapRightHomologyIso F)
(fun f => ShortComplex.mapRightHomologyIso_hom_naturality f F)
end
/-- The natural isomorphism
`F.mapShortComplex ⋙ homologyFunctor D ≅ homologyFunctor C ⋙ F`
for a functor `F : C ⥤ D` which preserves homology. -/
noncomputable def homologyFunctorIso
[CategoryWithHomology C] [CategoryWithHomology D] [F.PreservesHomology] :
F.mapShortComplex ⋙ ShortComplex.homologyFunctor D ≅
ShortComplex.homologyFunctor C ⋙ F :=
NatIso.ofComponents (fun S => S.mapHomologyIso F)
(fun f => ShortComplex.mapHomologyIso_hom_naturality f F)
section
variable
{S₁ S₂ : ShortComplex C} {φ : S₁ ⟶ S₂}
{hl₁ : S₁.LeftHomologyData} {hr₁ : S₁.RightHomologyData}
{hl₂ : S₂.LeftHomologyData} {hr₂ : S₂.RightHomologyData}
(ψl : LeftHomologyMapData φ hl₁ hl₂)
(ψr : RightHomologyMapData φ hr₁ hr₂)
lemma LeftHomologyMapData.quasiIso_map_iff
[(F.mapShortComplex.obj S₁).HasHomology]
[(F.mapShortComplex.obj S₂).HasHomology]
[hl₁.IsPreservedBy F] [hl₂.IsPreservedBy F] :
QuasiIso (F.mapShortComplex.map φ) ↔ IsIso (F.map ψl.φH) :=
(ψl.map F).quasiIso_iff
lemma RightHomologyMapData.quasiIso_map_iff
[(F.mapShortComplex.obj S₁).HasHomology]
[(F.mapShortComplex.obj S₂).HasHomology]
[hr₁.IsPreservedBy F] [hr₂.IsPreservedBy F] :
QuasiIso (F.mapShortComplex.map φ) ↔ IsIso (F.map ψr.φH) :=
(ψr.map F).quasiIso_iff
variable (φ) [S₁.HasHomology] [S₂.HasHomology]
[(F.mapShortComplex.obj S₁).HasHomology] [(F.mapShortComplex.obj S₂).HasHomology]
instance quasiIso_map_of_preservesLeftHomology
[F.PreservesLeftHomologyOf S₁] [F.PreservesLeftHomologyOf S₂]
[QuasiIso φ] : QuasiIso (F.mapShortComplex.map φ) := by
have γ : LeftHomologyMapData φ S₁.leftHomologyData S₂.leftHomologyData := default
have : IsIso γ.φH := by
rw [← γ.quasiIso_iff]
infer_instance
rw [(γ.map F).quasiIso_iff, LeftHomologyMapData.map_φH]
infer_instance
lemma quasiIso_map_iff_of_preservesLeftHomology
[F.PreservesLeftHomologyOf S₁] [F.PreservesLeftHomologyOf S₂]
[F.ReflectsIsomorphisms] :
QuasiIso (F.mapShortComplex.map φ) ↔ QuasiIso φ := by
have γ : LeftHomologyMapData φ S₁.leftHomologyData S₂.leftHomologyData := default
rw [γ.quasiIso_iff, (γ.map F).quasiIso_iff, LeftHomologyMapData.map_φH]
constructor
· intro
exact isIso_of_reflects_iso _ F
· intro
infer_instance
instance quasiIso_map_of_preservesRightHomology
[F.PreservesRightHomologyOf S₁] [F.PreservesRightHomologyOf S₂]
[QuasiIso φ] : QuasiIso (F.mapShortComplex.map φ) := by
have γ : RightHomologyMapData φ S₁.rightHomologyData S₂.rightHomologyData := default
have : IsIso γ.φH := by
rw [← γ.quasiIso_iff]
infer_instance
rw [(γ.map F).quasiIso_iff, RightHomologyMapData.map_φH]
| infer_instance
lemma quasiIso_map_iff_of_preservesRightHomology
[F.PreservesRightHomologyOf S₁] [F.PreservesRightHomologyOf S₂]
[F.ReflectsIsomorphisms] :
QuasiIso (F.mapShortComplex.map φ) ↔ QuasiIso φ := by
have γ : RightHomologyMapData φ S₁.rightHomologyData S₂.rightHomologyData := default
rw [γ.quasiIso_iff, (γ.map F).quasiIso_iff, RightHomologyMapData.map_φH]
constructor
· intro
exact isIso_of_reflects_iso _ F
| Mathlib/Algebra/Homology/ShortComplex/PreservesHomology.lean | 786 | 796 |
/-
Copyright (c) 2020 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.Algebra.Group.Conj
import Mathlib.Algebra.Group.Pi.Lemmas
import Mathlib.Algebra.Group.Subgroup.Ker
/-!
# Basic results on subgroups
We prove basic results on the definitions of subgroups. The bundled subgroups use bundled monoid
homomorphisms.
Special thanks goes to Amelia Livingston and Yury Kudryashov for their help and inspiration.
## Main definitions
Notation used here:
- `G N` are `Group`s
- `A` is an `AddGroup`
- `H K` are `Subgroup`s of `G` or `AddSubgroup`s of `A`
- `x` is an element of type `G` or type `A`
- `f g : N →* G` are group homomorphisms
- `s k` are sets of elements of type `G`
Definitions in the file:
* `Subgroup.prod H K` : the product of subgroups `H`, `K` of groups `G`, `N` respectively, `H × K`
is a subgroup of `G × N`
## Implementation notes
Subgroup inclusion is denoted `≤` rather than `⊆`, although `∈` is defined as
membership of a subgroup's underlying set.
## Tags
subgroup, subgroups
-/
assert_not_exists OrderedAddCommMonoid Multiset Ring
open Function
open scoped Int
variable {G G' G'' : Type*} [Group G] [Group G'] [Group G'']
variable {A : Type*} [AddGroup A]
section SubgroupClass
variable {M S : Type*} [DivInvMonoid M] [SetLike S M] [hSM : SubgroupClass S M] {H K : S}
variable [SetLike S G] [SubgroupClass S G]
@[to_additive]
theorem div_mem_comm_iff {a b : G} : a / b ∈ H ↔ b / a ∈ H :=
inv_div b a ▸ inv_mem_iff
end SubgroupClass
namespace Subgroup
variable (H K : Subgroup G)
@[to_additive]
protected theorem div_mem_comm_iff {a b : G} : a / b ∈ H ↔ b / a ∈ H :=
div_mem_comm_iff
variable {k : Set G}
open Set
variable {N : Type*} [Group N] {P : Type*} [Group P]
/-- Given `Subgroup`s `H`, `K` of groups `G`, `N` respectively, `H × K` as a subgroup of `G × N`. -/
@[to_additive prod
"Given `AddSubgroup`s `H`, `K` of `AddGroup`s `A`, `B` respectively, `H × K`
as an `AddSubgroup` of `A × B`."]
def prod (H : Subgroup G) (K : Subgroup N) : Subgroup (G × N) :=
{ Submonoid.prod H.toSubmonoid K.toSubmonoid with
inv_mem' := fun hx => ⟨H.inv_mem' hx.1, K.inv_mem' hx.2⟩ }
@[to_additive coe_prod]
theorem coe_prod (H : Subgroup G) (K : Subgroup N) :
(H.prod K : Set (G × N)) = (H : Set G) ×ˢ (K : Set N) :=
rfl
@[to_additive mem_prod]
theorem mem_prod {H : Subgroup G} {K : Subgroup N} {p : G × N} : p ∈ H.prod K ↔ p.1 ∈ H ∧ p.2 ∈ K :=
Iff.rfl
open scoped Relator in
@[to_additive prod_mono]
theorem prod_mono : ((· ≤ ·) ⇒ (· ≤ ·) ⇒ (· ≤ ·)) (@prod G _ N _) (@prod G _ N _) :=
fun _s _s' hs _t _t' ht => Set.prod_mono hs ht
@[to_additive prod_mono_right]
theorem prod_mono_right (K : Subgroup G) : Monotone fun t : Subgroup N => K.prod t :=
prod_mono (le_refl K)
@[to_additive prod_mono_left]
theorem prod_mono_left (H : Subgroup N) : Monotone fun K : Subgroup G => K.prod H := fun _ _ hs =>
prod_mono hs (le_refl H)
@[to_additive prod_top]
theorem prod_top (K : Subgroup G) : K.prod (⊤ : Subgroup N) = K.comap (MonoidHom.fst G N) :=
ext fun x => by simp [mem_prod, MonoidHom.coe_fst]
@[to_additive top_prod]
theorem top_prod (H : Subgroup N) : (⊤ : Subgroup G).prod H = H.comap (MonoidHom.snd G N) :=
ext fun x => by simp [mem_prod, MonoidHom.coe_snd]
@[to_additive (attr := simp) top_prod_top]
theorem top_prod_top : (⊤ : Subgroup G).prod (⊤ : Subgroup N) = ⊤ :=
(top_prod _).trans <| comap_top _
@[to_additive (attr := simp) bot_prod_bot]
theorem bot_prod_bot : (⊥ : Subgroup G).prod (⊥ : Subgroup N) = ⊥ :=
SetLike.coe_injective <| by simp [coe_prod]
@[deprecated (since := "2025-03-11")]
alias _root_.AddSubgroup.bot_sum_bot := AddSubgroup.bot_prod_bot
@[to_additive le_prod_iff]
theorem le_prod_iff {H : Subgroup G} {K : Subgroup N} {J : Subgroup (G × N)} :
J ≤ H.prod K ↔ map (MonoidHom.fst G N) J ≤ H ∧ map (MonoidHom.snd G N) J ≤ K := by
simpa only [← Subgroup.toSubmonoid_le] using Submonoid.le_prod_iff
@[to_additive prod_le_iff]
theorem prod_le_iff {H : Subgroup G} {K : Subgroup N} {J : Subgroup (G × N)} :
H.prod K ≤ J ↔ map (MonoidHom.inl G N) H ≤ J ∧ map (MonoidHom.inr G N) K ≤ J := by
simpa only [← Subgroup.toSubmonoid_le] using Submonoid.prod_le_iff
@[to_additive (attr := simp) prod_eq_bot_iff]
theorem prod_eq_bot_iff {H : Subgroup G} {K : Subgroup N} : H.prod K = ⊥ ↔ H = ⊥ ∧ K = ⊥ := by
simpa only [← Subgroup.toSubmonoid_inj] using Submonoid.prod_eq_bot_iff
@[to_additive closure_prod]
theorem closure_prod {s : Set G} {t : Set N} (hs : 1 ∈ s) (ht : 1 ∈ t) :
closure (s ×ˢ t) = (closure s).prod (closure t) :=
le_antisymm
(closure_le _ |>.2 <| Set.prod_subset_prod_iff.2 <| .inl ⟨subset_closure, subset_closure⟩)
(prod_le_iff.2 ⟨
map_le_iff_le_comap.2 <| closure_le _ |>.2 fun _x hx => subset_closure ⟨hx, ht⟩,
map_le_iff_le_comap.2 <| closure_le _ |>.2 fun _y hy => subset_closure ⟨hs, hy⟩⟩)
/-- Product of subgroups is isomorphic to their product as groups. -/
@[to_additive prodEquiv
"Product of additive subgroups is isomorphic to their product
as additive groups"]
def prodEquiv (H : Subgroup G) (K : Subgroup N) : H.prod K ≃* H × K :=
{ Equiv.Set.prod (H : Set G) (K : Set N) with map_mul' := fun _ _ => rfl }
section Pi
variable {η : Type*} {f : η → Type*}
-- defined here and not in Algebra.Group.Submonoid.Operations to have access to Algebra.Group.Pi
/-- A version of `Set.pi` for submonoids. Given an index set `I` and a family of submodules
`s : Π i, Submonoid f i`, `pi I s` is the submonoid of dependent functions `f : Π i, f i` such that
`f i` belongs to `Pi I s` whenever `i ∈ I`. -/
@[to_additive "A version of `Set.pi` for `AddSubmonoid`s. Given an index set `I` and a family
of submodules `s : Π i, AddSubmonoid f i`, `pi I s` is the `AddSubmonoid` of dependent functions
`f : Π i, f i` such that `f i` belongs to `pi I s` whenever `i ∈ I`."]
def _root_.Submonoid.pi [∀ i, MulOneClass (f i)] (I : Set η) (s : ∀ i, Submonoid (f i)) :
Submonoid (∀ i, f i) where
carrier := I.pi fun i => (s i).carrier
one_mem' i _ := (s i).one_mem
mul_mem' hp hq i hI := (s i).mul_mem (hp i hI) (hq i hI)
variable [∀ i, Group (f i)]
/-- A version of `Set.pi` for subgroups. Given an index set `I` and a family of submodules
`s : Π i, Subgroup f i`, `pi I s` is the subgroup of dependent functions `f : Π i, f i` such that
`f i` belongs to `pi I s` whenever `i ∈ I`. -/
@[to_additive
"A version of `Set.pi` for `AddSubgroup`s. Given an index set `I` and a family
of submodules `s : Π i, AddSubgroup f i`, `pi I s` is the `AddSubgroup` of dependent functions
`f : Π i, f i` such that `f i` belongs to `pi I s` whenever `i ∈ I`."]
def pi (I : Set η) (H : ∀ i, Subgroup (f i)) : Subgroup (∀ i, f i) :=
{ Submonoid.pi I fun i => (H i).toSubmonoid with
inv_mem' := fun hp i hI => (H i).inv_mem (hp i hI) }
@[to_additive]
theorem coe_pi (I : Set η) (H : ∀ i, Subgroup (f i)) :
(pi I H : Set (∀ i, f i)) = Set.pi I fun i => (H i : Set (f i)) :=
rfl
@[to_additive]
theorem mem_pi (I : Set η) {H : ∀ i, Subgroup (f i)} {p : ∀ i, f i} :
p ∈ pi I H ↔ ∀ i : η, i ∈ I → p i ∈ H i :=
Iff.rfl
@[to_additive]
theorem pi_top (I : Set η) : (pi I fun i => (⊤ : Subgroup (f i))) = ⊤ :=
ext fun x => by simp [mem_pi]
@[to_additive]
theorem pi_empty (H : ∀ i, Subgroup (f i)) : pi ∅ H = ⊤ :=
ext fun x => by simp [mem_pi]
@[to_additive]
theorem pi_bot : (pi Set.univ fun i => (⊥ : Subgroup (f i))) = ⊥ :=
(eq_bot_iff_forall _).mpr fun p hp => by
simp only [mem_pi, mem_bot] at *
ext j
exact hp j trivial
@[to_additive]
theorem le_pi_iff {I : Set η} {H : ∀ i, Subgroup (f i)} {J : Subgroup (∀ i, f i)} :
J ≤ pi I H ↔ ∀ i : η, i ∈ I → map (Pi.evalMonoidHom f i) J ≤ H i := by
constructor
· intro h i hi
rintro _ ⟨x, hx, rfl⟩
exact (h hx) _ hi
· intro h x hx i hi
exact h i hi ⟨_, hx, rfl⟩
@[to_additive (attr := simp)]
theorem mulSingle_mem_pi [DecidableEq η] {I : Set η} {H : ∀ i, Subgroup (f i)} (i : η) (x : f i) :
Pi.mulSingle i x ∈ pi I H ↔ i ∈ I → x ∈ H i := by
constructor
· intro h hi
simpa using h i hi
· intro h j hj
by_cases heq : j = i
· subst heq
simpa using h hj
· simp [heq, one_mem]
@[to_additive]
theorem pi_eq_bot_iff (H : ∀ i, Subgroup (f i)) : pi Set.univ H = ⊥ ↔ ∀ i, H i = ⊥ := by
classical
simp only [eq_bot_iff_forall]
constructor
· intro h i x hx
have : MonoidHom.mulSingle f i x = 1 :=
h (MonoidHom.mulSingle f i x) ((mulSingle_mem_pi i x).mpr fun _ => hx)
simpa using congr_fun this i
· exact fun h x hx => funext fun i => h _ _ (hx i trivial)
end Pi
end Subgroup
namespace Subgroup
variable {H K : Subgroup G}
variable (H)
/-- A subgroup is characteristic if it is fixed by all automorphisms.
Several equivalent conditions are provided by lemmas of the form `Characteristic.iff...` -/
structure Characteristic : Prop where
/-- `H` is fixed by all automorphisms -/
fixed : ∀ ϕ : G ≃* G, H.comap ϕ.toMonoidHom = H
attribute [class] Characteristic
instance (priority := 100) normal_of_characteristic [h : H.Characteristic] : H.Normal :=
⟨fun a ha b => (SetLike.ext_iff.mp (h.fixed (MulAut.conj b)) a).mpr ha⟩
end Subgroup
namespace AddSubgroup
variable (H : AddSubgroup A)
/-- An `AddSubgroup` is characteristic if it is fixed by all automorphisms.
Several equivalent conditions are provided by lemmas of the form `Characteristic.iff...` -/
structure Characteristic : Prop where
/-- `H` is fixed by all automorphisms -/
fixed : ∀ ϕ : A ≃+ A, H.comap ϕ.toAddMonoidHom = H
attribute [to_additive] Subgroup.Characteristic
attribute [class] Characteristic
instance (priority := 100) normal_of_characteristic [h : H.Characteristic] : H.Normal :=
⟨fun a ha b => (SetLike.ext_iff.mp (h.fixed (AddAut.conj b)) a).mpr ha⟩
end AddSubgroup
namespace Subgroup
variable {H K : Subgroup G}
@[to_additive]
theorem characteristic_iff_comap_eq : H.Characteristic ↔ ∀ ϕ : G ≃* G, H.comap ϕ.toMonoidHom = H :=
⟨Characteristic.fixed, Characteristic.mk⟩
@[to_additive]
theorem characteristic_iff_comap_le : H.Characteristic ↔ ∀ ϕ : G ≃* G, H.comap ϕ.toMonoidHom ≤ H :=
characteristic_iff_comap_eq.trans
⟨fun h ϕ => le_of_eq (h ϕ), fun h ϕ =>
le_antisymm (h ϕ) fun g hg => h ϕ.symm ((congr_arg (· ∈ H) (ϕ.symm_apply_apply g)).mpr hg)⟩
@[to_additive]
theorem characteristic_iff_le_comap : H.Characteristic ↔ ∀ ϕ : G ≃* G, H ≤ H.comap ϕ.toMonoidHom :=
characteristic_iff_comap_eq.trans
⟨fun h ϕ => ge_of_eq (h ϕ), fun h ϕ =>
le_antisymm (fun g hg => (congr_arg (· ∈ H) (ϕ.symm_apply_apply g)).mp (h ϕ.symm hg)) (h ϕ)⟩
@[to_additive]
theorem characteristic_iff_map_eq : H.Characteristic ↔ ∀ ϕ : G ≃* G, H.map ϕ.toMonoidHom = H := by
simp_rw [map_equiv_eq_comap_symm']
exact characteristic_iff_comap_eq.trans ⟨fun h ϕ => h ϕ.symm, fun h ϕ => h ϕ.symm⟩
@[to_additive]
theorem characteristic_iff_map_le : H.Characteristic ↔ ∀ ϕ : G ≃* G, H.map ϕ.toMonoidHom ≤ H := by
simp_rw [map_equiv_eq_comap_symm']
exact characteristic_iff_comap_le.trans ⟨fun h ϕ => h ϕ.symm, fun h ϕ => h ϕ.symm⟩
@[to_additive]
theorem characteristic_iff_le_map : H.Characteristic ↔ ∀ ϕ : G ≃* G, H ≤ H.map ϕ.toMonoidHom := by
simp_rw [map_equiv_eq_comap_symm']
exact characteristic_iff_le_comap.trans ⟨fun h ϕ => h ϕ.symm, fun h ϕ => h ϕ.symm⟩
@[to_additive]
instance botCharacteristic : Characteristic (⊥ : Subgroup G) :=
characteristic_iff_le_map.mpr fun _ϕ => bot_le
@[to_additive]
instance topCharacteristic : Characteristic (⊤ : Subgroup G) :=
characteristic_iff_map_le.mpr fun _ϕ => le_top
variable (H)
section Normalizer
variable {H}
@[to_additive]
theorem normalizer_eq_top_iff : H.normalizer = ⊤ ↔ H.Normal :=
eq_top_iff.trans
⟨fun h => ⟨fun a ha b => (h (mem_top b) a).mp ha⟩, fun h a _ha b =>
⟨fun hb => h.conj_mem b hb a, fun hb => by rwa [h.mem_comm_iff, inv_mul_cancel_left] at hb⟩⟩
variable (H) in
@[to_additive]
theorem normalizer_eq_top [h : H.Normal] : H.normalizer = ⊤ :=
normalizer_eq_top_iff.mpr h
variable {N : Type*} [Group N]
/-- The preimage of the normalizer is contained in the normalizer of the preimage. -/
@[to_additive "The preimage of the normalizer is contained in the normalizer of the preimage."]
theorem le_normalizer_comap (f : N →* G) :
H.normalizer.comap f ≤ (H.comap f).normalizer := fun x => by
simp only [mem_normalizer_iff, mem_comap]
intro h n
simp [h (f n)]
/-- The image of the normalizer is contained in the normalizer of the image. -/
@[to_additive "The image of the normalizer is contained in the normalizer of the image."]
theorem le_normalizer_map (f : G →* N) : H.normalizer.map f ≤ (H.map f).normalizer := fun _ => by
simp only [and_imp, exists_prop, mem_map, exists_imp, mem_normalizer_iff]
rintro x hx rfl n
constructor
· rintro ⟨y, hy, rfl⟩
use x * y * x⁻¹, (hx y).1 hy
simp
· rintro ⟨y, hyH, hy⟩
use x⁻¹ * y * x
rw [hx]
simp [hy, hyH, mul_assoc]
@[to_additive]
theorem comap_normalizer_eq_of_le_range {f : N →* G} (h : H ≤ f.range) :
comap f H.normalizer = (comap f H).normalizer := by
apply le_antisymm (le_normalizer_comap f)
rw [← map_le_iff_le_comap]
apply (le_normalizer_map f).trans
rw [map_comap_eq_self h]
@[to_additive]
theorem subgroupOf_normalizer_eq {H N : Subgroup G} (h : H ≤ N) :
H.normalizer.subgroupOf N = (H.subgroupOf N).normalizer :=
comap_normalizer_eq_of_le_range (h.trans_eq N.range_subtype.symm)
@[to_additive]
theorem normal_subgroupOf_iff_le_normalizer (h : H ≤ K) :
(H.subgroupOf K).Normal ↔ K ≤ H.normalizer := by
rw [← subgroupOf_eq_top, subgroupOf_normalizer_eq h, normalizer_eq_top_iff]
@[to_additive]
theorem normal_subgroupOf_iff_le_normalizer_inf :
(H.subgroupOf K).Normal ↔ K ≤ (H ⊓ K).normalizer :=
inf_subgroupOf_right H K ▸ normal_subgroupOf_iff_le_normalizer inf_le_right
@[to_additive]
instance (priority := 100) normal_in_normalizer : (H.subgroupOf H.normalizer).Normal :=
(normal_subgroupOf_iff_le_normalizer H.le_normalizer).mpr le_rfl
@[to_additive]
theorem le_normalizer_of_normal_subgroupOf [hK : (H.subgroupOf K).Normal] (HK : H ≤ K) :
K ≤ H.normalizer :=
(normal_subgroupOf_iff_le_normalizer HK).mp hK
@[to_additive]
theorem subset_normalizer_of_normal {S : Set G} [hH : H.Normal] : S ⊆ H.normalizer :=
(@normalizer_eq_top _ _ H hH) ▸ le_top
@[to_additive]
theorem le_normalizer_of_normal [H.Normal] : K ≤ H.normalizer := subset_normalizer_of_normal
@[to_additive]
theorem inf_normalizer_le_normalizer_inf : H.normalizer ⊓ K.normalizer ≤ (H ⊓ K).normalizer :=
fun _ h g ↦ and_congr (h.1 g) (h.2 g)
variable (G) in
/-- Every proper subgroup `H` of `G` is a proper normal subgroup of the normalizer of `H` in `G`. -/
def _root_.NormalizerCondition :=
∀ H : Subgroup G, H < ⊤ → H < normalizer H
/-- Alternative phrasing of the normalizer condition: Only the full group is self-normalizing.
This may be easier to work with, as it avoids inequalities and negations. -/
theorem _root_.normalizerCondition_iff_only_full_group_self_normalizing :
NormalizerCondition G ↔ ∀ H : Subgroup G, H.normalizer = H → H = ⊤ := by
apply forall_congr'; intro H
simp only [lt_iff_le_and_ne, le_normalizer, le_top, Ne]
tauto
variable (H)
end Normalizer
end Subgroup
namespace Group
variable {s : Set G}
/-- Given a set `s`, `conjugatesOfSet s` is the set of all conjugates of
the elements of `s`. -/
def conjugatesOfSet (s : Set G) : Set G :=
⋃ a ∈ s, conjugatesOf a
theorem mem_conjugatesOfSet_iff {x : G} : x ∈ conjugatesOfSet s ↔ ∃ a ∈ s, IsConj a x := by
rw [conjugatesOfSet, Set.mem_iUnion₂]
simp only [conjugatesOf, isConj_iff, Set.mem_setOf_eq, exists_prop]
theorem subset_conjugatesOfSet : s ⊆ conjugatesOfSet s := fun (x : G) (h : x ∈ s) =>
mem_conjugatesOfSet_iff.2 ⟨x, h, IsConj.refl _⟩
theorem conjugatesOfSet_mono {s t : Set G} (h : s ⊆ t) : conjugatesOfSet s ⊆ conjugatesOfSet t :=
Set.biUnion_subset_biUnion_left h
theorem conjugates_subset_normal {N : Subgroup G} [tn : N.Normal] {a : G} (h : a ∈ N) :
conjugatesOf a ⊆ N := by
rintro a hc
obtain ⟨c, rfl⟩ := isConj_iff.1 hc
exact tn.conj_mem a h c
theorem conjugatesOfSet_subset {s : Set G} {N : Subgroup G} [N.Normal] (h : s ⊆ N) :
conjugatesOfSet s ⊆ N :=
Set.iUnion₂_subset fun _x H => conjugates_subset_normal (h H)
/-- The set of conjugates of `s` is closed under conjugation. -/
theorem conj_mem_conjugatesOfSet {x c : G} :
x ∈ conjugatesOfSet s → c * x * c⁻¹ ∈ conjugatesOfSet s := fun H => by
rcases mem_conjugatesOfSet_iff.1 H with ⟨a, h₁, h₂⟩
exact mem_conjugatesOfSet_iff.2 ⟨a, h₁, h₂.trans (isConj_iff.2 ⟨c, rfl⟩)⟩
end Group
namespace Subgroup
open Group
variable {s : Set G}
/-- The normal closure of a set `s` is the subgroup closure of all the conjugates of
elements of `s`. It is the smallest normal subgroup containing `s`. -/
def normalClosure (s : Set G) : Subgroup G :=
closure (conjugatesOfSet s)
theorem conjugatesOfSet_subset_normalClosure : conjugatesOfSet s ⊆ normalClosure s :=
subset_closure
theorem subset_normalClosure : s ⊆ normalClosure s :=
Set.Subset.trans subset_conjugatesOfSet conjugatesOfSet_subset_normalClosure
theorem le_normalClosure {H : Subgroup G} : H ≤ normalClosure ↑H := fun _ h =>
subset_normalClosure h
/-- The normal closure of `s` is a normal subgroup. -/
instance normalClosure_normal : (normalClosure s).Normal :=
⟨fun n h g => by
refine Subgroup.closure_induction (fun x hx => ?_) ?_ (fun x y _ _ ihx ihy => ?_)
(fun x _ ihx => ?_) h
· exact conjugatesOfSet_subset_normalClosure (conj_mem_conjugatesOfSet hx)
· simpa using (normalClosure s).one_mem
· rw [← conj_mul]
exact mul_mem ihx ihy
· rw [← conj_inv]
exact inv_mem ihx⟩
/-- The normal closure of `s` is the smallest normal subgroup containing `s`. -/
theorem normalClosure_le_normal {N : Subgroup G} [N.Normal] (h : s ⊆ N) : normalClosure s ≤ N := by
intro a w
refine closure_induction (fun x hx => ?_) ?_ (fun x y _ _ ihx ihy => ?_) (fun x _ ihx => ?_) w
· exact conjugatesOfSet_subset h hx
· exact one_mem _
· exact mul_mem ihx ihy
· exact inv_mem ihx
theorem normalClosure_subset_iff {N : Subgroup G} [N.Normal] : s ⊆ N ↔ normalClosure s ≤ N :=
⟨normalClosure_le_normal, Set.Subset.trans subset_normalClosure⟩
@[gcongr]
theorem normalClosure_mono {s t : Set G} (h : s ⊆ t) : normalClosure s ≤ normalClosure t :=
normalClosure_le_normal (Set.Subset.trans h subset_normalClosure)
theorem normalClosure_eq_iInf :
normalClosure s = ⨅ (N : Subgroup G) (_ : Normal N) (_ : s ⊆ N), N :=
le_antisymm (le_iInf fun _ => le_iInf fun _ => le_iInf normalClosure_le_normal)
(iInf_le_of_le (normalClosure s)
(iInf_le_of_le (by infer_instance) (iInf_le_of_le subset_normalClosure le_rfl)))
@[simp]
theorem normalClosure_eq_self (H : Subgroup G) [H.Normal] : normalClosure ↑H = H :=
le_antisymm (normalClosure_le_normal rfl.subset) le_normalClosure
theorem normalClosure_idempotent : normalClosure ↑(normalClosure s) = normalClosure s :=
normalClosure_eq_self _
theorem closure_le_normalClosure {s : Set G} : closure s ≤ normalClosure s := by
simp only [subset_normalClosure, closure_le]
@[simp]
theorem normalClosure_closure_eq_normalClosure {s : Set G} :
normalClosure ↑(closure s) = normalClosure s :=
le_antisymm (normalClosure_le_normal closure_le_normalClosure) (normalClosure_mono subset_closure)
/-- The normal core of a subgroup `H` is the largest normal subgroup of `G` contained in `H`,
as shown by `Subgroup.normalCore_eq_iSup`. -/
def normalCore (H : Subgroup G) : Subgroup G where
carrier := { a : G | ∀ b : G, b * a * b⁻¹ ∈ H }
one_mem' a := by rw [mul_one, mul_inv_cancel]; exact H.one_mem
inv_mem' {_} h b := (congr_arg (· ∈ H) conj_inv).mp (H.inv_mem (h b))
mul_mem' {_ _} ha hb c := (congr_arg (· ∈ H) conj_mul).mp (H.mul_mem (ha c) (hb c))
theorem normalCore_le (H : Subgroup G) : H.normalCore ≤ H := fun a h => by
rw [← mul_one a, ← inv_one, ← one_mul a]
exact h 1
instance normalCore_normal (H : Subgroup G) : H.normalCore.Normal :=
⟨fun a h b c => by
rw [mul_assoc, mul_assoc, ← mul_inv_rev, ← mul_assoc, ← mul_assoc]; exact h (c * b)⟩
theorem normal_le_normalCore {H : Subgroup G} {N : Subgroup G} [hN : N.Normal] :
N ≤ H.normalCore ↔ N ≤ H :=
⟨ge_trans H.normalCore_le, fun h_le n hn g => h_le (hN.conj_mem n hn g)⟩
theorem normalCore_mono {H K : Subgroup G} (h : H ≤ K) : H.normalCore ≤ K.normalCore :=
normal_le_normalCore.mpr (H.normalCore_le.trans h)
theorem normalCore_eq_iSup (H : Subgroup G) :
H.normalCore = ⨆ (N : Subgroup G) (_ : Normal N) (_ : N ≤ H), N :=
le_antisymm
(le_iSup_of_le H.normalCore
(le_iSup_of_le H.normalCore_normal (le_iSup_of_le H.normalCore_le le_rfl)))
(iSup_le fun _ => iSup_le fun _ => iSup_le normal_le_normalCore.mpr)
@[simp]
theorem normalCore_eq_self (H : Subgroup G) [H.Normal] : H.normalCore = H :=
le_antisymm H.normalCore_le (normal_le_normalCore.mpr le_rfl)
theorem normalCore_idempotent (H : Subgroup G) : H.normalCore.normalCore = H.normalCore :=
H.normalCore.normalCore_eq_self
end Subgroup
namespace MonoidHom
variable {N : Type*} {P : Type*} [Group N] [Group P] (K : Subgroup G)
open Subgroup
section Ker
variable {M : Type*} [MulOneClass M]
@[to_additive prodMap_comap_prod]
theorem prodMap_comap_prod {G' : Type*} {N' : Type*} [Group G'] [Group N'] (f : G →* N)
(g : G' →* N') (S : Subgroup N) (S' : Subgroup N') :
(S.prod S').comap (prodMap f g) = (S.comap f).prod (S'.comap g) :=
SetLike.coe_injective <| Set.preimage_prod_map_prod f g _ _
@[deprecated (since := "2025-03-11")]
alias _root_.AddMonoidHom.sumMap_comap_sum := AddMonoidHom.prodMap_comap_prod
@[to_additive ker_prodMap]
theorem ker_prodMap {G' : Type*} {N' : Type*} [Group G'] [Group N'] (f : G →* N) (g : G' →* N') :
(prodMap f g).ker = f.ker.prod g.ker := by
rw [← comap_bot, ← comap_bot, ← comap_bot, ← prodMap_comap_prod, bot_prod_bot]
@[deprecated (since := "2025-03-11")]
alias _root_.AddMonoidHom.ker_sumMap := AddMonoidHom.ker_prodMap
@[to_additive (attr := simp)]
lemma ker_fst : ker (fst G G') = .prod ⊥ ⊤ := SetLike.ext fun _ => (iff_of_eq (and_true _)).symm
@[to_additive (attr := simp)]
lemma ker_snd : ker (snd G G') = .prod ⊤ ⊥ := SetLike.ext fun _ => (iff_of_eq (true_and _)).symm
end Ker
end MonoidHom
namespace Subgroup
variable {N : Type*} [Group N] (H : Subgroup G)
@[to_additive]
theorem Normal.map {H : Subgroup G} (h : H.Normal) (f : G →* N) (hf : Function.Surjective f) :
(H.map f).Normal := by
rw [← normalizer_eq_top_iff, ← top_le_iff, ← f.range_eq_top_of_surjective hf, f.range_eq_map,
← H.normalizer_eq_top]
exact le_normalizer_map _
end Subgroup
namespace Subgroup
open MonoidHom
variable {N : Type*} [Group N] (f : G →* N)
/-- The preimage of the normalizer is equal to the normalizer of the preimage of a surjective
function. -/
@[to_additive
"The preimage of the normalizer is equal to the normalizer of the preimage of
a surjective function."]
theorem comap_normalizer_eq_of_surjective (H : Subgroup G) {f : N →* G}
(hf : Function.Surjective f) : H.normalizer.comap f = (H.comap f).normalizer :=
comap_normalizer_eq_of_le_range fun x _ ↦ hf x
@[deprecated (since := "2025-03-13")]
alias comap_normalizer_eq_of_injective_of_le_range := comap_normalizer_eq_of_le_range
@[deprecated (since := "2025-03-13")]
alias _root_.AddSubgroup.comap_normalizer_eq_of_injective_of_le_range :=
AddSubgroup.comap_normalizer_eq_of_le_range
/-- The image of the normalizer is equal to the normalizer of the image of an isomorphism. -/
@[to_additive
"The image of the normalizer is equal to the normalizer of the image of an
isomorphism."]
theorem map_equiv_normalizer_eq (H : Subgroup G) (f : G ≃* N) :
H.normalizer.map f.toMonoidHom = (H.map f.toMonoidHom).normalizer := by
ext x
simp only [mem_normalizer_iff, mem_map_equiv]
rw [f.toEquiv.forall_congr]
intro
simp
/-- The image of the normalizer is equal to the normalizer of the image of a bijective
function. -/
@[to_additive
"The image of the normalizer is equal to the normalizer of the image of a bijective
function."]
theorem map_normalizer_eq_of_bijective (H : Subgroup G) {f : G →* N} (hf : Function.Bijective f) :
H.normalizer.map f = (H.map f).normalizer :=
map_equiv_normalizer_eq H (MulEquiv.ofBijective f hf)
end Subgroup
namespace MonoidHom
variable {G₁ G₂ G₃ : Type*} [Group G₁] [Group G₂] [Group G₃]
variable (f : G₁ →* G₂) (f_inv : G₂ → G₁)
/-- Auxiliary definition used to define `liftOfRightInverse` -/
@[to_additive "Auxiliary definition used to define `liftOfRightInverse`"]
def liftOfRightInverseAux (hf : Function.RightInverse f_inv f) (g : G₁ →* G₃) (hg : f.ker ≤ g.ker) :
G₂ →* G₃ where
toFun b := g (f_inv b)
map_one' := hg (hf 1)
map_mul' := by
intro x y
rw [← g.map_mul, ← mul_inv_eq_one, ← g.map_inv, ← g.map_mul, ← g.mem_ker]
apply hg
rw [f.mem_ker, f.map_mul, f.map_inv, mul_inv_eq_one, f.map_mul]
simp only [hf _]
@[to_additive (attr := simp)]
theorem liftOfRightInverseAux_comp_apply (hf : Function.RightInverse f_inv f) (g : G₁ →* G₃)
(hg : f.ker ≤ g.ker) (x : G₁) : (f.liftOfRightInverseAux f_inv hf g hg) (f x) = g x := by
dsimp [liftOfRightInverseAux]
rw [← mul_inv_eq_one, ← g.map_inv, ← g.map_mul, ← g.mem_ker]
apply hg
rw [f.mem_ker, f.map_mul, f.map_inv, mul_inv_eq_one]
simp only [hf _]
/-- `liftOfRightInverse f hf g hg` is the unique group homomorphism `φ`
* such that `φ.comp f = g` (`MonoidHom.liftOfRightInverse_comp`),
* where `f : G₁ →+* G₂` has a RightInverse `f_inv` (`hf`),
* and `g : G₂ →+* G₃` satisfies `hg : f.ker ≤ g.ker`.
See `MonoidHom.eq_liftOfRightInverse` for the uniqueness lemma.
```
G₁.
| \
f | \ g
| \
v \⌟
G₂----> G₃
∃!φ
```
-/
@[to_additive
"`liftOfRightInverse f f_inv hf g hg` is the unique additive group homomorphism `φ`
* such that `φ.comp f = g` (`AddMonoidHom.liftOfRightInverse_comp`),
* where `f : G₁ →+ G₂` has a RightInverse `f_inv` (`hf`),
* and `g : G₂ →+ G₃` satisfies `hg : f.ker ≤ g.ker`.
See `AddMonoidHom.eq_liftOfRightInverse` for the uniqueness lemma.
```
G₁.
| \\
f | \\ g
| \\
v \\⌟
G₂----> G₃
∃!φ
```"]
def liftOfRightInverse (hf : Function.RightInverse f_inv f) :
{ g : G₁ →* G₃ // f.ker ≤ g.ker } ≃ (G₂ →* G₃) where
toFun g := f.liftOfRightInverseAux f_inv hf g.1 g.2
invFun φ := ⟨φ.comp f, fun x hx ↦ mem_ker.mpr <| by simp [mem_ker.mp hx]⟩
left_inv g := by
ext
simp only [comp_apply, liftOfRightInverseAux_comp_apply, Subtype.coe_mk]
right_inv φ := by
ext b
simp [liftOfRightInverseAux, hf b]
/-- A non-computable version of `MonoidHom.liftOfRightInverse` for when no computable right
inverse is available, that uses `Function.surjInv`. -/
@[to_additive (attr := simp)
"A non-computable version of `AddMonoidHom.liftOfRightInverse` for when no
computable right inverse is available."]
noncomputable abbrev liftOfSurjective (hf : Function.Surjective f) :
{ g : G₁ →* G₃ // f.ker ≤ g.ker } ≃ (G₂ →* G₃) :=
f.liftOfRightInverse (Function.surjInv hf) (Function.rightInverse_surjInv hf)
@[to_additive (attr := simp)]
theorem liftOfRightInverse_comp_apply (hf : Function.RightInverse f_inv f)
(g : { g : G₁ →* G₃ // f.ker ≤ g.ker }) (x : G₁) :
(f.liftOfRightInverse f_inv hf g) (f x) = g.1 x :=
f.liftOfRightInverseAux_comp_apply f_inv hf g.1 g.2 x
@[to_additive (attr := simp)]
theorem liftOfRightInverse_comp (hf : Function.RightInverse f_inv f)
(g : { g : G₁ →* G₃ // f.ker ≤ g.ker }) : (f.liftOfRightInverse f_inv hf g).comp f = g :=
MonoidHom.ext <| f.liftOfRightInverse_comp_apply f_inv hf g
@[to_additive]
theorem eq_liftOfRightInverse (hf : Function.RightInverse f_inv f) (g : G₁ →* G₃)
(hg : f.ker ≤ g.ker) (h : G₂ →* G₃) (hh : h.comp f = g) :
h = f.liftOfRightInverse f_inv hf ⟨g, hg⟩ := by
simp_rw [← hh]
exact ((f.liftOfRightInverse f_inv hf).apply_symm_apply _).symm
end MonoidHom
variable {N : Type*} [Group N]
namespace Subgroup
-- Here `H.Normal` is an explicit argument so we can use dot notation with `comap`.
@[to_additive]
theorem Normal.comap {H : Subgroup N} (hH : H.Normal) (f : G →* N) : (H.comap f).Normal :=
⟨fun _ => by simp +contextual [Subgroup.mem_comap, hH.conj_mem]⟩
@[to_additive]
instance (priority := 100) normal_comap {H : Subgroup N} [nH : H.Normal] (f : G →* N) :
(H.comap f).Normal :=
nH.comap _
-- Here `H.Normal` is an explicit argument so we can use dot notation with `subgroupOf`.
@[to_additive]
theorem Normal.subgroupOf {H : Subgroup G} (hH : H.Normal) (K : Subgroup G) :
(H.subgroupOf K).Normal :=
hH.comap _
@[to_additive]
instance (priority := 100) normal_subgroupOf {H N : Subgroup G} [N.Normal] :
(N.subgroupOf H).Normal :=
Subgroup.normal_comap _
theorem map_normalClosure (s : Set G) (f : G →* N) (hf : Surjective f) :
(normalClosure s).map f = normalClosure (f '' s) := by
have : Normal (map f (normalClosure s)) := Normal.map inferInstance f hf
apply le_antisymm
· simp [map_le_iff_le_comap, normalClosure_le_normal, coe_comap,
← Set.image_subset_iff, subset_normalClosure]
· exact normalClosure_le_normal (Set.image_subset f subset_normalClosure)
theorem comap_normalClosure (s : Set N) (f : G ≃* N) :
normalClosure (f ⁻¹' s) = (normalClosure s).comap f := by
have := Set.preimage_equiv_eq_image_symm s f.toEquiv
simp_all [comap_equiv_eq_map_symm, map_normalClosure s (f.symm : N →* G) f.symm.surjective]
lemma Normal.of_map_injective {G H : Type*} [Group G] [Group H] {φ : G →* H}
(hφ : Function.Injective φ) {L : Subgroup G} (n : (L.map φ).Normal) : L.Normal :=
L.comap_map_eq_self_of_injective hφ ▸ n.comap φ
theorem Normal.of_map_subtype {K : Subgroup G} {L : Subgroup K}
(n : (Subgroup.map K.subtype L).Normal) : L.Normal :=
n.of_map_injective K.subtype_injective
end Subgroup
namespace Subgroup
section SubgroupNormal
@[to_additive]
theorem normal_subgroupOf_iff {H K : Subgroup G} (hHK : H ≤ K) :
(H.subgroupOf K).Normal ↔ ∀ h k, h ∈ H → k ∈ K → k * h * k⁻¹ ∈ H :=
⟨fun hN h k hH hK => hN.conj_mem ⟨h, hHK hH⟩ hH ⟨k, hK⟩, fun hN =>
{ conj_mem := fun h hm k => hN h.1 k.1 hm k.2 }⟩
@[to_additive prod_addSubgroupOf_prod_normal]
instance prod_subgroupOf_prod_normal {H₁ K₁ : Subgroup G} {H₂ K₂ : Subgroup N}
[h₁ : (H₁.subgroupOf K₁).Normal] [h₂ : (H₂.subgroupOf K₂).Normal] :
((H₁.prod H₂).subgroupOf (K₁.prod K₂)).Normal where
conj_mem n hgHK g :=
⟨h₁.conj_mem ⟨(n : G × N).fst, (mem_prod.mp n.2).1⟩ hgHK.1
⟨(g : G × N).fst, (mem_prod.mp g.2).1⟩,
h₂.conj_mem ⟨(n : G × N).snd, (mem_prod.mp n.2).2⟩ hgHK.2
⟨(g : G × N).snd, (mem_prod.mp g.2).2⟩⟩
@[deprecated (since := "2025-03-11")]
alias _root_.AddSubgroup.sum_addSubgroupOf_sum_normal := AddSubgroup.prod_addSubgroupOf_prod_normal
@[to_additive prod_normal]
instance prod_normal (H : Subgroup G) (K : Subgroup N) [hH : H.Normal] [hK : K.Normal] :
(H.prod K).Normal where
conj_mem n hg g :=
⟨hH.conj_mem n.fst (Subgroup.mem_prod.mp hg).1 g.fst,
hK.conj_mem n.snd (Subgroup.mem_prod.mp hg).2 g.snd⟩
@[deprecated (since := "2025-03-11")]
alias _root_.AddSubgroup.sum_normal := AddSubgroup.prod_normal
@[to_additive]
theorem inf_subgroupOf_inf_normal_of_right (A B' B : Subgroup G)
[hN : (B'.subgroupOf B).Normal] : ((A ⊓ B').subgroupOf (A ⊓ B)).Normal := by
rw [normal_subgroupOf_iff_le_normalizer_inf] at hN ⊢
rw [inf_inf_inf_comm, inf_idem]
exact le_trans (inf_le_inf A.le_normalizer hN) (inf_normalizer_le_normalizer_inf)
@[to_additive]
theorem inf_subgroupOf_inf_normal_of_left {A' A : Subgroup G} (B : Subgroup G)
[hN : (A'.subgroupOf A).Normal] : ((A' ⊓ B).subgroupOf (A ⊓ B)).Normal := by
rw [normal_subgroupOf_iff_le_normalizer_inf] at hN ⊢
rw [inf_inf_inf_comm, inf_idem]
exact le_trans (inf_le_inf hN B.le_normalizer) (inf_normalizer_le_normalizer_inf)
@[to_additive]
instance normal_inf_normal (H K : Subgroup G) [hH : H.Normal] [hK : K.Normal] : (H ⊓ K).Normal :=
⟨fun n hmem g => ⟨hH.conj_mem n hmem.1 g, hK.conj_mem n hmem.2 g⟩⟩
@[to_additive]
theorem normal_iInf_normal {ι : Type*} {a : ι → Subgroup G}
(norm : ∀ i : ι, (a i).Normal) : (iInf a).Normal := by
constructor
intro g g_in_iInf h
rw [Subgroup.mem_iInf] at g_in_iInf ⊢
intro i
exact (norm i).conj_mem g (g_in_iInf i) h
@[to_additive]
theorem SubgroupNormal.mem_comm {H K : Subgroup G} (hK : H ≤ K) [hN : (H.subgroupOf K).Normal]
{a b : G} (hb : b ∈ K) (h : a * b ∈ H) : b * a ∈ H := by
have := (normal_subgroupOf_iff hK).mp hN (a * b) b h hb
rwa [mul_assoc, mul_assoc, mul_inv_cancel, mul_one] at this
/-- Elements of disjoint, normal subgroups commute. -/
@[to_additive "Elements of disjoint, normal subgroups commute."]
theorem commute_of_normal_of_disjoint (H₁ H₂ : Subgroup G) (hH₁ : H₁.Normal) (hH₂ : H₂.Normal)
(hdis : Disjoint H₁ H₂) (x y : G) (hx : x ∈ H₁) (hy : y ∈ H₂) : Commute x y := by
suffices x * y * x⁻¹ * y⁻¹ = 1 by
show x * y = y * x
· rw [mul_assoc, mul_eq_one_iff_eq_inv] at this
simpa
apply hdis.le_bot
constructor
· suffices x * (y * x⁻¹ * y⁻¹) ∈ H₁ by simpa [mul_assoc]
exact H₁.mul_mem hx (hH₁.conj_mem _ (H₁.inv_mem hx) _)
· show x * y * x⁻¹ * y⁻¹ ∈ H₂
apply H₂.mul_mem _ (H₂.inv_mem hy)
apply hH₂.conj_mem _ hy
@[to_additive]
theorem normal_subgroupOf_of_le_normalizer {H N : Subgroup G}
(hLE : H ≤ N.normalizer) : (N.subgroupOf H).Normal := by
rw [normal_subgroupOf_iff_le_normalizer_inf]
exact (le_inf hLE H.le_normalizer).trans inf_normalizer_le_normalizer_inf
@[to_additive]
theorem normal_subgroupOf_sup_of_le_normalizer {H N : Subgroup G}
(hLE : H ≤ N.normalizer) : (N.subgroupOf (H ⊔ N)).Normal := by
rw [normal_subgroupOf_iff_le_normalizer le_sup_right]
exact sup_le hLE le_normalizer
end SubgroupNormal
end Subgroup
namespace IsConj
open Subgroup
theorem normalClosure_eq_top_of {N : Subgroup G} [hn : N.Normal] {g g' : G} {hg : g ∈ N}
{hg' : g' ∈ N} (hc : IsConj g g') (ht : normalClosure ({⟨g, hg⟩} : Set N) = ⊤) :
normalClosure ({⟨g', hg'⟩} : Set N) = ⊤ := by
obtain ⟨c, rfl⟩ := isConj_iff.1 hc
have h : ∀ x : N, (MulAut.conj c) x ∈ N := by
rintro ⟨x, hx⟩
exact hn.conj_mem _ hx c
have hs : Function.Surjective (((MulAut.conj c).toMonoidHom.restrict N).codRestrict _ h) := by
rintro ⟨x, hx⟩
refine ⟨⟨c⁻¹ * x * c, ?_⟩, ?_⟩
· have h := hn.conj_mem _ hx c⁻¹
rwa [inv_inv] at h
simp only [MonoidHom.codRestrict_apply, MulEquiv.coe_toMonoidHom, MulAut.conj_apply, coe_mk,
MonoidHom.restrict_apply, Subtype.mk_eq_mk, ← mul_assoc, mul_inv_cancel, one_mul]
rw [mul_assoc, mul_inv_cancel, mul_one]
rw [eq_top_iff, ← MonoidHom.range_eq_top.2 hs, MonoidHom.range_eq_map]
refine le_trans (map_mono (eq_top_iff.1 ht)) (map_le_iff_le_comap.2 (normalClosure_le_normal ?_))
rw [Set.singleton_subset_iff, SetLike.mem_coe]
simp only [MonoidHom.codRestrict_apply, MulEquiv.coe_toMonoidHom, MulAut.conj_apply, coe_mk,
MonoidHom.restrict_apply, mem_comap]
exact subset_normalClosure (Set.mem_singleton _)
end IsConj
namespace ConjClasses
/-- The conjugacy classes that are not trivial. -/
def noncenter (G : Type*) [Monoid G] : Set (ConjClasses G) :=
{x | x.carrier.Nontrivial}
@[simp] lemma mem_noncenter {G} [Monoid G] (g : ConjClasses G) :
g ∈ noncenter G ↔ g.carrier.Nontrivial := Iff.rfl
end ConjClasses
/-- Suppose `G` acts on `M` and `I` is a subgroup of `M`.
The inertia subgroup of `I` is the subgroup of `G` whose action is trivial mod `I`. -/
def AddSubgroup.inertia {M : Type*} [AddGroup M] (I : AddSubgroup M) (G : Type*)
[Group G] [MulAction G M] : Subgroup G where
carrier := { σ | ∀ x, σ • x - x ∈ I }
mul_mem' {a b} ha hb x := by simpa [mul_smul] using add_mem (ha (b • x)) (hb x)
one_mem' := by simp [zero_mem]
inv_mem' {a} ha x := by simpa using sub_mem_comm_iff.mp (ha (a⁻¹ • x))
@[simp] lemma AddSubgroup.mem_inertia {M : Type*} [AddGroup M] {I : AddSubgroup M} {G : Type*}
[Group G] [MulAction G M] {σ : G} : σ ∈ I.inertia G ↔ ∀ x, σ • x - x ∈ I := .rfl
| Mathlib/Algebra/Group/Subgroup/Basic.lean | 2,146 | 2,150 | |
/-
Copyright (c) 2022 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.ModelTheory.Quotients
import Mathlib.Order.Filter.Finite
import Mathlib.Order.Filter.Germ.Basic
import Mathlib.Order.Filter.Ultrafilter.Defs
/-!
# Ultraproducts and Łoś's Theorem
## Main Definitions
- `FirstOrder.Language.Ultraproduct.Structure` is the ultraproduct structure on `Filter.Product`.
## Main Results
- Łoś's Theorem: `FirstOrder.Language.Ultraproduct.sentence_realize`. An ultraproduct models a
sentence `φ` if and only if the set of structures in the product that model `φ` is in the
ultrafilter.
## Tags
ultraproduct, Los's theorem
-/
universe u v
variable {α : Type*} (M : α → Type*) (u : Ultrafilter α)
open FirstOrder Filter
open Filter
namespace FirstOrder
namespace Language
open Structure
variable {L : Language.{u, v}} [∀ a, L.Structure (M a)]
namespace Ultraproduct
instance setoidPrestructure : L.Prestructure ((u : Filter α).productSetoid M) :=
{ (u : Filter α).productSetoid M with
toStructure :=
{ funMap := fun {_} f x a => funMap f fun i => x i a
RelMap := fun {_} r x => ∀ᶠ a : α in u, RelMap r fun i => x i a }
fun_equiv := fun {n} f x y xy => by
refine mem_of_superset (iInter_mem.2 xy) fun a ha => ?_
simp only [Set.mem_iInter, Set.mem_setOf_eq] at ha
simp only [Set.mem_setOf_eq, ha]
rel_equiv := fun {n} r x y xy => by
rw [← iff_eq_eq]
refine ⟨fun hx => ?_, fun hy => ?_⟩
· refine mem_of_superset (inter_mem hx (iInter_mem.2 xy)) ?_
rintro a ⟨ha1, ha2⟩
simp only [Set.mem_iInter, Set.mem_setOf_eq] at *
rw [← funext ha2]
exact ha1
· refine mem_of_superset (inter_mem hy (iInter_mem.2 xy)) ?_
rintro a ⟨ha1, ha2⟩
simp only [Set.mem_iInter, Set.mem_setOf_eq] at *
rw [funext ha2]
exact ha1 }
variable {M} {u}
instance «structure» : L.Structure ((u : Filter α).Product M) :=
Language.quotientStructure
theorem funMap_cast {n : ℕ} (f : L.Functions n) (x : Fin n → ∀ a, M a) :
| (funMap f fun i => (x i : (u : Filter α).Product M)) =
(fun a => funMap f fun i => x i a : (u : Filter α).Product M) := by
apply funMap_quotient_mk'
| Mathlib/ModelTheory/Ultraproducts.lean | 76 | 79 |
/-
Copyright (c) 2023 Peter Nelson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Peter Nelson
-/
import Mathlib.SetTheory.Cardinal.Finite
import Mathlib.Data.Set.Finite.Powerset
/-!
# Noncomputable Set Cardinality
We define the cardinality of set `s` as a term `Set.encard s : ℕ∞` and a term `Set.ncard s : ℕ`.
The latter takes the junk value of zero if `s` is infinite. Both functions are noncomputable, and
are defined in terms of `ENat.card` (which takes a type as its argument); this file can be seen
as an API for the same function in the special case where the type is a coercion of a `Set`,
allowing for smoother interactions with the `Set` API.
`Set.encard` never takes junk values, so is more mathematically natural than `Set.ncard`, even
though it takes values in a less convenient type. It is probably the right choice in settings where
one is concerned with the cardinalities of sets that may or may not be infinite.
`Set.ncard` has a nicer codomain, but when using it, `Set.Finite` hypotheses are normally needed to
make sure its values are meaningful. More generally, `Set.ncard` is intended to be used over the
obvious alternative `Finset.card` when finiteness is 'propositional' rather than 'structural'.
When working with sets that are finite by virtue of their definition, then `Finset.card` probably
makes more sense. One setting where `Set.ncard` works nicely is in a type `α` with `[Finite α]`,
where every set is automatically finite. In this setting, we use default arguments and a simple
tactic so that finiteness goals are discharged automatically in `Set.ncard` theorems.
## Main Definitions
* `Set.encard s` is the cardinality of the set `s` as an extended natural number, with value `⊤` if
`s` is infinite.
* `Set.ncard s` is the cardinality of the set `s` as a natural number, provided `s` is Finite.
If `s` is Infinite, then `Set.ncard s = 0`.
* `toFinite_tac` is a tactic that tries to synthesize a `Set.Finite s` argument with
`Set.toFinite`. This will work for `s : Set α` where there is a `Finite α` instance.
## Implementation Notes
The theorems in this file are very similar to those in `Data.Finset.Card`, but with `Set` operations
instead of `Finset`. We first prove all the theorems for `Set.encard`, and then derive most of the
`Set.ncard` results as a consequence. Things are done this way to avoid reliance on the `Finset` API
for theorems about infinite sets, and to allow for a refactor that removes or modifies `Set.ncard`
in the future.
Nearly all the theorems for `Set.ncard` require finiteness of one or more of their arguments. We
provide this assumption with a default argument of the form `(hs : s.Finite := by toFinite_tac)`,
where `toFinite_tac` will find an `s.Finite` term in the cases where `s` is a set in a `Finite`
type.
Often, where there are two set arguments `s` and `t`, the finiteness of one follows from the other
in the context of the theorem, in which case we only include the ones that are needed, and derive
the other inside the proof. A few of the theorems, such as `ncard_union_le` do not require
finiteness arguments; they are true by coincidence due to junk values.
-/
namespace Set
variable {α β : Type*} {s t : Set α}
/-- The cardinality of a set as a term in `ℕ∞` -/
noncomputable def encard (s : Set α) : ℕ∞ := ENat.card s
@[simp] theorem encard_univ_coe (s : Set α) : encard (univ : Set s) = encard s := by
rw [encard, encard, ENat.card_congr (Equiv.Set.univ ↑s)]
theorem encard_univ (α : Type*) :
encard (univ : Set α) = ENat.card α := by
rw [encard, ENat.card_congr (Equiv.Set.univ α)]
theorem Finite.encard_eq_coe_toFinset_card (h : s.Finite) : s.encard = h.toFinset.card := by
have := h.fintype
rw [encard, ENat.card_eq_coe_fintype_card, toFinite_toFinset, toFinset_card]
theorem encard_eq_coe_toFinset_card (s : Set α) [Fintype s] : encard s = s.toFinset.card := by
have h := toFinite s
rw [h.encard_eq_coe_toFinset_card, toFinite_toFinset]
@[simp] theorem toENat_cardinalMk (s : Set α) : (Cardinal.mk s).toENat = s.encard := rfl
theorem toENat_cardinalMk_subtype (P : α → Prop) :
(Cardinal.mk {x // P x}).toENat = {x | P x}.encard :=
rfl
@[simp] theorem coe_fintypeCard (s : Set α) [Fintype s] : Fintype.card s = s.encard := by
simp [encard_eq_coe_toFinset_card]
@[simp, norm_cast] theorem encard_coe_eq_coe_finsetCard (s : Finset α) :
encard (s : Set α) = s.card := by
rw [Finite.encard_eq_coe_toFinset_card (Finset.finite_toSet s)]; simp
@[simp] theorem Infinite.encard_eq {s : Set α} (h : s.Infinite) : s.encard = ⊤ := by
have := h.to_subtype
rw [encard, ENat.card_eq_top_of_infinite]
@[simp] theorem encard_eq_zero : s.encard = 0 ↔ s = ∅ := by
rw [encard, ENat.card_eq_zero_iff_empty, isEmpty_subtype, eq_empty_iff_forall_not_mem]
@[simp] theorem encard_empty : (∅ : Set α).encard = 0 := by
rw [encard_eq_zero]
theorem nonempty_of_encard_ne_zero (h : s.encard ≠ 0) : s.Nonempty := by
rwa [nonempty_iff_ne_empty, Ne, ← encard_eq_zero]
theorem encard_ne_zero : s.encard ≠ 0 ↔ s.Nonempty := by
rw [ne_eq, encard_eq_zero, nonempty_iff_ne_empty]
@[simp] theorem encard_pos : 0 < s.encard ↔ s.Nonempty := by
rw [pos_iff_ne_zero, encard_ne_zero]
protected alias ⟨_, Nonempty.encard_pos⟩ := encard_pos
@[simp] theorem encard_singleton (e : α) : ({e} : Set α).encard = 1 := by
rw [encard, ENat.card_eq_coe_fintype_card, Fintype.card_ofSubsingleton, Nat.cast_one]
theorem encard_union_eq (h : Disjoint s t) : (s ∪ t).encard = s.encard + t.encard := by
classical
simp [encard, ENat.card_congr (Equiv.Set.union h)]
theorem encard_insert_of_not_mem {a : α} (has : a ∉ s) : (insert a s).encard = s.encard + 1 := by
rw [← union_singleton, encard_union_eq (by simpa), encard_singleton]
theorem Finite.encard_lt_top (h : s.Finite) : s.encard < ⊤ := by
induction s, h using Set.Finite.induction_on with
| empty => simp
| insert hat _ ht' =>
rw [encard_insert_of_not_mem hat]
exact lt_tsub_iff_right.1 ht'
theorem Finite.encard_eq_coe (h : s.Finite) : s.encard = ENat.toNat s.encard :=
(ENat.coe_toNat h.encard_lt_top.ne).symm
theorem Finite.exists_encard_eq_coe (h : s.Finite) : ∃ (n : ℕ), s.encard = n :=
⟨_, h.encard_eq_coe⟩
@[simp] theorem encard_lt_top_iff : s.encard < ⊤ ↔ s.Finite :=
⟨fun h ↦ by_contra fun h' ↦ h.ne (Infinite.encard_eq h'), Finite.encard_lt_top⟩
@[simp] theorem encard_eq_top_iff : s.encard = ⊤ ↔ s.Infinite := by
rw [← not_iff_not, ← Ne, ← lt_top_iff_ne_top, encard_lt_top_iff, not_infinite]
alias ⟨_, encard_eq_top⟩ := encard_eq_top_iff
theorem encard_ne_top_iff : s.encard ≠ ⊤ ↔ s.Finite := by
| simp
theorem finite_of_encard_le_coe {k : ℕ} (h : s.encard ≤ k) : s.Finite := by
| Mathlib/Data/Set/Card.lean | 146 | 148 |
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Fin.Fin2
import Mathlib.Data.PFun
import Mathlib.Data.Vector3
import Mathlib.NumberTheory.PellMatiyasevic
/-!
# Diophantine functions and Matiyasevic's theorem
Hilbert's tenth problem asked whether there exists an algorithm which for a given integer polynomial
determines whether this polynomial has integer solutions. It was answered in the negative in 1970,
the final step being completed by Matiyasevic who showed that the power function is Diophantine.
Here a function is called Diophantine if its graph is Diophantine as a set. A subset `S ⊆ ℕ ^ α` in
turn is called Diophantine if there exists an integer polynomial on `α ⊕ β` such that `v ∈ S` iff
there exists `t : ℕ^β` with `p (v, t) = 0`.
## Main definitions
* `IsPoly`: a predicate stating that a function is a multivariate integer polynomial.
* `Poly`: the type of multivariate integer polynomial functions.
* `Dioph`: a predicate stating that a set is Diophantine, i.e. a set `S ⊆ ℕ^α` is
Diophantine if there exists a polynomial on `α ⊕ β` such that `v ∈ S` iff there
exists `t : ℕ^β` with `p (v, t) = 0`.
* `DiophFn`: a predicate on a function stating that it is Diophantine in the sense that its graph
is Diophantine as a set.
## Main statements
* `pell_dioph` states that solutions to Pell's equation form a Diophantine set.
* `pow_dioph` states that the power function is Diophantine, a version of Matiyasevic's theorem.
## References
* [M. Carneiro, _A Lean formalization of Matiyasevic's theorem_][carneiro2018matiyasevic]
* [M. Davis, _Hilbert's tenth problem is unsolvable_][MR317916]
## Tags
Matiyasevic's theorem, Hilbert's tenth problem
## TODO
* Finish the solution of Hilbert's tenth problem.
* Connect `Poly` to `MvPolynomial`
-/
open Fin2 Function Nat Sum
local infixr:67 " ::ₒ " => Option.elim'
local infixr:65 " ⊗ " => Sum.elim
universe u
/-!
### Multivariate integer polynomials
Note that this duplicates `MvPolynomial`.
-/
section Polynomials
variable {α β : Type*}
/-- A predicate asserting that a function is a multivariate integer polynomial.
(We are being a bit lazy here by allowing many representations for multiplication,
rather than only allowing monomials and addition, but the definition is equivalent
and this is easier to use.) -/
inductive IsPoly : ((α → ℕ) → ℤ) → Prop
| proj : ∀ i, IsPoly fun x : α → ℕ => x i
| const : ∀ n : ℤ, IsPoly fun _ : α → ℕ => n
| sub : ∀ {f g : (α → ℕ) → ℤ}, IsPoly f → IsPoly g → IsPoly fun x => f x - g x
| mul : ∀ {f g : (α → ℕ) → ℤ}, IsPoly f → IsPoly g → IsPoly fun x => f x * g x
theorem IsPoly.neg {f : (α → ℕ) → ℤ} : IsPoly f → IsPoly (-f) := by
rw [← zero_sub]; exact (IsPoly.const 0).sub
theorem IsPoly.add {f g : (α → ℕ) → ℤ} (hf : IsPoly f) (hg : IsPoly g) : IsPoly (f + g) := by
rw [← sub_neg_eq_add]; exact hf.sub hg.neg
/-- The type of multivariate integer polynomials -/
def Poly (α : Type u) := { f : (α → ℕ) → ℤ // IsPoly f }
namespace Poly
section
instance instFunLike : FunLike (Poly α) (α → ℕ) ℤ :=
⟨Subtype.val, Subtype.val_injective⟩
/-- The underlying function of a `Poly` is a polynomial -/
protected theorem isPoly (f : Poly α) : IsPoly f := f.2
/-- Extensionality for `Poly α` -/
@[ext]
theorem ext {f g : Poly α} : (∀ x, f x = g x) → f = g := DFunLike.ext _ _
/-- The `i`th projection function, `x_i`. -/
def proj (i : α) : Poly α := ⟨_, IsPoly.proj i⟩
@[simp]
theorem proj_apply (i : α) (x) : proj i x = x i := rfl
/-- The constant function with value `n : ℤ`. -/
def const (n : ℤ) : Poly α := ⟨_, IsPoly.const n⟩
@[simp]
theorem const_apply (n) (x : α → ℕ) : const n x = n := rfl
instance : Zero (Poly α) := ⟨const 0⟩
instance : One (Poly α) := ⟨const 1⟩
instance : Neg (Poly α) := ⟨fun f => ⟨-f, f.2.neg⟩⟩
instance : Add (Poly α) := ⟨fun f g => ⟨f + g, f.2.add g.2⟩⟩
instance : Sub (Poly α) := ⟨fun f g => ⟨f - g, f.2.sub g.2⟩⟩
instance : Mul (Poly α) := ⟨fun f g => ⟨f * g, f.2.mul g.2⟩⟩
@[simp]
theorem coe_zero : ⇑(0 : Poly α) = const 0 := rfl
@[simp]
theorem coe_one : ⇑(1 : Poly α) = const 1 := rfl
@[simp]
theorem coe_neg (f : Poly α) : ⇑(-f) = -f := rfl
@[simp]
theorem coe_add (f g : Poly α) : ⇑(f + g) = f + g := rfl
@[simp]
theorem coe_sub (f g : Poly α) : ⇑(f - g) = f - g := rfl
@[simp]
theorem coe_mul (f g : Poly α) : ⇑(f * g) = f * g := rfl
@[simp]
theorem zero_apply (x) : (0 : Poly α) x = 0 := rfl
@[simp]
theorem one_apply (x) : (1 : Poly α) x = 1 := rfl
@[simp]
theorem neg_apply (f : Poly α) (x) : (-f) x = -f x := rfl
@[simp]
theorem add_apply (f g : Poly α) (x : α → ℕ) : (f + g) x = f x + g x := rfl
@[simp]
theorem sub_apply (f g : Poly α) (x : α → ℕ) : (f - g) x = f x - g x := rfl
@[simp]
theorem mul_apply (f g : Poly α) (x : α → ℕ) : (f * g) x = f x * g x := rfl
instance (α : Type*) : Inhabited (Poly α) := ⟨0⟩
instance : AddCommGroup (Poly α) where
add := ((· + ·) : Poly α → Poly α → Poly α)
neg := (Neg.neg : Poly α → Poly α)
sub := Sub.sub
zero := 0
nsmul := @nsmulRec _ ⟨(0 : Poly α)⟩ ⟨(· + ·)⟩
zsmul := @zsmulRec _ ⟨(0 : Poly α)⟩ ⟨(· + ·)⟩ ⟨Neg.neg⟩ (@nsmulRec _ ⟨(0 : Poly α)⟩ ⟨(· + ·)⟩)
add_zero _ := by ext; simp_rw [add_apply, zero_apply, add_zero]
zero_add _ := by ext; simp_rw [add_apply, zero_apply, zero_add]
add_comm _ _ := by ext; simp_rw [add_apply, add_comm]
add_assoc _ _ _ := by ext; simp_rw [add_apply, ← add_assoc]
neg_add_cancel _ := by ext; simp_rw [add_apply, neg_apply, neg_add_cancel, zero_apply]
instance : AddGroupWithOne (Poly α) :=
{ (inferInstance : AddCommGroup (Poly α)) with
one := 1
natCast := fun n => Poly.const n
intCast := Poly.const }
instance : CommRing (Poly α) where
__ := (inferInstance : AddCommGroup (Poly α))
__ := (inferInstance : AddGroupWithOne (Poly α))
mul := (· * ·)
npow := @npowRec _ ⟨(1 : Poly α)⟩ ⟨(· * ·)⟩
mul_zero _ := by ext; rw [mul_apply, zero_apply, mul_zero]
zero_mul _ := by ext; rw [mul_apply, zero_apply, zero_mul]
mul_one _ := by ext; rw [mul_apply, one_apply, mul_one]
one_mul _ := by ext; rw [mul_apply, one_apply, one_mul]
mul_comm _ _ := by ext; simp_rw [mul_apply, mul_comm]
mul_assoc _ _ _ := by ext; simp_rw [mul_apply, mul_assoc]
left_distrib _ _ _ := by ext; simp_rw [add_apply, mul_apply]; apply mul_add
right_distrib _ _ _ := by ext; simp only [add_apply, mul_apply]; apply add_mul
theorem induction {C : Poly α → Prop} (H1 : ∀ i, C (proj i)) (H2 : ∀ n, C (const n))
(H3 : ∀ f g, C f → C g → C (f - g)) (H4 : ∀ f g, C f → C g → C (f * g)) (f : Poly α) : C f := by
obtain ⟨f, pf⟩ := f
induction pf with
| proj => apply H1
| const => apply H2
| sub _ _ ihf ihg => apply H3 _ _ ihf ihg
| mul _ _ ihf ihg => apply H4 _ _ ihf ihg
/-- The sum of squares of a list of polynomials. This is relevant for
Diophantine equations, because it means that a list of equations
can be encoded as a single equation: `x = 0 ∧ y = 0 ∧ z = 0` is
equivalent to `x^2 + y^2 + z^2 = 0`. -/
def sumsq : List (Poly α) → Poly α
| [] => 0
| p::ps => p * p + sumsq ps
theorem sumsq_nonneg (x : α → ℕ) : ∀ l, 0 ≤ sumsq l x
| [] => le_refl 0
| p::ps => by
rw [sumsq]
exact add_nonneg (mul_self_nonneg _) (sumsq_nonneg _ ps)
theorem sumsq_eq_zero (x) : ∀ l, sumsq l x = 0 ↔ l.Forall fun a : Poly α => a x = 0
| [] => eq_self_iff_true _
| p::ps => by
rw [List.forall_cons, ← sumsq_eq_zero _ ps]; rw [sumsq]
exact
⟨fun h : p x * p x + sumsq ps x = 0 =>
have : p x = 0 :=
eq_zero_of_mul_self_eq_zero <|
le_antisymm
(by
rw [← h]
have t := add_le_add_left (sumsq_nonneg x ps) (p x * p x)
rwa [add_zero] at t)
(mul_self_nonneg _)
⟨this, by simpa [this] using h⟩,
fun ⟨h1, h2⟩ => by rw [add_apply, mul_apply, h1, h2]; rfl⟩
end
/-- Map the index set of variables, replacing `x_i` with `x_(f i)`. -/
def map {α β} (f : α → β) (g : Poly α) : Poly β :=
⟨fun v => g <| v ∘ f, Poly.induction (C := fun g => IsPoly (fun v => g (v ∘ f)))
(fun i => by simpa using IsPoly.proj _) (fun n => by simpa using IsPoly.const _)
(fun f g pf pg => by simpa using IsPoly.sub pf pg)
(fun f g pf pg => by simpa using IsPoly.mul pf pg) _⟩
@[simp]
theorem map_apply {α β} (f : α → β) (g : Poly α) (v) : map f g v = g (v ∘ f) := rfl
|
end Poly
end Polynomials
/-! ### Diophantine sets -/
/-- A set `S ⊆ ℕ^α` is Diophantine if there exists a polynomial on
`α ⊕ β` such that `v ∈ S` iff there exists `t : ℕ^β` with `p (v, t) = 0`. -/
def Dioph {α : Type u} (S : Set (α → ℕ)) : Prop :=
∃ (β : Type u) (p : Poly (α ⊕ β)), ∀ v, S v ↔ ∃ t, p (v ⊗ t) = 0
namespace Dioph
section
| Mathlib/NumberTheory/Dioph.lean | 251 | 266 |
/-
Copyright (c) 2020 Markus Himmel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel
-/
import Mathlib.RingTheory.Ideal.Maps
/-!
# Ideals in product rings
For commutative rings `R` and `S` and ideals `I ≤ R`, `J ≤ S`, we define `Ideal.prod I J` as the
product `I × J`, viewed as an ideal of `R × S`. In `ideal_prod_eq` we show that every ideal of
`R × S` is of this form. Furthermore, we show that every prime ideal of `R × S` is of the form
`p × S` or `R × p`, where `p` is a prime ideal.
-/
universe u v
variable {R : Type u} {S : Type v} [Semiring R] [Semiring S] (I : Ideal R) (J : Ideal S)
namespace Ideal
/-- `I × J` as an ideal of `R × S`. -/
def prod : Ideal (R × S) := I.comap (RingHom.fst R S) ⊓ J.comap (RingHom.snd R S)
@[simp]
theorem mem_prod {r : R} {s : S} : (⟨r, s⟩ : R × S) ∈ prod I J ↔ r ∈ I ∧ s ∈ J :=
Iff.rfl
@[simp]
theorem prod_top_top : prod (⊤ : Ideal R) (⊤ : Ideal S) = ⊤ :=
Ideal.ext <| by simp
/-- Every ideal of the product ring is of the form `I × J`, where `I` and `J` can be explicitly
given as the image under the projection maps. -/
theorem ideal_prod_eq (I : Ideal (R × S)) :
I = Ideal.prod (map (RingHom.fst R S) I : Ideal R) (map (RingHom.snd R S) I) := by
apply Ideal.ext
rintro ⟨r, s⟩
rw [mem_prod, mem_map_iff_of_surjective (RingHom.fst R S) Prod.fst_surjective,
mem_map_iff_of_surjective (RingHom.snd R S) Prod.snd_surjective]
refine ⟨fun h => ⟨⟨_, ⟨h, rfl⟩⟩, ⟨_, ⟨h, rfl⟩⟩⟩, ?_⟩
rintro ⟨⟨⟨r, s'⟩, ⟨h₁, rfl⟩⟩, ⟨⟨r', s⟩, ⟨h₂, rfl⟩⟩⟩
simpa using I.add_mem (I.mul_mem_left (1, 0) h₁) (I.mul_mem_left (0, 1) h₂)
@[simp]
theorem map_fst_prod (I : Ideal R) (J : Ideal S) : map (RingHom.fst R S) (prod I J) = I := by
ext x
rw [mem_map_iff_of_surjective (RingHom.fst R S) Prod.fst_surjective]
exact
⟨by
rintro ⟨x, ⟨h, rfl⟩⟩
exact h.1, fun h => ⟨⟨x, 0⟩, ⟨⟨h, Ideal.zero_mem _⟩, rfl⟩⟩⟩
@[simp]
theorem map_snd_prod (I : Ideal R) (J : Ideal S) : map (RingHom.snd R S) (prod I J) = J := by
ext x
rw [mem_map_iff_of_surjective (RingHom.snd R S) Prod.snd_surjective]
exact
⟨by
rintro ⟨x, ⟨h, rfl⟩⟩
exact h.2, fun h => ⟨⟨0, x⟩, ⟨⟨Ideal.zero_mem _, h⟩, rfl⟩⟩⟩
@[simp]
theorem map_prodComm_prod :
map ((RingEquiv.prodComm : R × S ≃+* S × R) : R × S →+* S × R) (prod I J) = prod J I := by
refine Trans.trans (ideal_prod_eq _) ?_
simp [map_map]
/-- Ideals of `R × S` are in one-to-one correspondence with pairs of ideals of `R` and ideals of
`S`. -/
def idealProdEquiv : Ideal (R × S) ≃o Ideal R × Ideal S where
toFun I := ⟨map (RingHom.fst R S) I, map (RingHom.snd R S) I⟩
invFun I := prod I.1 I.2
left_inv I := (ideal_prod_eq I).symm
right_inv := fun ⟨I, J⟩ => by simp
map_rel_iff' {I J} := by
simp only [Equiv.coe_fn_mk, ge_iff_le, Prod.mk_le_mk]
refine ⟨fun h ↦ ?_, fun h ↦ ⟨map_mono h, map_mono h⟩⟩
rw [ideal_prod_eq I, ideal_prod_eq J]
| exact inf_le_inf (comap_mono h.1) (comap_mono h.2)
@[simp]
theorem idealProdEquiv_symm_apply (I : Ideal R) (J : Ideal S) :
| Mathlib/RingTheory/Ideal/Prod.lean | 82 | 85 |
/-
Copyright (c) 2024 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.CategoryTheory.Sites.LeftExact
import Mathlib.CategoryTheory.Sites.PreservesSheafification
import Mathlib.CategoryTheory.Sites.Subsheaf
import Mathlib.CategoryTheory.Sites.Whiskering
/-!
# Locally injective morphisms of (pre)sheaves
Let `C` be a category equipped with a Grothendieck topology `J`,
and let `D` be a concrete category. In this file, we introduce the typeclass
`Presheaf.IsLocallyInjective J φ` for a morphism `φ : F₁ ⟶ F₂` in the category
`Cᵒᵖ ⥤ D`. This means that `φ` is locally injective. More precisely,
if `x` and `y` are two elements of some `F₁.obj U` such
the images of `x` and `y` in `F₂.obj U` coincide, then
the equality `x = y` must hold locally, i.e. after restriction
by the maps of a covering sieve.
-/
universe w v' v u' u
namespace CategoryTheory
open Opposite Limits
variable {C : Type u} [Category.{v} C]
{D : Type u'} [Category.{v'} D] {FD : D → D → Type*} {CD : D → Type w}
[∀ X Y, FunLike (FD X Y) (CD X) (CD Y)] [ConcreteCategory.{w} D FD]
(J : GrothendieckTopology C)
namespace Presheaf
/-- If `F : Cᵒᵖ ⥤ D` is a presheaf with values in a concrete category, if `x` and `y` are
elements in `F.obj X`, this is the sieve of `X.unop` consisting of morphisms `f`
such that `F.map f.op x = F.map f.op y`. -/
@[simps]
def equalizerSieve {F : Cᵒᵖ ⥤ D} {X : Cᵒᵖ} (x y : ToType (F.obj X)) : Sieve X.unop where
arrows _ f := F.map f.op x = F.map f.op y
downward_closed {X Y} f hf g := by
dsimp at hf ⊢
simp [hf]
@[simp]
lemma equalizerSieve_self_eq_top {F : Cᵒᵖ ⥤ D} {X : Cᵒᵖ} (x : ToType (F.obj X)) :
equalizerSieve x x = ⊤ := by aesop
@[simp]
| lemma equalizerSieve_eq_top_iff {F : Cᵒᵖ ⥤ D} {X : Cᵒᵖ} (x y : ToType (F.obj X)) :
equalizerSieve x y = ⊤ ↔ x = y := by
constructor
· intro h
simpa using (show equalizerSieve x y (𝟙 _) by simp [h])
· rintro rfl
apply equalizerSieve_self_eq_top
| Mathlib/CategoryTheory/Sites/LocallyInjective.lean | 53 | 60 |
/-
Copyright (c) 2021 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Analysis.Analytic.CPolynomial
import Mathlib.Analysis.Analytic.Inverse
import Mathlib.Analysis.Analytic.Within
import Mathlib.Analysis.Calculus.Deriv.Basic
import Mathlib.Analysis.Calculus.ContDiff.FTaylorSeries
import Mathlib.Analysis.Calculus.FDeriv.Add
import Mathlib.Analysis.Calculus.FDeriv.Prod
import Mathlib.Analysis.Normed.Module.Completion
/-!
# Frechet derivatives of analytic functions.
A function expressible as a power series at a point has a Frechet derivative there.
Also the special case in terms of `deriv` when the domain is 1-dimensional.
As an application, we show that continuous multilinear maps are smooth. We also compute their
iterated derivatives, in `ContinuousMultilinearMap.iteratedFDeriv_eq`.
## Main definitions and results
* `AnalyticAt.differentiableAt` : an analytic function at a point is differentiable there.
* `AnalyticOnNhd.fderiv` : in a complete space, if a function is analytic on a
neighborhood of a set `s`, so is its derivative.
* `AnalyticOnNhd.fderiv_of_isOpen` : if a function is analytic on a neighborhood of an
open set `s`, so is its derivative.
* `AnalyticOn.fderivWithin` : if a function is analytic on a set of unique differentiability,
so is its derivative within this set.
* `PartialHomeomorph.analyticAt_symm` : if a partial homeomorphism `f` is analytic at a
point `f.symm a`, with invertible derivative, then its inverse is analytic at `a`.
## Comments on completeness
Some theorems need a complete space, some don't, for the following reason.
(1) If a function is analytic at a point `x`, then it is differentiable there (with derivative given
by the first term in the power series). There is no issue of convergence here.
(2) If a function has a power series on a ball `B (x, r)`, there is no guarantee that the power
series for the derivative will converge at `y ≠ x`, if the space is not complete. So, to deduce
that `f` is differentiable at `y`, one needs completeness in general.
(3) However, if a function `f` has a power series on a ball `B (x, r)`, and is a priori known to be
differentiable at some point `y ≠ x`, then the power series for the derivative of `f` will
automatically converge at `y`, towards the given derivative: this follows from the facts that this
is true in the completion (thanks to the previous point) and that the map to the completion is
an embedding.
(4) Therefore, if one assumes `AnalyticOn 𝕜 f s` where `s` is an open set, then `f` is analytic
therefore differentiable at every point of `s`, by (1), so by (3) the power series for its
derivative converges on whole balls. Therefore, the derivative of `f` is also analytic on `s`. The
same holds if `s` is merely a set with unique differentials.
(5) However, this does not work for `AnalyticOnNhd 𝕜 f s`, as we don't get for free
differentiability at points in a neighborhood of `s`. Therefore, the theorem that deduces
`AnalyticOnNhd 𝕜 (fderiv 𝕜 f) s` from `AnalyticOnNhd 𝕜 f s` requires completeness of the space.
-/
open Filter Asymptotics Set
open scoped ENNReal Topology
universe u v
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜]
variable {E : Type u} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
variable {F : Type v} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
section fderiv
variable {p : FormalMultilinearSeries 𝕜 E F} {r : ℝ≥0∞}
variable {f : E → F} {x : E} {s : Set E}
/-- A function which is analytic within a set is strictly differentiable there. Since we
don't have a predicate `HasStrictFDerivWithinAt`, we spell out what it would mean. -/
theorem HasFPowerSeriesWithinAt.hasStrictFDerivWithinAt (h : HasFPowerSeriesWithinAt f p s x) :
(fun y ↦ f y.1 - f y.2 - (continuousMultilinearCurryFin1 𝕜 E F (p 1)) (y.1 - y.2))
=o[𝓝[insert x s ×ˢ insert x s] (x, x)] fun y ↦ y.1 - y.2 := by
refine h.isBigO_image_sub_norm_mul_norm_sub.trans_isLittleO (IsLittleO.of_norm_right ?_)
refine isLittleO_iff_exists_eq_mul.2 ⟨fun y => ‖y - (x, x)‖, ?_, EventuallyEq.rfl⟩
apply Tendsto.mono_left _ nhdsWithin_le_nhds
refine (continuous_id.sub continuous_const).norm.tendsto' _ _ ?_
rw [_root_.id, sub_self, norm_zero]
theorem HasFPowerSeriesAt.hasStrictFDerivAt (h : HasFPowerSeriesAt f p x) :
HasStrictFDerivAt f (continuousMultilinearCurryFin1 𝕜 E F (p 1)) x := by
simpa only [hasStrictFDerivAt_iff_isLittleO, Set.insert_eq_of_mem, Set.mem_univ,
Set.univ_prod_univ, nhdsWithin_univ]
using (h.hasFPowerSeriesWithinAt (s := Set.univ)).hasStrictFDerivWithinAt
theorem HasFPowerSeriesWithinAt.hasFDerivWithinAt (h : HasFPowerSeriesWithinAt f p s x) :
HasFDerivWithinAt f (continuousMultilinearCurryFin1 𝕜 E F (p 1)) (insert x s) x := by
rw [HasFDerivWithinAt, hasFDerivAtFilter_iff_isLittleO, isLittleO_iff]
intro c hc
have : Tendsto (fun y ↦ (y, x)) (𝓝[insert x s] x) (𝓝[insert x s ×ˢ insert x s] (x, x)) := by
rw [nhdsWithin_prod_eq]
exact Tendsto.prodMk tendsto_id (tendsto_const_nhdsWithin (by simp))
exact this (isLittleO_iff.1 h.hasStrictFDerivWithinAt hc)
theorem HasFPowerSeriesAt.hasFDerivAt (h : HasFPowerSeriesAt f p x) :
HasFDerivAt f (continuousMultilinearCurryFin1 𝕜 E F (p 1)) x :=
h.hasStrictFDerivAt.hasFDerivAt
theorem HasFPowerSeriesWithinAt.differentiableWithinAt (h : HasFPowerSeriesWithinAt f p s x) :
DifferentiableWithinAt 𝕜 f (insert x s) x :=
h.hasFDerivWithinAt.differentiableWithinAt
theorem HasFPowerSeriesAt.differentiableAt (h : HasFPowerSeriesAt f p x) : DifferentiableAt 𝕜 f x :=
h.hasFDerivAt.differentiableAt
theorem AnalyticWithinAt.differentiableWithinAt (h : AnalyticWithinAt 𝕜 f s x) :
DifferentiableWithinAt 𝕜 f (insert x s) x := by
obtain ⟨p, hp⟩ := h
exact hp.differentiableWithinAt
@[fun_prop]
theorem AnalyticAt.differentiableAt : AnalyticAt 𝕜 f x → DifferentiableAt 𝕜 f x
| ⟨_, hp⟩ => hp.differentiableAt
theorem AnalyticAt.differentiableWithinAt (h : AnalyticAt 𝕜 f x) : DifferentiableWithinAt 𝕜 f s x :=
h.differentiableAt.differentiableWithinAt
theorem HasFPowerSeriesWithinAt.fderivWithin_eq
(h : HasFPowerSeriesWithinAt f p s x) (hu : UniqueDiffWithinAt 𝕜 (insert x s) x) :
fderivWithin 𝕜 f (insert x s) x = continuousMultilinearCurryFin1 𝕜 E F (p 1) :=
h.hasFDerivWithinAt.fderivWithin hu
theorem HasFPowerSeriesAt.fderiv_eq (h : HasFPowerSeriesAt f p x) :
fderiv 𝕜 f x = continuousMultilinearCurryFin1 𝕜 E F (p 1) :=
h.hasFDerivAt.fderiv
theorem AnalyticAt.hasStrictFDerivAt (h : AnalyticAt 𝕜 f x) :
HasStrictFDerivAt f (fderiv 𝕜 f x) x := by
rcases h with ⟨p, hp⟩
rw [hp.fderiv_eq]
exact hp.hasStrictFDerivAt
theorem HasFPowerSeriesWithinOnBall.differentiableOn [CompleteSpace F]
(h : HasFPowerSeriesWithinOnBall f p s x r) :
DifferentiableOn 𝕜 f (insert x s ∩ EMetric.ball x r) := by
intro y hy
have Z := (h.analyticWithinAt_of_mem hy).differentiableWithinAt
rcases eq_or_ne y x with rfl | hy
· exact Z.mono inter_subset_left
· apply (Z.mono (subset_insert _ _)).mono_of_mem_nhdsWithin
suffices s ∈ 𝓝[insert x s] y from nhdsWithin_mono _ inter_subset_left this
rw [nhdsWithin_insert_of_ne hy]
exact self_mem_nhdsWithin
theorem HasFPowerSeriesOnBall.differentiableOn [CompleteSpace F]
(h : HasFPowerSeriesOnBall f p x r) : DifferentiableOn 𝕜 f (EMetric.ball x r) := fun _ hy =>
(h.analyticAt_of_mem hy).differentiableWithinAt
theorem AnalyticOn.differentiableOn (h : AnalyticOn 𝕜 f s) : DifferentiableOn 𝕜 f s :=
fun y hy ↦ (h y hy).differentiableWithinAt.mono (by simp)
theorem AnalyticOnNhd.differentiableOn (h : AnalyticOnNhd 𝕜 f s) : DifferentiableOn 𝕜 f s :=
fun y hy ↦ (h y hy).differentiableWithinAt
theorem HasFPowerSeriesWithinOnBall.hasFDerivWithinAt [CompleteSpace F]
(h : HasFPowerSeriesWithinOnBall f p s x r)
{y : E} (hy : (‖y‖₊ : ℝ≥0∞) < r) (h'y : x + y ∈ insert x s) :
HasFDerivWithinAt f (continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin y 1))
(insert x s) (x + y) := by
rcases eq_or_ne y 0 with rfl | h''y
· convert (h.changeOrigin hy h'y).hasFPowerSeriesWithinAt.hasFDerivWithinAt
simp
· have Z := (h.changeOrigin hy h'y).hasFPowerSeriesWithinAt.hasFDerivWithinAt
apply (Z.mono (subset_insert _ _)).mono_of_mem_nhdsWithin
rw [nhdsWithin_insert_of_ne]
· exact self_mem_nhdsWithin
· simpa using h''y
theorem HasFPowerSeriesOnBall.hasFDerivAt [CompleteSpace F] (h : HasFPowerSeriesOnBall f p x r)
{y : E} (hy : (‖y‖₊ : ℝ≥0∞) < r) :
HasFDerivAt f (continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin y 1)) (x + y) :=
(h.changeOrigin hy).hasFPowerSeriesAt.hasFDerivAt
theorem HasFPowerSeriesWithinOnBall.fderivWithin_eq [CompleteSpace F]
(h : HasFPowerSeriesWithinOnBall f p s x r)
{y : E} (hy : (‖y‖₊ : ℝ≥0∞) < r) (h'y : x + y ∈ insert x s) (hu : UniqueDiffOn 𝕜 (insert x s)) :
fderivWithin 𝕜 f (insert x s) (x + y) =
continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin y 1) :=
(h.hasFDerivWithinAt hy h'y).fderivWithin (hu _ h'y)
theorem HasFPowerSeriesOnBall.fderiv_eq [CompleteSpace F] (h : HasFPowerSeriesOnBall f p x r)
{y : E} (hy : (‖y‖₊ : ℝ≥0∞) < r) :
fderiv 𝕜 f (x + y) = continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin y 1) :=
(h.hasFDerivAt hy).fderiv
/-- If a function has a power series on a ball, then so does its derivative. -/
protected theorem HasFPowerSeriesOnBall.fderiv [CompleteSpace F]
(h : HasFPowerSeriesOnBall f p x r) :
HasFPowerSeriesOnBall (fderiv 𝕜 f) p.derivSeries x r := by
refine .congr (f := fun z ↦ continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin (z - x) 1)) ?_
fun z hz ↦ ?_
· refine continuousMultilinearCurryFin1 𝕜 E F
|>.toContinuousLinearEquiv.toContinuousLinearMap.comp_hasFPowerSeriesOnBall ?_
simpa using ((p.hasFPowerSeriesOnBall_changeOrigin 1
(h.r_pos.trans_le h.r_le)).mono h.r_pos h.r_le).comp_sub x
dsimp only
rw [← h.fderiv_eq, add_sub_cancel]
simpa only [edist_eq_enorm_sub, EMetric.mem_ball] using hz
/-- If a function has a power series within a set on a ball, then so does its derivative. -/
protected theorem HasFPowerSeriesWithinOnBall.fderivWithin [CompleteSpace F]
(h : HasFPowerSeriesWithinOnBall f p s x r) (hu : UniqueDiffOn 𝕜 (insert x s)) :
HasFPowerSeriesWithinOnBall (fderivWithin 𝕜 f (insert x s)) p.derivSeries s x r := by
refine .congr' (f := fun z ↦ continuousMultilinearCurryFin1 𝕜 E F (p.changeOrigin (z - x) 1)) ?_
(fun z hz ↦ ?_)
· refine continuousMultilinearCurryFin1 𝕜 E F
|>.toContinuousLinearEquiv.toContinuousLinearMap.comp_hasFPowerSeriesWithinOnBall ?_
apply HasFPowerSeriesOnBall.hasFPowerSeriesWithinOnBall
simpa using ((p.hasFPowerSeriesOnBall_changeOrigin 1
(h.r_pos.trans_le h.r_le)).mono h.r_pos h.r_le).comp_sub x
· dsimp only
rw [← h.fderivWithin_eq _ _ hu, add_sub_cancel]
· simpa only [edist_eq_enorm_sub, EMetric.mem_ball] using hz.2
· simpa using hz.1
/-- If a function has a power series within a set on a ball, then so does its derivative. For a
version without completeness, but assuming that the function is analytic on the set `s`, see
`HasFPowerSeriesWithinOnBall.fderivWithin_of_mem_of_analyticOn`. -/
protected theorem HasFPowerSeriesWithinOnBall.fderivWithin_of_mem [CompleteSpace F]
(h : HasFPowerSeriesWithinOnBall f p s x r) (hu : UniqueDiffOn 𝕜 s) (hx : x ∈ s) :
HasFPowerSeriesWithinOnBall (fderivWithin 𝕜 f s) p.derivSeries s x r := by
have : insert x s = s := insert_eq_of_mem hx
rw [← this] at hu
convert h.fderivWithin hu
exact this.symm
/-- If a function is analytic on a set `s`, so is its Fréchet derivative. -/
@[fun_prop]
protected theorem AnalyticAt.fderiv [CompleteSpace F] (h : AnalyticAt 𝕜 f x) :
AnalyticAt 𝕜 (fderiv 𝕜 f) x := by
rcases h with ⟨p, r, hp⟩
exact hp.fderiv.analyticAt
/-- If a function is analytic on a set `s`, so is its Fréchet derivative. See also
`AnalyticOnNhd.fderiv_of_isOpen`, removing the completeness assumption but requiring the set
to be open. -/
protected theorem AnalyticOnNhd.fderiv [CompleteSpace F] (h : AnalyticOnNhd 𝕜 f s) :
AnalyticOnNhd 𝕜 (fderiv 𝕜 f) s :=
fun y hy ↦ AnalyticAt.fderiv (h y hy)
/-- If a function is analytic on a set `s`, so are its successive Fréchet derivative. See also
`AnalyticOnNhd.iteratedFDeriv_of_isOpen`, removing the completeness assumption but requiring the set
to be open. -/
protected theorem AnalyticOnNhd.iteratedFDeriv [CompleteSpace F] (h : AnalyticOnNhd 𝕜 f s) (n : ℕ) :
AnalyticOnNhd 𝕜 (iteratedFDeriv 𝕜 n f) s := by
induction n with
| zero =>
rw [iteratedFDeriv_zero_eq_comp]
exact ((continuousMultilinearCurryFin0 𝕜 E F).symm : F →L[𝕜] E[×0]→L[𝕜] F).comp_analyticOnNhd h
| succ n IH =>
rw [iteratedFDeriv_succ_eq_comp_left]
-- Porting note: for reasons that I do not understand at all, `?g` cannot be inlined.
convert ContinuousLinearMap.comp_analyticOnNhd ?g IH.fderiv
case g => exact ↑(continuousMultilinearCurryLeftEquiv 𝕜 (fun _ : Fin (n + 1) ↦ E) F).symm
simp
/-- If a function is analytic on a neighborhood of a set `s`, then it has a Taylor series given
by the sequence of its derivatives. Note that, if the function were just analytic on `s`, then
one would have to use instead the sequence of derivatives inside the set, as in
`AnalyticOn.hasFTaylorSeriesUpToOn`. -/
lemma AnalyticOnNhd.hasFTaylorSeriesUpToOn [CompleteSpace F]
(n : WithTop ℕ∞) (h : AnalyticOnNhd 𝕜 f s) :
HasFTaylorSeriesUpToOn n f (ftaylorSeries 𝕜 f) s := by
refine ⟨fun x _hx ↦ rfl, fun m _hm x hx ↦ ?_, fun m _hm x hx ↦ ?_⟩
· apply HasFDerivAt.hasFDerivWithinAt
exact ((h.iteratedFDeriv m x hx).differentiableAt).hasFDerivAt
· apply (DifferentiableAt.continuousAt (𝕜 := 𝕜) ?_).continuousWithinAt
exact (h.iteratedFDeriv m x hx).differentiableAt
lemma AnalyticWithinAt.exists_hasFTaylorSeriesUpToOn [CompleteSpace F]
(n : WithTop ℕ∞) (h : AnalyticWithinAt 𝕜 f s x) :
∃ u ∈ 𝓝[insert x s] x, ∃ (p : E → FormalMultilinearSeries 𝕜 E F),
HasFTaylorSeriesUpToOn n f p u ∧ ∀ i, AnalyticOn 𝕜 (fun x ↦ p x i) u := by
rcases h.exists_analyticAt with ⟨g, -, fg, hg⟩
rcases hg.exists_mem_nhds_analyticOnNhd with ⟨v, vx, hv⟩
refine ⟨insert x s ∩ v, inter_mem_nhdsWithin _ vx, ftaylorSeries 𝕜 g, ?_, fun i ↦ ?_⟩
· suffices HasFTaylorSeriesUpToOn n g (ftaylorSeries 𝕜 g) (insert x s ∩ v) from
this.congr (fun y hy ↦ fg hy.1)
exact AnalyticOnNhd.hasFTaylorSeriesUpToOn _ (hv.mono Set.inter_subset_right)
· exact (hv.iteratedFDeriv i).analyticOn.mono Set.inter_subset_right
/-- If a function has a power series `p` within a set of unique differentiability, inside a ball,
and is differentiable at a point, then the derivative series of `p` is summable at a point, with
sum the given differential. Note that this theorem does not require completeness of the space. -/
theorem HasFPowerSeriesWithinOnBall.hasSum_derivSeries_of_hasFDerivWithinAt
(h : HasFPowerSeriesWithinOnBall f p s x r)
{f' : E →L[𝕜] F}
| {y : E} (hy : (‖y‖₊ : ℝ≥0∞) < r) (h'y : x + y ∈ insert x s)
(hf' : HasFDerivWithinAt f f' (insert x s) (x + y))
(hu : UniqueDiffOn 𝕜 (insert x s)) :
HasSum (fun n ↦ p.derivSeries n (fun _ ↦ y)) f' := by
/- In the completion of the space, the derivative series is summable, and its sum is a derivative
of the function. Therefore, by uniqueness of derivatives, its sum is the image of `f'` under
| Mathlib/Analysis/Calculus/FDeriv/Analytic.lean | 298 | 303 |
/-
Copyright (c) 2022 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth
-/
import Mathlib.Analysis.Complex.AbsMax
import Mathlib.Analysis.LocallyConvex.WithSeminorms
import Mathlib.Geometry.Manifold.MFDeriv.Basic
import Mathlib.Topology.LocallyConstant.Basic
/-! # Holomorphic functions on complex manifolds
Thanks to the rigidity of complex-differentiability compared to real-differentiability, there are
many results about complex manifolds with no analogue for manifolds over a general normed field. For
now, this file contains just two (closely related) such results:
## Main results
* `MDifferentiable.isLocallyConstant`: A complex-differentiable function on a compact complex
manifold is locally constant.
* `MDifferentiable.exists_eq_const_of_compactSpace`: A complex-differentiable function on a compact
preconnected complex manifold is constant.
## TODO
There is a whole theory to develop here. Maybe a next step would be to develop a theory of
holomorphic vector/line bundles, including:
* the finite-dimensionality of the space of sections of a holomorphic vector bundle
* Siegel's theorem: for any `n + 1` formal ratios `g 0 / h 0`, `g 1 / h 1`, .... `g n / h n` of
sections of a fixed line bundle `L` over a complex `n`-manifold, there exists a polynomial
relationship `P (g 0 / h 0, g 1 / h 1, .... g n / h n) = 0`
Another direction would be to develop the relationship with sheaf theory, building the sheaves of
holomorphic and meromorphic functions on a complex manifold and proving algebraic results about the
stalks, such as the Weierstrass preparation theorem.
-/
open scoped Manifold Topology Filter
open Function Set Filter Complex
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℂ E]
variable {F : Type*} [NormedAddCommGroup F] [NormedSpace ℂ F]
variable {H : Type*} [TopologicalSpace H] {I : ModelWithCorners ℂ E H} [I.Boundaryless]
variable {M : Type*} [TopologicalSpace M] [ChartedSpace H M]
[IsManifold I 1 M]
/-- **Maximum modulus principle**: if `f : M → F` is complex differentiable in a neighborhood of `c`
and the norm `‖f z‖` has a local maximum at `c`, then `‖f z‖` is locally constant in a neighborhood
of `c`. This is a manifold version of `Complex.norm_eventually_eq_of_isLocalMax`. -/
theorem Complex.norm_eventually_eq_of_mdifferentiableAt_of_isLocalMax {f : M → F} {c : M}
(hd : ∀ᶠ z in 𝓝 c, MDifferentiableAt I 𝓘(ℂ, F) f z) (hc : IsLocalMax (norm ∘ f) c) :
∀ᶠ y in 𝓝 c, ‖f y‖ = ‖f c‖ := by
set e := extChartAt I c
have hI : range I = univ := ModelWithCorners.Boundaryless.range_eq_univ
have H₁ : 𝓝[range I] (e c) = 𝓝 (e c) := by rw [hI, nhdsWithin_univ]
have H₂ : map e.symm (𝓝 (e c)) = 𝓝 c := by
rw [← map_extChartAt_symm_nhdsWithin_range (I := I) c, H₁]
rw [← H₂, eventually_map]
replace hd : ∀ᶠ y in 𝓝 (e c), DifferentiableAt ℂ (f ∘ e.symm) y := by
have : e.target ∈ 𝓝 (e c) := H₁ ▸ extChartAt_target_mem_nhdsWithin c
filter_upwards [this, Tendsto.eventually H₂.le hd] with y hyt hy₂
have hys : e.symm y ∈ (chartAt H c).source := by
rw [← extChartAt_source I c]
exact (extChartAt I c).map_target hyt
have hfy : f (e.symm y) ∈ (chartAt F (0 : F)).source := mem_univ _
rw [mdifferentiableAt_iff_of_mem_source hys hfy, hI, differentiableWithinAt_univ,
e.right_inv hyt] at hy₂
exact hy₂.2
convert norm_eventually_eq_of_isLocalMax hd _
· exact congr_arg f (extChartAt_to_inv _).symm
· simpa only [e, IsLocalMax, IsMaxFilter, ← H₂, (· ∘ ·), extChartAt_to_inv] using hc
/-!
### Functions holomorphic on a set
-/
namespace MDifferentiableOn
/-- **Maximum modulus principle** on a connected set. Let `U` be a (pre)connected open set in a
complex normed space. Let `f : E → F` be a function that is complex differentiable on `U`. Suppose
that `‖f x‖` takes its maximum value on `U` at `c ∈ U`. Then `‖f x‖ = ‖f c‖` for all `x ∈ U`. -/
theorem norm_eqOn_of_isPreconnected_of_isMaxOn {f : M → F} {U : Set M} {c : M}
(hd : MDifferentiableOn I 𝓘(ℂ, F) f U) (hc : IsPreconnected U) (ho : IsOpen U)
| (hcU : c ∈ U) (hm : IsMaxOn (norm ∘ f) U c) : EqOn (norm ∘ f) (const M ‖f c‖) U := by
set V := {z ∈ U | ‖f z‖ = ‖f c‖}
suffices U ⊆ V from fun x hx ↦ (this hx).2
have hVo : IsOpen V := by
refine isOpen_iff_mem_nhds.2 fun x hx ↦ inter_mem (ho.mem_nhds hx.1) ?_
replace hm : IsLocalMax (‖f ·‖) x :=
mem_of_superset (ho.mem_nhds hx.1) fun z hz ↦ (hm hz).out.trans_eq hx.2.symm
replace hd : ∀ᶠ y in 𝓝 x, MDifferentiableAt I 𝓘(ℂ, F) f y :=
(eventually_mem_nhds_iff.2 (ho.mem_nhds hx.1)).mono fun z ↦ hd.mdifferentiableAt
exact (Complex.norm_eventually_eq_of_mdifferentiableAt_of_isLocalMax hd hm).mono fun _ ↦
(Eq.trans · hx.2)
have hVne : (U ∩ V).Nonempty := ⟨c, hcU, hcU, rfl⟩
set W := U ∩ {z | ‖f z‖ = ‖f c‖}ᶜ
have hWo : IsOpen W := hd.continuousOn.norm.isOpen_inter_preimage ho isOpen_ne
have hdVW : Disjoint V W := disjoint_compl_right.mono inf_le_right inf_le_right
have hUVW : U ⊆ V ∪ W := fun x hx => (eq_or_ne ‖f x‖ ‖f c‖).imp (.intro hx) (.intro hx)
exact hc.subset_left_of_subset_union hVo hWo hdVW hUVW hVne
/-- **Maximum modulus principle** on a connected set. Let `U` be a (pre)connected open set in a
| Mathlib/Geometry/Manifold/Complex.lean | 85 | 103 |
/-
Copyright (c) 2021 François Sunatori. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: François Sunatori
-/
import Mathlib.Analysis.Complex.Circle
import Mathlib.LinearAlgebra.Determinant
import Mathlib.LinearAlgebra.Matrix.GeneralLinearGroup.Basic
/-!
# Isometries of the Complex Plane
The lemma `linear_isometry_complex` states the classification of isometries in the complex plane.
Specifically, isometries with rotations but without translation.
The proof involves:
1. creating a linear isometry `g` with two fixed points, `g(0) = 0`, `g(1) = 1`
2. applying `linear_isometry_complex_aux` to `g`
The proof of `linear_isometry_complex_aux` is separated in the following parts:
1. show that the real parts match up: `LinearIsometry.re_apply_eq_re`
2. show that I maps to either I or -I
3. every z is a linear combination of a + b * I
## References
* [Isometries of the Complex Plane](http://helmut.knaust.info/mediawiki/images/b/b5/Iso.pdf)
-/
noncomputable section
open Complex
open CharZero
open ComplexConjugate
local notation "|" x "|" => Complex.abs x
/-- An element of the unit circle defines a `LinearIsometryEquiv` from `ℂ` to itself, by
rotation. -/
def rotation : Circle →* ℂ ≃ₗᵢ[ℝ] ℂ where
toFun a :=
{ DistribMulAction.toLinearEquiv ℝ ℂ a with
norm_map' x := show ‖a * x‖ = ‖x‖ by
rw [norm_mul, Circle.norm_coe, one_mul] }
map_one' := LinearIsometryEquiv.ext <| by simp
map_mul' a b := LinearIsometryEquiv.ext <| mul_smul a b
@[simp]
theorem rotation_apply (a : Circle) (z : ℂ) : rotation a z = a * z :=
rfl
@[simp]
theorem rotation_symm (a : Circle) : (rotation a).symm = rotation a⁻¹ :=
LinearIsometryEquiv.ext fun _ => rfl
@[simp]
theorem rotation_trans (a b : Circle) : (rotation a).trans (rotation b) = rotation (b * a) := by
ext1
simp
theorem rotation_ne_conjLIE (a : Circle) : rotation a ≠ conjLIE := by
intro h
have h1 : rotation a 1 = conj 1 := LinearIsometryEquiv.congr_fun h 1
have hI : rotation a I = conj I := LinearIsometryEquiv.congr_fun h I
rw [rotation_apply, RingHom.map_one, mul_one] at h1
rw [rotation_apply, conj_I, ← neg_one_mul, mul_left_inj' I_ne_zero, h1, eq_neg_self_iff] at hI
exact one_ne_zero hI
/-- Takes an element of `ℂ ≃ₗᵢ[ℝ] ℂ` and checks if it is a rotation, returns an element of the
unit circle. -/
@[simps]
def rotationOf (e : ℂ ≃ₗᵢ[ℝ] ℂ) : Circle :=
⟨e 1 / ‖e 1‖, by simp [Submonoid.unitSphere]⟩
@[simp]
theorem rotationOf_rotation (a : Circle) : rotationOf (rotation a) = a :=
Subtype.ext <| by simp
theorem rotation_injective : Function.Injective rotation :=
Function.LeftInverse.injective rotationOf_rotation
theorem LinearIsometry.re_apply_eq_re_of_add_conj_eq (f : ℂ →ₗᵢ[ℝ] ℂ)
(h₃ : ∀ z, z + conj z = f z + conj (f z)) (z : ℂ) : (f z).re = z.re := by
simpa [Complex.ext_iff, add_re, add_im, conj_re, conj_im, ← two_mul,
show (2 : ℝ) ≠ 0 by simp [two_ne_zero]] using (h₃ z).symm
theorem LinearIsometry.im_apply_eq_im_or_neg_of_re_apply_eq_re {f : ℂ →ₗᵢ[ℝ] ℂ}
(h₂ : ∀ z, (f z).re = z.re) (z : ℂ) : (f z).im = z.im ∨ (f z).im = -z.im := by
| have h₁ := f.norm_map z
simp only [norm_def] at h₁
rwa [Real.sqrt_inj (normSq_nonneg _) (normSq_nonneg _), normSq_apply (f z), normSq_apply z,
h₂, add_left_cancel_iff, mul_self_eq_mul_self_iff] at h₁
| Mathlib/Analysis/Complex/Isometry.lean | 90 | 93 |
/-
Copyright (c) 2014 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Order.Ring.Nat
import Mathlib.Algebra.Ring.Int.Defs
import Mathlib.Data.Nat.Bitwise
import Mathlib.Data.Nat.Cast.Order.Basic
import Mathlib.Data.Nat.PSub
import Mathlib.Data.Nat.Size
import Mathlib.Data.Num.Bitwise
/-!
# Properties of the binary representation of integers
-/
open Int
attribute [local simp] add_assoc
namespace PosNum
variable {α : Type*}
@[simp, norm_cast]
theorem cast_one [One α] [Add α] : ((1 : PosNum) : α) = 1 :=
rfl
@[simp]
theorem cast_one' [One α] [Add α] : (PosNum.one : α) = 1 :=
rfl
@[simp, norm_cast]
theorem cast_bit0 [One α] [Add α] (n : PosNum) : (n.bit0 : α) = (n : α) + n :=
rfl
@[simp, norm_cast]
theorem cast_bit1 [One α] [Add α] (n : PosNum) : (n.bit1 : α) = ((n : α) + n) + 1 :=
rfl
@[simp, norm_cast]
theorem cast_to_nat [AddMonoidWithOne α] : ∀ n : PosNum, ((n : ℕ) : α) = n
| 1 => Nat.cast_one
| bit0 p => by dsimp; rw [Nat.cast_add, p.cast_to_nat]
| bit1 p => by dsimp; rw [Nat.cast_add, Nat.cast_add, Nat.cast_one, p.cast_to_nat]
@[norm_cast]
theorem to_nat_to_int (n : PosNum) : ((n : ℕ) : ℤ) = n :=
cast_to_nat _
@[simp, norm_cast]
theorem cast_to_int [AddGroupWithOne α] (n : PosNum) : ((n : ℤ) : α) = n := by
rw [← to_nat_to_int, Int.cast_natCast, cast_to_nat]
theorem succ_to_nat : ∀ n, (succ n : ℕ) = n + 1
| 1 => rfl
| bit0 _ => rfl
| bit1 p =>
(congr_arg (fun n ↦ n + n) (succ_to_nat p)).trans <|
show ↑p + 1 + ↑p + 1 = ↑p + ↑p + 1 + 1 by simp [add_left_comm]
theorem one_add (n : PosNum) : 1 + n = succ n := by cases n <;> rfl
theorem add_one (n : PosNum) : n + 1 = succ n := by cases n <;> rfl
@[norm_cast]
theorem add_to_nat : ∀ m n, ((m + n : PosNum) : ℕ) = m + n
| 1, b => by rw [one_add b, succ_to_nat, add_comm, cast_one]
| a, 1 => by rw [add_one a, succ_to_nat, cast_one]
| bit0 a, bit0 b => (congr_arg (fun n ↦ n + n) (add_to_nat a b)).trans <| add_add_add_comm _ _ _ _
| bit0 a, bit1 b =>
(congr_arg (fun n ↦ (n + n) + 1) (add_to_nat a b)).trans <|
show (a + b + (a + b) + 1 : ℕ) = a + a + (b + b + 1) by simp [add_left_comm]
| bit1 a, bit0 b =>
(congr_arg (fun n ↦ (n + n) + 1) (add_to_nat a b)).trans <|
show (a + b + (a + b) + 1 : ℕ) = a + a + 1 + (b + b) by simp [add_comm, add_left_comm]
| bit1 a, bit1 b =>
show (succ (a + b) + succ (a + b) : ℕ) = a + a + 1 + (b + b + 1) by
rw [succ_to_nat, add_to_nat a b]; simp [add_left_comm]
theorem add_succ : ∀ m n : PosNum, m + succ n = succ (m + n)
| 1, b => by simp [one_add]
| bit0 a, 1 => congr_arg bit0 (add_one a)
| bit1 a, 1 => congr_arg bit1 (add_one a)
| bit0 _, bit0 _ => rfl
| bit0 a, bit1 b => congr_arg bit0 (add_succ a b)
| bit1 _, bit0 _ => rfl
| bit1 a, bit1 b => congr_arg bit1 (add_succ a b)
theorem bit0_of_bit0 : ∀ n, n + n = bit0 n
| 1 => rfl
| bit0 p => congr_arg bit0 (bit0_of_bit0 p)
| bit1 p => show bit0 (succ (p + p)) = _ by rw [bit0_of_bit0 p, succ]
theorem bit1_of_bit1 (n : PosNum) : (n + n) + 1 = bit1 n :=
show (n + n) + 1 = bit1 n by rw [add_one, bit0_of_bit0, succ]
@[norm_cast]
theorem mul_to_nat (m) : ∀ n, ((m * n : PosNum) : ℕ) = m * n
| 1 => (mul_one _).symm
| bit0 p => show (↑(m * p) + ↑(m * p) : ℕ) = ↑m * (p + p) by rw [mul_to_nat m p, left_distrib]
| bit1 p =>
(add_to_nat (bit0 (m * p)) m).trans <|
show (↑(m * p) + ↑(m * p) + ↑m : ℕ) = ↑m * (p + p) + m by rw [mul_to_nat m p, left_distrib]
theorem to_nat_pos : ∀ n : PosNum, 0 < (n : ℕ)
| 1 => Nat.zero_lt_one
| bit0 p =>
let h := to_nat_pos p
add_pos h h
| bit1 _p => Nat.succ_pos _
theorem cmp_to_nat_lemma {m n : PosNum} : (m : ℕ) < n → (bit1 m : ℕ) < bit0 n :=
show (m : ℕ) < n → (m + m + 1 + 1 : ℕ) ≤ n + n by
intro h; rw [Nat.add_right_comm m m 1, add_assoc]; exact Nat.add_le_add h h
theorem cmp_swap (m) : ∀ n, (cmp m n).swap = cmp n m := by
induction' m with m IH m IH <;> intro n <;> obtain - | n | n := n <;> unfold cmp <;>
try { rfl } <;> rw [← IH] <;> cases cmp m n <;> rfl
theorem cmp_to_nat : ∀ m n, (Ordering.casesOn (cmp m n) ((m : ℕ) < n) (m = n) ((n : ℕ) < m) : Prop)
| 1, 1 => rfl
| bit0 a, 1 =>
let h : (1 : ℕ) ≤ a := to_nat_pos a
Nat.add_le_add h h
| bit1 a, 1 => Nat.succ_lt_succ <| to_nat_pos <| bit0 a
| 1, bit0 b =>
let h : (1 : ℕ) ≤ b := to_nat_pos b
Nat.add_le_add h h
| 1, bit1 b => Nat.succ_lt_succ <| to_nat_pos <| bit0 b
| bit0 a, bit0 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.add_lt_add this this
· rw [this]
· exact Nat.add_lt_add this this
| bit0 a, bit1 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.le_succ_of_le (Nat.add_lt_add this this)
· rw [this]
apply Nat.lt_succ_self
· exact cmp_to_nat_lemma this
| bit1 a, bit0 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact cmp_to_nat_lemma this
· rw [this]
apply Nat.lt_succ_self
· exact Nat.le_succ_of_le (Nat.add_lt_add this this)
| bit1 a, bit1 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.succ_lt_succ (Nat.add_lt_add this this)
· rw [this]
· exact Nat.succ_lt_succ (Nat.add_lt_add this this)
@[norm_cast]
theorem lt_to_nat {m n : PosNum} : (m : ℕ) < n ↔ m < n :=
show (m : ℕ) < n ↔ cmp m n = Ordering.lt from
match cmp m n, cmp_to_nat m n with
| Ordering.lt, h => by simp only at h; simp [h]
| Ordering.eq, h => by simp only at h; simp [h, lt_irrefl]
| Ordering.gt, h => by simp [not_lt_of_gt h]
@[norm_cast]
theorem le_to_nat {m n : PosNum} : (m : ℕ) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr lt_to_nat
end PosNum
namespace Num
variable {α : Type*}
open PosNum
theorem add_zero (n : Num) : n + 0 = n := by cases n <;> rfl
theorem zero_add (n : Num) : 0 + n = n := by cases n <;> rfl
theorem add_one : ∀ n : Num, n + 1 = succ n
| 0 => rfl
| pos p => by cases p <;> rfl
theorem add_succ : ∀ m n : Num, m + succ n = succ (m + n)
| 0, n => by simp [zero_add]
| pos p, 0 => show pos (p + 1) = succ (pos p + 0) by rw [PosNum.add_one, add_zero, succ, succ']
| pos _, pos _ => congr_arg pos (PosNum.add_succ _ _)
theorem bit0_of_bit0 : ∀ n : Num, n + n = n.bit0
| 0 => rfl
| pos p => congr_arg pos p.bit0_of_bit0
theorem bit1_of_bit1 : ∀ n : Num, (n + n) + 1 = n.bit1
| 0 => rfl
| pos p => congr_arg pos p.bit1_of_bit1
@[simp]
theorem ofNat'_zero : Num.ofNat' 0 = 0 := by simp [Num.ofNat']
theorem ofNat'_bit (b n) : ofNat' (Nat.bit b n) = cond b Num.bit1 Num.bit0 (ofNat' n) :=
Nat.binaryRec_eq _ _ (.inl rfl)
@[simp]
theorem ofNat'_one : Num.ofNat' 1 = 1 := by erw [ofNat'_bit true 0, cond, ofNat'_zero]; rfl
theorem bit1_succ : ∀ n : Num, n.bit1.succ = n.succ.bit0
| 0 => rfl
| pos _n => rfl
theorem ofNat'_succ : ∀ {n}, ofNat' (n + 1) = ofNat' n + 1 :=
@(Nat.binaryRec (by simp [zero_add]) fun b n ih => by
cases b
· erw [ofNat'_bit true n, ofNat'_bit]
simp only [← bit1_of_bit1, ← bit0_of_bit0, cond]
· rw [show n.bit true + 1 = (n + 1).bit false by simp [Nat.bit, mul_add],
ofNat'_bit, ofNat'_bit, ih]
simp only [cond, add_one, bit1_succ])
@[simp]
theorem add_ofNat' (m n) : Num.ofNat' (m + n) = Num.ofNat' m + Num.ofNat' n := by
induction n
· simp only [Nat.add_zero, ofNat'_zero, add_zero]
· simp only [Nat.add_succ, Nat.add_zero, ofNat'_succ, add_one, add_succ, *]
@[simp, norm_cast]
theorem cast_zero [Zero α] [One α] [Add α] : ((0 : Num) : α) = 0 :=
rfl
@[simp]
theorem cast_zero' [Zero α] [One α] [Add α] : (Num.zero : α) = 0 :=
rfl
@[simp, norm_cast]
theorem cast_one [Zero α] [One α] [Add α] : ((1 : Num) : α) = 1 :=
rfl
@[simp]
theorem cast_pos [Zero α] [One α] [Add α] (n : PosNum) : (Num.pos n : α) = n :=
rfl
theorem succ'_to_nat : ∀ n, (succ' n : ℕ) = n + 1
| 0 => (Nat.zero_add _).symm
| pos _p => PosNum.succ_to_nat _
theorem succ_to_nat (n) : (succ n : ℕ) = n + 1 :=
succ'_to_nat n
@[simp, norm_cast]
theorem cast_to_nat [AddMonoidWithOne α] : ∀ n : Num, ((n : ℕ) : α) = n
| 0 => Nat.cast_zero
| pos p => p.cast_to_nat
@[norm_cast]
theorem add_to_nat : ∀ m n, ((m + n : Num) : ℕ) = m + n
| 0, 0 => rfl
| 0, pos _q => (Nat.zero_add _).symm
| pos _p, 0 => rfl
| pos _p, pos _q => PosNum.add_to_nat _ _
@[norm_cast]
theorem mul_to_nat : ∀ m n, ((m * n : Num) : ℕ) = m * n
| 0, 0 => rfl
| 0, pos _q => (zero_mul _).symm
| pos _p, 0 => rfl
| pos _p, pos _q => PosNum.mul_to_nat _ _
theorem cmp_to_nat : ∀ m n, (Ordering.casesOn (cmp m n) ((m : ℕ) < n) (m = n) ((n : ℕ) < m) : Prop)
| 0, 0 => rfl
| 0, pos _ => to_nat_pos _
| pos _, 0 => to_nat_pos _
| pos a, pos b => by
have := PosNum.cmp_to_nat a b; revert this; dsimp [cmp]; cases PosNum.cmp a b
exacts [id, congr_arg pos, id]
@[norm_cast]
theorem lt_to_nat {m n : Num} : (m : ℕ) < n ↔ m < n :=
show (m : ℕ) < n ↔ cmp m n = Ordering.lt from
match cmp m n, cmp_to_nat m n with
| Ordering.lt, h => by simp only at h; simp [h]
| Ordering.eq, h => by simp only at h; simp [h, lt_irrefl]
| Ordering.gt, h => by simp [not_lt_of_gt h]
@[norm_cast]
theorem le_to_nat {m n : Num} : (m : ℕ) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr lt_to_nat
end Num
namespace PosNum
@[simp]
theorem of_to_nat' : ∀ n : PosNum, Num.ofNat' (n : ℕ) = Num.pos n
| 1 => by erw [@Num.ofNat'_bit true 0, Num.ofNat'_zero]; rfl
| bit0 p => by
simpa only [Nat.bit_false, cond_false, two_mul, of_to_nat' p] using Num.ofNat'_bit false p
| bit1 p => by
simpa only [Nat.bit_true, cond_true, two_mul, of_to_nat' p] using Num.ofNat'_bit true p
end PosNum
namespace Num
@[simp, norm_cast]
theorem of_to_nat' : ∀ n : Num, Num.ofNat' (n : ℕ) = n
| 0 => ofNat'_zero
| pos p => p.of_to_nat'
lemma toNat_injective : Function.Injective (castNum : Num → ℕ) :=
Function.LeftInverse.injective of_to_nat'
@[norm_cast]
theorem to_nat_inj {m n : Num} : (m : ℕ) = n ↔ m = n := toNat_injective.eq_iff
/-- This tactic tries to turn an (in)equality about `Num`s to one about `Nat`s by rewriting.
```lean
example (n : Num) (m : Num) : n ≤ n + m := by
transfer_rw
exact Nat.le_add_right _ _
```
-/
scoped macro (name := transfer_rw) "transfer_rw" : tactic => `(tactic|
(repeat first | rw [← to_nat_inj] | rw [← lt_to_nat] | rw [← le_to_nat]
repeat first | rw [add_to_nat] | rw [mul_to_nat] | rw [cast_one] | rw [cast_zero]))
/--
This tactic tries to prove (in)equalities about `Num`s by transferring them to the `Nat` world and
then trying to call `simp`.
```lean
example (n : Num) (m : Num) : n ≤ n + m := by transfer
```
-/
scoped macro (name := transfer) "transfer" : tactic => `(tactic|
(intros; transfer_rw; try simp))
instance addMonoid : AddMonoid Num where
add := (· + ·)
zero := 0
zero_add := zero_add
add_zero := add_zero
add_assoc := by transfer
nsmul := nsmulRec
instance addMonoidWithOne : AddMonoidWithOne Num :=
{ Num.addMonoid with
natCast := Num.ofNat'
one := 1
natCast_zero := ofNat'_zero
natCast_succ := fun _ => ofNat'_succ }
instance commSemiring : CommSemiring Num where
__ := Num.addMonoid
__ := Num.addMonoidWithOne
mul := (· * ·)
npow := @npowRec Num ⟨1⟩ ⟨(· * ·)⟩
mul_zero _ := by rw [← to_nat_inj, mul_to_nat, cast_zero, mul_zero]
zero_mul _ := by rw [← to_nat_inj, mul_to_nat, cast_zero, zero_mul]
mul_one _ := by rw [← to_nat_inj, mul_to_nat, cast_one, mul_one]
one_mul _ := by rw [← to_nat_inj, mul_to_nat, cast_one, one_mul]
add_comm _ _ := by simp_rw [← to_nat_inj, add_to_nat, add_comm]
mul_comm _ _ := by simp_rw [← to_nat_inj, mul_to_nat, mul_comm]
mul_assoc _ _ _ := by simp_rw [← to_nat_inj, mul_to_nat, mul_assoc]
left_distrib _ _ _ := by simp only [← to_nat_inj, mul_to_nat, add_to_nat, mul_add]
right_distrib _ _ _ := by simp only [← to_nat_inj, mul_to_nat, add_to_nat, add_mul]
instance partialOrder : PartialOrder Num where
lt_iff_le_not_le a b := by simp only [← lt_to_nat, ← le_to_nat, lt_iff_le_not_le]
le_refl := by transfer
le_trans a b c := by transfer_rw; apply le_trans
le_antisymm a b := by transfer_rw; apply le_antisymm
instance isOrderedCancelAddMonoid : IsOrderedCancelAddMonoid Num where
add_le_add_left a b h c := by revert h; transfer_rw; exact fun h => add_le_add_left h c
le_of_add_le_add_left a b c :=
show a + b ≤ a + c → b ≤ c by transfer_rw; apply le_of_add_le_add_left
instance linearOrder : LinearOrder Num :=
{ le_total := by
intro a b
transfer_rw
apply le_total
toDecidableLT := Num.decidableLT
toDecidableLE := Num.decidableLE
-- This is relying on an automatically generated instance name,
-- generated in a `deriving` handler.
-- See https://github.com/leanprover/lean4/issues/2343
toDecidableEq := instDecidableEqNum }
instance isStrictOrderedRing : IsStrictOrderedRing Num :=
{ zero_le_one := by decide
mul_lt_mul_of_pos_left := by
intro a b c
transfer_rw
apply mul_lt_mul_of_pos_left
mul_lt_mul_of_pos_right := by
intro a b c
transfer_rw
apply mul_lt_mul_of_pos_right
exists_pair_ne := ⟨0, 1, by decide⟩ }
@[norm_cast]
theorem add_of_nat (m n) : ((m + n : ℕ) : Num) = m + n :=
add_ofNat' _ _
@[norm_cast]
theorem to_nat_to_int (n : Num) : ((n : ℕ) : ℤ) = n :=
cast_to_nat _
@[simp, norm_cast]
theorem cast_to_int {α} [AddGroupWithOne α] (n : Num) : ((n : ℤ) : α) = n := by
rw [← to_nat_to_int, Int.cast_natCast, cast_to_nat]
theorem to_of_nat : ∀ n : ℕ, ((n : Num) : ℕ) = n
| 0 => by rw [Nat.cast_zero, cast_zero]
| n + 1 => by rw [Nat.cast_succ, add_one, succ_to_nat, to_of_nat n]
@[simp, norm_cast]
theorem of_natCast {α} [AddMonoidWithOne α] (n : ℕ) : ((n : Num) : α) = n := by
rw [← cast_to_nat, to_of_nat]
@[norm_cast]
theorem of_nat_inj {m n : ℕ} : (m : Num) = n ↔ m = n :=
⟨fun h => Function.LeftInverse.injective to_of_nat h, congr_arg _⟩
-- The priority should be `high`er than `cast_to_nat`.
@[simp high, norm_cast]
theorem of_to_nat : ∀ n : Num, ((n : ℕ) : Num) = n :=
of_to_nat'
@[norm_cast]
theorem dvd_to_nat (m n : Num) : (m : ℕ) ∣ n ↔ m ∣ n :=
⟨fun ⟨k, e⟩ => ⟨k, by rw [← of_to_nat n, e]; simp⟩, fun ⟨k, e⟩ => ⟨k, by simp [e, mul_to_nat]⟩⟩
end Num
namespace PosNum
variable {α : Type*}
open Num
-- The priority should be `high`er than `cast_to_nat`.
@[simp high, norm_cast]
theorem of_to_nat : ∀ n : PosNum, ((n : ℕ) : Num) = Num.pos n :=
of_to_nat'
@[norm_cast]
theorem to_nat_inj {m n : PosNum} : (m : ℕ) = n ↔ m = n :=
⟨fun h => Num.pos.inj <| by rw [← PosNum.of_to_nat, ← PosNum.of_to_nat, h], congr_arg _⟩
theorem pred'_to_nat : ∀ n, (pred' n : ℕ) = Nat.pred n
| 1 => rfl
| bit0 n =>
have : Nat.succ ↑(pred' n) = ↑n := by
rw [pred'_to_nat n, Nat.succ_pred_eq_of_pos (to_nat_pos n)]
match (motive :=
∀ k : Num, Nat.succ ↑k = ↑n → ↑(Num.casesOn k 1 bit1 : PosNum) = Nat.pred (n + n))
pred' n, this with
| 0, (h : ((1 : Num) : ℕ) = n) => by rw [← to_nat_inj.1 h]; rfl
| Num.pos p, (h : Nat.succ ↑p = n) => by rw [← h]; exact (Nat.succ_add p p).symm
| bit1 _ => rfl
@[simp]
theorem pred'_succ' (n) : pred' (succ' n) = n :=
Num.to_nat_inj.1 <| by rw [pred'_to_nat, succ'_to_nat, Nat.add_one, Nat.pred_succ]
@[simp]
theorem succ'_pred' (n) : succ' (pred' n) = n :=
to_nat_inj.1 <| by
rw [succ'_to_nat, pred'_to_nat, Nat.add_one, Nat.succ_pred_eq_of_pos (to_nat_pos _)]
instance dvd : Dvd PosNum :=
⟨fun m n => pos m ∣ pos n⟩
@[norm_cast]
theorem dvd_to_nat {m n : PosNum} : (m : ℕ) ∣ n ↔ m ∣ n :=
Num.dvd_to_nat (pos m) (pos n)
theorem size_to_nat : ∀ n, (size n : ℕ) = Nat.size n
| 1 => Nat.size_one.symm
| bit0 n => by
rw [size, succ_to_nat, size_to_nat n, cast_bit0, ← two_mul]
erw [@Nat.size_bit false n]
have := to_nat_pos n
dsimp [Nat.bit]; omega
| bit1 n => by
rw [size, succ_to_nat, size_to_nat n, cast_bit1, ← two_mul]
erw [@Nat.size_bit true n]
dsimp [Nat.bit]; omega
theorem size_eq_natSize : ∀ n, (size n : ℕ) = natSize n
| 1 => rfl
| bit0 n => by rw [size, succ_to_nat, natSize, size_eq_natSize n]
| bit1 n => by rw [size, succ_to_nat, natSize, size_eq_natSize n]
theorem natSize_to_nat (n) : natSize n = Nat.size n := by rw [← size_eq_natSize, size_to_nat]
theorem natSize_pos (n) : 0 < natSize n := by cases n <;> apply Nat.succ_pos
/-- This tactic tries to turn an (in)equality about `PosNum`s to one about `Nat`s by rewriting.
```lean
example (n : PosNum) (m : PosNum) : n ≤ n + m := by
transfer_rw
exact Nat.le_add_right _ _
```
-/
scoped macro (name := transfer_rw) "transfer_rw" : tactic => `(tactic|
(repeat first | rw [← to_nat_inj] | rw [← lt_to_nat] | rw [← le_to_nat]
repeat first | rw [add_to_nat] | rw [mul_to_nat] | rw [cast_one] | rw [cast_zero]))
/--
This tactic tries to prove (in)equalities about `PosNum`s by transferring them to the `Nat` world
and then trying to call `simp`.
```lean
example (n : PosNum) (m : PosNum) : n ≤ n + m := by transfer
```
-/
scoped macro (name := transfer) "transfer" : tactic => `(tactic|
(intros; transfer_rw; try simp [add_comm, add_left_comm, mul_comm, mul_left_comm]))
instance addCommSemigroup : AddCommSemigroup PosNum where
add := (· + ·)
add_assoc := by transfer
add_comm := by transfer
instance commMonoid : CommMonoid PosNum where
mul := (· * ·)
one := (1 : PosNum)
npow := @npowRec PosNum ⟨1⟩ ⟨(· * ·)⟩
mul_assoc := by transfer
one_mul := by transfer
mul_one := by transfer
mul_comm := by transfer
instance distrib : Distrib PosNum where
add := (· + ·)
mul := (· * ·)
left_distrib := by transfer; simp [mul_add]
right_distrib := by transfer; simp [mul_add, mul_comm]
instance linearOrder : LinearOrder PosNum where
lt := (· < ·)
lt_iff_le_not_le := by
intro a b
transfer_rw
apply lt_iff_le_not_le
le := (· ≤ ·)
le_refl := by transfer
le_trans := by
intro a b c
transfer_rw
apply le_trans
le_antisymm := by
intro a b
transfer_rw
apply le_antisymm
le_total := by
intro a b
transfer_rw
apply le_total
toDecidableLT := by infer_instance
toDecidableLE := by infer_instance
toDecidableEq := by infer_instance
@[simp]
theorem cast_to_num (n : PosNum) : ↑n = Num.pos n := by rw [← cast_to_nat, ← of_to_nat n]
@[simp, norm_cast]
theorem bit_to_nat (b n) : (bit b n : ℕ) = Nat.bit b n := by cases b <;> simp [bit, two_mul]
@[simp, norm_cast]
theorem cast_add [AddMonoidWithOne α] (m n) : ((m + n : PosNum) : α) = m + n := by
rw [← cast_to_nat, add_to_nat, Nat.cast_add, cast_to_nat, cast_to_nat]
@[simp 500, norm_cast]
theorem cast_succ [AddMonoidWithOne α] (n : PosNum) : (succ n : α) = n + 1 := by
rw [← add_one, cast_add, cast_one]
@[simp, norm_cast]
theorem cast_inj [AddMonoidWithOne α] [CharZero α] {m n : PosNum} : (m : α) = n ↔ m = n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_inj, to_nat_inj]
@[simp]
theorem one_le_cast [Semiring α] [PartialOrder α] [IsStrictOrderedRing α] (n : PosNum) :
(1 : α) ≤ n := by
rw [← cast_to_nat, ← Nat.cast_one, Nat.cast_le (α := α)]; apply to_nat_pos
@[simp]
theorem cast_pos [Semiring α] [PartialOrder α] [IsStrictOrderedRing α] (n : PosNum) : 0 < (n : α) :=
lt_of_lt_of_le zero_lt_one (one_le_cast n)
@[simp, norm_cast]
theorem cast_mul [NonAssocSemiring α] (m n) : ((m * n : PosNum) : α) = m * n := by
rw [← cast_to_nat, mul_to_nat, Nat.cast_mul, cast_to_nat, cast_to_nat]
@[simp]
theorem cmp_eq (m n) : cmp m n = Ordering.eq ↔ m = n := by
have := cmp_to_nat m n
-- Porting note: `cases` didn't rewrite at `this`, so `revert` & `intro` are required.
revert this; cases cmp m n <;> intro this <;> simp at this ⊢ <;> try { exact this } <;>
simp [show m ≠ n from fun e => by rw [e] at this;exact lt_irrefl _ this]
@[simp, norm_cast]
theorem cast_lt [Semiring α] [PartialOrder α] [IsStrictOrderedRing α] {m n : PosNum} :
(m : α) < n ↔ m < n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_lt (α := α), lt_to_nat]
@[simp, norm_cast]
theorem cast_le [Semiring α] [LinearOrder α] [IsStrictOrderedRing α] {m n : PosNum} :
(m : α) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr cast_lt
end PosNum
namespace Num
variable {α : Type*}
open PosNum
theorem bit_to_nat (b n) : (bit b n : ℕ) = Nat.bit b n := by
cases b <;> cases n <;> simp [bit, two_mul] <;> rfl
theorem cast_succ' [AddMonoidWithOne α] (n) : (succ' n : α) = n + 1 := by
rw [← PosNum.cast_to_nat, succ'_to_nat, Nat.cast_add_one, cast_to_nat]
theorem cast_succ [AddMonoidWithOne α] (n) : (succ n : α) = n + 1 :=
cast_succ' n
@[simp, norm_cast]
theorem cast_add [AddMonoidWithOne α] (m n) : ((m + n : Num) : α) = m + n := by
rw [← cast_to_nat, add_to_nat, Nat.cast_add, cast_to_nat, cast_to_nat]
@[simp, norm_cast]
theorem cast_bit0 [NonAssocSemiring α] (n : Num) : (n.bit0 : α) = 2 * (n : α) := by
rw [← bit0_of_bit0, two_mul, cast_add]
@[simp, norm_cast]
theorem cast_bit1 [NonAssocSemiring α] (n : Num) : (n.bit1 : α) = 2 * (n : α) + 1 := by
rw [← bit1_of_bit1, bit0_of_bit0, cast_add, cast_bit0]; rfl
@[simp, norm_cast]
theorem cast_mul [NonAssocSemiring α] : ∀ m n, ((m * n : Num) : α) = m * n
| 0, 0 => (zero_mul _).symm
| 0, pos _q => (zero_mul _).symm
| pos _p, 0 => (mul_zero _).symm
| pos _p, pos _q => PosNum.cast_mul _ _
theorem size_to_nat : ∀ n, (size n : ℕ) = Nat.size n
| 0 => Nat.size_zero.symm
| pos p => p.size_to_nat
theorem size_eq_natSize : ∀ n, (size n : ℕ) = natSize n
| 0 => rfl
| pos p => p.size_eq_natSize
theorem natSize_to_nat (n) : natSize n = Nat.size n := by rw [← size_eq_natSize, size_to_nat]
@[simp 999]
theorem ofNat'_eq : ∀ n, Num.ofNat' n = n :=
Nat.binaryRec (by simp) fun b n IH => by tauto
theorem zneg_toZNum (n : Num) : -n.toZNum = n.toZNumNeg := by cases n <;> rfl
theorem zneg_toZNumNeg (n : Num) : -n.toZNumNeg = n.toZNum := by cases n <;> rfl
theorem toZNum_inj {m n : Num} : m.toZNum = n.toZNum ↔ m = n :=
⟨fun h => by cases m <;> cases n <;> cases h <;> rfl, congr_arg _⟩
@[simp]
theorem cast_toZNum [Zero α] [One α] [Add α] [Neg α] : ∀ n : Num, (n.toZNum : α) = n
| 0 => rfl
| Num.pos _p => rfl
@[simp]
theorem cast_toZNumNeg [SubtractionMonoid α] [One α] : ∀ n : Num, (n.toZNumNeg : α) = -n
| 0 => neg_zero.symm
| Num.pos _p => rfl
@[simp]
theorem add_toZNum (m n : Num) : Num.toZNum (m + n) = m.toZNum + n.toZNum := by
cases m <;> cases n <;> rfl
end Num
namespace PosNum
open Num
theorem pred_to_nat {n : PosNum} (h : 1 < n) : (pred n : ℕ) = Nat.pred n := by
unfold pred
cases e : pred' n
· have : (1 : ℕ) ≤ Nat.pred n := Nat.pred_le_pred ((@cast_lt ℕ _ _ _).2 h)
rw [← pred'_to_nat, e] at this
exact absurd this (by decide)
· rw [← pred'_to_nat, e]
rfl
theorem sub'_one (a : PosNum) : sub' a 1 = (pred' a).toZNum := by cases a <;> rfl
theorem one_sub' (a : PosNum) : sub' 1 a = (pred' a).toZNumNeg := by cases a <;> rfl
theorem lt_iff_cmp {m n} : m < n ↔ cmp m n = Ordering.lt :=
Iff.rfl
theorem le_iff_cmp {m n} : m ≤ n ↔ cmp m n ≠ Ordering.gt :=
not_congr <| lt_iff_cmp.trans <| by rw [← cmp_swap]; cases cmp m n <;> decide
end PosNum
namespace Num
variable {α : Type*}
open PosNum
theorem pred_to_nat : ∀ n : Num, (pred n : ℕ) = Nat.pred n
| 0 => rfl
| pos p => by rw [pred, PosNum.pred'_to_nat]; rfl
theorem ppred_to_nat : ∀ n : Num, (↑) <$> ppred n = Nat.ppred n
| 0 => rfl
| pos p => by
rw [ppred, Option.map_some, Nat.ppred_eq_some.2]
rw [PosNum.pred'_to_nat, Nat.succ_pred_eq_of_pos (PosNum.to_nat_pos _)]
rfl
theorem cmp_swap (m n) : (cmp m n).swap = cmp n m := by
cases m <;> cases n <;> try { rfl }; apply PosNum.cmp_swap
theorem cmp_eq (m n) : cmp m n = Ordering.eq ↔ m = n := by
have := cmp_to_nat m n
-- Porting note: `cases` didn't rewrite at `this`, so `revert` & `intro` are required.
revert this; cases cmp m n <;> intro this <;> simp at this ⊢ <;> try { exact this } <;>
simp [show m ≠ n from fun e => by rw [e] at this; exact lt_irrefl _ this]
@[simp, norm_cast]
theorem cast_lt [Semiring α] [PartialOrder α] [IsStrictOrderedRing α] {m n : Num} :
(m : α) < n ↔ m < n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_lt (α := α), lt_to_nat]
@[simp, norm_cast]
theorem cast_le [Semiring α] [LinearOrder α] [IsStrictOrderedRing α] {m n : Num} :
(m : α) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr cast_lt
@[simp, norm_cast]
theorem cast_inj [Semiring α] [PartialOrder α] [IsStrictOrderedRing α] {m n : Num} :
(m : α) = n ↔ m = n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_inj, to_nat_inj]
theorem lt_iff_cmp {m n} : m < n ↔ cmp m n = Ordering.lt :=
Iff.rfl
theorem le_iff_cmp {m n} : m ≤ n ↔ cmp m n ≠ Ordering.gt :=
not_congr <| lt_iff_cmp.trans <| by rw [← cmp_swap]; cases cmp m n <;> decide
theorem castNum_eq_bitwise {f : Num → Num → Num} {g : Bool → Bool → Bool}
(p : PosNum → PosNum → Num)
(gff : g false false = false) (f00 : f 0 0 = 0)
(f0n : ∀ n, f 0 (pos n) = cond (g false true) (pos n) 0)
(fn0 : ∀ n, f (pos n) 0 = cond (g true false) (pos n) 0)
(fnn : ∀ m n, f (pos m) (pos n) = p m n) (p11 : p 1 1 = cond (g true true) 1 0)
(p1b : ∀ b n, p 1 (PosNum.bit b n) = bit (g true b) (cond (g false true) (pos n) 0))
(pb1 : ∀ a m, p (PosNum.bit a m) 1 = bit (g a true) (cond (g true false) (pos m) 0))
(pbb : ∀ a b m n, p (PosNum.bit a m) (PosNum.bit b n) = bit (g a b) (p m n)) :
∀ m n : Num, (f m n : ℕ) = Nat.bitwise g m n := by
intros m n
obtain - | m := m <;> obtain - | n := n <;>
try simp only [show zero = 0 from rfl, show ((0 : Num) : ℕ) = 0 from rfl]
· rw [f00, Nat.bitwise_zero]; rfl
· rw [f0n, Nat.bitwise_zero_left]
cases g false true <;> rfl
· rw [fn0, Nat.bitwise_zero_right]
cases g true false <;> rfl
· rw [fnn]
have this b (n : PosNum) : (cond b (↑n) 0 : ℕ) = ↑(cond b (pos n) 0 : Num) := by
cases b <;> rfl
have this' b (n : PosNum) : ↑ (pos (PosNum.bit b n)) = Nat.bit b ↑n := by
cases b <;> simp
induction' m with m IH m IH generalizing n <;> obtain - | n | n := n
any_goals simp only [show one = 1 from rfl, show pos 1 = 1 from rfl,
show PosNum.bit0 = PosNum.bit false from rfl, show PosNum.bit1 = PosNum.bit true from rfl,
show ((1 : Num) : ℕ) = Nat.bit true 0 from rfl]
all_goals
repeat rw [this']
rw [Nat.bitwise_bit gff]
any_goals rw [Nat.bitwise_zero, p11]; cases g true true <;> rfl
any_goals rw [Nat.bitwise_zero_left, ← Bool.cond_eq_ite, this, ← bit_to_nat, p1b]
any_goals rw [Nat.bitwise_zero_right, ← Bool.cond_eq_ite, this, ← bit_to_nat, pb1]
all_goals
rw [← show ∀ n : PosNum, ↑(p m n) = Nat.bitwise g ↑m ↑n from IH]
rw [← bit_to_nat, pbb]
@[simp, norm_cast]
theorem castNum_or : ∀ m n : Num, ↑(m ||| n) = (↑m ||| ↑n : ℕ) := by
apply castNum_eq_bitwise fun x y => pos (PosNum.lor x y) <;>
(try rintro (_ | _)) <;> (try rintro (_ | _)) <;> intros <;> rfl
@[simp, norm_cast]
theorem castNum_and : ∀ m n : Num, ↑(m &&& n) = (↑m &&& ↑n : ℕ) := by
apply castNum_eq_bitwise PosNum.land <;> intros <;> (try cases_type* Bool) <;> rfl
@[simp, norm_cast]
theorem castNum_ldiff : ∀ m n : Num, (ldiff m n : ℕ) = Nat.ldiff m n := by
apply castNum_eq_bitwise PosNum.ldiff <;> intros <;> (try cases_type* Bool) <;> rfl
@[simp, norm_cast]
theorem castNum_xor : ∀ m n : Num, ↑(m ^^^ n) = (↑m ^^^ ↑n : ℕ) := by
apply castNum_eq_bitwise PosNum.lxor <;> intros <;> (try cases_type* Bool) <;> rfl
@[simp, norm_cast]
theorem castNum_shiftLeft (m : Num) (n : Nat) : ↑(m <<< n) = (m : ℕ) <<< (n : ℕ) := by
cases m <;> dsimp only [← shiftl_eq_shiftLeft, shiftl]
· symm
apply Nat.zero_shiftLeft
simp only [cast_pos]
induction' n with n IH
· rfl
simp [PosNum.shiftl_succ_eq_bit0_shiftl, Nat.shiftLeft_succ, IH, pow_succ, ← mul_assoc, mul_comm,
-shiftl_eq_shiftLeft, -PosNum.shiftl_eq_shiftLeft, shiftl, mul_two]
@[simp, norm_cast]
theorem castNum_shiftRight (m : Num) (n : Nat) : ↑(m >>> n) = (m : ℕ) >>> (n : ℕ) := by
obtain - | m := m <;> dsimp only [← shiftr_eq_shiftRight, shiftr]
· symm
apply Nat.zero_shiftRight
induction' n with n IH generalizing m
· cases m <;> rfl
have hdiv2 : ∀ m, Nat.div2 (m + m) = m := by intro; rw [Nat.div2_val]; omega
obtain - | m | m := m <;> dsimp only [PosNum.shiftr, ← PosNum.shiftr_eq_shiftRight]
· rw [Nat.shiftRight_eq_div_pow]
symm
apply Nat.div_eq_of_lt
simp
· trans
· apply IH
change Nat.shiftRight m n = Nat.shiftRight (m + m + 1) (n + 1)
rw [add_comm n 1, @Nat.shiftRight_eq _ (1 + n), Nat.shiftRight_add]
apply congr_arg fun x => Nat.shiftRight x n
simp [-add_assoc, Nat.shiftRight_succ, Nat.shiftRight_zero, ← Nat.div2_val, hdiv2]
· trans
· apply IH
change Nat.shiftRight m n = Nat.shiftRight (m + m) (n + 1)
rw [add_comm n 1, @Nat.shiftRight_eq _ (1 + n), Nat.shiftRight_add]
apply congr_arg fun x => Nat.shiftRight x n
simp [-add_assoc, Nat.shiftRight_succ, Nat.shiftRight_zero, ← Nat.div2_val, hdiv2]
@[simp]
theorem castNum_testBit (m n) : testBit m n = Nat.testBit m n := by
cases m with dsimp only [testBit]
| zero =>
rw [show (Num.zero : Nat) = 0 from rfl, Nat.zero_testBit]
| pos m =>
rw [cast_pos]
induction' n with n IH generalizing m <;> obtain - | m | m := m
<;> simp only [PosNum.testBit]
· rfl
· rw [PosNum.cast_bit1, ← two_mul, ← congr_fun Nat.bit_true, Nat.testBit_bit_zero]
· rw [PosNum.cast_bit0, ← two_mul, ← congr_fun Nat.bit_false, Nat.testBit_bit_zero]
· simp [Nat.testBit_add_one]
· rw [PosNum.cast_bit1, ← two_mul, ← congr_fun Nat.bit_true, Nat.testBit_bit_succ, IH]
· rw [PosNum.cast_bit0, ← two_mul, ← congr_fun Nat.bit_false, Nat.testBit_bit_succ, IH]
end Num
namespace Int
/-- Cast a `SNum` to the corresponding integer. -/
def ofSnum : SNum → ℤ :=
SNum.rec' (fun a => cond a (-1) 0) fun a _p IH => cond a (2 * IH + 1) (2 * IH)
instance snumCoe : Coe SNum ℤ :=
⟨ofSnum⟩
end Int
instance SNum.lt : LT SNum :=
⟨fun a b => (a : ℤ) < b⟩
instance SNum.le : LE SNum :=
⟨fun a b => (a : ℤ) ≤ b⟩
| Mathlib/Data/Num/Lemmas.lean | 1,095 | 1,098 | |
/-
Copyright (c) 2023 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Order.SupClosed
/-!
# Sublattices
This file defines sublattices.
## TODO
Subsemilattices, if people care about them.
## Tags
sublattice
-/
open Function Set
variable {ι : Sort*} (α β γ : Type*) [Lattice α] [Lattice β] [Lattice γ]
/-- A sublattice of a lattice is a set containing the suprema and infima of any of its elements. -/
structure Sublattice where
/-- The underlying set of a sublattice. **Do not use directly**. Instead, use the coercion
`Sublattice α → Set α`, which Lean should automatically insert for you in most cases. -/
carrier : Set α
supClosed' : SupClosed carrier
infClosed' : InfClosed carrier
variable {α β γ}
namespace Sublattice
variable {L M : Sublattice α} {f : LatticeHom α β} {s t : Set α} {a b : α}
instance instSetLike : SetLike (Sublattice α) α where
coe L := L.carrier
coe_injective' L M h := by cases L; congr
/-- See Note [custom simps projection]. -/
def Simps.coe (L : Sublattice α) : Set α := L
initialize_simps_projections Sublattice (carrier → coe, as_prefix coe)
/-- Turn a set closed under supremum and infimum into a sublattice. -/
abbrev ofIsSublattice (s : Set α) (hs : IsSublattice s) : Sublattice α := ⟨s, hs.1, hs.2⟩
lemma coe_inj : (L : Set α) = M ↔ L = M := SetLike.coe_set_eq
@[simp] lemma supClosed (L : Sublattice α) : SupClosed (L : Set α) := L.supClosed'
@[simp] lemma infClosed (L : Sublattice α) : InfClosed (L : Set α) := L.infClosed'
lemma sup_mem (ha : a ∈ L) (hb : b ∈ L) : a ⊔ b ∈ L := L.supClosed ha hb
lemma inf_mem (ha : a ∈ L) (hb : b ∈ L) : a ⊓ b ∈ L := L.infClosed ha hb
@[simp] lemma isSublattice (L : Sublattice α) : IsSublattice (L : Set α) :=
⟨L.supClosed, L.infClosed⟩
@[simp] lemma mem_carrier : a ∈ L.carrier ↔ a ∈ L := Iff.rfl
@[simp] lemma mem_mk (h_sup h_inf) : a ∈ mk s h_sup h_inf ↔ a ∈ s := Iff.rfl
@[simp, norm_cast] lemma coe_mk (h_sup h_inf) : mk s h_sup h_inf = s := rfl
@[simp] lemma mk_le_mk (hs_sup hs_inf ht_sup ht_inf) :
mk s hs_sup hs_inf ≤ mk t ht_sup ht_inf ↔ s ⊆ t := Iff.rfl
@[simp] lemma mk_lt_mk (hs_sup hs_inf ht_sup ht_inf) :
mk s hs_sup hs_inf < mk t ht_sup ht_inf ↔ s ⊂ t := Iff.rfl
/-- Copy of a sublattice with a new `carrier` equal to the old one. Useful to fix definitional
equalities. -/
protected def copy (L : Sublattice α) (s : Set α) (hs : s = L) : Sublattice α where
carrier := s
supClosed' := hs.symm ▸ L.supClosed'
infClosed' := hs.symm ▸ L.infClosed'
@[simp, norm_cast] lemma coe_copy (L : Sublattice α) (s : Set α) (hs) : L.copy s hs = s := rfl
lemma copy_eq (L : Sublattice α) (s : Set α) (hs) : L.copy s hs = L := SetLike.coe_injective hs
/-- Two sublattices are equal if they have the same elements. -/
lemma ext : (∀ a, a ∈ L ↔ a ∈ M) → L = M := SetLike.ext
/-- A sublattice of a lattice inherits a supremum. -/
instance instSupCoe : Max L where
max a b := ⟨a ⊔ b, L.supClosed a.2 b.2⟩
/-- A sublattice of a lattice inherits an infimum. -/
instance instInfCoe : Min L where
min a b := ⟨a ⊓ b, L.infClosed a.2 b.2⟩
@[simp, norm_cast] lemma coe_sup (a b : L) : a ⊔ b = (a : α) ⊔ b := rfl
@[simp, norm_cast] lemma coe_inf (a b : L) : a ⊓ b = (a : α) ⊓ b := rfl
@[simp] lemma mk_sup_mk (a b : α) (ha hb) : (⟨a, ha⟩ ⊔ ⟨b, hb⟩ : L) = ⟨a ⊔ b, L.supClosed ha hb⟩ :=
rfl
@[simp] lemma mk_inf_mk (a b : α) (ha hb) : (⟨a, ha⟩ ⊓ ⟨b, hb⟩ : L) = ⟨a ⊓ b, L.infClosed ha hb⟩ :=
rfl
/-- A sublattice of a lattice inherits a lattice structure. -/
instance instLatticeCoe (L : Sublattice α) : Lattice L :=
Subtype.coe_injective.lattice _ (fun _ _ ↦ rfl) (fun _ _ ↦ rfl)
/-- A sublattice of a distributive lattice inherits a distributive lattice structure. -/
instance instDistribLatticeCoe {α : Type*} [DistribLattice α] (L : Sublattice α) :
DistribLattice L :=
Subtype.coe_injective.distribLattice _ (fun _ _ ↦ rfl) (fun _ _ ↦ rfl)
/-- The natural lattice hom from a sublattice to the original lattice. -/
def subtype (L : Sublattice α) : LatticeHom L α where
toFun := ((↑) : L → α)
map_sup' _ _ := rfl
map_inf' _ _ := rfl
@[simp, norm_cast] lemma coe_subtype (L : Sublattice α) : L.subtype = ((↑) : L → α) := rfl
lemma subtype_apply (L : Sublattice α) (a : L) : L.subtype a = a := rfl
lemma subtype_injective (L : Sublattice α) : Injective <| subtype L := Subtype.coe_injective
/-- The inclusion homomorphism from a sublattice `L` to a bigger sublattice `M`. -/
def inclusion (h : L ≤ M) : LatticeHom L M where
toFun := Set.inclusion h
map_sup' _ _ := rfl
map_inf' _ _ := rfl
@[simp] lemma coe_inclusion (h : L ≤ M) : inclusion h = Set.inclusion h := rfl
lemma inclusion_apply (h : L ≤ M) (a : L) : inclusion h a = Set.inclusion h a := rfl
lemma inclusion_injective (h : L ≤ M) : Injective <| inclusion h := Set.inclusion_injective h
@[simp] lemma inclusion_rfl (L : Sublattice α) : inclusion le_rfl = LatticeHom.id L := rfl
@[simp] lemma subtype_comp_inclusion (h : L ≤ M) : M.subtype.comp (inclusion h) = L.subtype := rfl
/-- The maximum sublattice of a lattice. -/
instance instTop : Top (Sublattice α) where
top.carrier := univ
top.supClosed' := supClosed_univ
top.infClosed' := infClosed_univ
/-- The empty sublattice of a lattice. -/
instance instBot : Bot (Sublattice α) where
bot.carrier := ∅
bot.supClosed' := supClosed_empty
bot.infClosed' := infClosed_empty
/-- The inf of two sublattices is their intersection. -/
instance instInf : Min (Sublattice α) where
min L M := { carrier := L ∩ M
supClosed' := L.supClosed.inter M.supClosed
infClosed' := L.infClosed.inter M.infClosed }
/-- The inf of sublattices is their intersection. -/
instance instInfSet : InfSet (Sublattice α) where
sInf S := { carrier := ⨅ L ∈ S, L
supClosed' := supClosed_sInter <| forall_mem_range.2 fun L ↦ supClosed_sInter <|
forall_mem_range.2 fun _ ↦ L.supClosed
infClosed' := infClosed_sInter <| forall_mem_range.2 fun L ↦ infClosed_sInter <|
forall_mem_range.2 fun _ ↦ L.infClosed }
instance instInhabited : Inhabited (Sublattice α) := ⟨⊥⟩
/-- The top sublattice is isomorphic to the original lattice.
This is the sublattice version of `Equiv.Set.univ α`. -/
def topEquiv : (⊤ : Sublattice α) ≃o α where
toEquiv := Equiv.Set.univ _
map_rel_iff' := Iff.rfl
@[simp, norm_cast] lemma coe_top : (⊤ : Sublattice α) = (univ : Set α) := rfl
@[simp, norm_cast] lemma coe_bot : (⊥ : Sublattice α) = (∅ : Set α) := rfl
@[simp, norm_cast] lemma coe_inf' (L M : Sublattice α) : L ⊓ M = (L : Set α) ∩ M := rfl
@[simp, norm_cast] lemma coe_sInf (S : Set (Sublattice α)) : sInf S = ⋂ L ∈ S, (L : Set α) := rfl
@[simp, norm_cast] lemma coe_iInf (f : ι → Sublattice α) : ⨅ i, f i = ⋂ i, (f i : Set α) := by
simp [iInf]
@[simp, norm_cast] lemma coe_eq_univ : L = (univ : Set α) ↔ L = ⊤ := by rw [← coe_top, coe_inj]
@[simp, norm_cast] lemma coe_eq_empty : L = (∅ : Set α) ↔ L = ⊥ := by rw [← coe_bot, coe_inj]
@[simp] lemma not_mem_bot (a : α) : a ∉ (⊥ : Sublattice α) := id
@[simp] lemma mem_top (a : α) : a ∈ (⊤ : Sublattice α) := mem_univ _
@[simp] lemma mem_inf : a ∈ L ⊓ M ↔ a ∈ L ∧ a ∈ M := Iff.rfl
@[simp] lemma mem_sInf {S : Set (Sublattice α)} : a ∈ sInf S ↔ ∀ L ∈ S, a ∈ L := by
rw [← SetLike.mem_coe]; simp
@[simp] lemma mem_iInf {f : ι → Sublattice α} : a ∈ ⨅ i, f i ↔ ∀ i, a ∈ f i := by
rw [← SetLike.mem_coe]; simp
/-- Sublattices of a lattice form a complete lattice. -/
instance instCompleteLattice : CompleteLattice (Sublattice α) where
bot := ⊥
bot_le := fun _S _a ↦ False.elim
top := ⊤
le_top := fun _S a _ha ↦ mem_top a
inf := (· ⊓ ·)
le_inf := fun _L _M _N hM hN _a ha ↦ ⟨hM ha, hN ha⟩
inf_le_left := fun _L _M _a ↦ And.left
inf_le_right := fun _L _M _a ↦ And.right
__ := completeLatticeOfInf (Sublattice α)
fun _s ↦ IsGLB.of_image SetLike.coe_subset_coe isGLB_biInf
lemma subsingleton_iff : Subsingleton (Sublattice α) ↔ IsEmpty α :=
⟨fun _ ↦ univ_eq_empty_iff.1 <| coe_inj.2 <| Subsingleton.elim ⊤ ⊥,
fun _ ↦ SetLike.coe_injective.subsingleton⟩
instance [IsEmpty α] : Unique (Sublattice α) where
uniq _ := @Subsingleton.elim _ (subsingleton_iff.2 ‹_›) _ _
/-- The preimage of a sublattice along a lattice homomorphism. -/
def comap (f : LatticeHom α β) (L : Sublattice β) : Sublattice α where
carrier := f ⁻¹' L
supClosed' := L.supClosed.preimage _
infClosed' := L.infClosed.preimage _
@[simp, norm_cast] lemma coe_comap (L : Sublattice β) (f : LatticeHom α β) : L.comap f = f ⁻¹' L :=
rfl
@[simp] lemma mem_comap {L : Sublattice β} : a ∈ L.comap f ↔ f a ∈ L := Iff.rfl
lemma comap_mono : Monotone (comap f) := fun _ _ ↦ preimage_mono
@[simp] lemma comap_id (L : Sublattice α) : L.comap (LatticeHom.id _) = L := rfl
@[simp] lemma comap_comap (L : Sublattice γ) (g : LatticeHom β γ) (f : LatticeHom α β) :
(L.comap g).comap f = L.comap (g.comp f) := rfl
/-- The image of a sublattice along a monoid homomorphism is a sublattice. -/
def map (f : LatticeHom α β) (L : Sublattice α) : Sublattice β where
carrier := f '' L
supClosed' := L.supClosed.image f
infClosed' := L.infClosed.image f
@[simp] lemma coe_map (f : LatticeHom α β) (L : Sublattice α) : (L.map f : Set β) = f '' L := rfl
@[simp] lemma mem_map {b : β} : b ∈ L.map f ↔ ∃ a ∈ L, f a = b := Iff.rfl
lemma mem_map_of_mem (f : LatticeHom α β) {a : α} : a ∈ L → f a ∈ L.map f := mem_image_of_mem f
lemma apply_coe_mem_map (f : LatticeHom α β) (a : L) : f a ∈ L.map f := mem_map_of_mem f a.prop
lemma map_mono : Monotone (map f) := fun _ _ ↦ image_subset _
@[simp] lemma map_id : L.map (LatticeHom.id α) = L := SetLike.coe_injective <| image_id _
@[simp] lemma map_map (g : LatticeHom β γ) (f : LatticeHom α β) :
(L.map f).map g = L.map (g.comp f) := SetLike.coe_injective <| image_image _ _ _
lemma mem_map_equiv {f : α ≃o β} {a : β} : a ∈ L.map f ↔ f.symm a ∈ L := Set.mem_image_equiv
lemma apply_mem_map_iff (hf : Injective f) : f a ∈ L.map f ↔ a ∈ L := hf.mem_set_image
lemma map_equiv_eq_comap_symm (f : α ≃o β) (L : Sublattice α) :
L.map f = L.comap (f.symm : LatticeHom β α) :=
| SetLike.coe_injective <| f.toEquiv.image_eq_preimage L
lemma comap_equiv_eq_map_symm (f : β ≃o α) (L : Sublattice α) :
| Mathlib/Order/Sublattice.lean | 247 | 249 |
/-
Copyright (c) 2022 Jake Levinson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jake Levinson
-/
import Mathlib.Data.Finset.Preimage
import Mathlib.Data.Finset.Prod
import Mathlib.Data.SetLike.Basic
import Mathlib.Order.UpperLower.Basic
/-!
# Young diagrams
A Young diagram is a finite set of up-left justified boxes:
```text
□□□□□
□□□
□□□
□
```
This Young diagram corresponds to the [5, 3, 3, 1] partition of 12.
We represent it as a lower set in `ℕ × ℕ` in the product partial order. We write `(i, j) ∈ μ`
to say that `(i, j)` (in matrix coordinates) is in the Young diagram `μ`.
## Main definitions
- `YoungDiagram` : Young diagrams
- `YoungDiagram.card` : the number of cells in a Young diagram (its *cardinality*)
- `YoungDiagram.instDistribLatticeYoungDiagram` : a distributive lattice instance for Young diagrams
ordered by containment, with `(⊥ : YoungDiagram)` the empty diagram.
- `YoungDiagram.row` and `YoungDiagram.rowLen`: rows of a Young diagram and their lengths
- `YoungDiagram.col` and `YoungDiagram.colLen`: columns of a Young diagram and their lengths
## Notation
In "English notation", a Young diagram is drawn so that (i1, j1) ≤ (i2, j2)
means (i1, j1) is weakly up-and-left of (i2, j2). This terminology is used
below, e.g. in `YoungDiagram.up_left_mem`.
## Tags
Young diagram
## References
<https://en.wikipedia.org/wiki/Young_tableau>
-/
open Function
/-- A Young diagram is a finite collection of cells on the `ℕ × ℕ` grid such that whenever
a cell is present, so are all the ones above and to the left of it. Like matrices, an `(i, j)` cell
is a cell in row `i` and column `j`, where rows are enumerated downward and columns rightward.
Young diagrams are modeled as finite sets in `ℕ × ℕ` that are lower sets with respect to the
standard order on products. -/
@[ext]
structure YoungDiagram where
/-- A finite set which represents a finite collection of cells on the `ℕ × ℕ` grid. -/
cells : Finset (ℕ × ℕ)
/-- Cells are up-left justified, witnessed by the fact that `cells` is a lower set in `ℕ × ℕ`. -/
isLowerSet : IsLowerSet (cells : Set (ℕ × ℕ))
namespace YoungDiagram
instance : SetLike YoungDiagram (ℕ × ℕ) where
-- Porting note (https://github.com/leanprover-community/mathlib4/issues/11215): TODO: figure out how to do this correctly
coe y := y.cells
coe_injective' μ ν h := by rwa [YoungDiagram.ext_iff, ← Finset.coe_inj]
@[simp]
theorem mem_cells {μ : YoungDiagram} (c : ℕ × ℕ) : c ∈ μ.cells ↔ c ∈ μ :=
Iff.rfl
@[simp]
theorem mem_mk (c : ℕ × ℕ) (cells) (isLowerSet) :
c ∈ YoungDiagram.mk cells isLowerSet ↔ c ∈ cells :=
Iff.rfl
instance decidableMem (μ : YoungDiagram) : DecidablePred (· ∈ μ) :=
inferInstanceAs (DecidablePred (· ∈ μ.cells))
/-- In "English notation", a Young diagram is drawn so that (i1, j1) ≤ (i2, j2)
means (i1, j1) is weakly up-and-left of (i2, j2). -/
theorem up_left_mem (μ : YoungDiagram) {i1 i2 j1 j2 : ℕ} (hi : i1 ≤ i2) (hj : j1 ≤ j2)
(hcell : (i2, j2) ∈ μ) : (i1, j1) ∈ μ :=
μ.isLowerSet (Prod.mk_le_mk.mpr ⟨hi, hj⟩) hcell
section DistribLattice
@[simp]
theorem cells_subset_iff {μ ν : YoungDiagram} : μ.cells ⊆ ν.cells ↔ μ ≤ ν :=
Iff.rfl
@[simp]
theorem cells_ssubset_iff {μ ν : YoungDiagram} : μ.cells ⊂ ν.cells ↔ μ < ν :=
Iff.rfl
instance : Max YoungDiagram where
max μ ν :=
{ cells := μ.cells ∪ ν.cells
isLowerSet := by
rw [Finset.coe_union]
exact μ.isLowerSet.union ν.isLowerSet }
@[simp]
theorem cells_sup (μ ν : YoungDiagram) : (μ ⊔ ν).cells = μ.cells ∪ ν.cells :=
rfl
@[simp, norm_cast]
theorem coe_sup (μ ν : YoungDiagram) : ↑(μ ⊔ ν) = (μ ∪ ν : Set (ℕ × ℕ)) :=
Finset.coe_union _ _
@[simp]
theorem mem_sup {μ ν : YoungDiagram} {x : ℕ × ℕ} : x ∈ μ ⊔ ν ↔ x ∈ μ ∨ x ∈ ν :=
Finset.mem_union
instance : Min YoungDiagram where
min μ ν :=
{ cells := μ.cells ∩ ν.cells
isLowerSet := by
rw [Finset.coe_inter]
exact μ.isLowerSet.inter ν.isLowerSet }
@[simp]
theorem cells_inf (μ ν : YoungDiagram) : (μ ⊓ ν).cells = μ.cells ∩ ν.cells :=
rfl
@[simp, norm_cast]
theorem coe_inf (μ ν : YoungDiagram) : ↑(μ ⊓ ν) = (μ ∩ ν : Set (ℕ × ℕ)) :=
Finset.coe_inter _ _
@[simp]
theorem mem_inf {μ ν : YoungDiagram} {x : ℕ × ℕ} : x ∈ μ ⊓ ν ↔ x ∈ μ ∧ x ∈ ν :=
Finset.mem_inter
/-- The empty Young diagram is (⊥ : young_diagram). -/
instance : OrderBot YoungDiagram where
bot :=
{ cells := ∅
isLowerSet := by
intros a b _ h
simp only [Finset.coe_empty, Set.mem_empty_iff_false]
simp only [Finset.coe_empty, Set.mem_empty_iff_false] at h }
bot_le _ _ := by
intro y
simp only [mem_mk, Finset.not_mem_empty] at y
@[simp]
theorem cells_bot : (⊥ : YoungDiagram).cells = ∅ :=
rfl
@[simp]
theorem not_mem_bot (x : ℕ × ℕ) : x ∉ (⊥ : YoungDiagram) :=
Finset.not_mem_empty x
@[norm_cast]
theorem coe_bot : (⊥ : YoungDiagram) = (∅ : Set (ℕ × ℕ)) := by
ext; simp
instance : Inhabited YoungDiagram :=
⟨⊥⟩
instance : DistribLattice YoungDiagram :=
Function.Injective.distribLattice YoungDiagram.cells (fun μ ν h => by rwa [YoungDiagram.ext_iff])
(fun _ _ => rfl) fun _ _ => rfl
end DistribLattice
/-- Cardinality of a Young diagram -/
protected abbrev card (μ : YoungDiagram) : ℕ :=
μ.cells.card
section Transpose
/-- The `transpose` of a Young diagram is obtained by swapping i's with j's. -/
def transpose (μ : YoungDiagram) : YoungDiagram where
cells := (Equiv.prodComm _ _).finsetCongr μ.cells
isLowerSet _ _ h := by
simp only [Finset.mem_coe, Equiv.finsetCongr_apply, Finset.mem_map_equiv]
intro hcell
apply μ.isLowerSet _ hcell
simp [h]
@[simp]
theorem mem_transpose {μ : YoungDiagram} {c : ℕ × ℕ} : c ∈ μ.transpose ↔ c.swap ∈ μ := by
simp [transpose]
@[simp]
theorem transpose_transpose (μ : YoungDiagram) : μ.transpose.transpose = μ := by
ext x
simp
theorem transpose_eq_iff_eq_transpose {μ ν : YoungDiagram} : μ.transpose = ν ↔ μ = ν.transpose := by
constructor <;>
· rintro rfl
simp
@[simp]
theorem transpose_eq_iff {μ ν : YoungDiagram} : μ.transpose = ν.transpose ↔ μ = ν := by
rw [transpose_eq_iff_eq_transpose]
simp
-- This is effectively both directions of `transpose_le_iff` below.
protected theorem le_of_transpose_le {μ ν : YoungDiagram} (h_le : μ.transpose ≤ ν) :
μ ≤ ν.transpose := fun c hc => by
simp only [mem_cells, mem_transpose]
apply h_le
simpa
@[simp]
theorem transpose_le_iff {μ ν : YoungDiagram} : μ.transpose ≤ ν.transpose ↔ μ ≤ ν :=
⟨fun h => by
convert YoungDiagram.le_of_transpose_le h
simp, fun h => by
rw [← transpose_transpose μ] at h
exact YoungDiagram.le_of_transpose_le h ⟩
@[mono]
protected theorem transpose_mono {μ ν : YoungDiagram} (h_le : μ ≤ ν) : μ.transpose ≤ ν.transpose :=
transpose_le_iff.mpr h_le
/-- Transposing Young diagrams is an `OrderIso`. -/
@[simps]
def transposeOrderIso : YoungDiagram ≃o YoungDiagram :=
⟨⟨transpose, transpose, fun _ => by simp, fun _ => by simp⟩, by simp⟩
|
end Transpose
| Mathlib/Combinatorics/Young/YoungDiagram.lean | 231 | 233 |
/-
Copyright (c) 2023 Dagur Asgeirsson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Dagur Asgeirsson
-/
import Mathlib.Topology.Category.Profinite.Nobeling.Basic
import Mathlib.Topology.Category.Profinite.Nobeling.Induction
import Mathlib.Topology.Category.Profinite.Nobeling.Span
import Mathlib.Topology.Category.Profinite.Nobeling.Successor
import Mathlib.Topology.Category.Profinite.Nobeling.ZeroLimit
deprecated_module (since := "2025-04-13")
| Mathlib/Topology/Category/Profinite/Nobeling.lean | 506 | 515 | |
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Sophie Morel, Yury Kudryashov
-/
import Mathlib.Analysis.NormedSpace.OperatorNorm.NormedSpace
import Mathlib.Logic.Embedding.Basic
import Mathlib.Data.Fintype.CardEmbedding
import Mathlib.Topology.Algebra.Module.Multilinear.Topology
/-!
# Operator norm on the space of continuous multilinear maps
When `f` is a continuous multilinear map in finitely many variables, we define its norm `‖f‖` as the
smallest number such that `‖f m‖ ≤ ‖f‖ * ∏ i, ‖m i‖` for all `m`.
We show that it is indeed a norm, and prove its basic properties.
## Main results
Let `f` be a multilinear map in finitely many variables.
* `exists_bound_of_continuous` asserts that, if `f` is continuous, then there exists `C > 0`
with `‖f m‖ ≤ C * ∏ i, ‖m i‖` for all `m`.
* `continuous_of_bound`, conversely, asserts that this bound implies continuity.
* `mkContinuous` constructs the associated continuous multilinear map.
Let `f` be a continuous multilinear map in finitely many variables.
* `‖f‖` is its norm, i.e., the smallest number such that `‖f m‖ ≤ ‖f‖ * ∏ i, ‖m i‖` for
all `m`.
* `le_opNorm f m` asserts the fundamental inequality `‖f m‖ ≤ ‖f‖ * ∏ i, ‖m i‖`.
* `norm_image_sub_le f m₁ m₂` gives a control of the difference `f m₁ - f m₂` in terms of
`‖f‖` and `‖m₁ - m₂‖`.
## Implementation notes
We mostly follow the API (and the proofs) of `OperatorNorm.lean`, with the additional complexity
that we should deal with multilinear maps in several variables.
From the mathematical point of view, all the results follow from the results on operator norm in
one variable, by applying them to one variable after the other through currying. However, this
is only well defined when there is an order on the variables (for instance on `Fin n`) although
the final result is independent of the order. While everything could be done following this
approach, it turns out that direct proofs are easier and more efficient.
-/
suppress_compilation
noncomputable section
open scoped NNReal Topology Uniformity
open Finset Metric Function Filter
/-!
### Type variables
We use the following type variables in this file:
* `𝕜` : a `NontriviallyNormedField`;
* `ι`, `ι'` : finite index types with decidable equality;
* `E`, `E₁` : families of normed vector spaces over `𝕜` indexed by `i : ι`;
* `E'` : a family of normed vector spaces over `𝕜` indexed by `i' : ι'`;
* `Ei` : a family of normed vector spaces over `𝕜` indexed by `i : Fin (Nat.succ n)`;
* `G`, `G'` : normed vector spaces over `𝕜`.
-/
universe u v v' wE wE₁ wE' wG wG'
section continuous_eval
variable {𝕜 ι : Type*} {E : ι → Type*} {F : Type*}
[NormedField 𝕜] [Finite ι] [∀ i, SeminormedAddCommGroup (E i)] [∀ i, NormedSpace 𝕜 (E i)]
[TopologicalSpace F] [AddCommGroup F] [IsTopologicalAddGroup F] [Module 𝕜 F]
instance ContinuousMultilinearMap.instContinuousEval :
ContinuousEval (ContinuousMultilinearMap 𝕜 E F) (Π i, E i) F where
continuous_eval := by
cases nonempty_fintype ι
let _ := IsTopologicalAddGroup.toUniformSpace F
have := isUniformAddGroup_of_addCommGroup (G := F)
refine (UniformOnFun.continuousOn_eval₂ fun m ↦ ?_).comp_continuous
(isEmbedding_toUniformOnFun.continuous.prodMap continuous_id) fun (f, x) ↦ f.cont.continuousAt
exact ⟨ball m 1, NormedSpace.isVonNBounded_of_isBounded _ isBounded_ball,
ball_mem_nhds _ one_pos⟩
namespace ContinuousLinearMap
variable {G : Type*} [AddCommGroup G] [TopologicalSpace G] [Module 𝕜 G] [ContinuousConstSMul 𝕜 F]
lemma continuous_uncurry_of_multilinear (f : G →L[𝕜] ContinuousMultilinearMap 𝕜 E F) :
Continuous (fun (p : G × (Π i, E i)) ↦ f p.1 p.2) := by
fun_prop
lemma continuousOn_uncurry_of_multilinear (f : G →L[𝕜] ContinuousMultilinearMap 𝕜 E F) {s} :
ContinuousOn (fun (p : G × (Π i, E i)) ↦ f p.1 p.2) s :=
f.continuous_uncurry_of_multilinear.continuousOn
lemma continuousAt_uncurry_of_multilinear (f : G →L[𝕜] ContinuousMultilinearMap 𝕜 E F) {x} :
ContinuousAt (fun (p : G × (Π i, E i)) ↦ f p.1 p.2) x :=
f.continuous_uncurry_of_multilinear.continuousAt
lemma continuousWithinAt_uncurry_of_multilinear (f : G →L[𝕜] ContinuousMultilinearMap 𝕜 E F) {s x} :
ContinuousWithinAt (fun (p : G × (Π i, E i)) ↦ f p.1 p.2) s x :=
f.continuous_uncurry_of_multilinear.continuousWithinAt
end ContinuousLinearMap
end continuous_eval
section Seminorm
variable {𝕜 : Type u} {ι : Type v} {ι' : Type v'} {E : ι → Type wE} {E₁ : ι → Type wE₁}
{E' : ι' → Type wE'} {G : Type wG} {G' : Type wG'}
[Fintype ι'] [NontriviallyNormedField 𝕜] [∀ i, SeminormedAddCommGroup (E i)]
[∀ i, NormedSpace 𝕜 (E i)] [∀ i, SeminormedAddCommGroup (E₁ i)] [∀ i, NormedSpace 𝕜 (E₁ i)]
[SeminormedAddCommGroup G] [NormedSpace 𝕜 G] [SeminormedAddCommGroup G'] [NormedSpace 𝕜 G']
/-!
### Continuity properties of multilinear maps
We relate continuity of multilinear maps to the inequality `‖f m‖ ≤ C * ∏ i, ‖m i‖`, in
both directions. Along the way, we prove useful bounds on the difference `‖f m₁ - f m₂‖`.
-/
namespace MultilinearMap
/-- If `f` is a continuous multilinear map on `E`
and `m` is an element of `∀ i, E i` such that one of the `m i` has norm `0`,
then `f m` has norm `0`.
Note that we cannot drop the continuity assumption because `f (m : Unit → E) = f (m ())`,
where the domain has zero norm and the codomain has a nonzero norm
does not satisfy this condition. -/
lemma norm_map_coord_zero (f : MultilinearMap 𝕜 E G) (hf : Continuous f)
{m : ∀ i, E i} {i : ι} (hi : ‖m i‖ = 0) : ‖f m‖ = 0 := by
classical
rw [← inseparable_zero_iff_norm] at hi ⊢
have : Inseparable (update m i 0) m := inseparable_pi.2 <|
(forall_update_iff m fun i a ↦ Inseparable a (m i)).2 ⟨hi.symm, fun _ _ ↦ rfl⟩
simpa only [map_update_zero] using this.symm.map hf
variable [Fintype ι]
/-- If a multilinear map in finitely many variables on seminormed spaces
sends vectors with a component of norm zero to vectors of norm zero
and satisfies the inequality `‖f m‖ ≤ C * ∏ i, ‖m i‖` on a shell `ε i / ‖c i‖ < ‖m i‖ < ε i`
for some positive numbers `ε i` and elements `c i : 𝕜`, `1 < ‖c i‖`,
then it satisfies this inequality for all `m`.
The first assumption is automatically satisfied on normed spaces, see `bound_of_shell` below.
For seminormed spaces, it follows from continuity of `f`, see next lemma,
see `bound_of_shell_of_continuous` below. -/
theorem bound_of_shell_of_norm_map_coord_zero (f : MultilinearMap 𝕜 E G)
(hf₀ : ∀ {m i}, ‖m i‖ = 0 → ‖f m‖ = 0)
{ε : ι → ℝ} {C : ℝ} (hε : ∀ i, 0 < ε i) {c : ι → 𝕜} (hc : ∀ i, 1 < ‖c i‖)
(hf : ∀ m : ∀ i, E i, (∀ i, ε i / ‖c i‖ ≤ ‖m i‖) → (∀ i, ‖m i‖ < ε i) → ‖f m‖ ≤ C * ∏ i, ‖m i‖)
(m : ∀ i, E i) : ‖f m‖ ≤ C * ∏ i, ‖m i‖ := by
rcases em (∃ i, ‖m i‖ = 0) with (⟨i, hi⟩ | hm)
· rw [hf₀ hi, prod_eq_zero (mem_univ i) hi, mul_zero]
push_neg at hm
choose δ hδ0 hδm_lt hle_δm _ using fun i => rescale_to_shell_semi_normed (hc i) (hε i) (hm i)
have hδ0 : 0 < ∏ i, ‖δ i‖ := prod_pos fun i _ => norm_pos_iff.2 (hδ0 i)
simpa [map_smul_univ, norm_smul, prod_mul_distrib, mul_left_comm C, mul_le_mul_left hδ0] using
hf (fun i => δ i • m i) hle_δm hδm_lt
/-- If a continuous multilinear map in finitely many variables on normed spaces satisfies
the inequality `‖f m‖ ≤ C * ∏ i, ‖m i‖` on a shell `ε i / ‖c i‖ < ‖m i‖ < ε i` for some positive
numbers `ε i` and elements `c i : 𝕜`, `1 < ‖c i‖`, then it satisfies this inequality for all `m`. -/
theorem bound_of_shell_of_continuous (f : MultilinearMap 𝕜 E G) (hfc : Continuous f)
{ε : ι → ℝ} {C : ℝ} (hε : ∀ i, 0 < ε i) {c : ι → 𝕜} (hc : ∀ i, 1 < ‖c i‖)
(hf : ∀ m : ∀ i, E i, (∀ i, ε i / ‖c i‖ ≤ ‖m i‖) → (∀ i, ‖m i‖ < ε i) → ‖f m‖ ≤ C * ∏ i, ‖m i‖)
(m : ∀ i, E i) : ‖f m‖ ≤ C * ∏ i, ‖m i‖ :=
bound_of_shell_of_norm_map_coord_zero f (norm_map_coord_zero f hfc) hε hc hf m
/-- If a multilinear map in finitely many variables on normed spaces is continuous, then it
satisfies the inequality `‖f m‖ ≤ C * ∏ i, ‖m i‖`, for some `C` which can be chosen to be
positive. -/
theorem exists_bound_of_continuous (f : MultilinearMap 𝕜 E G) (hf : Continuous f) :
∃ C : ℝ, 0 < C ∧ ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖ := by
cases isEmpty_or_nonempty ι
· refine ⟨‖f 0‖ + 1, add_pos_of_nonneg_of_pos (norm_nonneg _) zero_lt_one, fun m => ?_⟩
obtain rfl : m = 0 := funext (IsEmpty.elim ‹_›)
simp [univ_eq_empty, zero_le_one]
obtain ⟨ε : ℝ, ε0 : 0 < ε, hε : ∀ m : ∀ i, E i, ‖m - 0‖ < ε → ‖f m - f 0‖ < 1⟩ :=
NormedAddCommGroup.tendsto_nhds_nhds.1 (hf.tendsto 0) 1 zero_lt_one
simp only [sub_zero, f.map_zero] at hε
rcases NormedField.exists_one_lt_norm 𝕜 with ⟨c, hc⟩
have : 0 < (‖c‖ / ε) ^ Fintype.card ι := pow_pos (div_pos (zero_lt_one.trans hc) ε0) _
refine ⟨_, this, ?_⟩
refine f.bound_of_shell_of_continuous hf (fun _ => ε0) (fun _ => hc) fun m hcm hm => ?_
refine (hε m ((pi_norm_lt_iff ε0).2 hm)).le.trans ?_
rw [← div_le_iff₀' this, one_div, ← inv_pow, inv_div, Fintype.card, ← prod_const]
exact prod_le_prod (fun _ _ => div_nonneg ε0.le (norm_nonneg _)) fun i _ => hcm i
/-- If a multilinear map `f` satisfies a boundedness property around `0`,
one can deduce a bound on `f m₁ - f m₂` using the multilinearity.
Here, we give a precise but hard to use version.
See `norm_image_sub_le_of_bound` for a less precise but more usable version.
The bound reads
`‖f m - f m'‖ ≤
C * ‖m 1 - m' 1‖ * max ‖m 2‖ ‖m' 2‖ * max ‖m 3‖ ‖m' 3‖ * ... * max ‖m n‖ ‖m' n‖ + ...`,
where the other terms in the sum are the same products where `1` is replaced by any `i`. -/
theorem norm_image_sub_le_of_bound' [DecidableEq ι] (f : MultilinearMap 𝕜 E G) {C : ℝ} (hC : 0 ≤ C)
(H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖) (m₁ m₂ : ∀ i, E i) :
‖f m₁ - f m₂‖ ≤ C * ∑ i, ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ := by
have A :
∀ s : Finset ι,
‖f m₁ - f (s.piecewise m₂ m₁)‖ ≤
C * ∑ i ∈ s, ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ := by
intro s
induction' s using Finset.induction with i s his Hrec
· simp
have I :
‖f (s.piecewise m₂ m₁) - f ((insert i s).piecewise m₂ m₁)‖ ≤
C * ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ := by
have A : (insert i s).piecewise m₂ m₁ = Function.update (s.piecewise m₂ m₁) i (m₂ i) :=
s.piecewise_insert _ _ _
have B : s.piecewise m₂ m₁ = Function.update (s.piecewise m₂ m₁) i (m₁ i) := by
simp [eq_update_iff, his]
rw [B, A, ← f.map_update_sub]
apply le_trans (H _)
gcongr with j
by_cases h : j = i
· rw [h]
simp
· by_cases h' : j ∈ s <;> simp [h', h, le_refl]
calc
‖f m₁ - f ((insert i s).piecewise m₂ m₁)‖ ≤
‖f m₁ - f (s.piecewise m₂ m₁)‖ +
‖f (s.piecewise m₂ m₁) - f ((insert i s).piecewise m₂ m₁)‖ := by
rw [← dist_eq_norm, ← dist_eq_norm, ← dist_eq_norm]
exact dist_triangle _ _ _
_ ≤ (C * ∑ i ∈ s, ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖) +
C * ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ :=
(add_le_add Hrec I)
_ = C * ∑ i ∈ insert i s, ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ := by
simp [his, add_comm, left_distrib]
convert A univ
simp
/-- If `f` satisfies a boundedness property around `0`, one can deduce a bound on `f m₁ - f m₂`
using the multilinearity. Here, we give a usable but not very precise version. See
`norm_image_sub_le_of_bound'` for a more precise but less usable version. The bound is
`‖f m - f m'‖ ≤ C * card ι * ‖m - m'‖ * (max ‖m‖ ‖m'‖) ^ (card ι - 1)`. -/
theorem norm_image_sub_le_of_bound (f : MultilinearMap 𝕜 E G)
{C : ℝ} (hC : 0 ≤ C) (H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖) (m₁ m₂ : ∀ i, E i) :
‖f m₁ - f m₂‖ ≤ C * Fintype.card ι * max ‖m₁‖ ‖m₂‖ ^ (Fintype.card ι - 1) * ‖m₁ - m₂‖ := by
classical
have A :
∀ i : ι,
∏ j, (if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖) ≤
‖m₁ - m₂‖ * max ‖m₁‖ ‖m₂‖ ^ (Fintype.card ι - 1) := by
intro i
calc
∏ j, (if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖) ≤
∏ j : ι, Function.update (fun _ => max ‖m₁‖ ‖m₂‖) i ‖m₁ - m₂‖ j := by
apply Finset.prod_le_prod
· intro j _
by_cases h : j = i <;> simp [h, norm_nonneg]
· intro j _
by_cases h : j = i
· rw [h]
simp only [ite_true, Function.update_self]
exact norm_le_pi_norm (m₁ - m₂) i
· simp [h, - le_sup_iff, - sup_le_iff, sup_le_sup, norm_le_pi_norm]
_ = ‖m₁ - m₂‖ * max ‖m₁‖ ‖m₂‖ ^ (Fintype.card ι - 1) := by
rw [prod_update_of_mem (Finset.mem_univ _)]
simp [card_univ_diff]
calc
‖f m₁ - f m₂‖ ≤ C * ∑ i, ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ :=
f.norm_image_sub_le_of_bound' hC H m₁ m₂
_ ≤ C * ∑ _i, ‖m₁ - m₂‖ * max ‖m₁‖ ‖m₂‖ ^ (Fintype.card ι - 1) := by gcongr; apply A
_ = C * Fintype.card ι * max ‖m₁‖ ‖m₂‖ ^ (Fintype.card ι - 1) * ‖m₁ - m₂‖ := by
rw [sum_const, card_univ, nsmul_eq_mul]
ring
/-- If a multilinear map satisfies an inequality `‖f m‖ ≤ C * ∏ i, ‖m i‖`, then it is
continuous. -/
theorem continuous_of_bound (f : MultilinearMap 𝕜 E G) (C : ℝ) (H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖) :
Continuous f := by
let D := max C 1
have D_pos : 0 ≤ D := le_trans zero_le_one (le_max_right _ _)
replace H (m) : ‖f m‖ ≤ D * ∏ i, ‖m i‖ :=
(H m).trans (mul_le_mul_of_nonneg_right (le_max_left _ _) <| by positivity)
refine continuous_iff_continuousAt.2 fun m => ?_
refine
continuousAt_of_locally_lipschitz zero_lt_one
(D * Fintype.card ι * (‖m‖ + 1) ^ (Fintype.card ι - 1)) fun m' h' => ?_
rw [dist_eq_norm, dist_eq_norm]
have : max ‖m'‖ ‖m‖ ≤ ‖m‖ + 1 := by
simp [zero_le_one, norm_le_of_mem_closedBall (le_of_lt h')]
calc
‖f m' - f m‖ ≤ D * Fintype.card ι * max ‖m'‖ ‖m‖ ^ (Fintype.card ι - 1) * ‖m' - m‖ :=
f.norm_image_sub_le_of_bound D_pos H m' m
_ ≤ D * Fintype.card ι * (‖m‖ + 1) ^ (Fintype.card ι - 1) * ‖m' - m‖ := by gcongr
/-- Constructing a continuous multilinear map from a multilinear map satisfying a boundedness
condition. -/
def mkContinuous (f : MultilinearMap 𝕜 E G) (C : ℝ) (H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖) :
ContinuousMultilinearMap 𝕜 E G :=
{ f with cont := f.continuous_of_bound C H }
@[simp]
theorem coe_mkContinuous (f : MultilinearMap 𝕜 E G) (C : ℝ) (H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖) :
⇑(f.mkContinuous C H) = f :=
rfl
/-- Given a multilinear map in `n` variables, if one restricts it to `k` variables putting `z` on
the other coordinates, then the resulting restricted function satisfies an inequality
`‖f.restr v‖ ≤ C * ‖z‖^(n-k) * Π ‖v i‖` if the original function satisfies `‖f v‖ ≤ C * Π ‖v i‖`. -/
theorem restr_norm_le {k n : ℕ} (f : MultilinearMap 𝕜 (fun _ : Fin n => G) G')
(s : Finset (Fin n)) (hk : #s = k) (z : G) {C : ℝ} (H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖)
(v : Fin k → G) : ‖f.restr s hk z v‖ ≤ C * ‖z‖ ^ (n - k) * ∏ i, ‖v i‖ := by
rw [mul_right_comm, mul_assoc]
convert H _ using 2
simp only [apply_dite norm, Fintype.prod_dite, prod_const ‖z‖, Finset.card_univ,
Fintype.card_of_subtype sᶜ fun _ => mem_compl, card_compl, Fintype.card_fin, hk, mk_coe, ←
(s.orderIsoOfFin hk).symm.bijective.prod_comp fun x => ‖v x‖]
convert rfl
end MultilinearMap
/-!
### Continuous multilinear maps
We define the norm `‖f‖` of a continuous multilinear map `f` in finitely many variables as the
smallest number such that `‖f m‖ ≤ ‖f‖ * ∏ i, ‖m i‖` for all `m`. We show that this
defines a normed space structure on `ContinuousMultilinearMap 𝕜 E G`.
-/
namespace ContinuousMultilinearMap
variable [Fintype ι]
theorem bound (f : ContinuousMultilinearMap 𝕜 E G) :
∃ C : ℝ, 0 < C ∧ ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖ :=
f.toMultilinearMap.exists_bound_of_continuous f.2
open Real
/-- The operator norm of a continuous multilinear map is the inf of all its bounds. -/
def opNorm (f : ContinuousMultilinearMap 𝕜 E G) : ℝ :=
sInf { c | 0 ≤ (c : ℝ) ∧ ∀ m, ‖f m‖ ≤ c * ∏ i, ‖m i‖ }
instance hasOpNorm : Norm (ContinuousMultilinearMap 𝕜 E G) :=
⟨opNorm⟩
/-- An alias of `ContinuousMultilinearMap.hasOpNorm` with non-dependent types to help typeclass
search. -/
instance hasOpNorm' : Norm (ContinuousMultilinearMap 𝕜 (fun _ : ι => G) G') :=
ContinuousMultilinearMap.hasOpNorm
theorem norm_def (f : ContinuousMultilinearMap 𝕜 E G) :
‖f‖ = sInf { c | 0 ≤ (c : ℝ) ∧ ∀ m, ‖f m‖ ≤ c * ∏ i, ‖m i‖ } :=
rfl
-- So that invocations of `le_csInf` make sense: we show that the set of
-- bounds is nonempty and bounded below.
theorem bounds_nonempty {f : ContinuousMultilinearMap 𝕜 E G} :
∃ c, c ∈ { c | 0 ≤ c ∧ ∀ m, ‖f m‖ ≤ c * ∏ i, ‖m i‖ } :=
let ⟨M, hMp, hMb⟩ := f.bound
⟨M, le_of_lt hMp, hMb⟩
theorem bounds_bddBelow {f : ContinuousMultilinearMap 𝕜 E G} :
BddBelow { c | 0 ≤ c ∧ ∀ m, ‖f m‖ ≤ c * ∏ i, ‖m i‖ } :=
⟨0, fun _ ⟨hn, _⟩ => hn⟩
theorem isLeast_opNorm (f : ContinuousMultilinearMap 𝕜 E G) :
IsLeast {c : ℝ | 0 ≤ c ∧ ∀ m, ‖f m‖ ≤ c * ∏ i, ‖m i‖} ‖f‖ := by
refine IsClosed.isLeast_csInf ?_ bounds_nonempty bounds_bddBelow
simp only [Set.setOf_and, Set.setOf_forall]
exact isClosed_Ici.inter (isClosed_iInter fun m ↦
isClosed_le continuous_const (continuous_id.mul continuous_const))
theorem opNorm_nonneg (f : ContinuousMultilinearMap 𝕜 E G) : 0 ≤ ‖f‖ :=
Real.sInf_nonneg fun _ ⟨hx, _⟩ => hx
/-- The fundamental property of the operator norm of a continuous multilinear map:
`‖f m‖` is bounded by `‖f‖` times the product of the `‖m i‖`. -/
theorem le_opNorm (f : ContinuousMultilinearMap 𝕜 E G) (m : ∀ i, E i) :
‖f m‖ ≤ ‖f‖ * ∏ i, ‖m i‖ :=
f.isLeast_opNorm.1.2 m
theorem le_mul_prod_of_opNorm_le_of_le {f : ContinuousMultilinearMap 𝕜 E G}
{m : ∀ i, E i} {C : ℝ} {b : ι → ℝ} (hC : ‖f‖ ≤ C) (hm : ∀ i, ‖m i‖ ≤ b i) :
‖f m‖ ≤ C * ∏ i, b i :=
(f.le_opNorm m).trans <| by gcongr; exacts [f.opNorm_nonneg.trans hC, hm _]
@[deprecated (since := "2024-11-27")]
alias le_mul_prod_of_le_opNorm_of_le := le_mul_prod_of_opNorm_le_of_le
theorem le_opNorm_mul_prod_of_le (f : ContinuousMultilinearMap 𝕜 E G)
{m : ∀ i, E i} {b : ι → ℝ} (hm : ∀ i, ‖m i‖ ≤ b i) : ‖f m‖ ≤ ‖f‖ * ∏ i, b i :=
le_mul_prod_of_opNorm_le_of_le le_rfl hm
theorem le_opNorm_mul_pow_card_of_le (f : ContinuousMultilinearMap 𝕜 E G) {m b} (hm : ‖m‖ ≤ b) :
‖f m‖ ≤ ‖f‖ * b ^ Fintype.card ι := by
simpa only [prod_const] using f.le_opNorm_mul_prod_of_le fun i => (norm_le_pi_norm m i).trans hm
theorem le_opNorm_mul_pow_of_le {n : ℕ} {Ei : Fin n → Type*} [∀ i, SeminormedAddCommGroup (Ei i)]
[∀ i, NormedSpace 𝕜 (Ei i)] (f : ContinuousMultilinearMap 𝕜 Ei G) {m : ∀ i, Ei i} {b : ℝ}
(hm : ‖m‖ ≤ b) : ‖f m‖ ≤ ‖f‖ * b ^ n := by
simpa only [Fintype.card_fin] using f.le_opNorm_mul_pow_card_of_le hm
theorem le_of_opNorm_le {f : ContinuousMultilinearMap 𝕜 E G} {C : ℝ} (h : ‖f‖ ≤ C) (m : ∀ i, E i) :
‖f m‖ ≤ C * ∏ i, ‖m i‖ :=
le_mul_prod_of_opNorm_le_of_le h fun _ ↦ le_rfl
theorem ratio_le_opNorm (f : ContinuousMultilinearMap 𝕜 E G) (m : ∀ i, E i) :
(‖f m‖ / ∏ i, ‖m i‖) ≤ ‖f‖ :=
div_le_of_le_mul₀ (by positivity) (opNorm_nonneg _) (f.le_opNorm m)
/-- The image of the unit ball under a continuous multilinear map is bounded. -/
theorem unit_le_opNorm (f : ContinuousMultilinearMap 𝕜 E G) {m : ∀ i, E i} (h : ‖m‖ ≤ 1) :
‖f m‖ ≤ ‖f‖ :=
(le_opNorm_mul_pow_card_of_le f h).trans <| by simp
/-- If one controls the norm of every `f x`, then one controls the norm of `f`. -/
theorem opNorm_le_bound {f : ContinuousMultilinearMap 𝕜 E G}
{M : ℝ} (hMp : 0 ≤ M) (hM : ∀ m, ‖f m‖ ≤ M * ∏ i, ‖m i‖) : ‖f‖ ≤ M :=
csInf_le bounds_bddBelow ⟨hMp, hM⟩
theorem opNorm_le_iff {f : ContinuousMultilinearMap 𝕜 E G} {C : ℝ} (hC : 0 ≤ C) :
‖f‖ ≤ C ↔ ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖ :=
⟨fun h _ ↦ le_of_opNorm_le h _, opNorm_le_bound hC⟩
/-- The operator norm satisfies the triangle inequality. -/
theorem opNorm_add_le (f g : ContinuousMultilinearMap 𝕜 E G) : ‖f + g‖ ≤ ‖f‖ + ‖g‖ :=
opNorm_le_bound (add_nonneg (opNorm_nonneg f) (opNorm_nonneg g)) fun x => by
rw [add_mul]
exact norm_add_le_of_le (le_opNorm _ _) (le_opNorm _ _)
theorem opNorm_zero : ‖(0 : ContinuousMultilinearMap 𝕜 E G)‖ = 0 :=
(opNorm_nonneg _).antisymm' <| opNorm_le_bound le_rfl fun m => by simp
section
variable {𝕜' : Type*} [NormedField 𝕜'] [NormedSpace 𝕜' G] [SMulCommClass 𝕜 𝕜' G]
theorem opNorm_smul_le (c : 𝕜') (f : ContinuousMultilinearMap 𝕜 E G) : ‖c • f‖ ≤ ‖c‖ * ‖f‖ :=
(c • f).opNorm_le_bound (mul_nonneg (norm_nonneg _) (opNorm_nonneg _)) fun m ↦ by
rw [smul_apply, norm_smul, mul_assoc]
exact mul_le_mul_of_nonneg_left (le_opNorm _ _) (norm_nonneg _)
variable (𝕜 E G) in
/-- Operator seminorm on the space of continuous multilinear maps, as `Seminorm`.
We use this seminorm
to define a `SeminormedAddCommGroup` structure on `ContinuousMultilinearMap 𝕜 E G`,
but we have to override the projection `UniformSpace`
so that it is definitionally equal to the one coming from the topologies on `E` and `G`. -/
protected def seminorm : Seminorm 𝕜 (ContinuousMultilinearMap 𝕜 E G) :=
.ofSMulLE norm opNorm_zero opNorm_add_le fun c f ↦ f.opNorm_smul_le c
private lemma uniformity_eq_seminorm :
𝓤 (ContinuousMultilinearMap 𝕜 E G) = ⨅ r > 0, 𝓟 {f | ‖f.1 - f.2‖ < r} := by
refine (ContinuousMultilinearMap.seminorm 𝕜 E G).uniformity_eq_of_hasBasis
(ContinuousMultilinearMap.hasBasis_nhds_zero_of_basis Metric.nhds_basis_closedBall)
?_ fun (s, r) ⟨hs, hr⟩ ↦ ?_
· rcases NormedField.exists_lt_norm 𝕜 1 with ⟨c, hc⟩
have hc₀ : 0 < ‖c‖ := one_pos.trans hc
simp only [hasBasis_nhds_zero.mem_iff, Prod.exists]
use 1, closedBall 0 ‖c‖, closedBall 0 1
suffices ∀ f : ContinuousMultilinearMap 𝕜 E G, (∀ x, ‖x‖ ≤ ‖c‖ → ‖f x‖ ≤ 1) → ‖f‖ ≤ 1 by
simpa [NormedSpace.isVonNBounded_closedBall, closedBall_mem_nhds, Set.subset_def, Set.MapsTo]
intro f hf
refine opNorm_le_bound (by positivity) <|
f.1.bound_of_shell_of_continuous f.2 (fun _ ↦ hc₀) (fun _ ↦ hc) fun x hcx hx ↦ ?_
calc
‖f x‖ ≤ 1 := hf _ <| (pi_norm_le_iff_of_nonneg (norm_nonneg c)).2 fun i ↦ (hx i).le
_ = ∏ i : ι, 1 := by simp
_ ≤ ∏ i, ‖x i‖ := Finset.prod_le_prod (fun _ _ ↦ zero_le_one) fun i _ ↦ by
simpa only [div_self hc₀.ne'] using hcx i
_ = 1 * ∏ i, ‖x i‖ := (one_mul _).symm
· rcases (NormedSpace.isVonNBounded_iff' _).1 hs with ⟨ε, hε⟩
rcases exists_pos_mul_lt hr (ε ^ Fintype.card ι) with ⟨δ, hδ₀, hδ⟩
refine ⟨δ, hδ₀, fun f hf x hx ↦ ?_⟩
simp only [Seminorm.mem_ball_zero, mem_closedBall_zero_iff] at hf ⊢
replace hf : ‖f‖ ≤ δ := hf.le
replace hx : ‖x‖ ≤ ε := hε x hx
calc
‖f x‖ ≤ ‖f‖ * ε ^ Fintype.card ι := le_opNorm_mul_pow_card_of_le f hx
_ ≤ δ * ε ^ Fintype.card ι := by have := (norm_nonneg x).trans hx; gcongr
_ ≤ r := (mul_comm _ _).trans_le hδ.le
instance instPseudoMetricSpace : PseudoMetricSpace (ContinuousMultilinearMap 𝕜 E G) :=
.replaceUniformity
(ContinuousMultilinearMap.seminorm 𝕜 E G).toSeminormedAddCommGroup.toPseudoMetricSpace
uniformity_eq_seminorm
/-- Continuous multilinear maps themselves form a seminormed space with respect to
the operator norm. -/
instance seminormedAddCommGroup :
SeminormedAddCommGroup (ContinuousMultilinearMap 𝕜 E G) := ⟨fun _ _ ↦ rfl⟩
/-- An alias of `ContinuousMultilinearMap.seminormedAddCommGroup` with non-dependent types to help
typeclass search. -/
instance seminormedAddCommGroup' :
SeminormedAddCommGroup (ContinuousMultilinearMap 𝕜 (fun _ : ι => G) G') :=
ContinuousMultilinearMap.seminormedAddCommGroup
instance normedSpace : NormedSpace 𝕜' (ContinuousMultilinearMap 𝕜 E G) :=
⟨fun c f => f.opNorm_smul_le c⟩
/-- An alias of `ContinuousMultilinearMap.normedSpace` with non-dependent types to help typeclass
search. -/
instance normedSpace' : NormedSpace 𝕜' (ContinuousMultilinearMap 𝕜 (fun _ : ι => G') G) :=
ContinuousMultilinearMap.normedSpace
@[deprecated norm_neg (since := "2024-11-24")]
theorem opNorm_neg (f : ContinuousMultilinearMap 𝕜 E G) : ‖-f‖ = ‖f‖ := norm_neg f
/-- The fundamental property of the operator norm of a continuous multilinear map:
`‖f m‖` is bounded by `‖f‖` times the product of the `‖m i‖`, `nnnorm` version. -/
theorem le_opNNNorm (f : ContinuousMultilinearMap 𝕜 E G) (m : ∀ i, E i) :
‖f m‖₊ ≤ ‖f‖₊ * ∏ i, ‖m i‖₊ :=
NNReal.coe_le_coe.1 <| by
push_cast
exact f.le_opNorm m
theorem le_of_opNNNorm_le (f : ContinuousMultilinearMap 𝕜 E G)
{C : ℝ≥0} (h : ‖f‖₊ ≤ C) (m : ∀ i, E i) : ‖f m‖₊ ≤ C * ∏ i, ‖m i‖₊ :=
(f.le_opNNNorm m).trans <| mul_le_mul' h le_rfl
theorem opNNNorm_le_iff {f : ContinuousMultilinearMap 𝕜 E G} {C : ℝ≥0} :
‖f‖₊ ≤ C ↔ ∀ m, ‖f m‖₊ ≤ C * ∏ i, ‖m i‖₊ := by
simp only [← NNReal.coe_le_coe]; simp [opNorm_le_iff C.coe_nonneg, NNReal.coe_prod]
theorem isLeast_opNNNorm (f : ContinuousMultilinearMap 𝕜 E G) :
IsLeast {C : ℝ≥0 | ∀ m, ‖f m‖₊ ≤ C * ∏ i, ‖m i‖₊} ‖f‖₊ := by
simpa only [← opNNNorm_le_iff] using isLeast_Ici
theorem opNNNorm_prod (f : ContinuousMultilinearMap 𝕜 E G) (g : ContinuousMultilinearMap 𝕜 E G') :
‖f.prod g‖₊ = max ‖f‖₊ ‖g‖₊ :=
eq_of_forall_ge_iff fun _ ↦ by
simp only [opNNNorm_le_iff, prod_apply, Prod.nnnorm_def, max_le_iff, forall_and]
theorem opNorm_prod (f : ContinuousMultilinearMap 𝕜 E G) (g : ContinuousMultilinearMap 𝕜 E G') :
‖f.prod g‖ = max ‖f‖ ‖g‖ :=
congr_arg NNReal.toReal (opNNNorm_prod f g)
theorem opNNNorm_pi
[∀ i', SeminormedAddCommGroup (E' i')] [∀ i', NormedSpace 𝕜 (E' i')]
(f : ∀ i', ContinuousMultilinearMap 𝕜 E (E' i')) : ‖pi f‖₊ = ‖f‖₊ :=
eq_of_forall_ge_iff fun _ ↦ by simpa [opNNNorm_le_iff, pi_nnnorm_le_iff] using forall_swap
theorem opNorm_pi {ι' : Type v'} [Fintype ι'] {E' : ι' → Type wE'}
[∀ i', SeminormedAddCommGroup (E' i')] [∀ i', NormedSpace 𝕜 (E' i')]
(f : ∀ i', ContinuousMultilinearMap 𝕜 E (E' i')) :
‖pi f‖ = ‖f‖ :=
congr_arg NNReal.toReal (opNNNorm_pi f)
section
@[simp]
theorem norm_ofSubsingleton [Subsingleton ι] (i : ι) (f : G →L[𝕜] G') :
‖ofSubsingleton 𝕜 G G' i f‖ = ‖f‖ := by
letI : Unique ι := uniqueOfSubsingleton i
simp [norm_def, ContinuousLinearMap.norm_def, (Equiv.funUnique _ _).symm.surjective.forall]
@[simp]
theorem nnnorm_ofSubsingleton [Subsingleton ι] (i : ι) (f : G →L[𝕜] G') :
‖ofSubsingleton 𝕜 G G' i f‖₊ = ‖f‖₊ :=
NNReal.eq <| norm_ofSubsingleton i f
variable (𝕜 G)
/-- Linear isometry between continuous linear maps from `G` to `G'`
and continuous `1`-multilinear maps from `G` to `G'`. -/
@[simps apply symm_apply]
def ofSubsingletonₗᵢ [Subsingleton ι] (i : ι) :
(G →L[𝕜] G') ≃ₗᵢ[𝕜] ContinuousMultilinearMap 𝕜 (fun _ : ι ↦ G) G' :=
{ ofSubsingleton 𝕜 G G' i with
map_add' := fun _ _ ↦ rfl
map_smul' := fun _ _ ↦ rfl
norm_map' := norm_ofSubsingleton i }
theorem norm_ofSubsingleton_id_le [Subsingleton ι] (i : ι) :
‖ofSubsingleton 𝕜 G G i (.id _ _)‖ ≤ 1 := by
rw [norm_ofSubsingleton]
apply ContinuousLinearMap.norm_id_le
theorem nnnorm_ofSubsingleton_id_le [Subsingleton ι] (i : ι) :
‖ofSubsingleton 𝕜 G G i (.id _ _)‖₊ ≤ 1 :=
norm_ofSubsingleton_id_le _ _ _
variable {G} (E)
@[simp]
theorem norm_constOfIsEmpty [IsEmpty ι] (x : G) : ‖constOfIsEmpty 𝕜 E x‖ = ‖x‖ := by
apply le_antisymm
· refine opNorm_le_bound (norm_nonneg _) fun x => ?_
rw [Fintype.prod_empty, mul_one, constOfIsEmpty_apply]
· simpa using (constOfIsEmpty 𝕜 E x).le_opNorm 0
@[simp]
theorem nnnorm_constOfIsEmpty [IsEmpty ι] (x : G) : ‖constOfIsEmpty 𝕜 E x‖₊ = ‖x‖₊ :=
NNReal.eq <| norm_constOfIsEmpty _ _ _
end
section
variable (𝕜 E E' G G')
/-- `ContinuousMultilinearMap.prod` as a `LinearIsometryEquiv`. -/
@[simps]
def prodL :
ContinuousMultilinearMap 𝕜 E G × ContinuousMultilinearMap 𝕜 E G' ≃ₗᵢ[𝕜]
ContinuousMultilinearMap 𝕜 E (G × G') where
__ := prodEquiv
map_add' _ _ := rfl
map_smul' _ _ := rfl
norm_map' f := opNorm_prod f.1 f.2
/-- `ContinuousMultilinearMap.pi` as a `LinearIsometryEquiv`. -/
@[simps! apply symm_apply]
def piₗᵢ {ι' : Type v'} [Fintype ι'] {E' : ι' → Type wE'} [∀ i', NormedAddCommGroup (E' i')]
[∀ i', NormedSpace 𝕜 (E' i')] :
(Π i', ContinuousMultilinearMap 𝕜 E (E' i'))
≃ₗᵢ[𝕜] (ContinuousMultilinearMap 𝕜 E (Π i, E' i)) where
toLinearEquiv := piLinearEquiv
norm_map' := opNorm_pi
end
end
section RestrictScalars
variable {𝕜' : Type*} [NontriviallyNormedField 𝕜'] [NormedAlgebra 𝕜' 𝕜]
variable [NormedSpace 𝕜' G] [IsScalarTower 𝕜' 𝕜 G]
variable [∀ i, NormedSpace 𝕜' (E i)] [∀ i, IsScalarTower 𝕜' 𝕜 (E i)]
@[simp]
theorem norm_restrictScalars (f : ContinuousMultilinearMap 𝕜 E G) :
‖f.restrictScalars 𝕜'‖ = ‖f‖ :=
rfl
variable (𝕜')
/-- `ContinuousMultilinearMap.restrictScalars` as a `LinearIsometry`. -/
def restrictScalarsₗᵢ : ContinuousMultilinearMap 𝕜 E G →ₗᵢ[𝕜'] ContinuousMultilinearMap 𝕜' E G where
toFun := restrictScalars 𝕜'
map_add' _ _ := rfl
map_smul' _ _ := rfl
norm_map' _ := rfl
end RestrictScalars
/-- The difference `f m₁ - f m₂` is controlled in terms of `‖f‖` and `‖m₁ - m₂‖`, precise version.
For a less precise but more usable version, see `norm_image_sub_le`. The bound reads
`‖f m - f m'‖ ≤
‖f‖ * ‖m 1 - m' 1‖ * max ‖m 2‖ ‖m' 2‖ * max ‖m 3‖ ‖m' 3‖ * ... * max ‖m n‖ ‖m' n‖ + ...`,
where the other terms in the sum are the same products where `1` is replaced by any `i`. -/
theorem norm_image_sub_le' [DecidableEq ι] (f : ContinuousMultilinearMap 𝕜 E G) (m₁ m₂ : ∀ i, E i) :
‖f m₁ - f m₂‖ ≤ ‖f‖ * ∑ i, ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ :=
f.toMultilinearMap.norm_image_sub_le_of_bound' (norm_nonneg _) f.le_opNorm _ _
/-- The difference `f m₁ - f m₂` is controlled in terms of `‖f‖` and `‖m₁ - m₂‖`, less precise
version. For a more precise but less usable version, see `norm_image_sub_le'`.
The bound is `‖f m - f m'‖ ≤ ‖f‖ * card ι * ‖m - m'‖ * (max ‖m‖ ‖m'‖) ^ (card ι - 1)`. -/
theorem norm_image_sub_le (f : ContinuousMultilinearMap 𝕜 E G) (m₁ m₂ : ∀ i, E i) :
‖f m₁ - f m₂‖ ≤ ‖f‖ * Fintype.card ι * max ‖m₁‖ ‖m₂‖ ^ (Fintype.card ι - 1) * ‖m₁ - m₂‖ :=
f.toMultilinearMap.norm_image_sub_le_of_bound (norm_nonneg _) f.le_opNorm _ _
end ContinuousMultilinearMap
variable [Fintype ι]
/-- If a continuous multilinear map is constructed from a multilinear map via the constructor
`mkContinuous`, then its norm is bounded by the bound given to the constructor if it is
nonnegative. -/
theorem MultilinearMap.mkContinuous_norm_le (f : MultilinearMap 𝕜 E G) {C : ℝ} (hC : 0 ≤ C)
(H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖) : ‖f.mkContinuous C H‖ ≤ C :=
ContinuousMultilinearMap.opNorm_le_bound hC fun m => H m
/-- If a continuous multilinear map is constructed from a multilinear map via the constructor
`mkContinuous`, then its norm is bounded by the bound given to the constructor if it is
nonnegative. -/
theorem MultilinearMap.mkContinuous_norm_le' (f : MultilinearMap 𝕜 E G) {C : ℝ}
(H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖) : ‖f.mkContinuous C H‖ ≤ max C 0 :=
ContinuousMultilinearMap.opNorm_le_bound (le_max_right _ _) fun m ↦ (H m).trans <|
mul_le_mul_of_nonneg_right (le_max_left _ _) <| by positivity
namespace ContinuousMultilinearMap
/-- Given a continuous multilinear map `f` on `n` variables (parameterized by `Fin n`) and a subset
`s` of `k` of these variables, one gets a new continuous multilinear map on `Fin k` by varying
these variables, and fixing the other ones equal to a given value `z`. It is denoted by
`f.restr s hk z`, where `hk` is a proof that the cardinality of `s` is `k`. The implicit
identification between `Fin k` and `s` that we use is the canonical (increasing) bijection. -/
def restr {k n : ℕ} (f : (G [×n]→L[𝕜] G' :)) (s : Finset (Fin n)) (hk : #s = k) (z : G) :
G [×k]→L[𝕜] G' :=
(f.toMultilinearMap.restr s hk z).mkContinuous (‖f‖ * ‖z‖ ^ (n - k)) fun _ =>
MultilinearMap.restr_norm_le _ _ _ _ f.le_opNorm _
theorem norm_restr {k n : ℕ} (f : G [×n]→L[𝕜] G') (s : Finset (Fin n)) (hk : #s = k) (z : G) :
‖f.restr s hk z‖ ≤ ‖f‖ * ‖z‖ ^ (n - k) := by
apply MultilinearMap.mkContinuous_norm_le
exact mul_nonneg (norm_nonneg _) (pow_nonneg (norm_nonneg _) _)
section
variable {A : Type*} [NormedCommRing A] [NormedAlgebra 𝕜 A]
@[simp]
theorem norm_mkPiAlgebra_le [Nonempty ι] : ‖ContinuousMultilinearMap.mkPiAlgebra 𝕜 ι A‖ ≤ 1 := by
refine opNorm_le_bound zero_le_one fun m => ?_
simp only [ContinuousMultilinearMap.mkPiAlgebra_apply, one_mul]
exact norm_prod_le' _ univ_nonempty _
theorem norm_mkPiAlgebra_of_empty [IsEmpty ι] :
‖ContinuousMultilinearMap.mkPiAlgebra 𝕜 ι A‖ = ‖(1 : A)‖ := by
apply le_antisymm
· apply opNorm_le_bound <;> simp
· convert ratio_le_opNorm (ContinuousMultilinearMap.mkPiAlgebra 𝕜 ι A) fun _ => 1
simp [eq_empty_of_isEmpty univ]
@[simp]
theorem norm_mkPiAlgebra [NormOneClass A] : ‖ContinuousMultilinearMap.mkPiAlgebra 𝕜 ι A‖ = 1 := by
cases isEmpty_or_nonempty ι
· simp [norm_mkPiAlgebra_of_empty]
· refine le_antisymm norm_mkPiAlgebra_le ?_
convert ratio_le_opNorm (ContinuousMultilinearMap.mkPiAlgebra 𝕜 ι A) fun _ => 1
simp
end
section
variable {n : ℕ} {A : Type*} [SeminormedRing A] [NormedAlgebra 𝕜 A]
theorem norm_mkPiAlgebraFin_succ_le : ‖ContinuousMultilinearMap.mkPiAlgebraFin 𝕜 n.succ A‖ ≤ 1 := by
refine opNorm_le_bound zero_le_one fun m => ?_
simp only [ContinuousMultilinearMap.mkPiAlgebraFin_apply, one_mul, List.ofFn_eq_map,
Fin.prod_univ_def, Multiset.map_coe, Multiset.prod_coe]
refine (List.norm_prod_le' ?_).trans_eq ?_
· rw [Ne, List.map_eq_nil_iff, List.finRange_eq_nil]
exact Nat.succ_ne_zero _
rw [List.map_map, Function.comp_def]
theorem norm_mkPiAlgebraFin_le_of_pos (hn : 0 < n) :
‖ContinuousMultilinearMap.mkPiAlgebraFin 𝕜 n A‖ ≤ 1 := by
obtain ⟨n, rfl⟩ := Nat.exists_eq_succ_of_ne_zero hn.ne'
exact norm_mkPiAlgebraFin_succ_le
theorem norm_mkPiAlgebraFin_zero : ‖ContinuousMultilinearMap.mkPiAlgebraFin 𝕜 0 A‖ = ‖(1 : A)‖ := by
refine le_antisymm ?_ ?_
· refine opNorm_le_bound (norm_nonneg (1 : A)) ?_
simp
· convert ratio_le_opNorm (ContinuousMultilinearMap.mkPiAlgebraFin 𝕜 0 A) fun _ => (1 : A)
simp
theorem norm_mkPiAlgebraFin_le :
‖ContinuousMultilinearMap.mkPiAlgebraFin 𝕜 n A‖ ≤ max 1 ‖(1 : A)‖ := by
cases n
· exact norm_mkPiAlgebraFin_zero.le.trans (le_max_right _ _)
· exact (norm_mkPiAlgebraFin_le_of_pos (Nat.zero_lt_succ _)).trans (le_max_left _ _)
@[simp]
theorem norm_mkPiAlgebraFin [NormOneClass A] :
‖ContinuousMultilinearMap.mkPiAlgebraFin 𝕜 n A‖ = 1 := by
cases n
· rw [norm_mkPiAlgebraFin_zero]
simp
· refine le_antisymm norm_mkPiAlgebraFin_succ_le ?_
refine le_of_eq_of_le ?_ <|
ratio_le_opNorm (ContinuousMultilinearMap.mkPiAlgebraFin 𝕜 (Nat.succ _) A) fun _ => 1
simp
end
@[simp]
theorem nnnorm_smulRight (f : ContinuousMultilinearMap 𝕜 E 𝕜) (z : G) :
‖f.smulRight z‖₊ = ‖f‖₊ * ‖z‖₊ := by
refine le_antisymm ?_ ?_
· refine opNNNorm_le_iff.2 fun m => (nnnorm_smul_le _ _).trans ?_
rw [mul_right_comm]
gcongr
exact le_opNNNorm _ _
· obtain hz | hz := eq_zero_or_pos ‖z‖₊
· simp [hz]
rw [← le_div_iff₀ hz, opNNNorm_le_iff]
intro m
rw [div_mul_eq_mul_div, le_div_iff₀ hz]
refine le_trans ?_ ((f.smulRight z).le_opNNNorm m)
rw [smulRight_apply, nnnorm_smul]
@[simp]
theorem norm_smulRight (f : ContinuousMultilinearMap 𝕜 E 𝕜) (z : G) :
‖f.smulRight z‖ = ‖f‖ * ‖z‖ :=
congr_arg NNReal.toReal (nnnorm_smulRight f z)
@[simp]
theorem norm_mkPiRing (z : G) : ‖ContinuousMultilinearMap.mkPiRing 𝕜 ι z‖ = ‖z‖ := by
rw [ContinuousMultilinearMap.mkPiRing, norm_smulRight, norm_mkPiAlgebra, one_mul]
variable (𝕜 E G) in
/-- Continuous bilinear map realizing `(f, z) ↦ f.smulRight z`. -/
def smulRightL : ContinuousMultilinearMap 𝕜 E 𝕜 →L[𝕜] G →L[𝕜] ContinuousMultilinearMap 𝕜 E G :=
LinearMap.mkContinuous₂
{ toFun := fun f ↦
{ toFun := fun z ↦ f.smulRight z
map_add' := fun x y ↦ by ext; simp
map_smul' := fun c x ↦ by ext; simp [smul_smul, mul_comm] }
map_add' := fun f g ↦ by ext; simp [add_smul]
map_smul' := fun c f ↦ by ext; simp [smul_smul] }
1 (fun f z ↦ by simp [norm_smulRight])
@[simp] lemma smulRightL_apply (f : ContinuousMultilinearMap 𝕜 E 𝕜) (z : G) :
smulRightL 𝕜 E G f z = f.smulRight z := rfl
lemma norm_smulRightL_le : ‖smulRightL 𝕜 E G‖ ≤ 1 :=
LinearMap.mkContinuous₂_norm_le _ zero_le_one _
variable (𝕜 ι G)
/-- Continuous multilinear maps on `𝕜^n` with values in `G` are in bijection with `G`, as such a
continuous multilinear map is completely determined by its value on the constant vector made of
ones. We register this bijection as a linear isometry in
`ContinuousMultilinearMap.piFieldEquiv`. -/
protected def piFieldEquiv : G ≃ₗᵢ[𝕜] ContinuousMultilinearMap 𝕜 (fun _ : ι => 𝕜) G where
toFun z := ContinuousMultilinearMap.mkPiRing 𝕜 ι z
invFun f := f fun _ => 1
map_add' z z' := by
ext m
simp [smul_add]
map_smul' c z := by
ext m
simp [smul_smul, mul_comm]
left_inv z := by simp
right_inv f := f.mkPiRing_apply_one_eq_self
norm_map' := norm_mkPiRing
end ContinuousMultilinearMap
namespace ContinuousLinearMap
theorem norm_compContinuousMultilinearMap_le (g : G →L[𝕜] G') (f : ContinuousMultilinearMap 𝕜 E G) :
‖g.compContinuousMultilinearMap f‖ ≤ ‖g‖ * ‖f‖ :=
ContinuousMultilinearMap.opNorm_le_bound (by positivity) fun m ↦
calc
‖g (f m)‖ ≤ ‖g‖ * (‖f‖ * ∏ i, ‖m i‖) := g.le_opNorm_of_le <| f.le_opNorm _
_ = _ := (mul_assoc _ _ _).symm
variable (𝕜 E G G')
/-- `ContinuousLinearMap.compContinuousMultilinearMap` as a bundled continuous bilinear map. -/
def compContinuousMultilinearMapL :
(G →L[𝕜] G') →L[𝕜] ContinuousMultilinearMap 𝕜 E G →L[𝕜] ContinuousMultilinearMap 𝕜 E G' :=
LinearMap.mkContinuous₂
(LinearMap.mk₂ 𝕜 compContinuousMultilinearMap (fun _ _ _ => rfl) (fun _ _ _ => rfl)
(fun f g₁ g₂ => by ext1; apply f.map_add)
(fun c f g => by ext1; simp))
1
fun f g => by rw [one_mul]; exact f.norm_compContinuousMultilinearMap_le g
variable {𝕜 G G'}
/-- `ContinuousLinearMap.compContinuousMultilinearMap` as a bundled
continuous linear equiv. -/
def _root_.ContinuousLinearEquiv.continuousMultilinearMapCongrRight (g : G ≃L[𝕜] G') :
ContinuousMultilinearMap 𝕜 E G ≃L[𝕜] ContinuousMultilinearMap 𝕜 E G' :=
{ compContinuousMultilinearMapL 𝕜 E G G' g.toContinuousLinearMap with
invFun := compContinuousMultilinearMapL 𝕜 E G' G g.symm.toContinuousLinearMap
left_inv := by
intro f
ext1 m
simp [compContinuousMultilinearMapL]
right_inv := by
intro f
ext1 m
simp [compContinuousMultilinearMapL]
continuous_invFun :=
(compContinuousMultilinearMapL 𝕜 E G' G g.symm.toContinuousLinearMap).continuous }
@[deprecated (since := "2025-04-19")]
alias _root_.ContinuousLinearEquiv.compContinuousMultilinearMapL :=
ContinuousLinearEquiv.continuousMultilinearMapCongrRight
@[simp]
theorem _root_.ContinuousLinearEquiv.continuousMultilinearMapCongrRight_symm (g : G ≃L[𝕜] G') :
(g.continuousMultilinearMapCongrRight E).symm = g.symm.continuousMultilinearMapCongrRight E :=
rfl
@[deprecated (since := "2025-04-19")]
alias _root_.ContinuousLinearEquiv.compContinuousMultilinearMapL_symm :=
ContinuousLinearEquiv.continuousMultilinearMapCongrRight_symm
variable {E}
@[simp]
theorem _root_.ContinuousLinearEquiv.continuousMultilinearMapCongrRight_apply (g : G ≃L[𝕜] G')
(f : ContinuousMultilinearMap 𝕜 E G) :
g.continuousMultilinearMapCongrRight E f = (g : G →L[𝕜] G').compContinuousMultilinearMap f :=
rfl
@[deprecated (since := "2025-04-19")]
alias _root_.ContinuousLinearEquiv.compContinuousMultilinearMapL_apply :=
ContinuousLinearEquiv.continuousMultilinearMapCongrRight_apply
/-- Flip arguments in `f : G →L[𝕜] ContinuousMultilinearMap 𝕜 E G'` to get
`ContinuousMultilinearMap 𝕜 E (G →L[𝕜] G')` -/
@[simps! apply_apply]
def flipMultilinear (f : G →L[𝕜] ContinuousMultilinearMap 𝕜 E G') :
ContinuousMultilinearMap 𝕜 E (G →L[𝕜] G') :=
MultilinearMap.mkContinuous
{ toFun := fun m =>
LinearMap.mkContinuous
{ toFun := fun x => f x m
map_add' := fun x y => by simp only [map_add, ContinuousMultilinearMap.add_apply]
map_smul' := fun c x => by
simp only [ContinuousMultilinearMap.smul_apply, map_smul, RingHom.id_apply] }
(‖f‖ * ∏ i, ‖m i‖) fun x => by
rw [mul_right_comm]
exact (f x).le_of_opNorm_le (f.le_opNorm x) _
map_update_add' := fun m i x y => by
ext1
simp only [add_apply, ContinuousMultilinearMap.map_update_add, LinearMap.coe_mk,
LinearMap.mkContinuous_apply, AddHom.coe_mk]
map_update_smul' := fun m i c x => by
ext1
simp only [coe_smul', ContinuousMultilinearMap.map_update_smul, LinearMap.coe_mk,
LinearMap.mkContinuous_apply, Pi.smul_apply, AddHom.coe_mk] }
‖f‖ fun m => by
dsimp only [MultilinearMap.coe_mk]
exact LinearMap.mkContinuous_norm_le _ (by positivity) _
end ContinuousLinearMap
theorem LinearIsometry.norm_compContinuousMultilinearMap (g : G →ₗᵢ[𝕜] G')
(f : ContinuousMultilinearMap 𝕜 E G) :
‖g.toContinuousLinearMap.compContinuousMultilinearMap f‖ = ‖f‖ := by
simp only [ContinuousLinearMap.compContinuousMultilinearMap_coe,
LinearIsometry.coe_toContinuousLinearMap, LinearIsometry.norm_map,
ContinuousMultilinearMap.norm_def, Function.comp_apply]
open ContinuousMultilinearMap
namespace MultilinearMap
/-- Given a map `f : G →ₗ[𝕜] MultilinearMap 𝕜 E G'` and an estimate
`H : ∀ x m, ‖f x m‖ ≤ C * ‖x‖ * ∏ i, ‖m i‖`, construct a continuous linear
map from `G` to `ContinuousMultilinearMap 𝕜 E G'`.
In order to lift, e.g., a map `f : (MultilinearMap 𝕜 E G) →ₗ[𝕜] MultilinearMap 𝕜 E' G'`
to a map `(ContinuousMultilinearMap 𝕜 E G) →L[𝕜] ContinuousMultilinearMap 𝕜 E' G'`,
one can apply this construction to `f.comp ContinuousMultilinearMap.toMultilinearMapLinear`
which is a linear map from `ContinuousMultilinearMap 𝕜 E G` to `MultilinearMap 𝕜 E' G'`. -/
def mkContinuousLinear (f : G →ₗ[𝕜] MultilinearMap 𝕜 E G') (C : ℝ)
(H : ∀ x m, ‖f x m‖ ≤ C * ‖x‖ * ∏ i, ‖m i‖) : G →L[𝕜] ContinuousMultilinearMap 𝕜 E G' :=
LinearMap.mkContinuous
{ toFun := fun x => (f x).mkContinuous (C * ‖x‖) <| H x
map_add' := fun x y => by
ext1
simp
map_smul' := fun c x => by
ext1
simp }
(max C 0) fun x => by
simpa using ((f x).mkContinuous_norm_le' _).trans_eq <| by
rw [max_mul_of_nonneg _ _ (norm_nonneg x), zero_mul]
theorem mkContinuousLinear_norm_le' (f : G →ₗ[𝕜] MultilinearMap 𝕜 E G') (C : ℝ)
(H : ∀ x m, ‖f x m‖ ≤ C * ‖x‖ * ∏ i, ‖m i‖) : ‖mkContinuousLinear f C H‖ ≤ max C 0 := by
dsimp only [mkContinuousLinear]
exact LinearMap.mkContinuous_norm_le _ (le_max_right _ _) _
theorem mkContinuousLinear_norm_le (f : G →ₗ[𝕜] MultilinearMap 𝕜 E G') {C : ℝ} (hC : 0 ≤ C)
(H : ∀ x m, ‖f x m‖ ≤ C * ‖x‖ * ∏ i, ‖m i‖) : ‖mkContinuousLinear f C H‖ ≤ C :=
(mkContinuousLinear_norm_le' f C H).trans_eq (max_eq_left hC)
variable [∀ i, SeminormedAddCommGroup (E' i)] [∀ i, NormedSpace 𝕜 (E' i)]
/-- Given a map `f : MultilinearMap 𝕜 E (MultilinearMap 𝕜 E' G)` and an estimate
`H : ∀ m m', ‖f m m'‖ ≤ C * ∏ i, ‖m i‖ * ∏ i, ‖m' i‖`, upgrade all `MultilinearMap`s in the type to
`ContinuousMultilinearMap`s. -/
def mkContinuousMultilinear (f : MultilinearMap 𝕜 E (MultilinearMap 𝕜 E' G)) (C : ℝ)
(H : ∀ m₁ m₂, ‖f m₁ m₂‖ ≤ (C * ∏ i, ‖m₁ i‖) * ∏ i, ‖m₂ i‖) :
ContinuousMultilinearMap 𝕜 E (ContinuousMultilinearMap 𝕜 E' G) :=
mkContinuous
{ toFun := fun m => mkContinuous (f m) (C * ∏ i, ‖m i‖) <| H m
map_update_add' := fun m i x y => by
ext1
simp
map_update_smul' := fun m i c x => by
ext1
simp }
(max C 0) fun m => by
simp only [coe_mk]
refine ((f m).mkContinuous_norm_le' _).trans_eq ?_
rw [max_mul_of_nonneg, zero_mul]
positivity
@[simp]
theorem mkContinuousMultilinear_apply (f : MultilinearMap 𝕜 E (MultilinearMap 𝕜 E' G)) {C : ℝ}
(H : ∀ m₁ m₂, ‖f m₁ m₂‖ ≤ (C * ∏ i, ‖m₁ i‖) * ∏ i, ‖m₂ i‖) (m : ∀ i, E i) :
⇑(mkContinuousMultilinear f C H m) = f m :=
rfl
theorem mkContinuousMultilinear_norm_le' (f : MultilinearMap 𝕜 E (MultilinearMap 𝕜 E' G)) (C : ℝ)
(H : ∀ m₁ m₂, ‖f m₁ m₂‖ ≤ (C * ∏ i, ‖m₁ i‖) * ∏ i, ‖m₂ i‖) :
‖mkContinuousMultilinear f C H‖ ≤ max C 0 := by
dsimp only [mkContinuousMultilinear]
exact mkContinuous_norm_le _ (le_max_right _ _) _
theorem mkContinuousMultilinear_norm_le (f : MultilinearMap 𝕜 E (MultilinearMap 𝕜 E' G)) {C : ℝ}
(hC : 0 ≤ C) (H : ∀ m₁ m₂, ‖f m₁ m₂‖ ≤ (C * ∏ i, ‖m₁ i‖) * ∏ i, ‖m₂ i‖) :
‖mkContinuousMultilinear f C H‖ ≤ C :=
(mkContinuousMultilinear_norm_le' f C H).trans_eq (max_eq_left hC)
end MultilinearMap
namespace ContinuousMultilinearMap
theorem norm_compContinuousLinearMap_le (g : ContinuousMultilinearMap 𝕜 E₁ G)
(f : ∀ i, E i →L[𝕜] E₁ i) : ‖g.compContinuousLinearMap f‖ ≤ ‖g‖ * ∏ i, ‖f i‖ :=
opNorm_le_bound (by positivity) fun m =>
calc
‖g fun i => f i (m i)‖ ≤ ‖g‖ * ∏ i, ‖f i (m i)‖ := g.le_opNorm _
_ ≤ ‖g‖ * ∏ i, ‖f i‖ * ‖m i‖ :=
(mul_le_mul_of_nonneg_left
(prod_le_prod (fun _ _ => norm_nonneg _) fun i _ => (f i).le_opNorm (m i))
(norm_nonneg g))
_ = (‖g‖ * ∏ i, ‖f i‖) * ∏ i, ‖m i‖ := by rw [prod_mul_distrib, mul_assoc]
theorem norm_compContinuous_linearIsometry_le (g : ContinuousMultilinearMap 𝕜 E₁ G)
(f : ∀ i, E i →ₗᵢ[𝕜] E₁ i) :
‖g.compContinuousLinearMap fun i => (f i).toContinuousLinearMap‖ ≤ ‖g‖ := by
refine opNorm_le_bound (norm_nonneg _) fun m => ?_
apply (g.le_opNorm _).trans _
simp only [ContinuousLinearMap.coe_coe, LinearIsometry.coe_toContinuousLinearMap,
LinearIsometry.norm_map, le_rfl]
theorem norm_compContinuous_linearIsometryEquiv (g : ContinuousMultilinearMap 𝕜 E₁ G)
(f : ∀ i, E i ≃ₗᵢ[𝕜] E₁ i) :
‖g.compContinuousLinearMap fun i => (f i : E i →L[𝕜] E₁ i)‖ = ‖g‖ := by
apply le_antisymm (g.norm_compContinuous_linearIsometry_le fun i => (f i).toLinearIsometry)
have : g = (g.compContinuousLinearMap fun i => (f i : E i →L[𝕜] E₁ i)).compContinuousLinearMap
fun i => ((f i).symm : E₁ i →L[𝕜] E i) := by
ext1 m
simp only [compContinuousLinearMap_apply, LinearIsometryEquiv.coe_coe'',
LinearIsometryEquiv.apply_symm_apply]
conv_lhs => rw [this]
apply (g.compContinuousLinearMap fun i =>
(f i : E i →L[𝕜] E₁ i)).norm_compContinuous_linearIsometry_le
fun i => (f i).symm.toLinearIsometry
/-- `ContinuousMultilinearMap.compContinuousLinearMap` as a bundled continuous linear map.
This implementation fixes `f : Π i, E i →L[𝕜] E₁ i`.
Actually, the map is multilinear in `f`,
see `ContinuousMultilinearMap.compContinuousLinearMapContinuousMultilinear`.
For a version fixing `g` and varying `f`, see `compContinuousLinearMapLRight`. -/
def compContinuousLinearMapL (f : ∀ i, E i →L[𝕜] E₁ i) :
ContinuousMultilinearMap 𝕜 E₁ G →L[𝕜] ContinuousMultilinearMap 𝕜 E G :=
LinearMap.mkContinuous
{ toFun := fun g => g.compContinuousLinearMap f
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
(∏ i, ‖f i‖)
fun _ => (norm_compContinuousLinearMap_le _ _).trans_eq (mul_comm _ _)
@[simp]
theorem compContinuousLinearMapL_apply (g : ContinuousMultilinearMap 𝕜 E₁ G)
(f : ∀ i, E i →L[𝕜] E₁ i) : compContinuousLinearMapL f g = g.compContinuousLinearMap f :=
rfl
variable (G) in
theorem norm_compContinuousLinearMapL_le (f : ∀ i, E i →L[𝕜] E₁ i) :
‖compContinuousLinearMapL (G := G) f‖ ≤ ∏ i, ‖f i‖ :=
LinearMap.mkContinuous_norm_le _ (by positivity) _
/-- `ContinuousMultilinearMap.compContinuousLinearMap` as a bundled continuous linear map.
This implementation fixes `g : ContinuousMultilinearMap 𝕜 E₁ G`.
Actually, the map is linear in `g`,
see `ContinuousMultilinearMap.compContinuousLinearMapContinuousMultilinear`.
For a version fixing `f` and varying `g`, see `compContinuousLinearMapL`. -/
def compContinuousLinearMapLRight (g : ContinuousMultilinearMap 𝕜 E₁ G) :
ContinuousMultilinearMap 𝕜 (fun i ↦ E i →L[𝕜] E₁ i) (ContinuousMultilinearMap 𝕜 E G) :=
MultilinearMap.mkContinuous
{ toFun := fun f => g.compContinuousLinearMap f
map_update_add' := by
intro h f i f₁ f₂
ext x
simp only [compContinuousLinearMap_apply, add_apply]
convert g.map_update_add (fun j ↦ f j (x j)) i (f₁ (x i)) (f₂ (x i)) <;>
exact apply_update (fun (i : ι) (f : E i →L[𝕜] E₁ i) ↦ f (x i)) f i _ _
map_update_smul' := by
intro h f i a f₀
ext x
simp only [compContinuousLinearMap_apply, smul_apply]
convert g.map_update_smul (fun j ↦ f j (x j)) i a (f₀ (x i)) <;>
exact apply_update (fun (i : ι) (f : E i →L[𝕜] E₁ i) ↦ f (x i)) f i _ _ }
(‖g‖) (fun f ↦ by simp [norm_compContinuousLinearMap_le])
@[simp]
theorem compContinuousLinearMapLRight_apply (g : ContinuousMultilinearMap 𝕜 E₁ G)
(f : ∀ i, E i →L[𝕜] E₁ i) : compContinuousLinearMapLRight g f = g.compContinuousLinearMap f :=
rfl
variable (E) in
theorem norm_compContinuousLinearMapLRight_le (g : ContinuousMultilinearMap 𝕜 E₁ G) :
‖compContinuousLinearMapLRight (E := E) g‖ ≤ ‖g‖ :=
MultilinearMap.mkContinuous_norm_le _ (norm_nonneg _) _
variable (𝕜 E E₁ G)
open Function in
/-- If `f` is a collection of continuous linear maps, then the construction
`ContinuousMultilinearMap.compContinuousLinearMap`
sending a continuous multilinear map `g` to `g (f₁ ·, ..., fₙ ·)`
is continuous-linear in `g` and multilinear in `f₁, ..., fₙ`. -/
noncomputable def compContinuousLinearMapMultilinear :
MultilinearMap 𝕜 (fun i ↦ E i →L[𝕜] E₁ i)
((ContinuousMultilinearMap 𝕜 E₁ G) →L[𝕜] ContinuousMultilinearMap 𝕜 E G) where
toFun := compContinuousLinearMapL
map_update_add' f i f₁ f₂ := by
ext g x
change (g fun j ↦ update f i (f₁ + f₂) j <| x j) =
(g fun j ↦ update f i f₁ j <| x j) + g fun j ↦ update f i f₂ j (x j)
convert g.map_update_add (fun j ↦ f j (x j)) i (f₁ (x i)) (f₂ (x i)) <;>
exact apply_update (fun (i : ι) (f : E i →L[𝕜] E₁ i) ↦ f (x i)) f i _ _
map_update_smul' f i a f₀ := by
ext g x
change (g fun j ↦ update f i (a • f₀) j <| x j) = a • g fun j ↦ update f i f₀ j (x j)
| convert g.map_update_smul (fun j ↦ f j (x j)) i a (f₀ (x i)) <;>
exact apply_update (fun (i : ι) (f : E i →L[𝕜] E₁ i) ↦ f (x i)) f i _ _
/-- If `f` is a collection of continuous linear maps, then the construction
`ContinuousMultilinearMap.compContinuousLinearMap`
sending a continuous multilinear map `g` to `g (f₁ ·, ..., fₙ ·)` is continuous-linear in `g` and
continuous-multilinear in `f₁, ..., fₙ`. -/
noncomputable def compContinuousLinearMapContinuousMultilinear :
ContinuousMultilinearMap 𝕜 (fun i ↦ E i →L[𝕜] E₁ i)
((ContinuousMultilinearMap 𝕜 E₁ G) →L[𝕜] ContinuousMultilinearMap 𝕜 E G) :=
| Mathlib/Analysis/NormedSpace/Multilinear/Basic.lean | 1,131 | 1,140 |
/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Analysis.Asymptotics.Lemmas
import Mathlib.Analysis.Normed.Module.Basic
/-!
# Asymptotic equivalence up to a constant
In this file we define `Asymptotics.IsTheta l f g` (notation: `f =Θ[l] g`) as
`f =O[l] g ∧ g =O[l] f`, then prove basic properties of this equivalence relation.
-/
open Filter
open Topology
namespace Asymptotics
variable {α : Type*} {β : Type*} {E : Type*} {F : Type*} {G : Type*} {E' : Type*}
{F' : Type*} {G' : Type*} {E'' : Type*} {F'' : Type*} {G'' : Type*} {R : Type*}
{R' : Type*} {𝕜 : Type*} {𝕜' : Type*}
variable [Norm E] [Norm F] [Norm G]
variable [SeminormedAddCommGroup E'] [SeminormedAddCommGroup F'] [SeminormedAddCommGroup G']
[NormedAddCommGroup E''] [NormedAddCommGroup F''] [NormedAddCommGroup G''] [SeminormedRing R]
[SeminormedRing R']
variable [NormedField 𝕜] [NormedField 𝕜']
variable {c c' c₁ c₂ : ℝ} {f : α → E} {g : α → F} {k : α → G}
variable {f' : α → E'} {g' : α → F'} {k' : α → G'}
variable {f'' : α → E''} {g'' : α → F''}
variable {l l' : Filter α}
/-- We say that `f` is `Θ(g)` along a filter `l` (notation: `f =Θ[l] g`) if `f =O[l] g` and
`g =O[l] f`. -/
def IsTheta (l : Filter α) (f : α → E) (g : α → F) : Prop :=
IsBigO l f g ∧ IsBigO l g f
@[inherit_doc]
notation:100 f " =Θ[" l "] " g:100 => IsTheta l f g
theorem IsBigO.antisymm (h₁ : f =O[l] g) (h₂ : g =O[l] f) : f =Θ[l] g :=
⟨h₁, h₂⟩
lemma IsTheta.isBigO (h : f =Θ[l] g) : f =O[l] g := h.1
lemma IsTheta.isBigO_symm (h : f =Θ[l] g) : g =O[l] f := h.2
@[refl]
theorem isTheta_refl (f : α → E) (l : Filter α) : f =Θ[l] f :=
⟨isBigO_refl _ _, isBigO_refl _ _⟩
theorem isTheta_rfl : f =Θ[l] f :=
isTheta_refl _ _
@[symm]
nonrec theorem IsTheta.symm (h : f =Θ[l] g) : g =Θ[l] f :=
h.symm
theorem isTheta_comm : f =Θ[l] g ↔ g =Θ[l] f :=
⟨fun h ↦ h.symm, fun h ↦ h.symm⟩
@[trans]
theorem IsTheta.trans {f : α → E} {g : α → F'} {k : α → G} (h₁ : f =Θ[l] g) (h₂ : g =Θ[l] k) :
f =Θ[l] k :=
⟨h₁.1.trans h₂.1, h₂.2.trans h₁.2⟩
instance : Trans (α := α → E) (β := α → F') (γ := α → G) (IsTheta l) (IsTheta l) (IsTheta l) :=
⟨IsTheta.trans⟩
@[trans]
theorem IsBigO.trans_isTheta {f : α → E} {g : α → F'} {k : α → G} (h₁ : f =O[l] g)
(h₂ : g =Θ[l] k) : f =O[l] k :=
h₁.trans h₂.1
instance : Trans (α := α → E) (β := α → F') (γ := α → G) (IsBigO l) (IsTheta l) (IsBigO l) :=
⟨IsBigO.trans_isTheta⟩
@[trans]
theorem IsTheta.trans_isBigO {f : α → E} {g : α → F'} {k : α → G} (h₁ : f =Θ[l] g)
(h₂ : g =O[l] k) : f =O[l] k :=
h₁.1.trans h₂
instance : Trans (α := α → E) (β := α → F') (γ := α → G) (IsTheta l) (IsBigO l) (IsBigO l) :=
⟨IsTheta.trans_isBigO⟩
@[trans]
theorem IsLittleO.trans_isTheta {f : α → E} {g : α → F} {k : α → G'} (h₁ : f =o[l] g)
(h₂ : g =Θ[l] k) : f =o[l] k :=
h₁.trans_isBigO h₂.1
instance : Trans (α := α → E) (β := α → F') (γ := α → G') (IsLittleO l) (IsTheta l) (IsLittleO l) :=
⟨IsLittleO.trans_isTheta⟩
@[trans]
theorem IsTheta.trans_isLittleO {f : α → E} {g : α → F'} {k : α → G} (h₁ : f =Θ[l] g)
(h₂ : g =o[l] k) : f =o[l] k :=
h₁.1.trans_isLittleO h₂
instance : Trans (α := α → E) (β := α → F') (γ := α → G) (IsTheta l) (IsLittleO l) (IsLittleO l) :=
⟨IsTheta.trans_isLittleO⟩
@[trans]
theorem IsTheta.trans_eventuallyEq {f : α → E} {g₁ g₂ : α → F} (h : f =Θ[l] g₁) (hg : g₁ =ᶠ[l] g₂) :
f =Θ[l] g₂ :=
⟨h.1.trans_eventuallyEq hg, hg.symm.trans_isBigO h.2⟩
instance : Trans (α := α → E) (β := α → F) (γ := α → F) (IsTheta l) (EventuallyEq l) (IsTheta l) :=
⟨IsTheta.trans_eventuallyEq⟩
@[trans]
theorem _root_.Filter.EventuallyEq.trans_isTheta {f₁ f₂ : α → E} {g : α → F} (hf : f₁ =ᶠ[l] f₂)
(h : f₂ =Θ[l] g) : f₁ =Θ[l] g :=
⟨hf.trans_isBigO h.1, h.2.trans_eventuallyEq hf.symm⟩
instance : Trans (α := α → E) (β := α → E) (γ := α → F) (EventuallyEq l) (IsTheta l) (IsTheta l) :=
⟨EventuallyEq.trans_isTheta⟩
lemma _root_.Filter.EventuallyEq.isTheta {f g : α → E} (h : f =ᶠ[l] g) : f =Θ[l] g :=
h.trans_isTheta isTheta_rfl
@[simp]
theorem isTheta_bot : f =Θ[⊥] g := by simp [IsTheta]
@[simp]
theorem isTheta_norm_left : (fun x ↦ ‖f' x‖) =Θ[l] g ↔ f' =Θ[l] g := by simp [IsTheta]
@[simp]
theorem isTheta_norm_right : (f =Θ[l] fun x ↦ ‖g' x‖) ↔ f =Θ[l] g' := by simp [IsTheta]
alias ⟨IsTheta.of_norm_left, IsTheta.norm_left⟩ := isTheta_norm_left
alias ⟨IsTheta.of_norm_right, IsTheta.norm_right⟩ := isTheta_norm_right
theorem IsTheta.of_norm_eventuallyEq_norm (h : (fun x ↦ ‖f x‖) =ᶠ[l] fun x ↦ ‖g x‖) : f =Θ[l] g :=
⟨.of_bound' h.le, .of_bound' h.symm.le⟩
@[deprecated (since := "2025-01-03")]
alias isTheta_of_norm_eventuallyEq := IsTheta.of_norm_eventuallyEq_norm
theorem IsTheta.of_norm_eventuallyEq {g : α → ℝ} (h : (fun x ↦ ‖f' x‖) =ᶠ[l] g) : f' =Θ[l] g :=
of_norm_eventuallyEq_norm <| h.mono fun x hx ↦ by simp only [← hx, norm_norm]
@[deprecated (since := "2025-01-03")]
alias isTheta_of_norm_eventuallyEq' := IsTheta.of_norm_eventuallyEq
theorem IsTheta.isLittleO_congr_left (h : f' =Θ[l] g') : f' =o[l] k ↔ g' =o[l] k :=
⟨h.symm.trans_isLittleO, h.trans_isLittleO⟩
theorem IsTheta.isLittleO_congr_right (h : g' =Θ[l] k') : f =o[l] g' ↔ f =o[l] k' :=
⟨fun H ↦ H.trans_isTheta h, fun H ↦ H.trans_isTheta h.symm⟩
theorem IsTheta.isBigO_congr_left (h : f' =Θ[l] g') : f' =O[l] k ↔ g' =O[l] k :=
⟨h.symm.trans_isBigO, h.trans_isBigO⟩
theorem IsTheta.isBigO_congr_right (h : g' =Θ[l] k') : f =O[l] g' ↔ f =O[l] k' :=
⟨fun H ↦ H.trans_isTheta h, fun H ↦ H.trans_isTheta h.symm⟩
lemma IsTheta.isTheta_congr_left (h : f' =Θ[l] g') : f' =Θ[l] k ↔ g' =Θ[l] k :=
h.isBigO_congr_left.and h.isBigO_congr_right
lemma IsTheta.isTheta_congr_right (h : f' =Θ[l] g') : k =Θ[l] f' ↔ k =Θ[l] g' :=
h.isBigO_congr_right.and h.isBigO_congr_left
theorem IsTheta.mono (h : f =Θ[l] g) (hl : l' ≤ l) : f =Θ[l'] g :=
⟨h.1.mono hl, h.2.mono hl⟩
theorem IsTheta.sup (h : f' =Θ[l] g') (h' : f' =Θ[l'] g') : f' =Θ[l ⊔ l'] g' :=
⟨h.1.sup h'.1, h.2.sup h'.2⟩
@[simp]
theorem isTheta_sup : f' =Θ[l ⊔ l'] g' ↔ f' =Θ[l] g' ∧ f' =Θ[l'] g' :=
⟨fun h ↦ ⟨h.mono le_sup_left, h.mono le_sup_right⟩, fun h ↦ h.1.sup h.2⟩
theorem IsTheta.eq_zero_iff (h : f'' =Θ[l] g'') : ∀ᶠ x in l, f'' x = 0 ↔ g'' x = 0 :=
h.1.eq_zero_imp.mp <| h.2.eq_zero_imp.mono fun _ ↦ Iff.intro
theorem IsTheta.tendsto_zero_iff (h : f'' =Θ[l] g'') :
Tendsto f'' l (𝓝 0) ↔ Tendsto g'' l (𝓝 0) := by
simp only [← isLittleO_one_iff ℝ, h.isLittleO_congr_left]
theorem IsTheta.tendsto_norm_atTop_iff (h : f' =Θ[l] g') :
Tendsto (norm ∘ f') l atTop ↔ Tendsto (norm ∘ g') l atTop := by
simp only [Function.comp_def, ← isLittleO_const_left_of_ne (one_ne_zero' ℝ),
h.isLittleO_congr_right]
theorem IsTheta.isBoundedUnder_le_iff (h : f' =Θ[l] g') :
IsBoundedUnder (· ≤ ·) l (norm ∘ f') ↔ IsBoundedUnder (· ≤ ·) l (norm ∘ g') := by
simp only [← isBigO_const_of_ne (one_ne_zero' ℝ), h.isBigO_congr_left]
theorem IsTheta.smul [NormedSpace 𝕜 E'] [NormedSpace 𝕜' F'] {f₁ : α → 𝕜} {f₂ : α → 𝕜'} {g₁ : α → E'}
{g₂ : α → F'} (hf : f₁ =Θ[l] f₂) (hg : g₁ =Θ[l] g₂) :
(fun x ↦ f₁ x • g₁ x) =Θ[l] fun x ↦ f₂ x • g₂ x :=
⟨hf.1.smul hg.1, hf.2.smul hg.2⟩
theorem IsTheta.mul {f₁ f₂ : α → 𝕜} {g₁ g₂ : α → 𝕜'} (h₁ : f₁ =Θ[l] g₁) (h₂ : f₂ =Θ[l] g₂) :
(fun x ↦ f₁ x * f₂ x) =Θ[l] fun x ↦ g₁ x * g₂ x :=
h₁.smul h₂
theorem IsTheta.listProd {ι : Type*} {L : List ι} {f : ι → α → 𝕜} {g : ι → α → 𝕜'}
(h : ∀ i ∈ L, f i =Θ[l] g i) :
(fun x ↦ (L.map (f · x)).prod) =Θ[l] (fun x ↦ (L.map (g · x)).prod) :=
⟨.listProd fun i hi ↦ (h i hi).isBigO, .listProd fun i hi ↦ (h i hi).symm.isBigO⟩
theorem IsTheta.multisetProd {ι : Type*} {s : Multiset ι} {f : ι → α → 𝕜} {g : ι → α → 𝕜'}
(h : ∀ i ∈ s, f i =Θ[l] g i) :
(fun x ↦ (s.map (f · x)).prod) =Θ[l] (fun x ↦ (s.map (g · x)).prod) :=
⟨.multisetProd fun i hi ↦ (h i hi).isBigO, .multisetProd fun i hi ↦ (h i hi).symm.isBigO⟩
theorem IsTheta.finsetProd {ι : Type*} {s : Finset ι} {f : ι → α → 𝕜} {g : ι → α → 𝕜'}
(h : ∀ i ∈ s, f i =Θ[l] g i) : (∏ i ∈ s, f i ·) =Θ[l] (∏ i ∈ s, g i ·) :=
⟨.finsetProd fun i hi ↦ (h i hi).isBigO, .finsetProd fun i hi ↦ (h i hi).symm.isBigO⟩
theorem IsTheta.inv {f : α → 𝕜} {g : α → 𝕜'} (h : f =Θ[l] g) :
(fun x ↦ (f x)⁻¹) =Θ[l] fun x ↦ (g x)⁻¹ :=
⟨h.2.inv_rev h.1.eq_zero_imp, h.1.inv_rev h.2.eq_zero_imp⟩
@[simp]
theorem isTheta_inv {f : α → 𝕜} {g : α → 𝕜'} :
((fun x ↦ (f x)⁻¹) =Θ[l] fun x ↦ (g x)⁻¹) ↔ f =Θ[l] g :=
⟨fun h ↦ by simpa only [inv_inv] using h.inv, IsTheta.inv⟩
theorem IsTheta.div {f₁ f₂ : α → 𝕜} {g₁ g₂ : α → 𝕜'} (h₁ : f₁ =Θ[l] g₁) (h₂ : f₂ =Θ[l] g₂) :
(fun x ↦ f₁ x / f₂ x) =Θ[l] fun x ↦ g₁ x / g₂ x := by
simpa only [div_eq_mul_inv] using h₁.mul h₂.inv
theorem IsTheta.pow {f : α → 𝕜} {g : α → 𝕜'} (h : f =Θ[l] g) (n : ℕ) :
(fun x ↦ f x ^ n) =Θ[l] fun x ↦ g x ^ n :=
⟨h.1.pow n, h.2.pow n⟩
theorem IsTheta.zpow {f : α → 𝕜} {g : α → 𝕜'} (h : f =Θ[l] g) (n : ℤ) :
(fun x ↦ f x ^ n) =Θ[l] fun x ↦ g x ^ n := by
cases n
· simpa only [Int.ofNat_eq_coe, zpow_natCast] using h.pow _
· simpa only [zpow_negSucc] using (h.pow _).inv
theorem isTheta_const_const {c₁ : E''} {c₂ : F''} (h₁ : c₁ ≠ 0) (h₂ : c₂ ≠ 0) :
(fun _ : α ↦ c₁) =Θ[l] fun _ ↦ c₂ :=
⟨isBigO_const_const _ h₂ _, isBigO_const_const _ h₁ _⟩
@[simp]
theorem isTheta_const_const_iff [NeBot l] {c₁ : E''} {c₂ : F''} :
((fun _ : α ↦ c₁) =Θ[l] fun _ ↦ c₂) ↔ (c₁ = 0 ↔ c₂ = 0) := by
simpa only [IsTheta, isBigO_const_const_iff, ← iff_def] using Iff.comm
| @[simp]
theorem isTheta_zero_left : (fun _ ↦ (0 : E')) =Θ[l] g'' ↔ g'' =ᶠ[l] 0 := by
simp only [IsTheta, isBigO_zero, isBigO_zero_right_iff, true_and]
| Mathlib/Analysis/Asymptotics/Theta.lean | 251 | 253 |
/-
Copyright (c) 2022 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta
-/
import Mathlib.Analysis.SpecialFunctions.Log.Basic
import Mathlib.Data.Nat.Cast.Field
import Mathlib.NumberTheory.ArithmeticFunction
/-!
# The von Mangoldt Function
In this file we define the von Mangoldt function: the function on natural numbers that returns
`log p` if the input can be expressed as `p^k` for a prime `p`.
## Main Results
The main definition for this file is
- `ArithmeticFunction.vonMangoldt`: The von Mangoldt function `Λ`.
We then prove the classical summation property of the von Mangoldt function in
`ArithmeticFunction.vonMangoldt_sum`, that `∑ i ∈ n.divisors, Λ i = Real.log n`, and use this
to deduce alternative expressions for the von Mangoldt function via Möbius inversion, see
`ArithmeticFunction.sum_moebius_mul_log_eq`.
## Notation
We use the standard notation `Λ` to represent the von Mangoldt function.
It is accessible in the locales `ArithmeticFunction` (like the notations for other arithmetic
functions) and also in the locale `ArithmeticFunction.vonMangoldt`.
-/
namespace ArithmeticFunction
open Finset Nat
open scoped ArithmeticFunction
/-- `log` as an arithmetic function `ℕ → ℝ`. Note this is in the `ArithmeticFunction`
namespace to indicate that it is bundled as an `ArithmeticFunction` rather than being the usual
real logarithm. -/
noncomputable def log : ArithmeticFunction ℝ :=
⟨fun n => Real.log n, by simp⟩
@[simp]
theorem log_apply {n : ℕ} : log n = Real.log n :=
rfl
/--
The `vonMangoldt` function is the function on natural numbers that returns `log p` if the input can
be expressed as `p^k` for a prime `p`.
In the case when `n` is a prime power, `Nat.minFac` will give the appropriate prime, as it is the
smallest prime factor.
In the `ArithmeticFunction` locale, we have the notation `Λ` for this function.
This is also available in the `ArithmeticFunction.vonMangoldt` locale, allowing for selective
access to the notation.
-/
noncomputable def vonMangoldt : ArithmeticFunction ℝ :=
⟨fun n => if IsPrimePow n then Real.log (minFac n) else 0, if_neg not_isPrimePow_zero⟩
@[inherit_doc] scoped[ArithmeticFunction] notation "Λ" => ArithmeticFunction.vonMangoldt
@[inherit_doc] scoped[ArithmeticFunction.vonMangoldt] notation "Λ" =>
ArithmeticFunction.vonMangoldt
theorem vonMangoldt_apply {n : ℕ} : Λ n = if IsPrimePow n then Real.log (minFac n) else 0 :=
rfl
@[simp]
theorem vonMangoldt_apply_one : Λ 1 = 0 := by simp [vonMangoldt_apply]
@[simp]
theorem vonMangoldt_nonneg {n : ℕ} : 0 ≤ Λ n := by
rw [vonMangoldt_apply]
split_ifs
| · exact Real.log_nonneg (one_le_cast.2 (Nat.minFac_pos n))
| Mathlib/NumberTheory/VonMangoldt.lean | 79 | 79 |
/-
Copyright (c) 2019 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Nat.Choose.Basic
import Mathlib.Data.List.FinRange
import Mathlib.Data.List.Perm.Basic
import Mathlib.Data.List.Lex
import Mathlib.Data.List.Induction
/-! # sublists
`List.Sublists` gives a list of all (not necessarily contiguous) sublists of a list.
This file contains basic results on this function.
-/
universe u v w
variable {α : Type u} {β : Type v} {γ : Type w}
open Nat
namespace List
/-! ### sublists -/
@[simp]
theorem sublists'_nil : sublists' (@nil α) = [[]] :=
rfl
@[simp]
theorem sublists'_singleton (a : α) : sublists' [a] = [[], [a]] :=
rfl
/-- Auxiliary helper definition for `sublists'` -/
def sublists'Aux (a : α) (r₁ r₂ : List (List α)) : List (List α) :=
r₁.foldl (init := r₂) fun r l => r ++ [a :: l]
theorem sublists'Aux_eq_array_foldl (a : α) : ∀ (r₁ r₂ : List (List α)),
sublists'Aux a r₁ r₂ = ((r₁.toArray).foldl (init := r₂.toArray)
(fun r l => r.push (a :: l))).toList := by
intro r₁ r₂
rw [sublists'Aux, Array.foldl_toList]
have := List.foldl_hom Array.toList (g₁ := fun r l => r.push (a :: l))
(g₂ := fun r l => r ++ [a :: l]) (l := r₁) (init := r₂.toArray) (by simp)
simpa using this
theorem sublists'_eq_sublists'Aux (l : List α) :
sublists' l = l.foldr (fun a r => sublists'Aux a r r) [[]] := by
simp only [sublists', sublists'Aux_eq_array_foldl]
rw [← List.foldr_hom Array.toList]
· intros _ _; congr
theorem sublists'Aux_eq_map (a : α) (r₁ : List (List α)) : ∀ (r₂ : List (List α)),
sublists'Aux a r₁ r₂ = r₂ ++ map (cons a) r₁ :=
List.reverseRecOn r₁ (fun _ => by simp [sublists'Aux]) fun r₁ l ih r₂ => by
rw [map_append, map_singleton, ← append_assoc, ← ih, sublists'Aux, foldl_append, foldl]
simp [sublists'Aux]
@[simp 900]
theorem sublists'_cons (a : α) (l : List α) :
sublists' (a :: l) = sublists' l ++ map (cons a) (sublists' l) := by
simp [sublists'_eq_sublists'Aux, foldr_cons, sublists'Aux_eq_map]
@[simp]
theorem mem_sublists' {s t : List α} : s ∈ sublists' t ↔ s <+ t := by
induction' t with a t IH generalizing s
· simp only [sublists'_nil, mem_singleton]
exact ⟨fun h => by rw [h], eq_nil_of_sublist_nil⟩
simp only [sublists'_cons, mem_append, IH, mem_map]
constructor <;> intro h
· rcases h with (h | ⟨s, h, rfl⟩)
· exact sublist_cons_of_sublist _ h
· exact h.cons_cons _
· obtain - | ⟨-, h⟩ | ⟨-, h⟩ := h
· exact Or.inl h
· exact Or.inr ⟨_, h, rfl⟩
@[simp]
theorem length_sublists' : ∀ l : List α, length (sublists' l) = 2 ^ length l
| [] => rfl
| a :: l => by
simp +arith only [sublists'_cons, length_append, length_sublists' l,
length_map, length, Nat.pow_succ']
@[simp]
theorem sublists_nil : sublists (@nil α) = [[]] :=
rfl
@[simp]
theorem sublists_singleton (a : α) : sublists [a] = [[], [a]] :=
rfl
/-- Auxiliary helper function for `sublists` -/
def sublistsAux (a : α) (r : List (List α)) : List (List α) :=
r.foldl (init := []) fun r l => r ++ [l, a :: l]
theorem sublistsAux_eq_array_foldl :
sublistsAux = fun (a : α) (r : List (List α)) =>
(r.toArray.foldl (init := #[])
fun r l => (r.push l).push (a :: l)).toList := by
funext a r
simp only [sublistsAux, Array.foldl_toList, Array.mkEmpty]
have := foldl_hom Array.toList (g₁ := fun r l => (r.push l).push (a :: l))
(g₂ := fun r l => r ++ [l, a :: l]) (l := r) (init := #[]) (by simp)
simpa using this
theorem sublistsAux_eq_flatMap :
sublistsAux = fun (a : α) (r : List (List α)) => r.flatMap fun l => [l, a :: l] :=
funext fun a => funext fun r =>
List.reverseRecOn r
(by simp [sublistsAux])
(fun r l ih => by
rw [flatMap_append, ← ih, flatMap_singleton, sublistsAux, foldl_append]
simp [sublistsAux])
@[csimp] theorem sublists_eq_sublistsFast : @sublists = @sublistsFast := by
ext α l : 2
trans l.foldr sublistsAux [[]]
· rw [sublistsAux_eq_flatMap, sublists]
· simp only [sublistsFast, sublistsAux_eq_array_foldl, Array.foldr_toList]
rw [← foldr_hom Array.toList]
· intros _ _; congr
theorem sublists_append (l₁ l₂ : List α) :
sublists (l₁ ++ l₂) = (sublists l₂) >>= (fun x => (sublists l₁).map (· ++ x)) := by
simp only [sublists, foldr_append]
induction l₁ with
| nil => simp
| cons a l₁ ih =>
rw [foldr_cons, ih]
simp [List.flatMap, flatten_flatten, Function.comp_def]
theorem sublists_cons (a : α) (l : List α) :
sublists (a :: l) = sublists l >>= (fun x => [x, a :: x]) :=
show sublists ([a] ++ l) = _ by
rw [sublists_append]
simp only [sublists_singleton, map_cons, bind_eq_flatMap, nil_append, cons_append, map_nil]
@[simp]
theorem sublists_concat (l : List α) (a : α) :
sublists (l ++ [a]) = sublists l ++ map (fun x => x ++ [a]) (sublists l) := by
rw [sublists_append, sublists_singleton, bind_eq_flatMap, flatMap_cons, flatMap_cons, flatMap_nil,
map_id'' append_nil, append_nil]
theorem sublists_reverse (l : List α) : sublists (reverse l) = map reverse (sublists' l) := by
induction' l with hd tl ih <;> [rfl;
simp only [reverse_cons, sublists_append, sublists'_cons, map_append, ih, sublists_singleton,
map_eq_map, bind_eq_flatMap, map_map, flatMap_cons, append_nil, flatMap_nil,
Function.comp_def]]
theorem sublists_eq_sublists' (l : List α) : sublists l = map reverse (sublists' (reverse l)) := by
rw [← sublists_reverse, reverse_reverse]
theorem sublists'_reverse (l : List α) : sublists' (reverse l) = map reverse (sublists l) := by
simp only [sublists_eq_sublists', map_map, map_id'' reverse_reverse, Function.comp_def]
theorem sublists'_eq_sublists (l : List α) : sublists' l = map reverse (sublists (reverse l)) := by
rw [← sublists'_reverse, reverse_reverse]
@[simp]
theorem mem_sublists {s t : List α} : s ∈ sublists t ↔ s <+ t := by
rw [← reverse_sublist, ← mem_sublists', sublists'_reverse,
mem_map_of_injective reverse_injective]
@[simp]
theorem length_sublists (l : List α) : length (sublists l) = 2 ^ length l := by
simp only [sublists_eq_sublists', length_map, length_sublists', length_reverse]
theorem map_pure_sublist_sublists (l : List α) : map pure l <+ sublists l := by
induction' l using reverseRecOn with l a ih <;> simp only [map, map_append, sublists_concat]
· simp only [sublists_nil, sublist_cons_self]
exact ((append_sublist_append_left _).2 <|
singleton_sublist.2 <| mem_map.2 ⟨[], mem_sublists.2 (nil_sublist _), by rfl⟩).trans
((append_sublist_append_right _).2 ih)
/-! ### sublistsLen -/
/-- Auxiliary function to construct the list of all sublists of a given length. Given an
integer `n`, a list `l`, a function `f` and an auxiliary list `L`, it returns the list made of
`f` applied to all sublists of `l` of length `n`, concatenated with `L`. -/
def sublistsLenAux : ℕ → List α → (List α → β) → List β → List β
| 0, _, f, r => f [] :: r
| _ + 1, [], _, r => r
| n + 1, a :: l, f, r => sublistsLenAux (n + 1) l f (sublistsLenAux n l (f ∘ List.cons a) r)
/-- The list of all sublists of a list `l` that are of length `n`. For instance, for
`l = [0, 1, 2, 3]` and `n = 2`, one gets
`[[2, 3], [1, 3], [1, 2], [0, 3], [0, 2], [0, 1]]`. -/
def sublistsLen (n : ℕ) (l : List α) : List (List α) :=
sublistsLenAux n l id []
theorem sublistsLenAux_append :
∀ (n : ℕ) (l : List α) (f : List α → β) (g : β → γ) (r : List β) (s : List γ),
sublistsLenAux n l (g ∘ f) (r.map g ++ s) = (sublistsLenAux n l f r).map g ++ s
| 0, l, f, g, r, s => by unfold sublistsLenAux; simp
| _ + 1, [], _, _, _, _ => rfl
| n + 1, a :: l, f, g, r, s => by
unfold sublistsLenAux
simp only [show (g ∘ f) ∘ List.cons a = g ∘ f ∘ List.cons a by rfl, sublistsLenAux_append,
sublistsLenAux_append]
theorem sublistsLenAux_eq (l : List α) (n) (f : List α → β) (r) :
sublistsLenAux n l f r = (sublistsLen n l).map f ++ r := by
rw [sublistsLen, ← sublistsLenAux_append]; rfl
theorem sublistsLenAux_zero (l : List α) (f : List α → β) (r) :
sublistsLenAux 0 l f r = f [] :: r := by cases l <;> rfl
@[simp]
theorem sublistsLen_zero (l : List α) : sublistsLen 0 l = [[]] :=
sublistsLenAux_zero _ _ _
@[simp]
theorem sublistsLen_succ_nil (n) : sublistsLen (n + 1) (@nil α) = [] :=
rfl
@[simp]
theorem sublistsLen_succ_cons (n) (a : α) (l) :
sublistsLen (n + 1) (a :: l) = sublistsLen (n + 1) l ++ (sublistsLen n l).map (cons a) := by
rw [sublistsLen, sublistsLenAux, sublistsLenAux_eq, sublistsLenAux_eq, map_id,
append_nil]; rfl
theorem sublistsLen_one (l : List α) : sublistsLen 1 l = l.reverse.map ([·]) :=
l.rec (by rw [sublistsLen_succ_nil, reverse_nil, map_nil]) fun a s ih ↦ by
rw [sublistsLen_succ_cons, ih, reverse_cons, map_append, sublistsLen_zero]; rfl
@[simp]
theorem length_sublistsLen :
∀ (n) (l : List α), length (sublistsLen n l) = Nat.choose (length l) n
| 0, l => by simp
| _ + 1, [] => by simp
| n + 1, a :: l => by
rw [sublistsLen_succ_cons, length_append, length_sublistsLen (n+1) l,
length_map, length_sublistsLen n l, length_cons, Nat.choose_succ_succ, Nat.add_comm]
theorem sublistsLen_sublist_sublists' :
∀ (n) (l : List α), sublistsLen n l <+ sublists' l
| 0, l => by simp
| _ + 1, [] => nil_sublist _
| n + 1, a :: l => by
| rw [sublistsLen_succ_cons, sublists'_cons]
exact (sublistsLen_sublist_sublists' _ _).append ((sublistsLen_sublist_sublists' _ _).map _)
theorem sublistsLen_sublist_of_sublist (n) {l₁ l₂ : List α} (h : l₁ <+ l₂) :
sublistsLen n l₁ <+ sublistsLen n l₂ := by
induction' n with n IHn generalizing l₁ l₂; · simp
induction h with
| slnil => rfl
| cons a _ IH =>
| Mathlib/Data/List/Sublists.lean | 244 | 252 |
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn, Heather Macbeth
-/
import Mathlib.Topology.FiberBundle.Trivialization
import Mathlib.Topology.Order.LeftRightNhds
/-!
# Fiber bundles
Mathematically, a (topological) fiber bundle with fiber `F` over a base `B` is a space projecting on
`B` for which the fibers are all homeomorphic to `F`, such that the local situation around each
point is a direct product.
In our formalism, a fiber bundle is by definition the type `Bundle.TotalSpace F E` where
`E : B → Type*` is a function associating to `x : B` the fiber over `x`. This type
`Bundle.TotalSpace F E` is a type of pairs `⟨proj : B, snd : E proj⟩`.
To have a fiber bundle structure on `Bundle.TotalSpace F E`, one should
additionally have the following data:
* `F` should be a topological space;
* There should be a topology on `Bundle.TotalSpace F E`, for which the projection to `B` is
a fiber bundle with fiber `F` (in particular, each fiber `E x` is homeomorphic to `F`);
* For each `x`, the fiber `E x` should be a topological space, and the injection
from `E x` to `Bundle.TotalSpace F E` should be an embedding;
* There should be a distinguished set of bundle trivializations, the "trivialization atlas"
* There should be a choice of bundle trivialization at each point, which belongs to this atlas.
If all these conditions are satisfied, we register the typeclass `FiberBundle F E`.
It is in general nontrivial to construct a fiber bundle. A way is to start from the knowledge of
how changes of local trivializations act on the fiber. From this, one can construct the total space
of the bundle and its topology by a suitable gluing construction. The main content of this file is
an implementation of this construction: starting from an object of type
`FiberBundleCore` registering the trivialization changes, one gets the corresponding
fiber bundle and projection.
Similarly we implement the object `FiberPrebundle` which allows to define a topological
fiber bundle from trivializations given as partial equivalences with minimum additional properties.
## Main definitions
### Basic definitions
* `FiberBundle F E` : Structure saying that `E : B → Type*` is a fiber bundle with fiber `F`.
### Construction of a bundle from trivializations
* `Bundle.TotalSpace F E` is the type of pairs `(proj : B, snd : E proj)`. We can use the extra
argument `F` to construct topology on the total space.
* `FiberBundleCore ι B F` : structure registering how changes of coordinates act
on the fiber `F` above open subsets of `B`, where local trivializations are indexed by `ι`.
Let `Z : FiberBundleCore ι B F`. Then we define
* `Z.Fiber x` : the fiber above `x`, homeomorphic to `F` (and defeq to `F` as a type).
* `Z.TotalSpace` : the total space of `Z`, defined as `Bundle.TotalSpace F Z.Fiber` with a custom
topology.
* `Z.proj` : projection from `Z.TotalSpace` to `B`. It is continuous.
* `Z.localTriv i` : for `i : ι`, bundle trivialization above the set `Z.baseSet i`, which is an
open set in `B`.
* `FiberPrebundle F E` : structure registering a cover of prebundle trivializations
and requiring that the relative transition maps are partial homeomorphisms.
* `FiberPrebundle.totalSpaceTopology a` : natural topology of the total space, making
the prebundle into a bundle.
## Implementation notes
### Data vs mixins
For both fiber and vector bundles, one faces a choice: should the definition state the *existence*
of local trivializations (a propositional typeclass), or specify a fixed atlas of trivializations (a
typeclass containing data)?
In their initial mathlib implementations, both fiber and vector bundles were defined
propositionally. For vector bundles, this turns out to be mathematically wrong: in infinite
dimension, the transition function between two trivializations is not automatically continuous as a
map from the base `B` to the endomorphisms `F →L[R] F` of the fiber (considered with the
operator-norm topology), and so the definition needs to be modified by restricting consideration to
a family of trivializations (constituting the data) which are all mutually-compatible in this sense.
The PRs https://github.com/leanprover-community/mathlib4/pull/13052 and https://github.com/leanprover-community/mathlib4/pull/13175 implemented this change.
There is still the choice about whether to hold this data at the level of fiber bundles or of vector
bundles. As of PR https://github.com/leanprover-community/mathlib4/pull/17505, the data is all held in `FiberBundle`, with `VectorBundle` a
(propositional) mixin stating fiberwise-linearity.
This allows bundles to carry instances of typeclasses in which the scalar field, `R`, does not
appear as a parameter. Notably, we would like a vector bundle over `R` with fiber `F` over base `B`
to be a `ChartedSpace (B × F)`, with the trivializations providing the charts. This would be a
dangerous instance for typeclass inference, because `R` does not appear as a parameter in
`ChartedSpace (B × F)`. But if the data of the trivializations is held in `FiberBundle`, then a
fiber bundle with fiber `F` over base `B` can be a `ChartedSpace (B × F)`, and this is safe for
typeclass inference.
We expect that this choice of definition will also streamline constructions of fiber bundles with
similar underlying structure (e.g., the same bundle being both a real and complex vector bundle).
### Core construction
A fiber bundle with fiber `F` over a base `B` is a family of spaces isomorphic to `F`,
indexed by `B`, which is locally trivial in the following sense: there is a covering of `B` by open
sets such that, on each such open set `s`, the bundle is isomorphic to `s × F`.
To construct a fiber bundle formally, the main data is what happens when one changes trivializations
from `s × F` to `s' × F` on `s ∩ s'`: one should get a family of homeomorphisms of `F`, depending
continuously on the base point, satisfying basic compatibility conditions (cocycle property).
Useful classes of bundles can then be specified by requiring that these homeomorphisms of `F`
belong to some subgroup, preserving some structure (the "structure group of the bundle"): then
these structures are inherited by the fibers of the bundle.
Given such trivialization change data (encoded below in a structure called
`FiberBundleCore`), one can construct the fiber bundle. The intrinsic canonical
mathematical construction is the following.
The fiber above `x` is the disjoint union of `F` over all trivializations, modulo the gluing
identifications: one gets a fiber which is isomorphic to `F`, but non-canonically
(each choice of one of the trivializations around `x` gives such an isomorphism). Given a
trivialization over a set `s`, one gets an isomorphism between `s × F` and `proj^{-1} s`, by using
the identification corresponding to this trivialization. One chooses the topology on the bundle that
makes all of these into homeomorphisms.
For the practical implementation, it turns out to be more convenient to avoid completely the
gluing and quotienting construction above, and to declare above each `x` that the fiber is `F`,
but thinking that it corresponds to the `F` coming from the choice of one trivialization around `x`.
This has several practical advantages:
* without any work, one gets a topological space structure on the fiber. And if `F` has more
structure it is inherited for free by the fiber.
* In the case of the tangent bundle of manifolds, this implies that on vector spaces the derivative
(from `F` to `F`) and the manifold derivative (from `TangentSpace I x` to `TangentSpace I' (f x)`)
are equal.
A drawback is that some silly constructions will typecheck: in the case of the tangent bundle, one
can add two vectors in different tangent spaces (as they both are elements of `F` from the point of
view of Lean). To solve this, one could mark the tangent space as irreducible, but then one would
lose the identification of the tangent space to `F` with `F`. There is however a big advantage of
this situation: even if Lean can not check that two basepoints are defeq, it will accept the fact
that the tangent spaces are the same. For instance, if two maps `f` and `g` are locally inverse to
each other, one can express that the composition of their derivatives is the identity of
`TangentSpace I x`. One could fear issues as this composition goes from `TangentSpace I x` to
`TangentSpace I (g (f x))` (which should be the same, but should not be obvious to Lean
as it does not know that `g (f x) = x`). As these types are the same to Lean (equal to `F`), there
are in fact no dependent type difficulties here!
For this construction of a fiber bundle from a `FiberBundleCore`, we should thus
choose for each `x` one specific trivialization around it. We include this choice in the definition
of the `FiberBundleCore`, as it makes some constructions more
functorial and it is a nice way to say that the trivializations cover the whole space `B`.
With this definition, the type of the fiber bundle space constructed from the core data is
`Bundle.TotalSpace F (fun b : B ↦ F)`, but the topology is not the product one, in general.
We also take the indexing type (indexing all the trivializations) as a parameter to the fiber bundle
core: it could always be taken as a subtype of all the maps from open subsets of `B` to continuous
maps of `F`, but in practice it will sometimes be something else. For instance, on a manifold, one
will use the set of charts as a good parameterization for the trivializations of the tangent bundle.
Or for the pullback of a `FiberBundleCore`, the indexing type will be the same as
for the initial bundle.
## Tags
Fiber bundle, topological bundle, structure group
-/
variable {ι B F X : Type*} [TopologicalSpace X]
open TopologicalSpace Filter Set Bundle Topology
/-! ### General definition of fiber bundles -/
section FiberBundle
variable (F)
variable [TopologicalSpace B] [TopologicalSpace F] (E : B → Type*)
[TopologicalSpace (TotalSpace F E)] [∀ b, TopologicalSpace (E b)]
/-- A (topological) fiber bundle with fiber `F` over a base `B` is a space projecting on `B`
for which the fibers are all homeomorphic to `F`, such that the local situation around each point
is a direct product. -/
class FiberBundle where
totalSpaceMk_isInducing' : ∀ b : B, IsInducing (@TotalSpace.mk B F E b)
trivializationAtlas' : Set (Trivialization F (π F E))
trivializationAt' : B → Trivialization F (π F E)
mem_baseSet_trivializationAt' : ∀ b : B, b ∈ (trivializationAt' b).baseSet
trivialization_mem_atlas' : ∀ b : B, trivializationAt' b ∈ trivializationAtlas'
namespace FiberBundle
variable [FiberBundle F E] (b : B)
theorem totalSpaceMk_isInducing : IsInducing (@TotalSpace.mk B F E b) := totalSpaceMk_isInducing' b
@[deprecated (since := "2024-10-28")] alias totalSpaceMk_inducing := totalSpaceMk_isInducing
/-- Atlas of a fiber bundle. -/
abbrev trivializationAtlas : Set (Trivialization F (π F E)) := trivializationAtlas'
/-- Trivialization of a fiber bundle at a point. -/
abbrev trivializationAt : Trivialization F (π F E) := trivializationAt' b
theorem mem_baseSet_trivializationAt : b ∈ (trivializationAt F E b).baseSet :=
mem_baseSet_trivializationAt' b
theorem trivialization_mem_atlas : trivializationAt F E b ∈ trivializationAtlas F E :=
trivialization_mem_atlas' b
end FiberBundle
export FiberBundle (totalSpaceMk_isInducing trivializationAtlas trivializationAt
mem_baseSet_trivializationAt trivialization_mem_atlas)
variable {F}
variable {E}
/-- Given a type `E` equipped with a fiber bundle structure, this is a `Prop` typeclass
for trivializations of `E`, expressing that a trivialization is in the designated atlas for the
bundle. This is needed because lemmas about the linearity of trivializations or the continuity (as
functions to `F →L[R] F`, where `F` is the model fiber) of the transition functions are only
expected to hold for trivializations in the designated atlas. -/
@[mk_iff]
class MemTrivializationAtlas [FiberBundle F E] (e : Trivialization F (π F E)) : Prop where
out : e ∈ trivializationAtlas F E
instance [FiberBundle F E] (b : B) : MemTrivializationAtlas (trivializationAt F E b) where
out := trivialization_mem_atlas F E b
namespace FiberBundle
variable (F)
variable [FiberBundle F E]
theorem map_proj_nhds (x : TotalSpace F E) : map (π F E) (𝓝 x) = 𝓝 x.proj :=
(trivializationAt F E x.proj).map_proj_nhds <|
(trivializationAt F E x.proj).mem_source.2 <| mem_baseSet_trivializationAt F E x.proj
variable (E)
/-- The projection from a fiber bundle to its base is continuous. -/
@[continuity]
theorem continuous_proj : Continuous (π F E) :=
continuous_iff_continuousAt.2 fun x => (map_proj_nhds F x).le
/-- The projection from a fiber bundle to its base is an open map. -/
theorem isOpenMap_proj : IsOpenMap (π F E) :=
IsOpenMap.of_nhds_le fun x => (map_proj_nhds F x).ge
/-- The projection from a fiber bundle with a nonempty fiber to its base is a surjective
map. -/
theorem surjective_proj [Nonempty F] : Function.Surjective (π F E) := fun b =>
let ⟨p, _, hpb⟩ :=
(trivializationAt F E b).proj_surjOn_baseSet (mem_baseSet_trivializationAt F E b)
⟨p, hpb⟩
/-- The projection from a fiber bundle with a nonempty fiber to its base is a quotient
map. -/
theorem isQuotientMap_proj [Nonempty F] : IsQuotientMap (π F E) :=
(isOpenMap_proj F E).isQuotientMap (continuous_proj F E) (surjective_proj F E)
@[deprecated (since := "2024-10-22")]
alias quotientMap_proj := isQuotientMap_proj
theorem continuous_totalSpaceMk (x : B) : Continuous (@TotalSpace.mk B F E x) :=
(totalSpaceMk_isInducing F E x).continuous
theorem totalSpaceMk_isEmbedding (x : B) : IsEmbedding (@TotalSpace.mk B F E x) :=
⟨totalSpaceMk_isInducing F E x, TotalSpace.mk_injective x⟩
@[deprecated (since := "2024-10-26")]
alias totalSpaceMk_embedding := totalSpaceMk_isEmbedding
theorem totalSpaceMk_isClosedEmbedding [T1Space B] (x : B) :
IsClosedEmbedding (@TotalSpace.mk B F E x) :=
⟨totalSpaceMk_isEmbedding F E x, by
rw [TotalSpace.range_mk]
exact isClosed_singleton.preimage <| continuous_proj F E⟩
variable {E F}
@[simp, mfld_simps]
theorem mem_trivializationAt_proj_source {x : TotalSpace F E} :
x ∈ (trivializationAt F E x.proj).source :=
(Trivialization.mem_source _).mpr <| mem_baseSet_trivializationAt F E x.proj
theorem trivializationAt_proj_fst {x : TotalSpace F E} :
((trivializationAt F E x.proj) x).1 = x.proj :=
Trivialization.coe_fst' _ <| mem_baseSet_trivializationAt F E x.proj
variable (F)
open Trivialization
/-- Characterization of continuous functions (at a point, within a set) into a fiber bundle. -/
theorem continuousWithinAt_totalSpace (f : X → TotalSpace F E) {s : Set X} {x₀ : X} :
ContinuousWithinAt f s x₀ ↔
ContinuousWithinAt (fun x => (f x).proj) s x₀ ∧
ContinuousWithinAt (fun x => ((trivializationAt F E (f x₀).proj) (f x)).2) s x₀ :=
(trivializationAt F E (f x₀).proj).tendsto_nhds_iff mem_trivializationAt_proj_source
/-- Characterization of continuous functions (at a point) into a fiber bundle. -/
theorem continuousAt_totalSpace (f : X → TotalSpace F E) {x₀ : X} :
ContinuousAt f x₀ ↔
ContinuousAt (fun x => (f x).proj) x₀ ∧
ContinuousAt (fun x => ((trivializationAt F E (f x₀).proj) (f x)).2) x₀ :=
(trivializationAt F E (f x₀).proj).tendsto_nhds_iff mem_trivializationAt_proj_source
end FiberBundle
variable (F)
variable (E)
/-- If `E` is a fiber bundle over a conditionally complete linear order,
then it is trivial over any closed interval. -/
theorem FiberBundle.exists_trivialization_Icc_subset [ConditionallyCompleteLinearOrder B]
[OrderTopology B] [FiberBundle F E] (a b : B) :
∃ e : Trivialization F (π F E), Icc a b ⊆ e.baseSet := by
obtain ⟨ea, hea⟩ : ∃ ea : Trivialization F (π F E), a ∈ ea.baseSet :=
⟨trivializationAt F E a, mem_baseSet_trivializationAt F E a⟩
-- If `a < b`, then `[a, b] = ∅`, and the statement is trivial
rcases lt_or_le b a with _ | hab
· exact ⟨ea, by simp [*]⟩
/- Let `s` be the set of points `x ∈ [a, b]` such that `E` is trivializable over `[a, x]`.
We need to show that `b ∈ s`. Let `c = Sup s`. We will show that `c ∈ s` and `c = b`. -/
set s : Set B := { x ∈ Icc a b | ∃ e : Trivialization F (π F E), Icc a x ⊆ e.baseSet }
have ha : a ∈ s := ⟨left_mem_Icc.2 hab, ea, by simp [hea]⟩
have sne : s.Nonempty := ⟨a, ha⟩
have hsb : b ∈ upperBounds s := fun x hx => hx.1.2
have sbd : BddAbove s := ⟨b, hsb⟩
set c := sSup s
have hsc : IsLUB s c := isLUB_csSup sne sbd
have hc : c ∈ Icc a b := ⟨hsc.1 ha, hsc.2 hsb⟩
obtain ⟨-, ec : Trivialization F (π F E), hec : Icc a c ⊆ ec.baseSet⟩ : c ∈ s := by
rcases hc.1.eq_or_lt with heq | hlt
· rwa [← heq]
refine ⟨hc, ?_⟩
/- In order to show that `c ∈ s`, consider a trivialization `ec` of `proj` over a neighborhood
of `c`. Its base set includes `(c', c]` for some `c' ∈ [a, c)`. -/
obtain ⟨ec, hc⟩ : ∃ ec : Trivialization F (π F E), c ∈ ec.baseSet :=
⟨trivializationAt F E c, mem_baseSet_trivializationAt F E c⟩
obtain ⟨c', hc', hc'e⟩ : ∃ c' ∈ Ico a c, Ioc c' c ⊆ ec.baseSet :=
(mem_nhdsLE_iff_exists_mem_Ico_Ioc_subset hlt).1
(mem_nhdsWithin_of_mem_nhds <| IsOpen.mem_nhds ec.open_baseSet hc)
/- Since `c' < c = Sup s`, there exists `d ∈ s ∩ (c', c]`. Let `ead` be a trivialization of
`proj` over `[a, d]`. Then we can glue `ead` and `ec` into a trivialization over `[a, c]`. -/
obtain ⟨d, ⟨hdab, ead, had⟩, hd⟩ : ∃ d ∈ s, d ∈ Ioc c' c := hsc.exists_between hc'.2
refine ⟨ead.piecewiseLe ec d (had ⟨hdab.1, le_rfl⟩) (hc'e hd), subset_ite.2 ?_⟩
exact ⟨fun x hx => had ⟨hx.1.1, hx.2⟩, fun x hx => hc'e ⟨hd.1.trans (not_le.1 hx.2), hx.1.2⟩⟩
/- So, `c ∈ s`. Let `ec` be a trivialization of `proj` over `[a, c]`. If `c = b`, then we are
done. Otherwise we show that `proj` can be trivialized over a larger interval `[a, d]`,
`d ∈ (c, b]`, hence `c` is not an upper bound of `s`. -/
rcases hc.2.eq_or_lt with heq | hlt
· exact ⟨ec, heq ▸ hec⟩
rsuffices ⟨d, hdcb, hd⟩ : ∃ d ∈ Ioc c b, ∃ e : Trivialization F (π F E), Icc a d ⊆ e.baseSet
· exact ((hsc.1 ⟨⟨hc.1.trans hdcb.1.le, hdcb.2⟩, hd⟩).not_lt hdcb.1).elim
/- Since the base set of `ec` is open, it includes `[c, d)` (hence, `[a, d)`) for some
`d ∈ (c, b]`. -/
obtain ⟨d, hdcb, hd⟩ : ∃ d ∈ Ioc c b, Ico c d ⊆ ec.baseSet :=
(mem_nhdsGE_iff_exists_mem_Ioc_Ico_subset hlt).1
(mem_nhdsWithin_of_mem_nhds <| IsOpen.mem_nhds ec.open_baseSet (hec ⟨hc.1, le_rfl⟩))
have had : Ico a d ⊆ ec.baseSet := Ico_subset_Icc_union_Ico.trans (union_subset hec hd)
by_cases he : Disjoint (Iio d) (Ioi c)
· /- If `(c, d) = ∅`, then let `ed` be a trivialization of `proj` over a neighborhood of `d`.
Then the disjoint union of `ec` restricted to `(-∞, d)` and `ed` restricted to `(c, ∞)` is
a trivialization over `[a, d]`. -/
obtain ⟨ed, hed⟩ : ∃ ed : Trivialization F (π F E), d ∈ ed.baseSet :=
⟨trivializationAt F E d, mem_baseSet_trivializationAt F E d⟩
refine ⟨d, hdcb,
(ec.restrOpen (Iio d) isOpen_Iio).disjointUnion (ed.restrOpen (Ioi c) isOpen_Ioi)
(he.mono inter_subset_right inter_subset_right), fun x hx => ?_⟩
rcases hx.2.eq_or_lt with (rfl | hxd)
exacts [Or.inr ⟨hed, hdcb.1⟩, Or.inl ⟨had ⟨hx.1, hxd⟩, hxd⟩]
· /- If `(c, d)` is nonempty, then take `d' ∈ (c, d)`. Since the base set of `ec` includes
`[a, d)`, it includes `[a, d'] ⊆ [a, d)` as well. -/
rw [disjoint_left] at he
push_neg at he
rcases he with ⟨d', hdd' : d' < d, hd'c⟩
exact ⟨d', ⟨hd'c, hdd'.le.trans hdcb.2⟩, ec, (Icc_subset_Ico_right hdd').trans had⟩
end FiberBundle
/-! ### Core construction for constructing fiber bundles -/
/-- Core data defining a locally trivial bundle with fiber `F` over a topological
space `B`. Note that "bundle" is used in its mathematical sense. This is the (computer science)
bundled version, i.e., all the relevant data is contained in the following structure. A family of
local trivializations is indexed by a type `ι`, on open subsets `baseSet i` for each `i : ι`.
Trivialization changes from `i` to `j` are given by continuous maps `coordChange i j` from
`baseSet i ∩ baseSet j` to the set of homeomorphisms of `F`, but we express them as maps
`B → F → F` and require continuity on `(baseSet i ∩ baseSet j) × F` to avoid the topology on the
space of continuous maps on `F`. -/
structure FiberBundleCore (ι : Type*) (B : Type*) [TopologicalSpace B] (F : Type*)
[TopologicalSpace F] where
baseSet : ι → Set B
isOpen_baseSet : ∀ i, IsOpen (baseSet i)
indexAt : B → ι
mem_baseSet_at : ∀ x, x ∈ baseSet (indexAt x)
coordChange : ι → ι → B → F → F
coordChange_self : ∀ i, ∀ x ∈ baseSet i, ∀ v, coordChange i i x v = v
continuousOn_coordChange : ∀ i j,
ContinuousOn (fun p : B × F => coordChange i j p.1 p.2) ((baseSet i ∩ baseSet j) ×ˢ univ)
coordChange_comp : ∀ i j k, ∀ x ∈ baseSet i ∩ baseSet j ∩ baseSet k, ∀ v,
(coordChange j k x) (coordChange i j x v) = coordChange i k x v
namespace FiberBundleCore
variable [TopologicalSpace B] [TopologicalSpace F] (Z : FiberBundleCore ι B F)
/-- The index set of a fiber bundle core, as a convenience function for dot notation -/
@[nolint unusedArguments]
def Index (_Z : FiberBundleCore ι B F) := ι
/-- The base space of a fiber bundle core, as a convenience function for dot notation -/
@[nolint unusedArguments, reducible]
def Base (_Z : FiberBundleCore ι B F) := B
/-- The fiber of a fiber bundle core, as a convenience function for dot notation and
typeclass inference -/
@[nolint unusedArguments]
def Fiber (_ : FiberBundleCore ι B F) (_x : B) := F
instance topologicalSpaceFiber (x : B) : TopologicalSpace (Z.Fiber x) := ‹_›
/-- The total space of the fiber bundle, as a convenience function for dot notation.
It is by definition equal to `Bundle.TotalSpace F Z.Fiber`. -/
abbrev TotalSpace := Bundle.TotalSpace F Z.Fiber
/-- The projection from the total space of a fiber bundle core, on its base. -/
@[reducible, simp, mfld_simps]
def proj : Z.TotalSpace → B :=
Bundle.TotalSpace.proj
/-- Local homeomorphism version of the trivialization change. -/
def trivChange (i j : ι) : PartialHomeomorph (B × F) (B × F) where
source := (Z.baseSet i ∩ Z.baseSet j) ×ˢ univ
target := (Z.baseSet i ∩ Z.baseSet j) ×ˢ univ
toFun p := ⟨p.1, Z.coordChange i j p.1 p.2⟩
invFun p := ⟨p.1, Z.coordChange j i p.1 p.2⟩
map_source' p hp := by simpa using hp
map_target' p hp := by simpa using hp
left_inv' := by
rintro ⟨x, v⟩ hx
simp only [prodMk_mem_set_prod_eq, mem_inter_iff, and_true, mem_univ] at hx
dsimp only
rw [coordChange_comp, Z.coordChange_self]
exacts [hx.1, ⟨⟨hx.1, hx.2⟩, hx.1⟩]
right_inv' := by
rintro ⟨x, v⟩ hx
simp only [prodMk_mem_set_prod_eq, mem_inter_iff, and_true, mem_univ] at hx
dsimp only
rw [Z.coordChange_comp, Z.coordChange_self]
· exact hx.2
· simp [hx]
open_source := ((Z.isOpen_baseSet i).inter (Z.isOpen_baseSet j)).prod isOpen_univ
open_target := ((Z.isOpen_baseSet i).inter (Z.isOpen_baseSet j)).prod isOpen_univ
continuousOn_toFun := continuous_fst.continuousOn.prodMk (Z.continuousOn_coordChange i j)
continuousOn_invFun := by
simpa [inter_comm] using continuous_fst.continuousOn.prodMk (Z.continuousOn_coordChange j i)
@[simp, mfld_simps]
theorem mem_trivChange_source (i j : ι) (p : B × F) :
p ∈ (Z.trivChange i j).source ↔ p.1 ∈ Z.baseSet i ∩ Z.baseSet j := by
rw [trivChange, mem_prod]
simp
/-- Associate to a trivialization index `i : ι` the corresponding trivialization, i.e., a bijection
between `proj ⁻¹ (baseSet i)` and `baseSet i × F`. As the fiber above `x` is `F` but read in the
chart with index `index_at x`, the trivialization in the fiber above x is by definition the
coordinate change from i to `index_at x`, so it depends on `x`.
The local trivialization will ultimately be a partial homeomorphism. For now, we only introduce the
partial equivalence version, denoted with a prime.
In further developments, avoid this auxiliary version, and use `Z.local_triv` instead. -/
def localTrivAsPartialEquiv (i : ι) : PartialEquiv Z.TotalSpace (B × F) where
source := Z.proj ⁻¹' Z.baseSet i
target := Z.baseSet i ×ˢ univ
invFun p := ⟨p.1, Z.coordChange i (Z.indexAt p.1) p.1 p.2⟩
toFun p := ⟨p.1, Z.coordChange (Z.indexAt p.1) i p.1 p.2⟩
map_source' p hp := by
simpa only [Set.mem_preimage, and_true, Set.mem_univ, Set.prodMk_mem_set_prod_eq] using hp
map_target' p hp := by
simpa only [Set.mem_preimage, and_true, Set.mem_univ, Set.mem_prod] using hp
left_inv' := by
rintro ⟨x, v⟩ hx
replace hx : x ∈ Z.baseSet i := hx
dsimp only
rw [Z.coordChange_comp, Z.coordChange_self] <;> apply_rules [mem_baseSet_at, mem_inter]
right_inv' := by
rintro ⟨x, v⟩ hx
simp only [prodMk_mem_set_prod_eq, and_true, mem_univ] at hx
dsimp only
rw [Z.coordChange_comp, Z.coordChange_self]
exacts [hx, ⟨⟨hx, Z.mem_baseSet_at _⟩, hx⟩]
variable (i : ι)
theorem mem_localTrivAsPartialEquiv_source (p : Z.TotalSpace) :
p ∈ (Z.localTrivAsPartialEquiv i).source ↔ p.1 ∈ Z.baseSet i :=
Iff.rfl
theorem mem_localTrivAsPartialEquiv_target (p : B × F) :
p ∈ (Z.localTrivAsPartialEquiv i).target ↔ p.1 ∈ Z.baseSet i := by
rw [localTrivAsPartialEquiv, mem_prod]
simp only [and_true, mem_univ]
theorem localTrivAsPartialEquiv_apply (p : Z.TotalSpace) :
(Z.localTrivAsPartialEquiv i) p = ⟨p.1, Z.coordChange (Z.indexAt p.1) i p.1 p.2⟩ :=
rfl
/-- The composition of two local trivializations is the trivialization change Z.triv_change i j. -/
theorem localTrivAsPartialEquiv_trans (i j : ι) :
(Z.localTrivAsPartialEquiv i).symm.trans (Z.localTrivAsPartialEquiv j) ≈
(Z.trivChange i j).toPartialEquiv := by
constructor
· ext x
simp only [mem_localTrivAsPartialEquiv_target, mfld_simps]
rfl
| · rintro ⟨x, v⟩ hx
simp only [trivChange, localTrivAsPartialEquiv, PartialEquiv.symm,
Prod.mk_inj, prodMk_mem_set_prod_eq, PartialEquiv.trans_source, mem_inter_iff,
mem_preimage, proj, mem_univ, eq_self_iff_true, (· ∘ ·),
| Mathlib/Topology/FiberBundle/Basic.lean | 516 | 519 |
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Johannes Hölzl, Sander Dahmen, Kim Morrison
-/
import Mathlib.SetTheory.Cardinal.Cofinality
import Mathlib.LinearAlgebra.FreeModule.Finite.Basic
import Mathlib.LinearAlgebra.Dimension.StrongRankCondition
import Mathlib.LinearAlgebra.Dimension.Constructions
/-!
# Conditions for rank to be finite
Also contains characterization for when rank equals zero or rank equals one.
-/
noncomputable section
universe u v v' w
variable {R : Type u} {M M₁ : Type v} {M' : Type v'} {ι : Type w}
variable [Ring R] [AddCommGroup M] [AddCommGroup M'] [AddCommGroup M₁]
variable [Module R M] [Module R M'] [Module R M₁]
attribute [local instance] nontrivial_of_invariantBasisNumber
open Basis Cardinal Function Module Set Submodule
/-- If every finite set of linearly independent vectors has cardinality at most `n`,
then the same is true for arbitrary sets of linearly independent vectors.
-/
theorem linearIndependent_bounded_of_finset_linearIndependent_bounded {n : ℕ}
(H : ∀ s : Finset M, (LinearIndependent R fun i : s => (i : M)) → s.card ≤ n) :
∀ s : Set M, LinearIndependent R ((↑) : s → M) → #s ≤ n := by
intro s li
apply Cardinal.card_le_of
intro t
rw [← Finset.card_map (Embedding.subtype s)]
apply H
apply linearIndependent_finset_map_embedding_subtype _ li
theorem rank_le {n : ℕ}
(H : ∀ s : Finset M, (LinearIndependent R fun i : s => (i : M)) → s.card ≤ n) :
Module.rank R M ≤ n := by
rw [Module.rank_def]
apply ciSup_le'
rintro ⟨s, li⟩
exact linearIndependent_bounded_of_finset_linearIndependent_bounded H _ li
section RankZero
/-- See `rank_zero_iff` for a stronger version with `NoZeroSMulDivisor R M`. -/
lemma rank_eq_zero_iff :
Module.rank R M = 0 ↔ ∀ x : M, ∃ a : R, a ≠ 0 ∧ a • x = 0 := by
nontriviality R
constructor
· contrapose!
rintro ⟨x, hx⟩
rw [← Cardinal.one_le_iff_ne_zero]
have : LinearIndependent R (fun _ : Unit ↦ x) :=
linearIndependent_iff.mpr (fun l hl ↦ Finsupp.unique_ext <| not_not.mp fun H ↦
hx _ H ((Finsupp.linearCombination_unique _ _ _).symm.trans hl))
simpa using this.cardinal_lift_le_rank
· intro h
rw [← le_zero_iff, Module.rank_def]
apply ciSup_le'
intro ⟨s, hs⟩
rw [nonpos_iff_eq_zero, Cardinal.mk_eq_zero_iff, ← not_nonempty_iff]
rintro ⟨i : s⟩
obtain ⟨a, ha, ha'⟩ := h i
apply ha
simpa using DFunLike.congr_fun (linearIndependent_iff.mp hs (Finsupp.single i a) (by simpa)) i
theorem rank_pos_of_free [Module.Free R M] [Nontrivial M] :
0 < Module.rank R M :=
have := Module.nontrivial R M
(pos_of_ne_zero <| Cardinal.mk_ne_zero _).trans_le
(Free.chooseBasis R M).linearIndependent.cardinal_le_rank
variable [Nontrivial R]
section
variable [NoZeroSMulDivisors R M]
theorem rank_zero_iff_forall_zero :
Module.rank R M = 0 ↔ ∀ x : M, x = 0 := by
simp_rw [rank_eq_zero_iff, smul_eq_zero, and_or_left, not_and_self_iff, false_or,
exists_and_right, and_iff_right (exists_ne (0 : R))]
/-- See `rank_subsingleton` for the reason that `Nontrivial R` is needed.
Also see `rank_eq_zero_iff` for the version without `NoZeroSMulDivisor R M`. -/
theorem rank_zero_iff : Module.rank R M = 0 ↔ Subsingleton M :=
rank_zero_iff_forall_zero.trans (subsingleton_iff_forall_eq 0).symm
theorem rank_pos_iff_exists_ne_zero : 0 < Module.rank R M ↔ ∃ x : M, x ≠ 0 := by
rw [← not_iff_not]
simpa using rank_zero_iff_forall_zero
theorem rank_pos_iff_nontrivial : 0 < Module.rank R M ↔ Nontrivial M :=
rank_pos_iff_exists_ne_zero.trans (nontrivial_iff_exists_ne 0).symm
theorem rank_pos [Nontrivial M] : 0 < Module.rank R M :=
rank_pos_iff_nontrivial.mpr ‹_›
end
variable (R M)
/-- See `rank_subsingleton` that assumes `Subsingleton R` instead. -/
@[nontriviality]
theorem rank_subsingleton' [Subsingleton M] : Module.rank R M = 0 :=
rank_eq_zero_iff.mpr fun _ ↦ ⟨1, one_ne_zero, Subsingleton.elim _ _⟩
@[simp]
theorem rank_punit : Module.rank R PUnit = 0 := rank_subsingleton' _ _
@[simp]
theorem rank_bot : Module.rank R (⊥ : Submodule R M) = 0 := rank_subsingleton' _ _
variable {R M}
theorem exists_mem_ne_zero_of_rank_pos {s : Submodule R M} (h : 0 < Module.rank R s) :
∃ b : M, b ∈ s ∧ b ≠ 0 :=
exists_mem_ne_zero_of_ne_bot fun eq => by rw [eq, rank_bot] at h; exact lt_irrefl _ h
end RankZero
section Finite
theorem Module.finite_of_rank_eq_nat [Module.Free R M] {n : ℕ} (h : Module.rank R M = n) :
Module.Finite R M := by
nontriviality R
obtain ⟨⟨ι, b⟩⟩ := Module.Free.exists_basis (R := R) (M := M)
have := mk_lt_aleph0_iff.mp <|
b.linearIndependent.cardinal_le_rank |>.trans_eq h |>.trans_lt <| nat_lt_aleph0 n
exact Module.Finite.of_basis b
theorem Module.finite_of_rank_eq_zero [NoZeroSMulDivisors R M]
(h : Module.rank R M = 0) :
Module.Finite R M := by
nontriviality R
rw [rank_zero_iff] at h
infer_instance
theorem Module.finite_of_rank_eq_one [Module.Free R M] (h : Module.rank R M = 1) :
Module.Finite R M :=
Module.finite_of_rank_eq_nat <| h.trans Nat.cast_one.symm
section
variable [StrongRankCondition R]
/-- If a module has a finite dimension, all bases are indexed by a finite type. -/
theorem Basis.nonempty_fintype_index_of_rank_lt_aleph0 {ι : Type*} (b : Basis ι R M)
(h : Module.rank R M < ℵ₀) : Nonempty (Fintype ι) := by
rwa [← Cardinal.lift_lt, ← b.mk_eq_rank, Cardinal.lift_aleph0, Cardinal.lift_lt_aleph0,
Cardinal.lt_aleph0_iff_fintype] at h
/-- If a module has a finite dimension, all bases are indexed by a finite type. -/
noncomputable def Basis.fintypeIndexOfRankLtAleph0 {ι : Type*} (b : Basis ι R M)
(h : Module.rank R M < ℵ₀) : Fintype ι :=
Classical.choice (b.nonempty_fintype_index_of_rank_lt_aleph0 h)
/-- If a module has a finite dimension, all bases are indexed by a finite set. -/
theorem Basis.finite_index_of_rank_lt_aleph0 {ι : Type*} {s : Set ι} (b : Basis s R M)
(h : Module.rank R M < ℵ₀) : s.Finite :=
finite_def.2 (b.nonempty_fintype_index_of_rank_lt_aleph0 h)
end
namespace LinearIndependent
variable [StrongRankCondition R]
theorem cardinalMk_le_finrank [Module.Finite R M]
{ι : Type w} {b : ι → M} (h : LinearIndependent R b) : #ι ≤ finrank R M := by
rw [← lift_le.{max v w}]
simpa only [← finrank_eq_rank, lift_natCast, lift_le_nat_iff] using h.cardinal_lift_le_rank
@[deprecated (since := "2024-11-10")] alias cardinal_mk_le_finrank := cardinalMk_le_finrank
theorem fintype_card_le_finrank [Module.Finite R M]
{ι : Type*} [Fintype ι] {b : ι → M} (h : LinearIndependent R b) :
Fintype.card ι ≤ finrank R M := by
simpa using h.cardinalMk_le_finrank
theorem finset_card_le_finrank [Module.Finite R M]
{b : Finset M} (h : LinearIndependent R (fun x => x : b → M)) :
b.card ≤ finrank R M := by
rw [← Fintype.card_coe]
exact h.fintype_card_le_finrank
theorem lt_aleph0_of_finite {ι : Type w}
[Module.Finite R M] {v : ι → M} (h : LinearIndependent R v) : #ι < ℵ₀ := by
apply Cardinal.lift_lt.1
apply lt_of_le_of_lt
· apply h.cardinal_lift_le_rank
· rw [← finrank_eq_rank, Cardinal.lift_aleph0, Cardinal.lift_natCast]
apply Cardinal.nat_lt_aleph0
theorem finite [Module.Finite R M] {ι : Type*} {f : ι → M}
(h : LinearIndependent R f) : Finite ι :=
Cardinal.lt_aleph0_iff_finite.1 <| h.lt_aleph0_of_finite
theorem setFinite [Module.Finite R M] {b : Set M}
(h : LinearIndependent R fun x : b => (x : M)) : b.Finite :=
Cardinal.lt_aleph0_iff_set_finite.mp h.lt_aleph0_of_finite
end LinearIndependent
lemma exists_set_linearIndependent_of_lt_rank {n : Cardinal} (hn : n < Module.rank R M) :
∃ s : Set M, #s = n ∧ LinearIndepOn R id s := by
obtain ⟨⟨s, hs⟩, hs'⟩ := exists_lt_of_lt_ciSup' (hn.trans_eq (Module.rank_def R M))
obtain ⟨t, ht, ht'⟩ := le_mk_iff_exists_subset.mp hs'.le
exact ⟨t, ht', hs.mono ht⟩
lemma exists_finset_linearIndependent_of_le_rank {n : ℕ} (hn : n ≤ Module.rank R M) :
∃ s : Finset M, s.card = n ∧ LinearIndepOn R id (s : Set M) := by
have := nonempty_linearIndependent_set
rcases hn.eq_or_lt with h | h
· obtain ⟨⟨s, hs⟩, hs'⟩ := Cardinal.exists_eq_natCast_of_iSup_eq _
(Cardinal.bddAbove_range _) _ (h.trans (Module.rank_def R M)).symm
have : Finite s := lt_aleph0_iff_finite.mp (hs' ▸ nat_lt_aleph0 n)
cases nonempty_fintype s
refine ⟨s.toFinset, by simpa using hs', by simpa⟩
· obtain ⟨s, hs, hs'⟩ := exists_set_linearIndependent_of_lt_rank h
have : Finite s := lt_aleph0_iff_finite.mp (hs ▸ nat_lt_aleph0 n)
cases nonempty_fintype s
exact ⟨s.toFinset, by simpa using hs, by simpa⟩
lemma exists_linearIndependent_of_le_rank {n : ℕ} (hn : n ≤ Module.rank R M) :
∃ f : Fin n → M, LinearIndependent R f :=
have ⟨_, hs, hs'⟩ := exists_finset_linearIndependent_of_le_rank hn
⟨_, (linearIndependent_equiv (Finset.equivFinOfCardEq hs).symm).mpr hs'⟩
lemma natCast_le_rank_iff [Nontrivial R] {n : ℕ} :
n ≤ Module.rank R M ↔ ∃ f : Fin n → M, LinearIndependent R f :=
⟨exists_linearIndependent_of_le_rank,
fun H ↦ by simpa using H.choose_spec.cardinal_lift_le_rank⟩
lemma natCast_le_rank_iff_finset [Nontrivial R] {n : ℕ} :
n ≤ Module.rank R M ↔ ∃ s : Finset M, s.card = n ∧ LinearIndependent R ((↑) : s → M) :=
⟨exists_finset_linearIndependent_of_le_rank,
fun ⟨s, h₁, h₂⟩ ↦ by simpa [h₁] using h₂.cardinal_le_rank⟩
lemma exists_finset_linearIndependent_of_le_finrank {n : ℕ} (hn : n ≤ finrank R M) :
∃ s : Finset M, s.card = n ∧ LinearIndependent R ((↑) : s → M) := by
by_cases h : finrank R M = 0
· rw [le_zero_iff.mp (hn.trans_eq h)]
exact ⟨∅, rfl, by convert linearIndependent_empty R M using 2 <;> aesop⟩
exact exists_finset_linearIndependent_of_le_rank
((Nat.cast_le.mpr hn).trans_eq (cast_toNat_of_lt_aleph0 (toNat_ne_zero.mp h).2))
lemma exists_linearIndependent_of_le_finrank {n : ℕ} (hn : n ≤ finrank R M) :
∃ f : Fin n → M, LinearIndependent R f :=
have ⟨_, hs, hs'⟩ := exists_finset_linearIndependent_of_le_finrank hn
⟨_, (linearIndependent_equiv (Finset.equivFinOfCardEq hs).symm).mpr hs'⟩
variable [Module.Finite R M] [StrongRankCondition R] in
theorem Module.Finite.not_linearIndependent_of_infinite {ι : Type*} [Infinite ι]
(v : ι → M) : ¬LinearIndependent R v := mt LinearIndependent.finite <| @not_finite _ _
section
variable [NoZeroSMulDivisors R M]
theorem iSupIndep.subtype_ne_bot_le_rank [Nontrivial R]
{V : ι → Submodule R M} (hV : iSupIndep V) :
Cardinal.lift.{v} #{ i : ι // V i ≠ ⊥ } ≤ Cardinal.lift.{w} (Module.rank R M) := by
set I := { i : ι // V i ≠ ⊥ }
have hI : ∀ i : I, ∃ v ∈ V i, v ≠ (0 : M) := by
intro i
rw [← Submodule.ne_bot_iff]
exact i.prop
choose v hvV hv using hI
have : LinearIndependent R v := (hV.comp Subtype.coe_injective).linearIndependent _ hvV hv
exact this.cardinal_lift_le_rank
@[deprecated (since := "2024-11-24")]
alias CompleteLattice.Independent.subtype_ne_bot_le_rank := iSupIndep.subtype_ne_bot_le_rank
variable [Module.Finite R M] [StrongRankCondition R]
theorem iSupIndep.subtype_ne_bot_le_finrank_aux
{p : ι → Submodule R M} (hp : iSupIndep p) :
#{ i // p i ≠ ⊥ } ≤ (finrank R M : Cardinal.{w}) := by
suffices Cardinal.lift.{v} #{ i // p i ≠ ⊥ } ≤ Cardinal.lift.{v} (finrank R M : Cardinal.{w}) by
rwa [Cardinal.lift_le] at this
calc
Cardinal.lift.{v} #{ i // p i ≠ ⊥ } ≤ Cardinal.lift.{w} (Module.rank R M) :=
hp.subtype_ne_bot_le_rank
_ = Cardinal.lift.{w} (finrank R M : Cardinal.{v}) := by rw [finrank_eq_rank]
_ = Cardinal.lift.{v} (finrank R M : Cardinal.{w}) := by simp
/-- If `p` is an independent family of submodules of a `R`-finite module `M`, then the
number of nontrivial subspaces in the family `p` is finite. -/
noncomputable def iSupIndep.fintypeNeBotOfFiniteDimensional
{p : ι → Submodule R M} (hp : iSupIndep p) :
Fintype { i : ι // p i ≠ ⊥ } := by
suffices #{ i // p i ≠ ⊥ } < (ℵ₀ : Cardinal.{w}) by
rw [Cardinal.lt_aleph0_iff_fintype] at this
exact this.some
refine lt_of_le_of_lt hp.subtype_ne_bot_le_finrank_aux ?_
simp [Cardinal.nat_lt_aleph0]
/-- If `p` is an independent family of submodules of a `R`-finite module `M`, then the
number of nontrivial subspaces in the family `p` is bounded above by the dimension of `M`.
Note that the `Fintype` hypothesis required here can be provided by
`iSupIndep.fintypeNeBotOfFiniteDimensional`. -/
theorem iSupIndep.subtype_ne_bot_le_finrank
{p : ι → Submodule R M} (hp : iSupIndep p) [Fintype { i // p i ≠ ⊥ }] :
Fintype.card { i // p i ≠ ⊥ } ≤ finrank R M := by simpa using hp.subtype_ne_bot_le_finrank_aux
end
variable [Module.Finite R M] [StrongRankCondition R]
section
open Finset
/-- If a finset has cardinality larger than the rank of a module,
then there is a nontrivial linear relation amongst its elements. -/
theorem Module.exists_nontrivial_relation_of_finrank_lt_card {t : Finset M}
(h : finrank R M < t.card) : ∃ f : M → R, ∑ e ∈ t, f e • e = 0 ∧ ∃ x ∈ t, f x ≠ 0 := by
obtain ⟨g, sum, z, nonzero⟩ := Fintype.not_linearIndependent_iff.mp
(mt LinearIndependent.finset_card_le_finrank h.not_le)
refine ⟨Subtype.val.extend g 0, ?_, z, z.2, by rwa [Subtype.val_injective.extend_apply]⟩
rw [← Finset.sum_finset_coe]; convert sum; apply Subtype.val_injective.extend_apply
/-- If a finset has cardinality larger than `finrank + 1`,
then there is a nontrivial linear relation amongst its elements,
such that the coefficients of the relation sum to zero. -/
theorem Module.exists_nontrivial_relation_sum_zero_of_finrank_succ_lt_card
{t : Finset M} (h : finrank R M + 1 < t.card) :
∃ f : M → R, ∑ e ∈ t, f e • e = 0 ∧ ∑ e ∈ t, f e = 0 ∧ ∃ x ∈ t, f x ≠ 0 := by
-- Pick an element x₀ ∈ t,
obtain ⟨x₀, x₀_mem⟩ := card_pos.1 ((Nat.succ_pos _).trans h)
-- and apply the previous lemma to the {xᵢ - x₀}
let shift : M ↪ M := ⟨(· - x₀), sub_left_injective⟩
classical
let t' := (t.erase x₀).map shift
have h' : finrank R M < t'.card := by
rw [card_map, card_erase_of_mem x₀_mem]
exact Nat.lt_pred_iff.mpr h
-- to obtain a function `g`.
obtain ⟨g, gsum, x₁, x₁_mem, nz⟩ := exists_nontrivial_relation_of_finrank_lt_card h'
-- Then obtain `f` by translating back by `x₀`,
-- and setting the value of `f` at `x₀` to ensure `∑ e ∈ t, f e = 0`.
let f : M → R := fun z ↦ if z = x₀ then -∑ z ∈ t.erase x₀, g (z - x₀) else g (z - x₀)
refine ⟨f, ?_, ?_, ?_⟩
-- After this, it's a matter of verifying the properties,
-- based on the corresponding properties for `g`.
· rw [sum_map, Embedding.coeFn_mk] at gsum
simp_rw [f, ← t.sum_erase_add _ x₀_mem, if_pos, neg_smul, sum_smul,
← sub_eq_add_neg, ← sum_sub_distrib, ← gsum, smul_sub]
refine sum_congr rfl fun x x_mem ↦ ?_
rw [if_neg (mem_erase.mp x_mem).1]
· simp_rw [f, ← t.sum_erase_add _ x₀_mem, if_pos, add_neg_eq_zero]
exact sum_congr rfl fun x x_mem ↦ if_neg (mem_erase.mp x_mem).1
· obtain ⟨x₁, x₁_mem', rfl⟩ := Finset.mem_map.mp x₁_mem
have := mem_erase.mp x₁_mem'
exact ⟨x₁, by
simpa only [f, Embedding.coeFn_mk, sub_add_cancel, this.2, true_and, if_neg this.1]⟩
end
end Finite
section FinrankZero
section
variable [Nontrivial R]
/-- A (finite dimensional) space that is a subsingleton has zero `finrank`. -/
@[nontriviality]
theorem Module.finrank_zero_of_subsingleton [Subsingleton M] :
finrank R M = 0 := by
rw [finrank, rank_subsingleton', map_zero]
lemma LinearIndependent.finrank_eq_zero_of_infinite {ι} [Infinite ι] {v : ι → M}
(hv : LinearIndependent R v) : finrank R M = 0 := toNat_eq_zero.mpr <| .inr hv.aleph0_le_rank
section
variable [NoZeroSMulDivisors R M]
/-- A finite dimensional space is nontrivial if it has positive `finrank`. -/
theorem Module.nontrivial_of_finrank_pos (h : 0 < finrank R M) : Nontrivial M :=
rank_pos_iff_nontrivial.mp (lt_rank_of_lt_finrank h)
/-- A finite dimensional space is nontrivial if it has `finrank` equal to the successor of a
natural number. -/
theorem Module.nontrivial_of_finrank_eq_succ {n : ℕ}
(hn : finrank R M = n.succ) : Nontrivial M :=
nontrivial_of_finrank_pos (R := R) (by rw [hn]; exact n.succ_pos)
end
variable (R M)
@[simp]
theorem finrank_bot : finrank R (⊥ : Submodule R M) = 0 :=
finrank_eq_of_rank_eq (rank_bot _ _)
end
section StrongRankCondition
variable [StrongRankCondition R] [Module.Finite R M]
/-- A finite rank torsion-free module has positive `finrank` iff it has a nonzero element. -/
theorem Module.finrank_pos_iff_exists_ne_zero [NoZeroSMulDivisors R M] :
0 < finrank R M ↔ ∃ x : M, x ≠ 0 := by
rw [← @rank_pos_iff_exists_ne_zero R M, ← finrank_eq_rank]
norm_cast
/-- An `R`-finite torsion-free module has positive `finrank` iff it is nontrivial. -/
theorem Module.finrank_pos_iff [NoZeroSMulDivisors R M] :
0 < finrank R M ↔ Nontrivial M := by
rw [← rank_pos_iff_nontrivial (R := R), ← finrank_eq_rank]
norm_cast
/-- A nontrivial finite dimensional space has positive `finrank`. -/
theorem Module.finrank_pos [NoZeroSMulDivisors R M] [h : Nontrivial M] :
0 < finrank R M :=
finrank_pos_iff.mpr h
/-- See `Module.finrank_zero_iff`
for the stronger version with `NoZeroSMulDivisors R M`. -/
theorem Module.finrank_eq_zero_iff :
finrank R M = 0 ↔ ∀ x : M, ∃ a : R, a ≠ 0 ∧ a • x = 0 := by
rw [← rank_eq_zero_iff (R := R), ← finrank_eq_rank]
norm_cast
/-- A finite dimensional space has zero `finrank` iff it is a subsingleton.
This is the `finrank` version of `rank_zero_iff`. -/
theorem Module.finrank_zero_iff [NoZeroSMulDivisors R M] :
| finrank R M = 0 ↔ Subsingleton M := by
rw [← rank_zero_iff (R := R), ← finrank_eq_rank]
norm_cast
/-- Similar to `rank_quotient_add_rank_le` but for `finrank` and a finite `M`. -/
| Mathlib/LinearAlgebra/Dimension/Finite.lean | 437 | 441 |
/-
Copyright (c) 2020 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison
-/
import Mathlib.AlgebraicGeometry.Spec
import Mathlib.Algebra.Category.Ring.Constructions
import Mathlib.CategoryTheory.Elementwise
/-!
# The category of schemes
A scheme is a locally ringed space such that every point is contained in some open set
where there is an isomorphism of presheaves between the restriction to that open set,
and the structure sheaf of `Spec R`, for some commutative ring `R`.
A morphism of schemes is just a morphism of the underlying locally ringed spaces.
-/
-- Explicit universe annotations were used in this file to improve performance https://github.com/leanprover-community/mathlib4/issues/12737
universe u
noncomputable section
open TopologicalSpace
open CategoryTheory
open TopCat
open Opposite
namespace AlgebraicGeometry
/-- We define `Scheme` as an `X : LocallyRingedSpace`,
along with a proof that every point has an open neighbourhood `U`
so that the restriction of `X` to `U` is isomorphic,
as a locally ringed space, to `Spec.toLocallyRingedSpace.obj (op R)`
for some `R : CommRingCat`.
-/
structure Scheme extends LocallyRingedSpace where
local_affine :
∀ x : toLocallyRingedSpace,
∃ (U : OpenNhds x) (R : CommRingCat),
Nonempty
(toLocallyRingedSpace.restrict U.isOpenEmbedding ≅ Spec.toLocallyRingedSpace.obj (op R))
namespace Scheme
instance : CoeSort Scheme Type* where
coe X := X.carrier
/-- The type of open sets of a scheme. -/
abbrev Opens (X : Scheme) : Type* := TopologicalSpace.Opens X
/-- A morphism between schemes is a morphism between the underlying locally ringed spaces. -/
structure Hom (X Y : Scheme)
extends toLRSHom' : X.toLocallyRingedSpace.Hom Y.toLocallyRingedSpace where
/-- Cast a morphism of schemes into morphisms of local ringed spaces. -/
abbrev Hom.toLRSHom {X Y : Scheme.{u}} (f : X.Hom Y) :
X.toLocallyRingedSpace ⟶ Y.toLocallyRingedSpace :=
f.toLRSHom'
/-- See Note [custom simps projection] -/
def Hom.Simps.toLRSHom {X Y : Scheme.{u}} (f : X.Hom Y) :
X.toLocallyRingedSpace ⟶ Y.toLocallyRingedSpace :=
f.toLRSHom
initialize_simps_projections Hom (toLRSHom' → toLRSHom)
/-- Schemes are a full subcategory of locally ringed spaces.
-/
instance : Category Scheme where
Hom := Hom
id X := Hom.mk (𝟙 X.toLocallyRingedSpace)
comp f g := Hom.mk (f.toLRSHom ≫ g.toLRSHom)
/-- `f ⁻¹ᵁ U` is notation for `(Opens.map f.base).obj U`,
the preimage of an open set `U` under `f`. -/
scoped[AlgebraicGeometry] notation3:90 f:91 " ⁻¹ᵁ " U:90 =>
@Prefunctor.obj (Scheme.Opens _) _ (Scheme.Opens _) _
(Opens.map (f : Scheme.Hom _ _).base).toPrefunctor U
/-- `Γ(X, U)` is notation for `X.presheaf.obj (op U)`. -/
scoped[AlgebraicGeometry] notation3 "Γ(" X ", " U ")" =>
(PresheafedSpace.presheaf (SheafedSpace.toPresheafedSpace
(LocallyRingedSpace.toSheafedSpace (Scheme.toLocallyRingedSpace X)))).obj
(op (α := Scheme.Opens _) U)
instance {X : Scheme.{u}} : Subsingleton Γ(X, ⊥) :=
CommRingCat.subsingleton_of_isTerminal X.sheaf.isTerminalOfEmpty
@[continuity, fun_prop]
lemma Hom.continuous {X Y : Scheme} (f : X.Hom Y) : Continuous f.base := f.base.hom.2
/-- The structure sheaf of a scheme. -/
protected abbrev sheaf (X : Scheme) :=
X.toSheafedSpace.sheaf
namespace Hom
variable {X Y : Scheme.{u}} (f : Hom X Y) {U U' : Y.Opens} {V V' : X.Opens}
/-- Given a morphism of schemes `f : X ⟶ Y`, and open `U ⊆ Y`,
this is the induced map `Γ(Y, U) ⟶ Γ(X, f ⁻¹ᵁ U)`. -/
abbrev app (U : Y.Opens) : Γ(Y, U) ⟶ Γ(X, f ⁻¹ᵁ U) :=
f.c.app (op U)
/-- Given a morphism of schemes `f : X ⟶ Y`,
this is the induced map `Γ(Y, ⊤) ⟶ Γ(X, ⊤)`. -/
abbrev appTop : Γ(Y, ⊤) ⟶ Γ(X, ⊤) :=
f.app ⊤
@[reassoc]
lemma naturality (i : op U' ⟶ op U) :
Y.presheaf.map i ≫ f.app U = f.app U' ≫ X.presheaf.map ((Opens.map f.base).map i.unop).op :=
f.c.naturality i
/-- Given a morphism of schemes `f : X ⟶ Y`, and open sets `U ⊆ Y`, `V ⊆ f ⁻¹' U`,
this is the induced map `Γ(Y, U) ⟶ Γ(X, V)`. -/
def appLE (U : Y.Opens) (V : X.Opens) (e : V ≤ f ⁻¹ᵁ U) : Γ(Y, U) ⟶ Γ(X, V) :=
f.app U ≫ X.presheaf.map (homOfLE e).op
@[reassoc (attr := simp)]
lemma appLE_map (e : V ≤ f ⁻¹ᵁ U) (i : op V ⟶ op V') :
f.appLE U V e ≫ X.presheaf.map i = f.appLE U V' (i.unop.le.trans e) := by
rw [Hom.appLE, Category.assoc, ← Functor.map_comp]
rfl
@[reassoc]
lemma appLE_map' (e : V ≤ f ⁻¹ᵁ U) (i : V = V') :
f.appLE U V' (i ▸ e) ≫ X.presheaf.map (eqToHom i).op = f.appLE U V e :=
appLE_map _ _ _
@[reassoc (attr := simp)]
lemma map_appLE (e : V ≤ f ⁻¹ᵁ U) (i : op U' ⟶ op U) :
Y.presheaf.map i ≫ f.appLE U V e =
f.appLE U' V (e.trans ((Opens.map f.base).map i.unop).le) := by
rw [Hom.appLE, f.naturality_assoc, ← Functor.map_comp]
rfl
@[reassoc]
lemma map_appLE' (e : V ≤ f ⁻¹ᵁ U) (i : U' = U) :
Y.presheaf.map (eqToHom i).op ≫ f.appLE U' V (i ▸ e) = f.appLE U V e :=
map_appLE _ _ _
lemma app_eq_appLE {U : Y.Opens} :
f.app U = f.appLE U _ le_rfl := by
simp [Hom.appLE]
lemma appLE_eq_app {U : Y.Opens} :
f.appLE U (f ⁻¹ᵁ U) le_rfl = f.app U :=
(app_eq_appLE f).symm
lemma appLE_congr (e : V ≤ f ⁻¹ᵁ U) (e₁ : U = U') (e₂ : V = V')
(P : ∀ {R S : CommRingCat.{u}} (_ : R ⟶ S), Prop) :
P (f.appLE U V e) ↔ P (f.appLE U' V' (e₁ ▸ e₂ ▸ e)) := by
subst e₁; subst e₂; rfl
/-- A morphism of schemes `f : X ⟶ Y` induces a local ring homomorphism from
`Y.presheaf.stalk (f x)` to `X.presheaf.stalk x` for any `x : X`. -/
def stalkMap (x : X) : Y.presheaf.stalk (f.base x) ⟶ X.presheaf.stalk x :=
f.toLRSHom.stalkMap x
@[ext (iff := false)]
protected lemma ext {f g : X ⟶ Y} (h_base : f.base = g.base)
(h_app : ∀ U, f.app U ≫ X.presheaf.map
(eqToHom congr((Opens.map $h_base.symm).obj U)).op = g.app U) : f = g := by
cases f; cases g; congr 1
exact LocallyRingedSpace.Hom.ext' <| SheafedSpace.ext _ _ h_base
(TopCat.Presheaf.ext fun U ↦ by simpa using h_app U)
/-- An alternative ext lemma for scheme morphisms. -/
protected lemma ext' {f g : X ⟶ Y} (h : f.toLRSHom = g.toLRSHom) : f = g := by
cases f; cases g; congr 1
lemma preimage_iSup {ι} (U : ι → Opens Y) : f ⁻¹ᵁ iSup U = ⨆ i, f ⁻¹ᵁ U i :=
Opens.ext (by simp)
lemma preimage_iSup_eq_top {ι} {U : ι → Opens Y} (hU : iSup U = ⊤) :
⨆ i, f ⁻¹ᵁ U i = ⊤ := f.preimage_iSup U ▸ hU ▸ rfl
lemma preimage_le_preimage_of_le {U U' : Y.Opens} (hUU' : U ≤ U') :
f ⁻¹ᵁ U ≤ f ⁻¹ᵁ U' :=
fun _ ha ↦ hUU' ha
end Hom
@[simp]
lemma preimage_comp {X Y Z : Scheme.{u}} (f : X ⟶ Y) (g : Y ⟶ Z) (U) :
(f ≫ g) ⁻¹ᵁ U = f ⁻¹ᵁ g ⁻¹ᵁ U := rfl
/-- The forgetful functor from `Scheme` to `LocallyRingedSpace`. -/
@[simps!]
def forgetToLocallyRingedSpace : Scheme ⥤ LocallyRingedSpace where
obj := toLocallyRingedSpace
map := Hom.toLRSHom
/-- The forget functor `Scheme ⥤ LocallyRingedSpace` is fully faithful. -/
@[simps preimage_toLRSHom]
def fullyFaithfulForgetToLocallyRingedSpace :
forgetToLocallyRingedSpace.FullyFaithful where
preimage := Hom.mk
instance : forgetToLocallyRingedSpace.Full :=
fullyFaithfulForgetToLocallyRingedSpace.full
instance : forgetToLocallyRingedSpace.Faithful :=
fullyFaithfulForgetToLocallyRingedSpace.faithful
/-- The forgetful functor from `Scheme` to `TopCat`. -/
@[simps!]
def forgetToTop : Scheme ⥤ TopCat :=
Scheme.forgetToLocallyRingedSpace ⋙ LocallyRingedSpace.forgetToTop
/-- An isomorphism of schemes induces a homeomorphism of the underlying topological spaces. -/
noncomputable def homeoOfIso {X Y : Scheme.{u}} (e : X ≅ Y) : X ≃ₜ Y :=
TopCat.homeoOfIso (forgetToTop.mapIso e)
@[simp]
lemma homeoOfIso_symm {X Y : Scheme} (e : X ≅ Y) :
(homeoOfIso e).symm = homeoOfIso e.symm := rfl
@[simp]
lemma homeoOfIso_apply {X Y : Scheme} (e : X ≅ Y) (x : X) :
homeoOfIso e x = e.hom.base x := rfl
alias _root_.CategoryTheory.Iso.schemeIsoToHomeo := homeoOfIso
/-- An isomorphism of schemes induces a homeomorphism of the underlying topological spaces. -/
noncomputable def Hom.homeomorph {X Y : Scheme.{u}} (f : X.Hom Y) [IsIso (C := Scheme) f] :
X ≃ₜ Y :=
(asIso f).schemeIsoToHomeo
@[simp]
lemma Hom.homeomorph_apply {X Y : Scheme.{u}} (f : X.Hom Y) [IsIso (C := Scheme) f] (x) :
f.homeomorph x = f.base x := rfl
-- Porting note: Lean seems not able to find this coercion any more
instance hasCoeToTopCat : CoeOut Scheme TopCat where
coe X := X.carrier
-- Porting note: added this unification hint just in case
/-- forgetful functor to `TopCat` is the same as coercion -/
unif_hint forgetToTop_obj_eq_coe (X : Scheme) where ⊢
forgetToTop.obj X ≟ (X : TopCat)
@[simp]
theorem id.base (X : Scheme) : (𝟙 X :).base = 𝟙 _ :=
rfl
@[simp]
theorem id_app {X : Scheme} (U : X.Opens) :
(𝟙 X :).app U = 𝟙 _ := rfl
@[simp]
theorem id_appTop {X : Scheme} :
(𝟙 X :).appTop = 𝟙 _ :=
rfl
@[reassoc]
theorem comp_toLRSHom {X Y Z : Scheme} (f : X ⟶ Y) (g : Y ⟶ Z) :
(f ≫ g).toLRSHom = f.toLRSHom ≫ g.toLRSHom :=
rfl
@[simp, reassoc] -- reassoc lemma does not need `simp`
theorem comp_coeBase {X Y Z : Scheme} (f : X ⟶ Y) (g : Y ⟶ Z) :
(f ≫ g).base = f.base ≫ g.base :=
rfl
@[reassoc]
theorem comp_base {X Y Z : Scheme} (f : X ⟶ Y) (g : Y ⟶ Z) :
(f ≫ g).base = f.base ≫ g.base :=
rfl
theorem comp_base_apply {X Y Z : Scheme} (f : X ⟶ Y) (g : Y ⟶ Z) (x : X) :
(f ≫ g).base x = g.base (f.base x) := by
simp
@[simp, reassoc] -- reassoc lemma does not need `simp`
theorem comp_app {X Y Z : Scheme} (f : X ⟶ Y) (g : Y ⟶ Z) (U) :
(f ≫ g).app U = g.app U ≫ f.app _ :=
rfl
@[simp, reassoc] -- reassoc lemma does not need `simp`
theorem comp_appTop {X Y Z : Scheme} (f : X ⟶ Y) (g : Y ⟶ Z) :
(f ≫ g).appTop = g.appTop ≫ f.appTop :=
rfl
theorem appLE_comp_appLE {X Y Z : Scheme} (f : X ⟶ Y) (g : Y ⟶ Z) (U V W e₁ e₂) :
g.appLE U V e₁ ≫ f.appLE V W e₂ =
(f ≫ g).appLE U W (e₂.trans ((Opens.map f.base).map (homOfLE e₁)).le) := by
dsimp [Hom.appLE]
rw [Category.assoc, f.naturality_assoc, ← Functor.map_comp]
rfl
@[simp, reassoc] -- reassoc lemma does not need `simp`
theorem comp_appLE {X Y Z : Scheme} (f : X ⟶ Y) (g : Y ⟶ Z) (U V e) :
(f ≫ g).appLE U V e = g.app U ≫ f.appLE _ V e := by
rw [g.app_eq_appLE, appLE_comp_appLE]
theorem congr_app {X Y : Scheme} {f g : X ⟶ Y} (e : f = g) (U) :
f.app U = g.app U ≫ X.presheaf.map (eqToHom (by subst e; rfl)).op := by
subst e; dsimp; simp
theorem app_eq {X Y : Scheme} (f : X ⟶ Y) {U V : Y.Opens} (e : U = V) :
f.app U =
Y.presheaf.map (eqToHom e.symm).op ≫
f.app V ≫
X.presheaf.map (eqToHom (congr_arg (Opens.map f.base).obj e)).op := by
rw [← IsIso.inv_comp_eq, ← Functor.map_inv, f.naturality]
cases e
rfl
theorem eqToHom_c_app {X Y : Scheme} (e : X = Y) (U) :
(eqToHom e).app U = eqToHom (by subst e; rfl) := by subst e; rfl
-- Porting note: in `AffineScheme.lean` file, `eqToHom_op` can't be used in `(e)rw` or `simp(_rw)`
-- when terms get very complicated. See `AlgebraicGeometry.IsAffineOpen.isLocalization_stalk_aux`.
lemma presheaf_map_eqToHom_op (X : Scheme) (U V : X.Opens) (i : U = V) :
X.presheaf.map (eqToHom i).op = eqToHom (i ▸ rfl) := by
rw [eqToHom_op, eqToHom_map]
instance isIso_toLRSHom {X Y : Scheme} (f : X ⟶ Y) [IsIso f] : IsIso f.toLRSHom :=
forgetToLocallyRingedSpace.map_isIso f
instance isIso_base {X Y : Scheme.{u}} (f : X ⟶ Y) [IsIso f] : IsIso f.base :=
Scheme.forgetToTop.map_isIso f
-- Porting note: need an extra instance here.
instance {X Y : Scheme} (f : X ⟶ Y) [IsIso f] (U) : IsIso (f.c.app U) :=
haveI := PresheafedSpace.c_isIso_of_iso f.toPshHom
NatIso.isIso_app_of_isIso f.c _
instance {X Y : Scheme} (f : X ⟶ Y) [IsIso f] (U) : IsIso (f.app U) :=
haveI := PresheafedSpace.c_isIso_of_iso f.toPshHom
NatIso.isIso_app_of_isIso f.c _
@[simp]
theorem inv_app {X Y : Scheme} (f : X ⟶ Y) [IsIso f] (U : X.Opens) :
(inv f).app U =
X.presheaf.map (eqToHom (show (f ≫ inv f) ⁻¹ᵁ U = U by rw [IsIso.hom_inv_id]; rfl)).op ≫
inv (f.app ((inv f) ⁻¹ᵁ U)) := by
rw [IsIso.eq_comp_inv, ← Scheme.comp_app, Scheme.congr_app (IsIso.hom_inv_id f),
Scheme.id_app, Category.id_comp]
theorem inv_appTop {X Y : Scheme} (f : X ⟶ Y) [IsIso f] :
(inv f).appTop = inv (f.appTop) := by simp
@[deprecated (since := "2024-11-23")] alias inv_app_top := inv_appTop
end Scheme
/-- The spectrum of a commutative ring, as a scheme.
-/
def Spec (R : CommRingCat) : Scheme where
local_affine _ := ⟨⟨⊤, trivial⟩, R, ⟨(Spec.toLocallyRingedSpace.obj (op R)).restrictTopIso⟩⟩
toLocallyRingedSpace := Spec.locallyRingedSpaceObj R
theorem Spec_toLocallyRingedSpace (R : CommRingCat) :
(Spec R).toLocallyRingedSpace = Spec.locallyRingedSpaceObj R :=
rfl
/-- The induced map of a ring homomorphism on the ring spectra, as a morphism of schemes.
-/
def Spec.map {R S : CommRingCat} (f : R ⟶ S) : Spec S ⟶ Spec R :=
⟨Spec.locallyRingedSpaceMap f⟩
@[simp]
theorem Spec.map_id (R : CommRingCat) : Spec.map (𝟙 R) = 𝟙 (Spec R) :=
Scheme.Hom.ext' <| Spec.locallyRingedSpaceMap_id R
@[reassoc, simp]
theorem Spec.map_comp {R S T : CommRingCat} (f : R ⟶ S) (g : S ⟶ T) :
Spec.map (f ≫ g) = Spec.map g ≫ Spec.map f :=
Scheme.Hom.ext' <| Spec.locallyRingedSpaceMap_comp f g
/-- The spectrum, as a contravariant functor from commutative rings to schemes. -/
@[simps]
protected def Scheme.Spec : CommRingCatᵒᵖ ⥤ Scheme where
obj R := Spec (unop R)
map f := Spec.map f.unop
map_id R := by simp
map_comp f g := by simp
lemma Spec.map_eqToHom {R S : CommRingCat} (e : R = S) :
Spec.map (eqToHom e) = eqToHom (e ▸ rfl) := by
subst e; exact Spec.map_id _
instance {R S : CommRingCat} (f : R ⟶ S) [IsIso f] : IsIso (Spec.map f) :=
inferInstanceAs (IsIso <| Scheme.Spec.map f.op)
@[simp]
lemma Spec.map_inv {R S : CommRingCat} (f : R ⟶ S) [IsIso f] :
Spec.map (inv f) = inv (Spec.map f) := by
show Scheme.Spec.map (inv f).op = inv (Scheme.Spec.map f.op)
rw [op_inv, ← Scheme.Spec.map_inv]
section
variable {R S : CommRingCat.{u}} (f : R ⟶ S)
-- The lemmas below are not tagged simp to respect the abstraction.
lemma Spec_carrier (R : CommRingCat.{u}) : (Spec R).carrier = PrimeSpectrum R := rfl
lemma Spec_sheaf (R : CommRingCat.{u}) : (Spec R).sheaf = Spec.structureSheaf R := rfl
lemma Spec_presheaf (R : CommRingCat.{u}) : (Spec R).presheaf = (Spec.structureSheaf R).1 := rfl
lemma Spec.map_base : (Spec.map f).base = ofHom (PrimeSpectrum.comap f.hom) := rfl
lemma Spec.map_base_apply (x : Spec S) : (Spec.map f).base x = PrimeSpectrum.comap f.hom x := rfl
lemma Spec.map_app (U) :
(Spec.map f).app U =
CommRingCat.ofHom (StructureSheaf.comap f.hom U (Spec.map f ⁻¹ᵁ U) le_rfl) := rfl
lemma Spec.map_appLE {U V} (e : U ≤ Spec.map f ⁻¹ᵁ V) :
(Spec.map f).appLE V U e = CommRingCat.ofHom (StructureSheaf.comap f.hom V U e) := rfl
instance {A : CommRingCat} [Nontrivial A] : Nonempty (Spec A) :=
inferInstanceAs <| Nonempty (PrimeSpectrum A)
end
namespace Scheme
theorem isEmpty_of_commSq {W X Y S : Scheme.{u}} {f : X ⟶ S} {g : Y ⟶ S}
{i : W ⟶ X} {j : W ⟶ Y} (h : CommSq i j f g)
(H : Disjoint (Set.range f.base) (Set.range g.base)) : IsEmpty W :=
⟨fun x ↦ (Set.disjoint_iff_inter_eq_empty.mp H).le
⟨⟨i.base x, congr($(h.w).base x)⟩, ⟨j.base x, rfl⟩⟩⟩
/-- The empty scheme. -/
@[simps]
def empty : Scheme where
carrier := TopCat.of PEmpty
presheaf := (CategoryTheory.Functor.const _).obj (CommRingCat.of PUnit)
IsSheaf := Presheaf.isSheaf_of_isTerminal _ CommRingCat.punitIsTerminal
isLocalRing x := PEmpty.elim x
local_affine x := PEmpty.elim x
instance : EmptyCollection Scheme :=
⟨empty⟩
instance : Inhabited Scheme :=
⟨∅⟩
/-- The global sections, notated Gamma.
-/
def Γ : Schemeᵒᵖ ⥤ CommRingCat :=
Scheme.forgetToLocallyRingedSpace.op ⋙ LocallyRingedSpace.Γ
theorem Γ_def : Γ = Scheme.forgetToLocallyRingedSpace.op ⋙ LocallyRingedSpace.Γ :=
rfl
@[simp]
theorem Γ_obj (X : Schemeᵒᵖ) : Γ.obj X = Γ(unop X, ⊤) :=
rfl
theorem Γ_obj_op (X : Scheme) : Γ.obj (op X) = Γ(X, ⊤) :=
rfl
@[simp]
theorem Γ_map {X Y : Schemeᵒᵖ} (f : X ⟶ Y) : Γ.map f = f.unop.appTop :=
rfl
theorem Γ_map_op {X Y : Scheme} (f : X ⟶ Y) : Γ.map f.op = f.appTop :=
rfl
/--
The counit (`SpecΓIdentity.inv.op`) of the adjunction `Γ ⊣ Spec` as an isomorphism.
This is almost never needed in practical use cases. Use `ΓSpecIso` instead.
-/
def SpecΓIdentity : Scheme.Spec.rightOp ⋙ Scheme.Γ ≅ 𝟭 _ :=
Iso.symm <| NatIso.ofComponents.{u,u,u+1,u+1}
(fun R => asIso (StructureSheaf.toOpen R ⊤))
(fun {X Y} f => by convert Spec_Γ_naturality (R := X) (S := Y) f)
variable (R : CommRingCat.{u})
/-- The global sections of `Spec R` is isomorphic to `R`. -/
def ΓSpecIso : Γ(Spec R, ⊤) ≅ R := SpecΓIdentity.app R
@[simp] lemma SpecΓIdentity_app : SpecΓIdentity.app R = ΓSpecIso R := rfl
@[simp] lemma SpecΓIdentity_hom_app : SpecΓIdentity.hom.app R = (ΓSpecIso R).hom := rfl
@[simp] lemma SpecΓIdentity_inv_app : SpecΓIdentity.inv.app R = (ΓSpecIso R).inv := rfl
@[reassoc (attr := simp)]
lemma ΓSpecIso_naturality {R S : CommRingCat.{u}} (f : R ⟶ S) :
(Spec.map f).appTop ≫ (ΓSpecIso S).hom = (ΓSpecIso R).hom ≫ f := SpecΓIdentity.hom.naturality f
-- The RHS is not necessarily simpler than the LHS, but this direction coincides with the simp
-- direction of `NatTrans.naturality`.
@[reassoc (attr := simp)]
lemma ΓSpecIso_inv_naturality {R S : CommRingCat.{u}} (f : R ⟶ S) :
f ≫ (ΓSpecIso S).inv = (ΓSpecIso R).inv ≫ (Spec.map f).appTop := SpecΓIdentity.inv.naturality f
-- This is not marked simp to respect the abstraction
lemma ΓSpecIso_inv : (ΓSpecIso R).inv = StructureSheaf.toOpen R ⊤ := rfl
lemma toOpen_eq (U) :
(by exact StructureSheaf.toOpen R U) =
(ΓSpecIso R).inv ≫ (Spec R).presheaf.map (homOfLE le_top).op := rfl
instance {K} [Field K] : Unique (Spec (.of K)) :=
inferInstanceAs <| Unique (PrimeSpectrum K)
@[simp]
lemma default_asIdeal {K} [Field K] : (default : Spec (.of K)).asIdeal = ⊥ := rfl
section BasicOpen
variable (X : Scheme) {V U : X.Opens} (f g : Γ(X, U))
| /-- The subset of the underlying space where the given section does not vanish. -/
def basicOpen : X.Opens :=
X.toLocallyRingedSpace.toRingedSpace.basicOpen f
theorem mem_basicOpen (x : X) (hx : x ∈ U) :
x ∈ X.basicOpen f ↔ IsUnit (X.presheaf.germ U x hx f) :=
RingedSpace.mem_basicOpen _ _ _ _
/-- A variant of `mem_basicOpen` for bundled `x : U`. -/
@[simp]
theorem mem_basicOpen' (x : U) : ↑x ∈ X.basicOpen f ↔ IsUnit (X.presheaf.germ U x x.2 f) :=
| Mathlib/AlgebraicGeometry/Scheme.lean | 516 | 526 |
/-
Copyright (c) 2022 Junyan Xu. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Junyan Xu
-/
import Mathlib.Data.Finsupp.Lex
import Mathlib.Data.Finsupp.Multiset
import Mathlib.Order.GameAdd
/-!
# Termination of a hydra game
This file deals with the following version of the hydra game: each head of the hydra is
labelled by an element in a type `α`, and when you cut off one head with label `a`, it
grows back an arbitrary but finite number of heads, all labelled by elements smaller than
`a` with respect to a well-founded relation `r` on `α`. We show that no matter how (in
what order) you choose cut off the heads, the game always terminates, i.e. all heads will
eventually be cut off (but of course it can last arbitrarily long, i.e. takes an
arbitrary finite number of steps).
This result is stated as the well-foundedness of the `CutExpand` relation defined in
this file: we model the heads of the hydra as a multiset of elements of `α`, and the
valid "moves" of the game are modelled by the relation `CutExpand r` on `Multiset α`:
`CutExpand r s' s` is true iff `s'` is obtained by removing one head `a ∈ s` and
adding back an arbitrary multiset `t` of heads such that all `a' ∈ t` satisfy `r a' a`.
We follow the proof by Peter LeFanu Lumsdaine at https://mathoverflow.net/a/229084/3332.
TODO: formalize the relations corresponding to more powerful (e.g. Kirby–Paris and Buchholz)
hydras, and prove their well-foundedness.
-/
namespace Relation
open Multiset Prod
variable {α : Type*}
/-- The relation that specifies valid moves in our hydra game. `CutExpand r s' s`
means that `s'` is obtained by removing one head `a ∈ s` and adding back an arbitrary
multiset `t` of heads such that all `a' ∈ t` satisfy `r a' a`.
This is most directly translated into `s' = s.erase a + t`, but `Multiset.erase` requires
`DecidableEq α`, so we use the equivalent condition `s' + {a} = s + t` instead, which
is also easier to verify for explicit multisets `s'`, `s` and `t`.
We also don't include the condition `a ∈ s` because `s' + {a} = s + t` already
guarantees `a ∈ s + t`, and if `r` is irreflexive then `a ∉ t`, which is the
case when `r` is well-founded, the case we are primarily interested in.
The lemma `Relation.cutExpand_iff` below converts between this convenient definition
and the direct translation when `r` is irreflexive. -/
def CutExpand (r : α → α → Prop) (s' s : Multiset α) : Prop :=
∃ (t : Multiset α) (a : α), (∀ a' ∈ t, r a' a) ∧ s' + {a} = s + t
variable {r : α → α → Prop}
theorem cutExpand_le_invImage_lex [DecidableEq α] [IsIrrefl α r] :
CutExpand r ≤ InvImage (Finsupp.Lex (rᶜ ⊓ (· ≠ ·)) (· < ·)) toFinsupp := by
rintro s t ⟨u, a, hr, he⟩
replace hr := fun a' ↦ mt (hr a')
classical
refine ⟨a, fun b h ↦ ?_, ?_⟩ <;> simp_rw [toFinsupp_apply]
· apply_fun count b at he
simpa only [count_add, count_singleton, if_neg h.2, add_zero, count_eq_zero.2 (hr b h.1)]
using he
· apply_fun count a at he
simp only [count_add, count_singleton_self, count_eq_zero.2 (hr _ (irrefl_of r a)),
add_zero] at he
exact he ▸ Nat.lt_succ_self _
theorem cutExpand_singleton {s x} (h : ∀ x' ∈ s, r x' x) : CutExpand r s {x} :=
⟨s, x, h, add_comm s _⟩
theorem cutExpand_singleton_singleton {x' x} (h : r x' x) : CutExpand r {x'} {x} :=
cutExpand_singleton fun a h ↦ by rwa [mem_singleton.1 h]
theorem cutExpand_add_left {t u} (s) : CutExpand r (s + t) (s + u) ↔ CutExpand r t u :=
exists₂_congr fun _ _ ↦ and_congr Iff.rfl <| by rw [add_assoc, add_assoc, add_left_cancel_iff]
lemma cutExpand_add_right {s' s} (t) : CutExpand r (s' + t) (s + t) ↔ CutExpand r s' s := by
convert cutExpand_add_left t using 2 <;> apply add_comm
theorem cutExpand_add_single {a' a : α} (s : Multiset α) (h : r a' a) :
CutExpand r (s + {a'}) (s + {a}) :=
(cutExpand_add_left s).2 <| cutExpand_singleton_singleton h
theorem cutExpand_single_add {a' a : α} (h : r a' a) (s : Multiset α) :
CutExpand r ({a'} + s) ({a} + s) :=
(cutExpand_add_right s).2 <| cutExpand_singleton_singleton h
|
theorem cutExpand_iff [DecidableEq α] [IsIrrefl α r] {s' s : Multiset α} :
CutExpand r s' s ↔
∃ (t : Multiset α) (a : α), (∀ a' ∈ t, r a' a) ∧ a ∈ s ∧ s' = s.erase a + t := by
simp_rw [CutExpand, add_singleton_eq_iff]
refine exists₂_congr fun t a ↦ ⟨?_, ?_⟩
· rintro ⟨ht, ha, rfl⟩
obtain h | h := mem_add.1 ha
exacts [⟨ht, h, erase_add_left_pos t h⟩, (@irrefl α r _ a (ht a h)).elim]
· rintro ⟨ht, h, rfl⟩
| Mathlib/Logic/Hydra.lean | 92 | 101 |
/-
Copyright (c) 2014 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura, Simon Hudon, Mario Carneiro
-/
import Aesop
import Mathlib.Algebra.Group.Defs
import Mathlib.Data.Nat.Init
import Mathlib.Data.Int.Init
import Mathlib.Logic.Function.Iterate
import Mathlib.Tactic.SimpRw
import Mathlib.Tactic.SplitIfs
/-!
# Basic lemmas about semigroups, monoids, and groups
This file lists various basic lemmas about semigroups, monoids, and groups. Most proofs are
one-liners from the corresponding axioms. For the definitions of semigroups, monoids and groups, see
`Algebra/Group/Defs.lean`.
-/
assert_not_exists MonoidWithZero DenselyOrdered
open Function
variable {α β G M : Type*}
section ite
variable [Pow α β]
@[to_additive (attr := simp) dite_smul]
lemma pow_dite (p : Prop) [Decidable p] (a : α) (b : p → β) (c : ¬ p → β) :
a ^ (if h : p then b h else c h) = if h : p then a ^ b h else a ^ c h := by split_ifs <;> rfl
@[to_additive (attr := simp) smul_dite]
lemma dite_pow (p : Prop) [Decidable p] (a : p → α) (b : ¬ p → α) (c : β) :
(if h : p then a h else b h) ^ c = if h : p then a h ^ c else b h ^ c := by split_ifs <;> rfl
@[to_additive (attr := simp) ite_smul]
lemma pow_ite (p : Prop) [Decidable p] (a : α) (b c : β) :
a ^ (if p then b else c) = if p then a ^ b else a ^ c := pow_dite _ _ _ _
@[to_additive (attr := simp) smul_ite]
lemma ite_pow (p : Prop) [Decidable p] (a b : α) (c : β) :
(if p then a else b) ^ c = if p then a ^ c else b ^ c := dite_pow _ _ _ _
set_option linter.existingAttributeWarning false in
attribute [to_additive (attr := simp)] dite_smul smul_dite ite_smul smul_ite
end ite
section Semigroup
variable [Semigroup α]
@[to_additive]
instance Semigroup.to_isAssociative : Std.Associative (α := α) (· * ·) := ⟨mul_assoc⟩
/-- Composing two multiplications on the left by `y` then `x`
is equal to a multiplication on the left by `x * y`.
-/
@[to_additive (attr := simp) "Composing two additions on the left by `y` then `x`
is equal to an addition on the left by `x + y`."]
theorem comp_mul_left (x y : α) : (x * ·) ∘ (y * ·) = (x * y * ·) := by
ext z
simp [mul_assoc]
/-- Composing two multiplications on the right by `y` and `x`
is equal to a multiplication on the right by `y * x`.
-/
@[to_additive (attr := simp) "Composing two additions on the right by `y` and `x`
is equal to an addition on the right by `y + x`."]
theorem comp_mul_right (x y : α) : (· * x) ∘ (· * y) = (· * (y * x)) := by
ext z
simp [mul_assoc]
end Semigroup
@[to_additive]
instance CommMagma.to_isCommutative [CommMagma G] : Std.Commutative (α := G) (· * ·) := ⟨mul_comm⟩
section MulOneClass
variable [MulOneClass M]
@[to_additive]
theorem ite_mul_one {P : Prop} [Decidable P] {a b : M} :
ite P (a * b) 1 = ite P a 1 * ite P b 1 := by
by_cases h : P <;> simp [h]
@[to_additive]
theorem ite_one_mul {P : Prop} [Decidable P] {a b : M} :
ite P 1 (a * b) = ite P 1 a * ite P 1 b := by
by_cases h : P <;> simp [h]
@[to_additive]
theorem eq_one_iff_eq_one_of_mul_eq_one {a b : M} (h : a * b = 1) : a = 1 ↔ b = 1 := by
constructor <;> (rintro rfl; simpa using h)
@[to_additive]
theorem one_mul_eq_id : ((1 : M) * ·) = id :=
funext one_mul
@[to_additive]
theorem mul_one_eq_id : (· * (1 : M)) = id :=
funext mul_one
end MulOneClass
section CommSemigroup
variable [CommSemigroup G]
@[to_additive]
theorem mul_left_comm (a b c : G) : a * (b * c) = b * (a * c) := by
rw [← mul_assoc, mul_comm a, mul_assoc]
@[to_additive]
theorem mul_right_comm (a b c : G) : a * b * c = a * c * b := by
rw [mul_assoc, mul_comm b, mul_assoc]
@[to_additive]
theorem mul_mul_mul_comm (a b c d : G) : a * b * (c * d) = a * c * (b * d) := by
simp only [mul_left_comm, mul_assoc]
@[to_additive]
theorem mul_rotate (a b c : G) : a * b * c = b * c * a := by
simp only [mul_left_comm, mul_comm]
@[to_additive]
theorem mul_rotate' (a b c : G) : a * (b * c) = b * (c * a) := by
simp only [mul_left_comm, mul_comm]
end CommSemigroup
attribute [local simp] mul_assoc sub_eq_add_neg
section Monoid
variable [Monoid M] {a b : M} {m n : ℕ}
@[to_additive boole_nsmul]
lemma pow_boole (P : Prop) [Decidable P] (a : M) :
(a ^ if P then 1 else 0) = if P then a else 1 := by simp only [pow_ite, pow_one, pow_zero]
@[to_additive nsmul_add_sub_nsmul]
lemma pow_mul_pow_sub (a : M) (h : m ≤ n) : a ^ m * a ^ (n - m) = a ^ n := by
rw [← pow_add, Nat.add_comm, Nat.sub_add_cancel h]
@[to_additive sub_nsmul_nsmul_add]
lemma pow_sub_mul_pow (a : M) (h : m ≤ n) : a ^ (n - m) * a ^ m = a ^ n := by
rw [← pow_add, Nat.sub_add_cancel h]
@[to_additive sub_one_nsmul_add]
lemma mul_pow_sub_one (hn : n ≠ 0) (a : M) : a * a ^ (n - 1) = a ^ n := by
rw [← pow_succ', Nat.sub_add_cancel <| Nat.one_le_iff_ne_zero.2 hn]
@[to_additive add_sub_one_nsmul]
lemma pow_sub_one_mul (hn : n ≠ 0) (a : M) : a ^ (n - 1) * a = a ^ n := by
rw [← pow_succ, Nat.sub_add_cancel <| Nat.one_le_iff_ne_zero.2 hn]
/-- If `x ^ n = 1`, then `x ^ m` is the same as `x ^ (m % n)` -/
@[to_additive nsmul_eq_mod_nsmul "If `n • x = 0`, then `m • x` is the same as `(m % n) • x`"]
lemma pow_eq_pow_mod (m : ℕ) (ha : a ^ n = 1) : a ^ m = a ^ (m % n) := by
calc
a ^ m = a ^ (m % n + n * (m / n)) := by rw [Nat.mod_add_div]
_ = a ^ (m % n) := by simp [pow_add, pow_mul, ha]
@[to_additive] lemma pow_mul_pow_eq_one : ∀ n, a * b = 1 → a ^ n * b ^ n = 1
| 0, _ => by simp
| n + 1, h =>
calc
a ^ n.succ * b ^ n.succ = a ^ n * a * (b * b ^ n) := by rw [pow_succ, pow_succ']
_ = a ^ n * (a * b) * b ^ n := by simp only [mul_assoc]
_ = 1 := by simp [h, pow_mul_pow_eq_one]
@[to_additive (attr := simp)]
lemma mul_left_iterate (a : M) : ∀ n : ℕ, (a * ·)^[n] = (a ^ n * ·)
| 0 => by ext; simp
| n + 1 => by ext; simp [pow_succ, mul_left_iterate]
@[to_additive (attr := simp)]
lemma mul_right_iterate (a : M) : ∀ n : ℕ, (· * a)^[n] = (· * a ^ n)
| 0 => by ext; simp
| n + 1 => by ext; simp [pow_succ', mul_right_iterate]
@[to_additive]
lemma mul_left_iterate_apply_one (a : M) : (a * ·)^[n] 1 = a ^ n := by simp [mul_right_iterate]
@[to_additive]
lemma mul_right_iterate_apply_one (a : M) : (· * a)^[n] 1 = a ^ n := by simp [mul_right_iterate]
@[to_additive (attr := simp)]
lemma pow_iterate (k : ℕ) : ∀ n : ℕ, (fun x : M ↦ x ^ k)^[n] = (· ^ k ^ n)
| 0 => by ext; simp
| n + 1 => by ext; simp [pow_iterate, Nat.pow_succ', pow_mul]
end Monoid
section CommMonoid
variable [CommMonoid M] {x y z : M}
@[to_additive]
theorem inv_unique (hy : x * y = 1) (hz : x * z = 1) : y = z :=
left_inv_eq_right_inv (Trans.trans (mul_comm _ _) hy) hz
@[to_additive nsmul_add] lemma mul_pow (a b : M) : ∀ n, (a * b) ^ n = a ^ n * b ^ n
| 0 => by rw [pow_zero, pow_zero, pow_zero, one_mul]
| n + 1 => by rw [pow_succ', pow_succ', pow_succ', mul_pow, mul_mul_mul_comm]
end CommMonoid
section LeftCancelMonoid
variable [Monoid M] [IsLeftCancelMul M] {a b : M}
@[to_additive (attr := simp)]
theorem mul_eq_left : a * b = a ↔ b = 1 := calc
a * b = a ↔ a * b = a * 1 := by rw [mul_one]
_ ↔ b = 1 := mul_left_cancel_iff
@[deprecated (since := "2025-03-05")] alias mul_right_eq_self := mul_eq_left
@[deprecated (since := "2025-03-05")] alias add_right_eq_self := add_eq_left
set_option linter.existingAttributeWarning false in
attribute [to_additive existing] mul_right_eq_self
@[to_additive (attr := simp)]
theorem left_eq_mul : a = a * b ↔ b = 1 :=
eq_comm.trans mul_eq_left
@[deprecated (since := "2025-03-05")] alias self_eq_mul_right := left_eq_mul
@[deprecated (since := "2025-03-05")] alias self_eq_add_right := left_eq_add
set_option linter.existingAttributeWarning false in
attribute [to_additive existing] self_eq_mul_right
@[to_additive]
theorem mul_ne_left : a * b ≠ a ↔ b ≠ 1 := mul_eq_left.not
@[deprecated (since := "2025-03-05")] alias mul_right_ne_self := mul_ne_left
@[deprecated (since := "2025-03-05")] alias add_right_ne_self := add_ne_left
set_option linter.existingAttributeWarning false in
attribute [to_additive existing] mul_right_ne_self
@[to_additive]
theorem left_ne_mul : a ≠ a * b ↔ b ≠ 1 := left_eq_mul.not
@[deprecated (since := "2025-03-05")] alias self_ne_mul_right := left_ne_mul
@[deprecated (since := "2025-03-05")] alias self_ne_add_right := left_ne_add
set_option linter.existingAttributeWarning false in
attribute [to_additive existing] self_ne_mul_right
end LeftCancelMonoid
section RightCancelMonoid
variable [RightCancelMonoid M] {a b : M}
@[to_additive (attr := simp)]
theorem mul_eq_right : a * b = b ↔ a = 1 := calc
a * b = b ↔ a * b = 1 * b := by rw [one_mul]
_ ↔ a = 1 := mul_right_cancel_iff
@[deprecated (since := "2025-03-05")] alias mul_left_eq_self := mul_eq_right
@[deprecated (since := "2025-03-05")] alias add_left_eq_self := add_eq_right
set_option linter.existingAttributeWarning false in
attribute [to_additive existing] mul_left_eq_self
@[to_additive (attr := simp)]
theorem right_eq_mul : b = a * b ↔ a = 1 :=
eq_comm.trans mul_eq_right
@[deprecated (since := "2025-03-05")] alias self_eq_mul_left := right_eq_mul
@[deprecated (since := "2025-03-05")] alias self_eq_add_left := right_eq_add
set_option linter.existingAttributeWarning false in
attribute [to_additive existing] self_eq_mul_left
@[to_additive]
theorem mul_ne_right : a * b ≠ b ↔ a ≠ 1 := mul_eq_right.not
@[deprecated (since := "2025-03-05")] alias mul_left_ne_self := mul_ne_right
@[deprecated (since := "2025-03-05")] alias add_left_ne_self := add_ne_right
set_option linter.existingAttributeWarning false in
attribute [to_additive existing] mul_left_ne_self
@[to_additive]
theorem right_ne_mul : b ≠ a * b ↔ a ≠ 1 := right_eq_mul.not
@[deprecated (since := "2025-03-05")] alias self_ne_mul_left := right_ne_mul
@[deprecated (since := "2025-03-05")] alias self_ne_add_left := right_ne_add
set_option linter.existingAttributeWarning false in
attribute [to_additive existing] self_ne_mul_left
end RightCancelMonoid
section CancelCommMonoid
variable [CancelCommMonoid α] {a b c d : α}
@[to_additive] lemma eq_iff_eq_of_mul_eq_mul (h : a * b = c * d) : a = c ↔ b = d := by aesop
@[to_additive] lemma ne_iff_ne_of_mul_eq_mul (h : a * b = c * d) : a ≠ c ↔ b ≠ d := by aesop
end CancelCommMonoid
section InvolutiveInv
variable [InvolutiveInv G] {a b : G}
@[to_additive (attr := simp)]
theorem inv_involutive : Function.Involutive (Inv.inv : G → G) :=
inv_inv
@[to_additive (attr := simp)]
theorem inv_surjective : Function.Surjective (Inv.inv : G → G) :=
inv_involutive.surjective
@[to_additive]
theorem inv_injective : Function.Injective (Inv.inv : G → G) :=
inv_involutive.injective
@[to_additive (attr := simp)]
theorem inv_inj : a⁻¹ = b⁻¹ ↔ a = b :=
inv_injective.eq_iff
@[to_additive]
theorem inv_eq_iff_eq_inv : a⁻¹ = b ↔ a = b⁻¹ :=
⟨fun h => h ▸ (inv_inv a).symm, fun h => h.symm ▸ inv_inv b⟩
variable (G)
@[to_additive]
theorem inv_comp_inv : Inv.inv ∘ Inv.inv = @id G :=
inv_involutive.comp_self
@[to_additive]
theorem leftInverse_inv : LeftInverse (fun a : G ↦ a⁻¹) fun a ↦ a⁻¹ :=
inv_inv
@[to_additive]
theorem rightInverse_inv : RightInverse (fun a : G ↦ a⁻¹) fun a ↦ a⁻¹ :=
inv_inv
end InvolutiveInv
section DivInvMonoid
variable [DivInvMonoid G]
@[to_additive]
theorem mul_one_div (x y : G) : x * (1 / y) = x / y := by
rw [div_eq_mul_inv, one_mul, div_eq_mul_inv]
@[to_additive, field_simps] -- The attributes are out of order on purpose
theorem mul_div_assoc' (a b c : G) : a * (b / c) = a * b / c :=
(mul_div_assoc _ _ _).symm
@[to_additive]
theorem mul_div (a b c : G) : a * (b / c) = a * b / c := by simp only [mul_assoc, div_eq_mul_inv]
@[to_additive]
theorem div_eq_mul_one_div (a b : G) : a / b = a * (1 / b) := by rw [div_eq_mul_inv, one_div]
end DivInvMonoid
section DivInvOneMonoid
variable [DivInvOneMonoid G]
@[to_additive (attr := simp)]
theorem div_one (a : G) : a / 1 = a := by simp [div_eq_mul_inv]
@[to_additive]
theorem one_div_one : (1 : G) / 1 = 1 :=
div_one _
end DivInvOneMonoid
section DivisionMonoid
variable [DivisionMonoid α] {a b c d : α}
attribute [local simp] mul_assoc div_eq_mul_inv
@[to_additive]
theorem eq_inv_of_mul_eq_one_right (h : a * b = 1) : b = a⁻¹ :=
(inv_eq_of_mul_eq_one_right h).symm
@[to_additive]
theorem eq_one_div_of_mul_eq_one_left (h : b * a = 1) : b = 1 / a := by
rw [eq_inv_of_mul_eq_one_left h, one_div]
@[to_additive]
theorem eq_one_div_of_mul_eq_one_right (h : a * b = 1) : b = 1 / a := by
rw [eq_inv_of_mul_eq_one_right h, one_div]
@[to_additive]
theorem eq_of_div_eq_one (h : a / b = 1) : a = b :=
inv_injective <| inv_eq_of_mul_eq_one_right <| by rwa [← div_eq_mul_inv]
@[to_additive]
lemma eq_of_inv_mul_eq_one (h : a⁻¹ * b = 1) : a = b := by simpa using eq_inv_of_mul_eq_one_left h
@[to_additive]
lemma eq_of_mul_inv_eq_one (h : a * b⁻¹ = 1) : a = b := by simpa using eq_inv_of_mul_eq_one_left h
@[to_additive]
theorem div_ne_one_of_ne : a ≠ b → a / b ≠ 1 :=
mt eq_of_div_eq_one
variable (a b c)
@[to_additive]
theorem one_div_mul_one_div_rev : 1 / a * (1 / b) = 1 / (b * a) := by simp
@[to_additive]
theorem inv_div_left : a⁻¹ / b = (b * a)⁻¹ := by simp
@[to_additive (attr := simp)]
theorem inv_div : (a / b)⁻¹ = b / a := by simp
@[to_additive]
theorem one_div_div : 1 / (a / b) = b / a := by simp
@[to_additive]
theorem one_div_one_div : 1 / (1 / a) = a := by simp
@[to_additive]
theorem div_eq_div_iff_comm : a / b = c / d ↔ b / a = d / c :=
inv_inj.symm.trans <| by simp only [inv_div]
@[to_additive]
instance (priority := 100) DivisionMonoid.toDivInvOneMonoid : DivInvOneMonoid α :=
{ DivisionMonoid.toDivInvMonoid with
inv_one := by simpa only [one_div, inv_inv] using (inv_div (1 : α) 1).symm }
@[to_additive (attr := simp)]
lemma inv_pow (a : α) : ∀ n : ℕ, a⁻¹ ^ n = (a ^ n)⁻¹
| 0 => by rw [pow_zero, pow_zero, inv_one]
| n + 1 => by rw [pow_succ', pow_succ, inv_pow _ n, mul_inv_rev]
-- the attributes are intentionally out of order. `smul_zero` proves `zsmul_zero`.
@[to_additive zsmul_zero, simp]
lemma one_zpow : ∀ n : ℤ, (1 : α) ^ n = 1
| (n : ℕ) => by rw [zpow_natCast, one_pow]
| .negSucc n => by rw [zpow_negSucc, one_pow, inv_one]
@[to_additive (attr := simp) neg_zsmul]
lemma zpow_neg (a : α) : ∀ n : ℤ, a ^ (-n) = (a ^ n)⁻¹
| (_ + 1 : ℕ) => DivInvMonoid.zpow_neg' _ _
| 0 => by simp
| Int.negSucc n => by
rw [zpow_negSucc, inv_inv, ← zpow_natCast]
rfl
@[to_additive neg_one_zsmul_add]
lemma mul_zpow_neg_one (a b : α) : (a * b) ^ (-1 : ℤ) = b ^ (-1 : ℤ) * a ^ (-1 : ℤ) := by
simp only [zpow_neg, zpow_one, mul_inv_rev]
@[to_additive zsmul_neg]
lemma inv_zpow (a : α) : ∀ n : ℤ, a⁻¹ ^ n = (a ^ n)⁻¹
| (n : ℕ) => by rw [zpow_natCast, zpow_natCast, inv_pow]
| .negSucc n => by rw [zpow_negSucc, zpow_negSucc, inv_pow]
@[to_additive (attr := simp) zsmul_neg']
lemma inv_zpow' (a : α) (n : ℤ) : a⁻¹ ^ n = a ^ (-n) := by rw [inv_zpow, zpow_neg]
@[to_additive nsmul_zero_sub]
lemma one_div_pow (a : α) (n : ℕ) : (1 / a) ^ n = 1 / a ^ n := by simp only [one_div, inv_pow]
@[to_additive zsmul_zero_sub]
lemma one_div_zpow (a : α) (n : ℤ) : (1 / a) ^ n = 1 / a ^ n := by simp only [one_div, inv_zpow]
variable {a b c}
@[to_additive (attr := simp)]
theorem inv_eq_one : a⁻¹ = 1 ↔ a = 1 :=
inv_injective.eq_iff' inv_one
@[to_additive (attr := simp)]
theorem one_eq_inv : 1 = a⁻¹ ↔ a = 1 :=
eq_comm.trans inv_eq_one
@[to_additive]
theorem inv_ne_one : a⁻¹ ≠ 1 ↔ a ≠ 1 :=
inv_eq_one.not
@[to_additive]
theorem eq_of_one_div_eq_one_div (h : 1 / a = 1 / b) : a = b := by
rw [← one_div_one_div a, h, one_div_one_div]
-- Note that `mul_zsmul` and `zpow_mul` have the primes swapped
-- when additivised since their argument order,
-- and therefore the more "natural" choice of lemma, is reversed.
@[to_additive mul_zsmul'] lemma zpow_mul (a : α) : ∀ m n : ℤ, a ^ (m * n) = (a ^ m) ^ n
| (m : ℕ), (n : ℕ) => by
rw [zpow_natCast, zpow_natCast, ← pow_mul, ← zpow_natCast]
rfl
| (m : ℕ), .negSucc n => by
rw [zpow_natCast, zpow_negSucc, ← pow_mul, Int.ofNat_mul_negSucc, zpow_neg, inv_inj,
← zpow_natCast]
| .negSucc m, (n : ℕ) => by
rw [zpow_natCast, zpow_negSucc, ← inv_pow, ← pow_mul, Int.negSucc_mul_ofNat, zpow_neg, inv_pow,
inv_inj, ← zpow_natCast]
| .negSucc m, .negSucc n => by
rw [zpow_negSucc, zpow_negSucc, Int.negSucc_mul_negSucc, inv_pow, inv_inv, ← pow_mul, ←
zpow_natCast]
rfl
@[to_additive mul_zsmul]
lemma zpow_mul' (a : α) (m n : ℤ) : a ^ (m * n) = (a ^ n) ^ m := by rw [Int.mul_comm, zpow_mul]
@[to_additive]
theorem zpow_comm (a : α) (m n : ℤ) : (a ^ m) ^ n = (a ^ n) ^ m := by rw [← zpow_mul, zpow_mul']
variable (a b c)
@[to_additive, field_simps] -- The attributes are out of order on purpose
theorem div_div_eq_mul_div : a / (b / c) = a * c / b := by simp
@[to_additive (attr := simp)]
theorem div_inv_eq_mul : a / b⁻¹ = a * b := by simp
@[to_additive]
theorem div_mul_eq_div_div_swap : a / (b * c) = a / c / b := by
simp only [mul_assoc, mul_inv_rev, div_eq_mul_inv]
end DivisionMonoid
section DivisionCommMonoid
variable [DivisionCommMonoid α] (a b c d : α)
attribute [local simp] mul_assoc mul_comm mul_left_comm div_eq_mul_inv
@[to_additive neg_add]
theorem mul_inv : (a * b)⁻¹ = a⁻¹ * b⁻¹ := by simp
@[to_additive]
theorem inv_div' : (a / b)⁻¹ = a⁻¹ / b⁻¹ := by simp
@[to_additive]
theorem div_eq_inv_mul : a / b = b⁻¹ * a := by simp
@[to_additive]
theorem inv_mul_eq_div : a⁻¹ * b = b / a := by simp
@[to_additive] lemma inv_div_comm (a b : α) : a⁻¹ / b = b⁻¹ / a := by simp
@[to_additive]
theorem inv_mul' : (a * b)⁻¹ = a⁻¹ / b := by simp
@[to_additive]
theorem inv_div_inv : a⁻¹ / b⁻¹ = b / a := by simp
@[to_additive]
theorem inv_inv_div_inv : (a⁻¹ / b⁻¹)⁻¹ = a / b := by simp
@[to_additive]
theorem one_div_mul_one_div : 1 / a * (1 / b) = 1 / (a * b) := by simp
@[to_additive]
theorem div_right_comm : a / b / c = a / c / b := by simp
@[to_additive, field_simps]
theorem div_div : a / b / c = a / (b * c) := by simp
@[to_additive]
theorem div_mul : a / b * c = a / (b / c) := by simp
@[to_additive]
theorem mul_div_left_comm : a * (b / c) = b * (a / c) := by simp
@[to_additive]
theorem mul_div_right_comm : a * b / c = a / c * b := by simp
@[to_additive]
theorem div_mul_eq_div_div : a / (b * c) = a / b / c := by simp
@[to_additive, field_simps]
theorem div_mul_eq_mul_div : a / b * c = a * c / b := by simp
@[to_additive]
theorem one_div_mul_eq_div : 1 / a * b = b / a := by simp
@[to_additive]
theorem mul_comm_div : a / b * c = a * (c / b) := by simp
@[to_additive]
theorem div_mul_comm : a / b * c = c / b * a := by simp
@[to_additive]
theorem div_mul_eq_div_mul_one_div : a / (b * c) = a / b * (1 / c) := by simp
@[to_additive]
theorem div_div_div_eq : a / b / (c / d) = a * d / (b * c) := by simp
@[to_additive]
theorem div_div_div_comm : a / b / (c / d) = a / c / (b / d) := by simp
@[to_additive]
theorem div_mul_div_comm : a / b * (c / d) = a * c / (b * d) := by simp
@[to_additive]
theorem mul_div_mul_comm : a * b / (c * d) = a / c * (b / d) := by simp
@[to_additive zsmul_add] lemma mul_zpow : ∀ n : ℤ, (a * b) ^ n = a ^ n * b ^ n
| (n : ℕ) => by simp_rw [zpow_natCast, mul_pow]
| .negSucc n => by simp_rw [zpow_negSucc, ← inv_pow, mul_inv, mul_pow]
@[to_additive nsmul_sub]
lemma div_pow (a b : α) (n : ℕ) : (a / b) ^ n = a ^ n / b ^ n := by
simp only [div_eq_mul_inv, mul_pow, inv_pow]
@[to_additive zsmul_sub]
lemma div_zpow (a b : α) (n : ℤ) : (a / b) ^ n = a ^ n / b ^ n := by
simp only [div_eq_mul_inv, mul_zpow, inv_zpow]
attribute [field_simps] div_pow div_zpow
end DivisionCommMonoid
section Group
variable [Group G] {a b c d : G} {n : ℤ}
@[to_additive (attr := simp)]
theorem div_eq_inv_self : a / b = b⁻¹ ↔ a = 1 := by rw [div_eq_mul_inv, mul_eq_right]
@[to_additive]
theorem mul_left_surjective (a : G) : Surjective (a * ·) :=
fun x ↦ ⟨a⁻¹ * x, mul_inv_cancel_left a x⟩
@[to_additive]
theorem mul_right_surjective (a : G) : Function.Surjective fun x ↦ x * a := fun x ↦
⟨x * a⁻¹, inv_mul_cancel_right x a⟩
@[to_additive]
theorem eq_mul_inv_of_mul_eq (h : a * c = b) : a = b * c⁻¹ := by simp [h.symm]
@[to_additive]
theorem eq_inv_mul_of_mul_eq (h : b * a = c) : a = b⁻¹ * c := by simp [h.symm]
@[to_additive]
theorem inv_mul_eq_of_eq_mul (h : b = a * c) : a⁻¹ * b = c := by simp [h]
@[to_additive]
theorem mul_inv_eq_of_eq_mul (h : a = c * b) : a * b⁻¹ = c := by simp [h]
@[to_additive]
theorem eq_mul_of_mul_inv_eq (h : a * c⁻¹ = b) : a = b * c := by simp [h.symm]
@[to_additive]
theorem eq_mul_of_inv_mul_eq (h : b⁻¹ * a = c) : a = b * c := by simp [h.symm, mul_inv_cancel_left]
@[to_additive]
theorem mul_eq_of_eq_inv_mul (h : b = a⁻¹ * c) : a * b = c := by rw [h, mul_inv_cancel_left]
@[to_additive]
theorem mul_eq_of_eq_mul_inv (h : a = c * b⁻¹) : a * b = c := by simp [h]
@[to_additive]
theorem mul_eq_one_iff_eq_inv : a * b = 1 ↔ a = b⁻¹ :=
⟨eq_inv_of_mul_eq_one_left, fun h ↦ by rw [h, inv_mul_cancel]⟩
@[to_additive]
theorem mul_eq_one_iff_inv_eq : a * b = 1 ↔ a⁻¹ = b := by
rw [mul_eq_one_iff_eq_inv, inv_eq_iff_eq_inv]
/-- Variant of `mul_eq_one_iff_eq_inv` with swapped equality. -/
@[to_additive]
theorem mul_eq_one_iff_eq_inv' : a * b = 1 ↔ b = a⁻¹ := by
rw [mul_eq_one_iff_inv_eq, eq_comm]
/-- Variant of `mul_eq_one_iff_inv_eq` with swapped equality. -/
@[to_additive]
theorem mul_eq_one_iff_inv_eq' : a * b = 1 ↔ b⁻¹ = a := by
rw [mul_eq_one_iff_eq_inv, eq_comm]
@[to_additive]
theorem eq_inv_iff_mul_eq_one : a = b⁻¹ ↔ a * b = 1 :=
mul_eq_one_iff_eq_inv.symm
@[to_additive]
theorem inv_eq_iff_mul_eq_one : a⁻¹ = b ↔ a * b = 1 :=
mul_eq_one_iff_inv_eq.symm
@[to_additive]
theorem eq_mul_inv_iff_mul_eq : a = b * c⁻¹ ↔ a * c = b :=
⟨fun h ↦ by rw [h, inv_mul_cancel_right], fun h ↦ by rw [← h, mul_inv_cancel_right]⟩
@[to_additive]
theorem eq_inv_mul_iff_mul_eq : a = b⁻¹ * c ↔ b * a = c :=
⟨fun h ↦ by rw [h, mul_inv_cancel_left], fun h ↦ by rw [← h, inv_mul_cancel_left]⟩
@[to_additive]
theorem inv_mul_eq_iff_eq_mul : a⁻¹ * b = c ↔ b = a * c :=
⟨fun h ↦ by rw [← h, mul_inv_cancel_left], fun h ↦ by rw [h, inv_mul_cancel_left]⟩
@[to_additive]
theorem mul_inv_eq_iff_eq_mul : a * b⁻¹ = c ↔ a = c * b :=
⟨fun h ↦ by rw [← h, inv_mul_cancel_right], fun h ↦ by rw [h, mul_inv_cancel_right]⟩
@[to_additive]
theorem mul_inv_eq_one : a * b⁻¹ = 1 ↔ a = b := by rw [mul_eq_one_iff_eq_inv, inv_inv]
@[to_additive]
theorem inv_mul_eq_one : a⁻¹ * b = 1 ↔ a = b := by rw [mul_eq_one_iff_eq_inv, inv_inj]
@[to_additive (attr := simp)]
theorem conj_eq_one_iff : a * b * a⁻¹ = 1 ↔ b = 1 := by
rw [mul_inv_eq_one, mul_eq_left]
@[to_additive]
theorem div_left_injective : Function.Injective fun a ↦ a / b := by
-- FIXME this could be by `simpa`, but it fails. This is probably a bug in `simpa`.
simp only [div_eq_mul_inv]
exact fun a a' h ↦ mul_left_injective b⁻¹ h
@[to_additive]
theorem div_right_injective : Function.Injective fun a ↦ b / a := by
-- FIXME see above
simp only [div_eq_mul_inv]
exact fun a a' h ↦ inv_injective (mul_right_injective b h)
@[to_additive (attr := simp)]
lemma div_mul_cancel_right (a b : G) : a / (b * a) = b⁻¹ := by rw [← inv_div, mul_div_cancel_right]
@[to_additive (attr := simp)]
theorem mul_div_mul_right_eq_div (a b c : G) : a * c / (b * c) = a / b := by
rw [div_mul_eq_div_div_swap]; simp only [mul_left_inj, eq_self_iff_true, mul_div_cancel_right]
@[to_additive eq_sub_of_add_eq]
theorem eq_div_of_mul_eq' (h : a * c = b) : a = b / c := by simp [← h]
@[to_additive sub_eq_of_eq_add]
theorem div_eq_of_eq_mul'' (h : a = c * b) : a / b = c := by simp [h]
@[to_additive]
theorem eq_mul_of_div_eq (h : a / c = b) : a = b * c := by simp [← h]
@[to_additive]
theorem mul_eq_of_eq_div (h : a = c / b) : a * b = c := by simp [h]
@[to_additive (attr := simp)]
theorem div_right_inj : a / b = a / c ↔ b = c :=
div_right_injective.eq_iff
@[to_additive (attr := simp)]
theorem div_left_inj : b / a = c / a ↔ b = c := by
rw [div_eq_mul_inv, div_eq_mul_inv]
exact mul_left_inj _
@[to_additive (attr := simp)]
theorem div_mul_div_cancel (a b c : G) : a / b * (b / c) = a / c := by
rw [← mul_div_assoc, div_mul_cancel]
| @[to_additive (attr := simp)]
| Mathlib/Algebra/Group/Basic.lean | 761 | 761 |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Data.Fintype.Card
import Mathlib.Algebra.Order.BigOperators.Group.Multiset
import Mathlib.Algebra.Order.Group.Nat
import Mathlib.Data.Multiset.OrderedMonoid
import Mathlib.Tactic.Bound.Attribute
import Mathlib.Algebra.BigOperators.Group.Finset.Sigma
import Mathlib.Data.Multiset.Powerset
/-!
# Big operators on a finset in ordered groups
This file contains the results concerning the interaction of multiset big operators with ordered
groups/monoids.
-/
assert_not_exists Ring
open Function
variable {ι α β M N G k R : Type*}
namespace Finset
section OrderedCommMonoid
variable [CommMonoid M] [CommMonoid N] [PartialOrder N] [IsOrderedMonoid N]
/-- Let `{x | p x}` be a subsemigroup of a commutative monoid `M`. Let `f : M → N` be a map
submultiplicative on `{x | p x}`, i.e., `p x → p y → f (x * y) ≤ f x * f y`. Let `g i`, `i ∈ s`, be
a nonempty finite family of elements of `M` such that `∀ i ∈ s, p (g i)`. Then
`f (∏ x ∈ s, g x) ≤ ∏ x ∈ s, f (g x)`. -/
@[to_additive le_sum_nonempty_of_subadditive_on_pred]
theorem le_prod_nonempty_of_submultiplicative_on_pred (f : M → N) (p : M → Prop)
(h_mul : ∀ x y, p x → p y → f (x * y) ≤ f x * f y) (hp_mul : ∀ x y, p x → p y → p (x * y))
(g : ι → M) (s : Finset ι) (hs_nonempty : s.Nonempty) (hs : ∀ i ∈ s, p (g i)) :
f (∏ i ∈ s, g i) ≤ ∏ i ∈ s, f (g i) := by
refine le_trans
(Multiset.le_prod_nonempty_of_submultiplicative_on_pred f p h_mul hp_mul _ ?_ ?_) ?_
· simp [hs_nonempty.ne_empty]
· exact Multiset.forall_mem_map_iff.mpr hs
rw [Multiset.map_map]
rfl
/-- Let `{x | p x}` be an additive subsemigroup of an additive commutative monoid `M`. Let
`f : M → N` be a map subadditive on `{x | p x}`, i.e., `p x → p y → f (x + y) ≤ f x + f y`. Let
`g i`, `i ∈ s`, be a nonempty finite family of elements of `M` such that `∀ i ∈ s, p (g i)`. Then
`f (∑ i ∈ s, g i) ≤ ∑ i ∈ s, f (g i)`. -/
add_decl_doc le_sum_nonempty_of_subadditive_on_pred
/-- If `f : M → N` is a submultiplicative function, `f (x * y) ≤ f x * f y` and `g i`, `i ∈ s`, is a
nonempty finite family of elements of `M`, then `f (∏ i ∈ s, g i) ≤ ∏ i ∈ s, f (g i)`. -/
@[to_additive le_sum_nonempty_of_subadditive]
theorem le_prod_nonempty_of_submultiplicative (f : M → N) (h_mul : ∀ x y, f (x * y) ≤ f x * f y)
{s : Finset ι} (hs : s.Nonempty) (g : ι → M) : f (∏ i ∈ s, g i) ≤ ∏ i ∈ s, f (g i) :=
le_prod_nonempty_of_submultiplicative_on_pred f (fun _ ↦ True) (fun x y _ _ ↦ h_mul x y)
(fun _ _ _ _ ↦ trivial) g s hs fun _ _ ↦ trivial
/-- If `f : M → N` is a subadditive function, `f (x + y) ≤ f x + f y` and `g i`, `i ∈ s`, is a
nonempty finite family of elements of `M`, then `f (∑ i ∈ s, g i) ≤ ∑ i ∈ s, f (g i)`. -/
add_decl_doc le_sum_nonempty_of_subadditive
/-- Let `{x | p x}` be a subsemigroup of a commutative monoid `M`. Let `f : M → N` be a map
such that `f 1 = 1` and `f` is submultiplicative on `{x | p x}`, i.e.,
`p x → p y → f (x * y) ≤ f x * f y`. Let `g i`, `i ∈ s`, be a finite family of elements of `M` such
that `∀ i ∈ s, p (g i)`. Then `f (∏ i ∈ s, g i) ≤ ∏ i ∈ s, f (g i)`. -/
@[to_additive le_sum_of_subadditive_on_pred]
theorem le_prod_of_submultiplicative_on_pred (f : M → N) (p : M → Prop) (h_one : f 1 = 1)
(h_mul : ∀ x y, p x → p y → f (x * y) ≤ f x * f y) (hp_mul : ∀ x y, p x → p y → p (x * y))
(g : ι → M) {s : Finset ι} (hs : ∀ i ∈ s, p (g i)) : f (∏ i ∈ s, g i) ≤ ∏ i ∈ s, f (g i) := by
rcases eq_empty_or_nonempty s with (rfl | hs_nonempty)
· simp [h_one]
· exact le_prod_nonempty_of_submultiplicative_on_pred f p h_mul hp_mul g s hs_nonempty hs
/-- Let `{x | p x}` be a subsemigroup of a commutative additive monoid `M`. Let `f : M → N` be a map
such that `f 0 = 0` and `f` is subadditive on `{x | p x}`, i.e. `p x → p y → f (x + y) ≤ f x + f y`.
Let `g i`, `i ∈ s`, be a finite family of elements of `M` such that `∀ i ∈ s, p (g i)`. Then
`f (∑ x ∈ s, g x) ≤ ∑ x ∈ s, f (g x)`. -/
add_decl_doc le_sum_of_subadditive_on_pred
/-- If `f : M → N` is a submultiplicative function, `f (x * y) ≤ f x * f y`, `f 1 = 1`, and `g i`,
`i ∈ s`, is a finite family of elements of `M`, then `f (∏ i ∈ s, g i) ≤ ∏ i ∈ s, f (g i)`. -/
@[to_additive le_sum_of_subadditive]
theorem le_prod_of_submultiplicative (f : M → N) (h_one : f 1 = 1)
(h_mul : ∀ x y, f (x * y) ≤ f x * f y) (s : Finset ι) (g : ι → M) :
f (∏ i ∈ s, g i) ≤ ∏ i ∈ s, f (g i) := by
refine le_trans (Multiset.le_prod_of_submultiplicative f h_one h_mul _) ?_
rw [Multiset.map_map]
rfl
/-- If `f : M → N` is a subadditive function, `f (x + y) ≤ f x + f y`, `f 0 = 0`, and `g i`,
`i ∈ s`, is a finite family of elements of `M`, then `f (∑ i ∈ s, g i) ≤ ∑ i ∈ s, f (g i)`. -/
add_decl_doc le_sum_of_subadditive
variable {f g : ι → N} {s t : Finset ι}
/-- In an ordered commutative monoid, if each factor `f i` of one finite product is less than or
equal to the corresponding factor `g i` of another finite product, then
`∏ i ∈ s, f i ≤ ∏ i ∈ s, g i`. -/
@[to_additive (attr := gcongr) sum_le_sum]
theorem prod_le_prod' (h : ∀ i ∈ s, f i ≤ g i) : ∏ i ∈ s, f i ≤ ∏ i ∈ s, g i :=
Multiset.prod_map_le_prod_map f g h
attribute [bound] sum_le_sum
/-- In an ordered additive commutative monoid, if each summand `f i` of one finite sum is less than
or equal to the corresponding summand `g i` of another finite sum, then
`∑ i ∈ s, f i ≤ ∑ i ∈ s, g i`. -/
add_decl_doc sum_le_sum
@[to_additive sum_nonneg]
theorem one_le_prod' (h : ∀ i ∈ s, 1 ≤ f i) : 1 ≤ ∏ i ∈ s, f i :=
le_trans (by rw [prod_const_one]) (prod_le_prod' h)
@[to_additive Finset.sum_nonneg']
theorem one_le_prod'' (h : ∀ i : ι, 1 ≤ f i) : 1 ≤ ∏ i ∈ s, f i :=
Finset.one_le_prod' fun i _ ↦ h i
@[to_additive sum_nonpos]
theorem prod_le_one' (h : ∀ i ∈ s, f i ≤ 1) : ∏ i ∈ s, f i ≤ 1 :=
(prod_le_prod' h).trans_eq (by rw [prod_const_one])
@[to_additive (attr := gcongr) sum_le_sum_of_subset_of_nonneg]
theorem prod_le_prod_of_subset_of_one_le' (h : s ⊆ t) (hf : ∀ i ∈ t, i ∉ s → 1 ≤ f i) :
∏ i ∈ s, f i ≤ ∏ i ∈ t, f i := by
classical calc
∏ i ∈ s, f i ≤ (∏ i ∈ t \ s, f i) * ∏ i ∈ s, f i :=
le_mul_of_one_le_left' <| one_le_prod' <| by simpa only [mem_sdiff, and_imp]
_ = ∏ i ∈ t \ s ∪ s, f i := (prod_union sdiff_disjoint).symm
_ = ∏ i ∈ t, f i := by rw [sdiff_union_of_subset h]
@[to_additive sum_mono_set_of_nonneg]
theorem prod_mono_set_of_one_le' (hf : ∀ x, 1 ≤ f x) : Monotone fun s ↦ ∏ x ∈ s, f x :=
fun _ _ hst ↦ prod_le_prod_of_subset_of_one_le' hst fun x _ _ ↦ hf x
@[to_additive sum_le_univ_sum_of_nonneg]
theorem prod_le_univ_prod_of_one_le' [Fintype ι] {s : Finset ι} (w : ∀ x, 1 ≤ f x) :
∏ x ∈ s, f x ≤ ∏ x, f x :=
prod_le_prod_of_subset_of_one_le' (subset_univ s) fun a _ _ ↦ w a
@[to_additive sum_eq_zero_iff_of_nonneg]
theorem prod_eq_one_iff_of_one_le' :
(∀ i ∈ s, 1 ≤ f i) → ((∏ i ∈ s, f i) = 1 ↔ ∀ i ∈ s, f i = 1) := by
classical
refine Finset.induction_on s
(fun _ ↦ ⟨fun _ _ h ↦ False.elim (Finset.not_mem_empty _ h), fun _ ↦ rfl⟩) ?_
intro a s ha ih H
have : ∀ i ∈ s, 1 ≤ f i := fun _ ↦ H _ ∘ mem_insert_of_mem
rw [prod_insert ha, mul_eq_one_iff_of_one_le (H _ <| mem_insert_self _ _) (one_le_prod' this),
forall_mem_insert, ih this]
@[to_additive sum_eq_zero_iff_of_nonpos]
theorem prod_eq_one_iff_of_le_one' :
(∀ i ∈ s, f i ≤ 1) → ((∏ i ∈ s, f i) = 1 ↔ ∀ i ∈ s, f i = 1) :=
prod_eq_one_iff_of_one_le' (N := Nᵒᵈ)
@[to_additive single_le_sum]
theorem single_le_prod' (hf : ∀ i ∈ s, 1 ≤ f i) {a} (h : a ∈ s) : f a ≤ ∏ x ∈ s, f x :=
calc
f a = ∏ i ∈ {a}, f i := (prod_singleton _ _).symm
_ ≤ ∏ i ∈ s, f i :=
prod_le_prod_of_subset_of_one_le' (singleton_subset_iff.2 h) fun i hi _ ↦ hf i hi
@[to_additive]
lemma mul_le_prod {i j : ι} (hf : ∀ i ∈ s, 1 ≤ f i) (hi : i ∈ s) (hj : j ∈ s) (hne : i ≠ j) :
f i * f j ≤ ∏ k ∈ s, f k :=
calc
f i * f j = ∏ k ∈ .cons i {j} (by simpa), f k := by rw [prod_cons, prod_singleton]
_ ≤ ∏ k ∈ s, f k := by
refine prod_le_prod_of_subset_of_one_le' ?_ fun k hk _ ↦ hf k hk
simp [cons_subset, *]
@[to_additive sum_le_card_nsmul]
theorem prod_le_pow_card (s : Finset ι) (f : ι → N) (n : N) (h : ∀ x ∈ s, f x ≤ n) :
s.prod f ≤ n ^ #s := by
refine (Multiset.prod_le_pow_card (s.val.map f) n ?_).trans ?_
· simpa using h
· simp
@[to_additive card_nsmul_le_sum]
theorem pow_card_le_prod (s : Finset ι) (f : ι → N) (n : N) (h : ∀ x ∈ s, n ≤ f x) :
n ^ #s ≤ s.prod f := Finset.prod_le_pow_card (N := Nᵒᵈ) _ _ _ h
theorem card_biUnion_le_card_mul [DecidableEq β] (s : Finset ι) (f : ι → Finset β) (n : ℕ)
(h : ∀ a ∈ s, #(f a) ≤ n) : #(s.biUnion f) ≤ #s * n :=
card_biUnion_le.trans <| sum_le_card_nsmul _ _ _ h
variable {ι' : Type*} [DecidableEq ι']
@[to_additive sum_fiberwise_le_sum_of_sum_fiber_nonneg]
theorem prod_fiberwise_le_prod_of_one_le_prod_fiber' {t : Finset ι'} {g : ι → ι'} {f : ι → N}
(h : ∀ y ∉ t, (1 : N) ≤ ∏ x ∈ s with g x = y, f x) :
(∏ y ∈ t, ∏ x ∈ s with g x = y, f x) ≤ ∏ x ∈ s, f x :=
calc
(∏ y ∈ t, ∏ x ∈ s with g x = y, f x) ≤
∏ y ∈ t ∪ s.image g, ∏ x ∈ s with g x = y, f x :=
prod_le_prod_of_subset_of_one_le' subset_union_left fun y _ ↦ h y
_ = ∏ x ∈ s, f x :=
prod_fiberwise_of_maps_to (fun _ hx ↦ mem_union.2 <| Or.inr <| mem_image_of_mem _ hx) _
@[to_additive sum_le_sum_fiberwise_of_sum_fiber_nonpos]
theorem prod_le_prod_fiberwise_of_prod_fiber_le_one' {t : Finset ι'} {g : ι → ι'} {f : ι → N}
(h : ∀ y ∉ t, ∏ x ∈ s with g x = y, f x ≤ 1) :
∏ x ∈ s, f x ≤ ∏ y ∈ t, ∏ x ∈ s with g x = y, f x :=
prod_fiberwise_le_prod_of_one_le_prod_fiber' (N := Nᵒᵈ) h
@[to_additive]
lemma prod_image_le_of_one_le
{g : ι → ι'} {f : ι' → N} (hf : ∀ u ∈ s.image g, 1 ≤ f u) :
∏ u ∈ s.image g, f u ≤ ∏ u ∈ s, f (g u) := by
rw [prod_comp f g]
refine prod_le_prod' fun a hag ↦ ?_
obtain ⟨i, hi, hig⟩ := Finset.mem_image.mp hag
apply le_self_pow (hf a hag)
rw [← Nat.pos_iff_ne_zero, card_pos]
exact ⟨i, mem_filter.mpr ⟨hi, hig⟩⟩
end OrderedCommMonoid
@[to_additive]
lemma max_prod_le [CommMonoid M] [LinearOrder M] [IsOrderedMonoid M] {f g : ι → M} {s : Finset ι} :
max (s.prod f) (s.prod g) ≤ s.prod (fun i ↦ max (f i) (g i)) :=
Multiset.max_prod_le
@[to_additive]
lemma prod_min_le [CommMonoid M] [LinearOrder M] [IsOrderedMonoid M] {f g : ι → M} {s : Finset ι} :
s.prod (fun i ↦ min (f i) (g i)) ≤ min (s.prod f) (s.prod g) :=
Multiset.prod_min_le
theorem abs_sum_le_sum_abs {G : Type*} [AddCommGroup G] [LinearOrder G] [IsOrderedAddMonoid G]
(f : ι → G) (s : Finset ι) :
|∑ i ∈ s, f i| ≤ ∑ i ∈ s, |f i| := le_sum_of_subadditive _ abs_zero abs_add s f
theorem abs_sum_of_nonneg {G : Type*} [AddCommGroup G] [LinearOrder G] [IsOrderedAddMonoid G]
{f : ι → G} {s : Finset ι}
(hf : ∀ i ∈ s, 0 ≤ f i) : |∑ i ∈ s, f i| = ∑ i ∈ s, f i := by
rw [abs_of_nonneg (Finset.sum_nonneg hf)]
theorem abs_sum_of_nonneg' {G : Type*} [AddCommGroup G] [LinearOrder G] [IsOrderedAddMonoid G]
{f : ι → G} {s : Finset ι}
(hf : ∀ i, 0 ≤ f i) : |∑ i ∈ s, f i| = ∑ i ∈ s, f i := by
rw [abs_of_nonneg (Finset.sum_nonneg' hf)]
section CommMonoid
variable [CommMonoid α] [LE α] [MulLeftMono α] {s : Finset ι} {f : ι → α}
@[to_additive (attr := simp)]
lemma mulLECancellable_prod :
MulLECancellable (∏ i ∈ s, f i) ↔ ∀ ⦃i⦄, i ∈ s → MulLECancellable (f i) := by
induction' s using Finset.cons_induction with i s hi ih <;> simp [*]
end CommMonoid
section Pigeonhole
variable [DecidableEq β]
theorem card_le_mul_card_image_of_maps_to {f : α → β} {s : Finset α} {t : Finset β}
(Hf : ∀ a ∈ s, f a ∈ t) (n : ℕ) (hn : ∀ b ∈ t, #{a ∈ s | f a = b} ≤ n) : #s ≤ n * #t :=
calc
#s = ∑ b ∈ t, #{a ∈ s | f a = b} := card_eq_sum_card_fiberwise Hf
_ ≤ ∑ _b ∈ t, n := sum_le_sum hn
_ = _ := by simp [mul_comm]
theorem card_le_mul_card_image {f : α → β} (s : Finset α) (n : ℕ)
(hn : ∀ b ∈ s.image f, #{a ∈ s | f a = b} ≤ n) : #s ≤ n * #(s.image f) :=
card_le_mul_card_image_of_maps_to (fun _ ↦ mem_image_of_mem _) n hn
theorem mul_card_image_le_card_of_maps_to {f : α → β} {s : Finset α} {t : Finset β}
(Hf : ∀ a ∈ s, f a ∈ t) (n : ℕ) (hn : ∀ b ∈ t, n ≤ #{a ∈ s | f a = b}) :
n * #t ≤ #s :=
calc
n * #t = ∑ _a ∈ t, n := by simp [mul_comm]
_ ≤ ∑ b ∈ t, #{a ∈ s | f a = b} := sum_le_sum hn
_ = #s := by rw [← card_eq_sum_card_fiberwise Hf]
theorem mul_card_image_le_card {f : α → β} (s : Finset α) (n : ℕ)
(hn : ∀ b ∈ s.image f, n ≤ #{a ∈ s | f a = b}) : n * #(s.image f) ≤ #s :=
mul_card_image_le_card_of_maps_to (fun _ ↦ mem_image_of_mem _) n hn
end Pigeonhole
section DoubleCounting
variable [DecidableEq α] {s : Finset α} {B : Finset (Finset α)} {n : ℕ}
/-- If every element belongs to at most `n` Finsets, then the sum of their sizes is at most `n`
times how many they are. -/
theorem sum_card_inter_le (h : ∀ a ∈ s, #{b ∈ B | a ∈ b} ≤ n) : (∑ t ∈ B, #(s ∩ t)) ≤ #s * n := by
refine le_trans ?_ (s.sum_le_card_nsmul _ _ h)
simp_rw [← filter_mem_eq_inter, card_eq_sum_ones, sum_filter]
exact sum_comm.le
/-- If every element belongs to at most `n` Finsets, then the sum of their sizes is at most `n`
times how many they are. -/
lemma sum_card_le [Fintype α] (h : ∀ a, #{b ∈ B | a ∈ b} ≤ n) : ∑ s ∈ B, #s ≤ Fintype.card α * n :=
calc
∑ s ∈ B, #s = ∑ s ∈ B, #(univ ∩ s) := by simp_rw [univ_inter]
_ ≤ Fintype.card α * n := sum_card_inter_le fun a _ ↦ h a
/-- If every element belongs to at least `n` Finsets, then the sum of their sizes is at least `n`
times how many they are. -/
theorem le_sum_card_inter (h : ∀ a ∈ s, n ≤ #{b ∈ B | a ∈ b}) : #s * n ≤ ∑ t ∈ B, #(s ∩ t) := by
apply (s.card_nsmul_le_sum _ _ h).trans
simp_rw [← filter_mem_eq_inter, card_eq_sum_ones, sum_filter]
exact sum_comm.le
/-- If every element belongs to at least `n` Finsets, then the sum of their sizes is at least `n`
times how many they are. -/
theorem le_sum_card [Fintype α] (h : ∀ a, n ≤ #{b ∈ B | a ∈ b}) :
Fintype.card α * n ≤ ∑ s ∈ B, #s :=
calc
Fintype.card α * n ≤ ∑ s ∈ B, #(univ ∩ s) := le_sum_card_inter fun a _ ↦ h a
_ = ∑ s ∈ B, #s := by simp_rw [univ_inter]
/-- If every element belongs to exactly `n` Finsets, then the sum of their sizes is `n` times how
many they are. -/
theorem sum_card_inter (h : ∀ a ∈ s, #{b ∈ B | a ∈ b} = n) :
(∑ t ∈ B, #(s ∩ t)) = #s * n :=
(sum_card_inter_le fun a ha ↦ (h a ha).le).antisymm (le_sum_card_inter fun a ha ↦ (h a ha).ge)
| /-- If every element belongs to exactly `n` Finsets, then the sum of their sizes is `n` times how
many they are. -/
theorem sum_card [Fintype α] (h : ∀ a, #{b ∈ B | a ∈ b} = n) :
∑ s ∈ B, #s = Fintype.card α * n := by
simp_rw [Fintype.card, ← sum_card_inter fun a _ ↦ h a, univ_inter]
| Mathlib/Algebra/Order/BigOperators/Group/Finset.lean | 326 | 330 |
/-
Copyright (c) 2019 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison
-/
import Mathlib.Geometry.RingedSpace.PresheafedSpace
import Mathlib.CategoryTheory.Limits.Final
import Mathlib.Topology.Sheaves.Stalks
/-!
# Stalks for presheaved spaces
This file lifts constructions of stalks and pushforwards of stalks to work with
the category of presheafed spaces. Additionally, we prove that restriction of
presheafed spaces does not change the stalks.
-/
noncomputable section
universe v u v' u'
open Opposite CategoryTheory CategoryTheory.Category CategoryTheory.Functor CategoryTheory.Limits
AlgebraicGeometry TopologicalSpace Topology
variable {C : Type u} [Category.{v} C] [HasColimits C]
-- Porting note: no tidy tactic
-- attribute [local tidy] tactic.auto_cases_opens
-- this could be replaced by
-- attribute [local aesop safe cases (rule_sets := [CategoryTheory])] Opens
-- but it doesn't appear to be needed here.
open TopCat.Presheaf
namespace AlgebraicGeometry.PresheafedSpace
/-- A morphism of presheafed spaces induces a morphism of stalks.
-/
def Hom.stalkMap {X Y : PresheafedSpace.{_, _, v} C} (α : Hom X Y) (x : X) :
Y.presheaf.stalk (α.base x) ⟶ X.presheaf.stalk x :=
(stalkFunctor C (α.base x)).map α.c ≫ X.presheaf.stalkPushforward C α.base x
@[elementwise, reassoc]
theorem stalkMap_germ {X Y : PresheafedSpace.{_, _, v} C} (α : X ⟶ Y) (U : Opens Y)
(x : X) (hx : α x ∈ U) :
Y.presheaf.germ U (α x) hx ≫ α.stalkMap x = α.c.app (op U) ≫
X.presheaf.germ ((Opens.map α.base).obj U) x hx := by
rw [Hom.stalkMap, stalkFunctor_map_germ_assoc, stalkPushforward_germ]
section Restrict
/-- For an open embedding `f : U ⟶ X` and a point `x : U`, we get an isomorphism between the stalk
of `X` at `f x` and the stalk of the restriction of `X` along `f` at t `x`.
-/
def restrictStalkIso {U : TopCat} (X : PresheafedSpace.{_, _, v} C) {f : U ⟶ (X : TopCat.{v})}
(h : IsOpenEmbedding f) (x : U) : (X.restrict h).presheaf.stalk x ≅ X.presheaf.stalk (f x) :=
haveI := initial_of_adjunction (h.isOpenMap.adjunctionNhds x)
Final.colimitIso (h.isOpenMap.functorNhds x).op ((OpenNhds.inclusion (f x)).op ⋙ X.presheaf)
-- As a left adjoint, the functor `h.is_open_map.functor_nhds x` is initial.
-- Typeclass resolution knows that the opposite of an initial functor is final. The result
-- follows from the general fact that postcomposing with a final functor doesn't change colimits.
-- Porting note (https://github.com/leanprover-community/mathlib4/issues/11119): removed `simp` attribute, for left hand side is not in simple normal form.
@[elementwise, reassoc]
theorem restrictStalkIso_hom_eq_germ {U : TopCat} (X : PresheafedSpace.{_, _, v} C)
{f : U ⟶ (X : TopCat.{v})} (h : IsOpenEmbedding f) (V : Opens U) (x : U) (hx : x ∈ V) :
(X.restrict h).presheaf.germ _ x hx ≫ (restrictStalkIso X h x).hom =
X.presheaf.germ (h.isOpenMap.functor.obj V) (f x) ⟨x, hx, rfl⟩ :=
colimit.ι_pre ((OpenNhds.inclusion (f x)).op ⋙ X.presheaf) (h.isOpenMap.functorNhds x).op
(op ⟨V, hx⟩)
-- We intentionally leave `simp` off the lemmas generated by `elementwise` and `reassoc`,
-- as the simpNF linter claims they never apply.
@[simp, elementwise, reassoc]
theorem restrictStalkIso_inv_eq_germ {U : TopCat} (X : PresheafedSpace.{_, _, v} C)
{f : U ⟶ (X : TopCat.{v})} (h : IsOpenEmbedding f) (V : Opens U) (x : U) (hx : x ∈ V) :
X.presheaf.germ (h.isOpenMap.functor.obj V) (f x) ⟨x, hx, rfl⟩ ≫
(restrictStalkIso X h x).inv =
(X.restrict h).presheaf.germ _ x hx := by
rw [← restrictStalkIso_hom_eq_germ, Category.assoc, Iso.hom_inv_id, Category.comp_id]
theorem restrictStalkIso_inv_eq_ofRestrict {U : TopCat} (X : PresheafedSpace.{_, _, v} C)
{f : U ⟶ (X : TopCat.{v})} (h : IsOpenEmbedding f) (x : U) :
(X.restrictStalkIso h x).inv = (X.ofRestrict h).stalkMap x := by
-- We can't use `ext` here due to https://github.com/leanprover/std4/pull/159
refine colimit.hom_ext fun V => ?_
induction V with | op V => ?_
let i : (h.isOpenMap.functorNhds x).obj ((OpenNhds.map f x).obj V) ⟶ V :=
homOfLE (Set.image_preimage_subset f _)
erw [Iso.comp_inv_eq, colimit.ι_map_assoc, colimit.ι_map_assoc, colimit.ι_pre]
simp_rw [Category.assoc]
erw [colimit.ι_pre ((OpenNhds.inclusion (f x)).op ⋙ X.presheaf)
(h.isOpenMap.functorNhds x).op]
erw [← X.presheaf.map_comp_assoc]
exact (colimit.w ((OpenNhds.inclusion (f x)).op ⋙ X.presheaf) i.op).symm
instance ofRestrict_stalkMap_isIso {U : TopCat} (X : PresheafedSpace.{_, _, v} C)
{f : U ⟶ (X : TopCat.{v})} (h : IsOpenEmbedding f) (x : U) :
IsIso ((X.ofRestrict h).stalkMap x) := by
rw [← restrictStalkIso_inv_eq_ofRestrict]; infer_instance
end Restrict
namespace stalkMap
@[simp]
| theorem id (X : PresheafedSpace.{_, _, v} C) (x : X) :
(𝟙 X : X ⟶ X).stalkMap x = 𝟙 (X.presheaf.stalk x) := by
dsimp [Hom.stalkMap]
simp only [stalkPushforward.id]
rw [← map_comp]
convert (stalkFunctor C x).map_id X.presheaf
ext
simp only [id_c, id_comp, Pushforward.id_hom_app, op_obj, eqToHom_refl, map_id]
rfl
@[simp]
theorem comp {X Y Z : PresheafedSpace.{_, _, v} C} (α : X ⟶ Y) (β : Y ⟶ Z) (x : X) :
(α ≫ β).stalkMap x =
(β.stalkMap (α.base x) : Z.presheaf.stalk (β.base (α.base x)) ⟶ Y.presheaf.stalk (α.base x)) ≫
| Mathlib/Geometry/RingedSpace/Stalks.lean | 108 | 121 |
/-
Copyright (c) 2019 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Analytic.Constructions
import Mathlib.Analysis.Calculus.FDeriv.Analytic
import Mathlib.Analysis.Calculus.FDeriv.Bilinear
/-!
# Multiplicative operations on derivatives
For detailed documentation of the Fréchet derivative,
see the module docstring of `Mathlib/Analysis/Calculus/FDeriv/Basic.lean`.
This file contains the usual formulas (and existence assertions) for the derivative of
* multiplication of a function by a scalar function
* product of finitely many scalar functions
* taking the pointwise multiplicative inverse (i.e. `Inv.inv` or `Ring.inverse`) of a function
-/
open Asymptotics ContinuousLinearMap Topology
section
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜]
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
variable {F : Type*} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
variable {G : Type*} [NormedAddCommGroup G] [NormedSpace 𝕜 G]
variable {f : E → F}
variable {f' : E →L[𝕜] F}
variable {x : E}
variable {s : Set E}
section CLMCompApply
/-! ### Derivative of the pointwise composition/application of continuous linear maps -/
variable {H : Type*} [NormedAddCommGroup H] [NormedSpace 𝕜 H] {c : E → G →L[𝕜] H}
{c' : E →L[𝕜] G →L[𝕜] H} {d : E → F →L[𝕜] G} {d' : E →L[𝕜] F →L[𝕜] G} {u : E → G} {u' : E →L[𝕜] G}
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
split proof term into steps to solve unification issues. -/
@[fun_prop]
theorem HasStrictFDerivAt.clm_comp (hc : HasStrictFDerivAt c c' x) (hd : HasStrictFDerivAt d d' x) :
HasStrictFDerivAt (fun y => (c y).comp (d y))
((compL 𝕜 F G H (c x)).comp d' + ((compL 𝕜 F G H).flip (d x)).comp c') x := by
have := isBoundedBilinearMap_comp.hasStrictFDerivAt (c x, d x)
have := this.comp x (hc.prodMk hd)
exact this
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivWithinAt.clm_comp (hc : HasFDerivWithinAt c c' s x)
(hd : HasFDerivWithinAt d d' s x) :
HasFDerivWithinAt (fun y => (c y).comp (d y))
((compL 𝕜 F G H (c x)).comp d' + ((compL 𝕜 F G H).flip (d x)).comp c') s x := by
exact (isBoundedBilinearMap_comp.hasFDerivAt (c x, d x) :).comp_hasFDerivWithinAt x (hc.prodMk hd)
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivAt.clm_comp (hc : HasFDerivAt c c' x) (hd : HasFDerivAt d d' x) :
HasFDerivAt (fun y => (c y).comp (d y))
((compL 𝕜 F G H (c x)).comp d' + ((compL 𝕜 F G H).flip (d x)).comp c') x := by
exact (isBoundedBilinearMap_comp.hasFDerivAt (c x, d x) :).comp x <| hc.prodMk hd
@[fun_prop]
theorem DifferentiableWithinAt.clm_comp (hc : DifferentiableWithinAt 𝕜 c s x)
(hd : DifferentiableWithinAt 𝕜 d s x) :
DifferentiableWithinAt 𝕜 (fun y => (c y).comp (d y)) s x :=
(hc.hasFDerivWithinAt.clm_comp hd.hasFDerivWithinAt).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.clm_comp (hc : DifferentiableAt 𝕜 c x) (hd : DifferentiableAt 𝕜 d x) :
DifferentiableAt 𝕜 (fun y => (c y).comp (d y)) x :=
(hc.hasFDerivAt.clm_comp hd.hasFDerivAt).differentiableAt
@[fun_prop]
theorem DifferentiableOn.clm_comp (hc : DifferentiableOn 𝕜 c s) (hd : DifferentiableOn 𝕜 d s) :
DifferentiableOn 𝕜 (fun y => (c y).comp (d y)) s := fun x hx => (hc x hx).clm_comp (hd x hx)
@[fun_prop]
theorem Differentiable.clm_comp (hc : Differentiable 𝕜 c) (hd : Differentiable 𝕜 d) :
Differentiable 𝕜 fun y => (c y).comp (d y) := fun x => (hc x).clm_comp (hd x)
theorem fderivWithin_clm_comp (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(hd : DifferentiableWithinAt 𝕜 d s x) :
fderivWithin 𝕜 (fun y => (c y).comp (d y)) s x =
(compL 𝕜 F G H (c x)).comp (fderivWithin 𝕜 d s x) +
((compL 𝕜 F G H).flip (d x)).comp (fderivWithin 𝕜 c s x) :=
(hc.hasFDerivWithinAt.clm_comp hd.hasFDerivWithinAt).fderivWithin hxs
theorem fderiv_clm_comp (hc : DifferentiableAt 𝕜 c x) (hd : DifferentiableAt 𝕜 d x) :
fderiv 𝕜 (fun y => (c y).comp (d y)) x =
(compL 𝕜 F G H (c x)).comp (fderiv 𝕜 d x) +
((compL 𝕜 F G H).flip (d x)).comp (fderiv 𝕜 c x) :=
(hc.hasFDerivAt.clm_comp hd.hasFDerivAt).fderiv
@[fun_prop]
theorem HasStrictFDerivAt.clm_apply (hc : HasStrictFDerivAt c c' x)
(hu : HasStrictFDerivAt u u' x) :
HasStrictFDerivAt (fun y => (c y) (u y)) ((c x).comp u' + c'.flip (u x)) x :=
(isBoundedBilinearMap_apply.hasStrictFDerivAt (c x, u x)).comp x (hc.prodMk hu)
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivWithinAt.clm_apply (hc : HasFDerivWithinAt c c' s x)
(hu : HasFDerivWithinAt u u' s x) :
HasFDerivWithinAt (fun y => (c y) (u y)) ((c x).comp u' + c'.flip (u x)) s x := by
exact (isBoundedBilinearMap_apply.hasFDerivAt (c x, u x) :).comp_hasFDerivWithinAt x
(hc.prodMk hu)
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivAt.clm_apply (hc : HasFDerivAt c c' x) (hu : HasFDerivAt u u' x) :
HasFDerivAt (fun y => (c y) (u y)) ((c x).comp u' + c'.flip (u x)) x := by
exact (isBoundedBilinearMap_apply.hasFDerivAt (c x, u x) :).comp x (hc.prodMk hu)
@[fun_prop]
theorem DifferentiableWithinAt.clm_apply (hc : DifferentiableWithinAt 𝕜 c s x)
(hu : DifferentiableWithinAt 𝕜 u s x) : DifferentiableWithinAt 𝕜 (fun y => (c y) (u y)) s x :=
(hc.hasFDerivWithinAt.clm_apply hu.hasFDerivWithinAt).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.clm_apply (hc : DifferentiableAt 𝕜 c x) (hu : DifferentiableAt 𝕜 u x) :
DifferentiableAt 𝕜 (fun y => (c y) (u y)) x :=
(hc.hasFDerivAt.clm_apply hu.hasFDerivAt).differentiableAt
@[fun_prop]
theorem DifferentiableOn.clm_apply (hc : DifferentiableOn 𝕜 c s) (hu : DifferentiableOn 𝕜 u s) :
DifferentiableOn 𝕜 (fun y => (c y) (u y)) s := fun x hx => (hc x hx).clm_apply (hu x hx)
@[fun_prop]
theorem Differentiable.clm_apply (hc : Differentiable 𝕜 c) (hu : Differentiable 𝕜 u) :
Differentiable 𝕜 fun y => (c y) (u y) := fun x => (hc x).clm_apply (hu x)
theorem fderivWithin_clm_apply (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (hu : DifferentiableWithinAt 𝕜 u s x) :
fderivWithin 𝕜 (fun y => (c y) (u y)) s x =
(c x).comp (fderivWithin 𝕜 u s x) + (fderivWithin 𝕜 c s x).flip (u x) :=
(hc.hasFDerivWithinAt.clm_apply hu.hasFDerivWithinAt).fderivWithin hxs
theorem fderiv_clm_apply (hc : DifferentiableAt 𝕜 c x) (hu : DifferentiableAt 𝕜 u x) :
fderiv 𝕜 (fun y => (c y) (u y)) x = (c x).comp (fderiv 𝕜 u x) + (fderiv 𝕜 c x).flip (u x) :=
(hc.hasFDerivAt.clm_apply hu.hasFDerivAt).fderiv
end CLMCompApply
section ContinuousMultilinearApplyConst
/-! ### Derivative of the application of continuous multilinear maps to a constant -/
variable {ι : Type*} [Fintype ι]
{M : ι → Type*} [∀ i, NormedAddCommGroup (M i)] [∀ i, NormedSpace 𝕜 (M i)]
{H : Type*} [NormedAddCommGroup H] [NormedSpace 𝕜 H]
{c : E → ContinuousMultilinearMap 𝕜 M H}
{c' : E →L[𝕜] ContinuousMultilinearMap 𝕜 M H}
@[fun_prop]
theorem HasStrictFDerivAt.continuousMultilinear_apply_const (hc : HasStrictFDerivAt c c' x)
(u : ∀ i, M i) : HasStrictFDerivAt (fun y ↦ (c y) u) (c'.flipMultilinear u) x :=
(ContinuousMultilinearMap.apply 𝕜 M H u).hasStrictFDerivAt.comp x hc
@[fun_prop]
theorem HasFDerivWithinAt.continuousMultilinear_apply_const (hc : HasFDerivWithinAt c c' s x)
(u : ∀ i, M i) :
HasFDerivWithinAt (fun y ↦ (c y) u) (c'.flipMultilinear u) s x :=
(ContinuousMultilinearMap.apply 𝕜 M H u).hasFDerivAt.comp_hasFDerivWithinAt x hc
@[fun_prop]
theorem HasFDerivAt.continuousMultilinear_apply_const (hc : HasFDerivAt c c' x) (u : ∀ i, M i) :
HasFDerivAt (fun y ↦ (c y) u) (c'.flipMultilinear u) x :=
(ContinuousMultilinearMap.apply 𝕜 M H u).hasFDerivAt.comp x hc
@[fun_prop]
theorem DifferentiableWithinAt.continuousMultilinear_apply_const
(hc : DifferentiableWithinAt 𝕜 c s x) (u : ∀ i, M i) :
DifferentiableWithinAt 𝕜 (fun y ↦ (c y) u) s x :=
(hc.hasFDerivWithinAt.continuousMultilinear_apply_const u).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.continuousMultilinear_apply_const (hc : DifferentiableAt 𝕜 c x)
(u : ∀ i, M i) :
DifferentiableAt 𝕜 (fun y ↦ (c y) u) x :=
(hc.hasFDerivAt.continuousMultilinear_apply_const u).differentiableAt
@[fun_prop]
theorem DifferentiableOn.continuousMultilinear_apply_const (hc : DifferentiableOn 𝕜 c s)
(u : ∀ i, M i) : DifferentiableOn 𝕜 (fun y ↦ (c y) u) s :=
fun x hx ↦ (hc x hx).continuousMultilinear_apply_const u
@[fun_prop]
theorem Differentiable.continuousMultilinear_apply_const (hc : Differentiable 𝕜 c) (u : ∀ i, M i) :
Differentiable 𝕜 fun y ↦ (c y) u := fun x ↦ (hc x).continuousMultilinear_apply_const u
theorem fderivWithin_continuousMultilinear_apply_const (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (u : ∀ i, M i) :
fderivWithin 𝕜 (fun y ↦ (c y) u) s x = ((fderivWithin 𝕜 c s x).flipMultilinear u) :=
(hc.hasFDerivWithinAt.continuousMultilinear_apply_const u).fderivWithin hxs
theorem fderiv_continuousMultilinear_apply_const (hc : DifferentiableAt 𝕜 c x) (u : ∀ i, M i) :
(fderiv 𝕜 (fun y ↦ (c y) u) x) = (fderiv 𝕜 c x).flipMultilinear u :=
(hc.hasFDerivAt.continuousMultilinear_apply_const u).fderiv
/-- Application of a `ContinuousMultilinearMap` to a constant commutes with `fderivWithin`. -/
theorem fderivWithin_continuousMultilinear_apply_const_apply (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (u : ∀ i, M i) (m : E) :
(fderivWithin 𝕜 (fun y ↦ (c y) u) s x) m = (fderivWithin 𝕜 c s x) m u := by
simp [fderivWithin_continuousMultilinear_apply_const hxs hc]
/-- Application of a `ContinuousMultilinearMap` to a constant commutes with `fderiv`. -/
theorem fderiv_continuousMultilinear_apply_const_apply (hc : DifferentiableAt 𝕜 c x)
(u : ∀ i, M i) (m : E) :
(fderiv 𝕜 (fun y ↦ (c y) u) x) m = (fderiv 𝕜 c x) m u := by
simp [fderiv_continuousMultilinear_apply_const hc]
end ContinuousMultilinearApplyConst
section SMul
/-! ### Derivative of the product of a scalar-valued function and a vector-valued function
If `c` is a differentiable scalar-valued function and `f` is a differentiable vector-valued
function, then `fun x ↦ c x • f x` is differentiable as well. Lemmas in this section works for
function `c` taking values in the base field, as well as in a normed algebra over the base
field: e.g., they work for `c : E → ℂ` and `f : E → F` provided that `F` is a complex
normed vector space.
-/
variable {𝕜' : Type*} [NontriviallyNormedField 𝕜'] [NormedAlgebra 𝕜 𝕜'] [NormedSpace 𝕜' F]
[IsScalarTower 𝕜 𝕜' F]
variable {c : E → 𝕜'} {c' : E →L[𝕜] 𝕜'}
@[fun_prop]
theorem HasStrictFDerivAt.smul (hc : HasStrictFDerivAt c c' x) (hf : HasStrictFDerivAt f f' x) :
HasStrictFDerivAt (fun y => c y • f y) (c x • f' + c'.smulRight (f x)) x :=
(isBoundedBilinearMap_smul.hasStrictFDerivAt (c x, f x)).comp x <| hc.prodMk hf
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivWithinAt.smul (hc : HasFDerivWithinAt c c' s x) (hf : HasFDerivWithinAt f f' s x) :
HasFDerivWithinAt (fun y => c y • f y) (c x • f' + c'.smulRight (f x)) s x := by
exact (isBoundedBilinearMap_smul.hasFDerivAt (𝕜 := 𝕜) (c x, f x) :).comp_hasFDerivWithinAt x <|
hc.prodMk hf
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivAt.smul (hc : HasFDerivAt c c' x) (hf : HasFDerivAt f f' x) :
HasFDerivAt (fun y => c y • f y) (c x • f' + c'.smulRight (f x)) x := by
exact (isBoundedBilinearMap_smul.hasFDerivAt (𝕜 := 𝕜) (c x, f x) :).comp x <| hc.prodMk hf
@[fun_prop]
theorem DifferentiableWithinAt.smul (hc : DifferentiableWithinAt 𝕜 c s x)
(hf : DifferentiableWithinAt 𝕜 f s x) : DifferentiableWithinAt 𝕜 (fun y => c y • f y) s x :=
(hc.hasFDerivWithinAt.smul hf.hasFDerivWithinAt).differentiableWithinAt
@[simp, fun_prop]
theorem DifferentiableAt.smul (hc : DifferentiableAt 𝕜 c x) (hf : DifferentiableAt 𝕜 f x) :
DifferentiableAt 𝕜 (fun y => c y • f y) x :=
(hc.hasFDerivAt.smul hf.hasFDerivAt).differentiableAt
@[fun_prop]
theorem DifferentiableOn.smul (hc : DifferentiableOn 𝕜 c s) (hf : DifferentiableOn 𝕜 f s) :
DifferentiableOn 𝕜 (fun y => c y • f y) s := fun x hx => (hc x hx).smul (hf x hx)
@[simp, fun_prop]
theorem Differentiable.smul (hc : Differentiable 𝕜 c) (hf : Differentiable 𝕜 f) :
Differentiable 𝕜 fun y => c y • f y := fun x => (hc x).smul (hf x)
theorem fderivWithin_smul (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(hf : DifferentiableWithinAt 𝕜 f s x) :
fderivWithin 𝕜 (fun y => c y • f y) s x =
c x • fderivWithin 𝕜 f s x + (fderivWithin 𝕜 c s x).smulRight (f x) :=
(hc.hasFDerivWithinAt.smul hf.hasFDerivWithinAt).fderivWithin hxs
theorem fderiv_smul (hc : DifferentiableAt 𝕜 c x) (hf : DifferentiableAt 𝕜 f x) :
fderiv 𝕜 (fun y => c y • f y) x = c x • fderiv 𝕜 f x + (fderiv 𝕜 c x).smulRight (f x) :=
(hc.hasFDerivAt.smul hf.hasFDerivAt).fderiv
@[fun_prop]
theorem HasStrictFDerivAt.smul_const (hc : HasStrictFDerivAt c c' x) (f : F) :
HasStrictFDerivAt (fun y => c y • f) (c'.smulRight f) x := by
simpa only [smul_zero, zero_add] using hc.smul (hasStrictFDerivAt_const f x)
@[fun_prop]
theorem HasFDerivWithinAt.smul_const (hc : HasFDerivWithinAt c c' s x) (f : F) :
HasFDerivWithinAt (fun y => c y • f) (c'.smulRight f) s x := by
simpa only [smul_zero, zero_add] using hc.smul (hasFDerivWithinAt_const f x s)
@[fun_prop]
theorem HasFDerivAt.smul_const (hc : HasFDerivAt c c' x) (f : F) :
HasFDerivAt (fun y => c y • f) (c'.smulRight f) x := by
simpa only [smul_zero, zero_add] using hc.smul (hasFDerivAt_const f x)
@[fun_prop]
theorem DifferentiableWithinAt.smul_const (hc : DifferentiableWithinAt 𝕜 c s x) (f : F) :
DifferentiableWithinAt 𝕜 (fun y => c y • f) s x :=
(hc.hasFDerivWithinAt.smul_const f).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.smul_const (hc : DifferentiableAt 𝕜 c x) (f : F) :
DifferentiableAt 𝕜 (fun y => c y • f) x :=
(hc.hasFDerivAt.smul_const f).differentiableAt
@[fun_prop]
theorem DifferentiableOn.smul_const (hc : DifferentiableOn 𝕜 c s) (f : F) :
DifferentiableOn 𝕜 (fun y => c y • f) s := fun x hx => (hc x hx).smul_const f
@[fun_prop]
theorem Differentiable.smul_const (hc : Differentiable 𝕜 c) (f : F) :
Differentiable 𝕜 fun y => c y • f := fun x => (hc x).smul_const f
theorem fderivWithin_smul_const (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (f : F) :
fderivWithin 𝕜 (fun y => c y • f) s x = (fderivWithin 𝕜 c s x).smulRight f :=
(hc.hasFDerivWithinAt.smul_const f).fderivWithin hxs
theorem fderiv_smul_const (hc : DifferentiableAt 𝕜 c x) (f : F) :
fderiv 𝕜 (fun y => c y • f) x = (fderiv 𝕜 c x).smulRight f :=
(hc.hasFDerivAt.smul_const f).fderiv
end SMul
section Mul
/-! ### Derivative of the product of two functions -/
variable {𝔸 𝔸' : Type*} [NormedRing 𝔸] [NormedCommRing 𝔸'] [NormedAlgebra 𝕜 𝔸] [NormedAlgebra 𝕜 𝔸']
{a b : E → 𝔸} {a' b' : E →L[𝕜] 𝔸} {c d : E → 𝔸'} {c' d' : E →L[𝕜] 𝔸'}
@[fun_prop]
theorem HasStrictFDerivAt.mul' {x : E} (ha : HasStrictFDerivAt a a' x)
(hb : HasStrictFDerivAt b b' x) :
HasStrictFDerivAt (fun y => a y * b y) (a x • b' + a'.smulRight (b x)) x :=
((ContinuousLinearMap.mul 𝕜 𝔸).isBoundedBilinearMap.hasStrictFDerivAt (a x, b x)).comp x
(ha.prodMk hb)
@[fun_prop]
theorem HasStrictFDerivAt.mul (hc : HasStrictFDerivAt c c' x) (hd : HasStrictFDerivAt d d' x) :
HasStrictFDerivAt (fun y => c y * d y) (c x • d' + d x • c') x := by
convert hc.mul' hd
ext z
apply mul_comm
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivWithinAt.mul' (ha : HasFDerivWithinAt a a' s x) (hb : HasFDerivWithinAt b b' s x) :
HasFDerivWithinAt (fun y => a y * b y) (a x • b' + a'.smulRight (b x)) s x := by
exact ((ContinuousLinearMap.mul 𝕜 𝔸).isBoundedBilinearMap.hasFDerivAt
(a x, b x)).comp_hasFDerivWithinAt x (ha.prodMk hb)
@[fun_prop]
theorem HasFDerivWithinAt.mul (hc : HasFDerivWithinAt c c' s x) (hd : HasFDerivWithinAt d d' s x) :
HasFDerivWithinAt (fun y => c y * d y) (c x • d' + d x • c') s x := by
convert hc.mul' hd
ext z
apply mul_comm
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivAt.mul' (ha : HasFDerivAt a a' x) (hb : HasFDerivAt b b' x) :
HasFDerivAt (fun y => a y * b y) (a x • b' + a'.smulRight (b x)) x := by
exact ((ContinuousLinearMap.mul 𝕜 𝔸).isBoundedBilinearMap.hasFDerivAt
(a x, b x)).comp x (ha.prodMk hb)
@[fun_prop]
theorem HasFDerivAt.mul (hc : HasFDerivAt c c' x) (hd : HasFDerivAt d d' x) :
HasFDerivAt (fun y => c y * d y) (c x • d' + d x • c') x := by
convert hc.mul' hd
ext z
apply mul_comm
@[fun_prop]
theorem DifferentiableWithinAt.mul (ha : DifferentiableWithinAt 𝕜 a s x)
(hb : DifferentiableWithinAt 𝕜 b s x) : DifferentiableWithinAt 𝕜 (fun y => a y * b y) s x :=
(ha.hasFDerivWithinAt.mul' hb.hasFDerivWithinAt).differentiableWithinAt
@[simp, fun_prop]
theorem DifferentiableAt.mul (ha : DifferentiableAt 𝕜 a x) (hb : DifferentiableAt 𝕜 b x) :
DifferentiableAt 𝕜 (fun y => a y * b y) x :=
(ha.hasFDerivAt.mul' hb.hasFDerivAt).differentiableAt
@[fun_prop]
theorem DifferentiableOn.mul (ha : DifferentiableOn 𝕜 a s) (hb : DifferentiableOn 𝕜 b s) :
DifferentiableOn 𝕜 (fun y => a y * b y) s := fun x hx => (ha x hx).mul (hb x hx)
@[simp, fun_prop]
theorem Differentiable.mul (ha : Differentiable 𝕜 a) (hb : Differentiable 𝕜 b) :
Differentiable 𝕜 fun y => a y * b y := fun x => (ha x).mul (hb x)
@[fun_prop]
theorem DifferentiableWithinAt.pow (ha : DifferentiableWithinAt 𝕜 a s x) :
∀ n : ℕ, DifferentiableWithinAt 𝕜 (fun x => a x ^ n) s x
| 0 => by simp only [pow_zero, differentiableWithinAt_const]
| n + 1 => by simp only [pow_succ', DifferentiableWithinAt.pow ha n, ha.mul]
@[simp, fun_prop]
theorem DifferentiableAt.pow (ha : DifferentiableAt 𝕜 a x) (n : ℕ) :
DifferentiableAt 𝕜 (fun x => a x ^ n) x :=
differentiableWithinAt_univ.mp <| ha.differentiableWithinAt.pow n
@[fun_prop]
theorem DifferentiableOn.pow (ha : DifferentiableOn 𝕜 a s) (n : ℕ) :
DifferentiableOn 𝕜 (fun x => a x ^ n) s := fun x h => (ha x h).pow n
@[simp, fun_prop]
theorem Differentiable.pow (ha : Differentiable 𝕜 a) (n : ℕ) : Differentiable 𝕜 fun x => a x ^ n :=
fun x => (ha x).pow n
theorem fderivWithin_mul' (hxs : UniqueDiffWithinAt 𝕜 s x) (ha : DifferentiableWithinAt 𝕜 a s x)
(hb : DifferentiableWithinAt 𝕜 b s x) :
fderivWithin 𝕜 (fun y => a y * b y) s x =
a x • fderivWithin 𝕜 b s x + (fderivWithin 𝕜 a s x).smulRight (b x) :=
(ha.hasFDerivWithinAt.mul' hb.hasFDerivWithinAt).fderivWithin hxs
theorem fderivWithin_mul (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(hd : DifferentiableWithinAt 𝕜 d s x) :
fderivWithin 𝕜 (fun y => c y * d y) s x =
c x • fderivWithin 𝕜 d s x + d x • fderivWithin 𝕜 c s x :=
(hc.hasFDerivWithinAt.mul hd.hasFDerivWithinAt).fderivWithin hxs
theorem fderiv_mul' (ha : DifferentiableAt 𝕜 a x) (hb : DifferentiableAt 𝕜 b x) :
fderiv 𝕜 (fun y => a y * b y) x = a x • fderiv 𝕜 b x + (fderiv 𝕜 a x).smulRight (b x) :=
(ha.hasFDerivAt.mul' hb.hasFDerivAt).fderiv
theorem fderiv_mul (hc : DifferentiableAt 𝕜 c x) (hd : DifferentiableAt 𝕜 d x) :
fderiv 𝕜 (fun y => c y * d y) x = c x • fderiv 𝕜 d x + d x • fderiv 𝕜 c x :=
(hc.hasFDerivAt.mul hd.hasFDerivAt).fderiv
@[fun_prop]
theorem HasStrictFDerivAt.mul_const' (ha : HasStrictFDerivAt a a' x) (b : 𝔸) :
HasStrictFDerivAt (fun y => a y * b) (a'.smulRight b) x :=
((ContinuousLinearMap.mul 𝕜 𝔸).flip b).hasStrictFDerivAt.comp x ha
@[fun_prop]
theorem HasStrictFDerivAt.mul_const (hc : HasStrictFDerivAt c c' x) (d : 𝔸') :
HasStrictFDerivAt (fun y => c y * d) (d • c') x := by
convert hc.mul_const' d
ext z
apply mul_comm
@[fun_prop]
theorem HasFDerivWithinAt.mul_const' (ha : HasFDerivWithinAt a a' s x) (b : 𝔸) :
HasFDerivWithinAt (fun y => a y * b) (a'.smulRight b) s x :=
((ContinuousLinearMap.mul 𝕜 𝔸).flip b).hasFDerivAt.comp_hasFDerivWithinAt x ha
@[fun_prop]
theorem HasFDerivWithinAt.mul_const (hc : HasFDerivWithinAt c c' s x) (d : 𝔸') :
HasFDerivWithinAt (fun y => c y * d) (d • c') s x := by
convert hc.mul_const' d
ext z
apply mul_comm
@[fun_prop]
theorem HasFDerivAt.mul_const' (ha : HasFDerivAt a a' x) (b : 𝔸) :
HasFDerivAt (fun y => a y * b) (a'.smulRight b) x :=
((ContinuousLinearMap.mul 𝕜 𝔸).flip b).hasFDerivAt.comp x ha
@[fun_prop]
theorem HasFDerivAt.mul_const (hc : HasFDerivAt c c' x) (d : 𝔸') :
HasFDerivAt (fun y => c y * d) (d • c') x := by
convert hc.mul_const' d
ext z
apply mul_comm
@[fun_prop]
theorem DifferentiableWithinAt.mul_const (ha : DifferentiableWithinAt 𝕜 a s x) (b : 𝔸) :
DifferentiableWithinAt 𝕜 (fun y => a y * b) s x :=
(ha.hasFDerivWithinAt.mul_const' b).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.mul_const (ha : DifferentiableAt 𝕜 a x) (b : 𝔸) :
DifferentiableAt 𝕜 (fun y => a y * b) x :=
(ha.hasFDerivAt.mul_const' b).differentiableAt
@[fun_prop]
theorem DifferentiableOn.mul_const (ha : DifferentiableOn 𝕜 a s) (b : 𝔸) :
DifferentiableOn 𝕜 (fun y => a y * b) s := fun x hx => (ha x hx).mul_const b
@[fun_prop]
theorem Differentiable.mul_const (ha : Differentiable 𝕜 a) (b : 𝔸) :
Differentiable 𝕜 fun y => a y * b := fun x => (ha x).mul_const b
theorem fderivWithin_mul_const' (hxs : UniqueDiffWithinAt 𝕜 s x)
(ha : DifferentiableWithinAt 𝕜 a s x) (b : 𝔸) :
fderivWithin 𝕜 (fun y => a y * b) s x = (fderivWithin 𝕜 a s x).smulRight b :=
(ha.hasFDerivWithinAt.mul_const' b).fderivWithin hxs
theorem fderivWithin_mul_const (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (d : 𝔸') :
fderivWithin 𝕜 (fun y => c y * d) s x = d • fderivWithin 𝕜 c s x :=
(hc.hasFDerivWithinAt.mul_const d).fderivWithin hxs
theorem fderiv_mul_const' (ha : DifferentiableAt 𝕜 a x) (b : 𝔸) :
fderiv 𝕜 (fun y => a y * b) x = (fderiv 𝕜 a x).smulRight b :=
(ha.hasFDerivAt.mul_const' b).fderiv
theorem fderiv_mul_const (hc : DifferentiableAt 𝕜 c x) (d : 𝔸') :
fderiv 𝕜 (fun y => c y * d) x = d • fderiv 𝕜 c x :=
(hc.hasFDerivAt.mul_const d).fderiv
@[fun_prop]
theorem HasStrictFDerivAt.const_mul (ha : HasStrictFDerivAt a a' x) (b : 𝔸) :
HasStrictFDerivAt (fun y => b * a y) (b • a') x :=
((ContinuousLinearMap.mul 𝕜 𝔸) b).hasStrictFDerivAt.comp x ha
@[fun_prop]
theorem HasFDerivWithinAt.const_mul (ha : HasFDerivWithinAt a a' s x) (b : 𝔸) :
HasFDerivWithinAt (fun y => b * a y) (b • a') s x :=
((ContinuousLinearMap.mul 𝕜 𝔸) b).hasFDerivAt.comp_hasFDerivWithinAt x ha
@[fun_prop]
theorem HasFDerivAt.const_mul (ha : HasFDerivAt a a' x) (b : 𝔸) :
HasFDerivAt (fun y => b * a y) (b • a') x :=
((ContinuousLinearMap.mul 𝕜 𝔸) b).hasFDerivAt.comp x ha
@[fun_prop]
theorem DifferentiableWithinAt.const_mul (ha : DifferentiableWithinAt 𝕜 a s x) (b : 𝔸) :
DifferentiableWithinAt 𝕜 (fun y => b * a y) s x :=
(ha.hasFDerivWithinAt.const_mul b).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.const_mul (ha : DifferentiableAt 𝕜 a x) (b : 𝔸) :
DifferentiableAt 𝕜 (fun y => b * a y) x :=
(ha.hasFDerivAt.const_mul b).differentiableAt
@[fun_prop]
theorem DifferentiableOn.const_mul (ha : DifferentiableOn 𝕜 a s) (b : 𝔸) :
DifferentiableOn 𝕜 (fun y => b * a y) s := fun x hx => (ha x hx).const_mul b
@[fun_prop]
theorem Differentiable.const_mul (ha : Differentiable 𝕜 a) (b : 𝔸) :
Differentiable 𝕜 fun y => b * a y := fun x => (ha x).const_mul b
theorem fderivWithin_const_mul (hxs : UniqueDiffWithinAt 𝕜 s x)
(ha : DifferentiableWithinAt 𝕜 a s x) (b : 𝔸) :
fderivWithin 𝕜 (fun y => b * a y) s x = b • fderivWithin 𝕜 a s x :=
(ha.hasFDerivWithinAt.const_mul b).fderivWithin hxs
theorem fderiv_const_mul (ha : DifferentiableAt 𝕜 a x) (b : 𝔸) :
fderiv 𝕜 (fun y => b * a y) x = b • fderiv 𝕜 a x :=
(ha.hasFDerivAt.const_mul b).fderiv
end Mul
section Prod
/-! ### Derivative of a finite product of functions -/
variable {ι : Type*} {𝔸 𝔸' : Type*} [NormedRing 𝔸] [NormedCommRing 𝔸'] [NormedAlgebra 𝕜 𝔸]
[NormedAlgebra 𝕜 𝔸'] {u : Finset ι} {f : ι → E → 𝔸} {f' : ι → E →L[𝕜] 𝔸} {g : ι → E → 𝔸'}
{g' : ι → E →L[𝕜] 𝔸'}
@[fun_prop]
theorem hasStrictFDerivAt_list_prod' [Fintype ι] {l : List ι} {x : ι → 𝔸} :
HasStrictFDerivAt (𝕜 := 𝕜) (fun x ↦ (l.map x).prod)
(∑ i : Fin l.length, ((l.take i).map x).prod •
smulRight (proj l[i]) ((l.drop (.succ i)).map x).prod) x := by
induction l with
| nil => simp [hasStrictFDerivAt_const]
| cons a l IH =>
simp only [List.map_cons, List.prod_cons, ← proj_apply (R := 𝕜) (φ := fun _ : ι ↦ 𝔸) a]
exact .congr_fderiv (.mul' (ContinuousLinearMap.hasStrictFDerivAt _) IH)
(by ext; simp [Fin.sum_univ_succ, Finset.mul_sum, mul_assoc, add_comm])
@[fun_prop]
theorem hasStrictFDerivAt_list_prod_finRange' {n : ℕ} {x : Fin n → 𝔸} :
HasStrictFDerivAt (𝕜 := 𝕜) (fun x ↦ ((List.finRange n).map x).prod)
(∑ i : Fin n, (((List.finRange n).take i).map x).prod •
smulRight (proj i) (((List.finRange n).drop (.succ i)).map x).prod) x :=
hasStrictFDerivAt_list_prod'.congr_fderiv <|
Finset.sum_equiv (finCongr List.length_finRange) (by simp) (by simp [Fin.forall_iff])
@[fun_prop]
theorem hasStrictFDerivAt_list_prod_attach' {l : List ι} {x : {i // i ∈ l} → 𝔸} :
HasStrictFDerivAt (𝕜 := 𝕜) (fun x ↦ (l.attach.map x).prod)
(∑ i : Fin l.length, ((l.attach.take i).map x).prod •
smulRight (proj l.attach[i.cast List.length_attach.symm])
((l.attach.drop (.succ i)).map x).prod) x := by
classical exact hasStrictFDerivAt_list_prod'.congr_fderiv <| Eq.symm <|
Finset.sum_equiv (finCongr List.length_attach.symm) (by simp) (by simp)
@[fun_prop]
theorem hasFDerivAt_list_prod' [Fintype ι] {l : List ι} {x : ι → 𝔸'} :
HasFDerivAt (𝕜 := 𝕜) (fun x ↦ (l.map x).prod)
(∑ i : Fin l.length, ((l.take i).map x).prod •
smulRight (proj l[i]) ((l.drop (.succ i)).map x).prod) x :=
hasStrictFDerivAt_list_prod'.hasFDerivAt
@[fun_prop]
theorem hasFDerivAt_list_prod_finRange' {n : ℕ} {x : Fin n → 𝔸} :
HasFDerivAt (𝕜 := 𝕜) (fun x ↦ ((List.finRange n).map x).prod)
(∑ i : Fin n, (((List.finRange n).take i).map x).prod •
smulRight (proj i) (((List.finRange n).drop (.succ i)).map x).prod) x :=
(hasStrictFDerivAt_list_prod_finRange').hasFDerivAt
@[fun_prop]
theorem hasFDerivAt_list_prod_attach' {l : List ι} {x : {i // i ∈ l} → 𝔸} :
HasFDerivAt (𝕜 := 𝕜) (fun x ↦ (l.attach.map x).prod)
(∑ i : Fin l.length, ((l.attach.take i).map x).prod •
smulRight (proj l.attach[i.cast List.length_attach.symm])
((l.attach.drop (.succ i)).map x).prod) x := by
classical exact hasStrictFDerivAt_list_prod_attach'.hasFDerivAt
/--
Auxiliary lemma for `hasStrictFDerivAt_multiset_prod`.
For `NormedCommRing 𝔸'`, can rewrite as `Multiset` using `Multiset.prod_coe`.
-/
@[fun_prop]
theorem hasStrictFDerivAt_list_prod [DecidableEq ι] [Fintype ι] {l : List ι} {x : ι → 𝔸'} :
HasStrictFDerivAt (𝕜 := 𝕜) (fun x ↦ (l.map x).prod)
(l.map fun i ↦ ((l.erase i).map x).prod • proj i).sum x := by
refine hasStrictFDerivAt_list_prod'.congr_fderiv ?_
conv_rhs => arg 1; arg 2; rw [← List.finRange_map_get l]
simp only [List.map_map, ← List.sum_toFinset _ (List.nodup_finRange _), List.toFinset_finRange,
Function.comp_def, ((List.erase_getElem _).map _).prod_eq, List.eraseIdx_eq_take_drop_succ,
List.map_append, List.prod_append, List.get_eq_getElem, Fin.getElem_fin, Nat.succ_eq_add_one]
exact Finset.sum_congr rfl fun i _ ↦ by
ext; simp only [smul_apply, smulRight_apply, smul_eq_mul]; ring
@[fun_prop]
theorem hasStrictFDerivAt_multiset_prod [DecidableEq ι] [Fintype ι] {u : Multiset ι} {x : ι → 𝔸'} :
HasStrictFDerivAt (𝕜 := 𝕜) (fun x ↦ (u.map x).prod)
(u.map (fun i ↦ ((u.erase i).map x).prod • proj i)).sum x :=
u.inductionOn fun l ↦ by simpa using hasStrictFDerivAt_list_prod
@[fun_prop]
theorem hasFDerivAt_multiset_prod [DecidableEq ι] [Fintype ι] {u : Multiset ι} {x : ι → 𝔸'} :
HasFDerivAt (𝕜 := 𝕜) (fun x ↦ (u.map x).prod)
(Multiset.sum (u.map (fun i ↦ ((u.erase i).map x).prod • proj i))) x :=
hasStrictFDerivAt_multiset_prod.hasFDerivAt
theorem hasStrictFDerivAt_finset_prod [DecidableEq ι] [Fintype ι] {x : ι → 𝔸'} :
HasStrictFDerivAt (𝕜 := 𝕜) (∏ i ∈ u, · i) (∑ i ∈ u, (∏ j ∈ u.erase i, x j) • proj i) x := by
simp only [Finset.sum_eq_multiset_sum, Finset.prod_eq_multiset_prod]
exact hasStrictFDerivAt_multiset_prod
theorem hasFDerivAt_finset_prod [DecidableEq ι] [Fintype ι] {x : ι → 𝔸'} :
HasFDerivAt (𝕜 := 𝕜) (∏ i ∈ u, · i) (∑ i ∈ u, (∏ j ∈ u.erase i, x j) • proj i) x :=
hasStrictFDerivAt_finset_prod.hasFDerivAt
section Comp
@[fun_prop]
theorem HasStrictFDerivAt.list_prod' {l : List ι} {x : E}
(h : ∀ i ∈ l, HasStrictFDerivAt (f i ·) (f' i) x) :
HasStrictFDerivAt (fun x ↦ (l.map (f · x)).prod)
(∑ i : Fin l.length, ((l.take i).map (f · x)).prod •
smulRight (f' l[i]) ((l.drop (.succ i)).map (f · x)).prod) x := by
simp_rw [Fin.getElem_fin, ← l.get_eq_getElem, ← List.finRange_map_get l, List.map_map]
-- After #19108, we have to be optimistic with `:)`s; otherwise Lean decides it need to find
-- `NormedAddCommGroup (List 𝔸)` which is nonsense.
refine .congr_fderiv (hasStrictFDerivAt_list_prod_finRange'.comp x
(hasStrictFDerivAt_pi.mpr fun i ↦ h (l.get i) (List.getElem_mem ..)) :) ?_
ext m
simp_rw [List.map_take, List.map_drop, List.map_map, comp_apply, sum_apply, smul_apply,
smulRight_apply, proj_apply, pi_apply, Function.comp_def]
/--
Unlike `HasFDerivAt.finset_prod`, supports non-commutative multiply and duplicate elements.
-/
@[fun_prop]
theorem HasFDerivAt.list_prod' {l : List ι} {x : E}
(h : ∀ i ∈ l, HasFDerivAt (f i ·) (f' i) x) :
HasFDerivAt (fun x ↦ (l.map (f · x)).prod)
(∑ i : Fin l.length, ((l.take i).map (f · x)).prod •
smulRight (f' l[i]) ((l.drop (.succ i)).map (f · x)).prod) x := by
simp_rw [Fin.getElem_fin, ← l.get_eq_getElem, ← List.finRange_map_get l, List.map_map]
refine .congr_fderiv (hasFDerivAt_list_prod_finRange'.comp x
(hasFDerivAt_pi.mpr fun i ↦ h (l.get i) (l.get_mem i)) :) ?_
ext m
simp_rw [List.map_take, List.map_drop, List.map_map, comp_apply, sum_apply, smul_apply,
smulRight_apply, proj_apply, pi_apply, Function.comp_def]
@[fun_prop]
theorem HasFDerivWithinAt.list_prod' {l : List ι} {x : E}
(h : ∀ i ∈ l, HasFDerivWithinAt (f i ·) (f' i) s x) :
HasFDerivWithinAt (fun x ↦ (l.map (f · x)).prod)
(∑ i : Fin l.length, ((l.take i).map (f · x)).prod •
smulRight (f' l[i]) ((l.drop (.succ i)).map (f · x)).prod) s x := by
simp_rw [Fin.getElem_fin, ← l.get_eq_getElem, ← List.finRange_map_get l, List.map_map]
refine .congr_fderiv (hasFDerivAt_list_prod_finRange'.comp_hasFDerivWithinAt x
(hasFDerivWithinAt_pi.mpr fun i ↦ h (l.get i) (l.get_mem i)) :) ?_
ext m
simp_rw [List.map_take, List.map_drop, List.map_map, comp_apply, sum_apply, smul_apply,
smulRight_apply, proj_apply, pi_apply, Function.comp_def]
theorem fderiv_list_prod' {l : List ι} {x : E}
(h : ∀ i ∈ l, DifferentiableAt 𝕜 (f i ·) x) :
fderiv 𝕜 (fun x ↦ (l.map (f · x)).prod) x =
∑ i : Fin l.length, ((l.take i).map (f · x)).prod •
smulRight (fderiv 𝕜 (fun x ↦ f l[i] x) x) ((l.drop (.succ i)).map (f · x)).prod :=
(HasFDerivAt.list_prod' fun i hi ↦ (h i hi).hasFDerivAt).fderiv
theorem fderivWithin_list_prod' {l : List ι} {x : E}
(hxs : UniqueDiffWithinAt 𝕜 s x) (h : ∀ i ∈ l, DifferentiableWithinAt 𝕜 (f i ·) s x) :
fderivWithin 𝕜 (fun x ↦ (l.map (f · x)).prod) s x =
∑ i : Fin l.length, ((l.take i).map (f · x)).prod •
smulRight (fderivWithin 𝕜 (fun x ↦ f l[i] x) s x) ((l.drop (.succ i)).map (f · x)).prod :=
(HasFDerivWithinAt.list_prod' fun i hi ↦ (h i hi).hasFDerivWithinAt).fderivWithin hxs
@[fun_prop]
theorem HasStrictFDerivAt.multiset_prod [DecidableEq ι] {u : Multiset ι} {x : E}
(h : ∀ i ∈ u, HasStrictFDerivAt (g i ·) (g' i) x) :
HasStrictFDerivAt (fun x ↦ (u.map (g · x)).prod)
(u.map fun i ↦ ((u.erase i).map (g · x)).prod • g' i).sum x := by
simp only [← Multiset.attach_map_val u, Multiset.map_map]
exact .congr_fderiv
(hasStrictFDerivAt_multiset_prod.comp x <|
hasStrictFDerivAt_pi.mpr fun i ↦ h (Subtype.val i) i.prop :)
(by ext; simp [Finset.sum_multiset_map_count, u.erase_attach_map (g · x)])
/--
Unlike `HasFDerivAt.finset_prod`, supports duplicate elements.
-/
@[fun_prop]
theorem HasFDerivAt.multiset_prod [DecidableEq ι] {u : Multiset ι} {x : E}
(h : ∀ i ∈ u, HasFDerivAt (g i ·) (g' i) x) :
HasFDerivAt (fun x ↦ (u.map (g · x)).prod)
(u.map fun i ↦ ((u.erase i).map (g · x)).prod • g' i).sum x := by
simp only [← Multiset.attach_map_val u, Multiset.map_map]
exact .congr_fderiv
(hasFDerivAt_multiset_prod.comp x <| hasFDerivAt_pi.mpr fun i ↦ h (Subtype.val i) i.prop :)
(by ext; simp [Finset.sum_multiset_map_count, u.erase_attach_map (g · x)])
@[fun_prop]
theorem HasFDerivWithinAt.multiset_prod [DecidableEq ι] {u : Multiset ι} {x : E}
(h : ∀ i ∈ u, HasFDerivWithinAt (g i ·) (g' i) s x) :
HasFDerivWithinAt (fun x ↦ (u.map (g · x)).prod)
(u.map fun i ↦ ((u.erase i).map (g · x)).prod • g' i).sum s x := by
simp only [← Multiset.attach_map_val u, Multiset.map_map]
exact .congr_fderiv
(hasFDerivAt_multiset_prod.comp_hasFDerivWithinAt x <|
hasFDerivWithinAt_pi.mpr fun i ↦ h (Subtype.val i) i.prop :)
(by ext; simp [Finset.sum_multiset_map_count, u.erase_attach_map (g · x)])
theorem fderiv_multiset_prod [DecidableEq ι] {u : Multiset ι} {x : E}
(h : ∀ i ∈ u, DifferentiableAt 𝕜 (g i ·) x) :
fderiv 𝕜 (fun x ↦ (u.map (g · x)).prod) x =
(u.map fun i ↦ ((u.erase i).map (g · x)).prod • fderiv 𝕜 (g i) x).sum :=
(HasFDerivAt.multiset_prod fun i hi ↦ (h i hi).hasFDerivAt).fderiv
theorem fderivWithin_multiset_prod [DecidableEq ι] {u : Multiset ι} {x : E}
(hxs : UniqueDiffWithinAt 𝕜 s x) (h : ∀ i ∈ u, DifferentiableWithinAt 𝕜 (g i ·) s x) :
fderivWithin 𝕜 (fun x ↦ (u.map (g · x)).prod) s x =
(u.map fun i ↦ ((u.erase i).map (g · x)).prod • fderivWithin 𝕜 (g i) s x).sum :=
(HasFDerivWithinAt.multiset_prod fun i hi ↦ (h i hi).hasFDerivWithinAt).fderivWithin hxs
theorem HasStrictFDerivAt.finset_prod [DecidableEq ι] {x : E}
(hg : ∀ i ∈ u, HasStrictFDerivAt (g i) (g' i) x) :
HasStrictFDerivAt (∏ i ∈ u, g i ·) (∑ i ∈ u, (∏ j ∈ u.erase i, g j x) • g' i) x := by
simpa [← Finset.prod_attach u] using .congr_fderiv
(hasStrictFDerivAt_finset_prod.comp x <| hasStrictFDerivAt_pi.mpr fun i ↦ hg i i.prop)
(by ext; simp [Finset.prod_erase_attach (g · x), ← u.sum_attach])
theorem HasFDerivAt.finset_prod [DecidableEq ι] {x : E}
(hg : ∀ i ∈ u, HasFDerivAt (g i) (g' i) x) :
HasFDerivAt (∏ i ∈ u, g i ·) (∑ i ∈ u, (∏ j ∈ u.erase i, g j x) • g' i) x := by
simpa [← Finset.prod_attach u] using .congr_fderiv
(hasFDerivAt_finset_prod.comp x <| hasFDerivAt_pi.mpr fun i ↦ hg (Subtype.val i) i.prop :)
(by ext; simp [Finset.prod_erase_attach (g · x), ← u.sum_attach])
theorem HasFDerivWithinAt.finset_prod [DecidableEq ι] {x : E}
(hg : ∀ i ∈ u, HasFDerivWithinAt (g i) (g' i) s x) :
HasFDerivWithinAt (∏ i ∈ u, g i ·) (∑ i ∈ u, (∏ j ∈ u.erase i, g j x) • g' i) s x := by
simpa [← Finset.prod_attach u] using .congr_fderiv
(hasFDerivAt_finset_prod.comp_hasFDerivWithinAt x <|
hasFDerivWithinAt_pi.mpr fun i ↦ hg (Subtype.val i) i.prop :)
(by ext; simp [Finset.prod_erase_attach (g · x), ← u.sum_attach])
theorem fderiv_finset_prod [DecidableEq ι] {x : E} (hg : ∀ i ∈ u, DifferentiableAt 𝕜 (g i) x) :
fderiv 𝕜 (∏ i ∈ u, g i ·) x = ∑ i ∈ u, (∏ j ∈ u.erase i, (g j x)) • fderiv 𝕜 (g i) x :=
| (HasFDerivAt.finset_prod fun i hi ↦ (hg i hi).hasFDerivAt).fderiv
theorem fderivWithin_finset_prod [DecidableEq ι] {x : E} (hxs : UniqueDiffWithinAt 𝕜 s x)
(hg : ∀ i ∈ u, DifferentiableWithinAt 𝕜 (g i) s x) :
fderivWithin 𝕜 (∏ i ∈ u, g i ·) s x =
∑ i ∈ u, (∏ j ∈ u.erase i, (g j x)) • fderivWithin 𝕜 (g i) s x :=
(HasFDerivWithinAt.finset_prod fun i hi ↦ (hg i hi).hasFDerivWithinAt).fderivWithin hxs
| Mathlib/Analysis/Calculus/FDeriv/Mul.lean | 788 | 795 |
/-
Copyright (c) 2021 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta, Alena Gusakov, Yaël Dillies
-/
import Mathlib.Data.Finset.Grade
import Mathlib.Data.Finset.Sups
import Mathlib.Logic.Function.Iterate
/-!
# Shadows
This file defines shadows of a set family. The shadow of a set family is the set family of sets we
get by removing any element from any set of the original family. If one pictures `Finset α` as a big
hypercube (each dimension being membership of a given element), then taking the shadow corresponds
to projecting each finset down once in all available directions.
## Main definitions
* `Finset.shadow`: The shadow of a set family. Everything we can get by removing a new element from
some set.
* `Finset.upShadow`: The upper shadow of a set family. Everything we can get by adding an element
to some set.
## Notation
We define notation in locale `FinsetFamily`:
* `∂ 𝒜`: Shadow of `𝒜`.
* `∂⁺ 𝒜`: Upper shadow of `𝒜`.
We also maintain the convention that `a, b : α` are elements of the ground type, `s, t : Finset α`
are finsets, and `𝒜, ℬ : Finset (Finset α)` are finset families.
## References
* https://github.com/b-mehta/maths-notes/blob/master/iii/mich/combinatorics.pdf
* http://discretemath.imp.fu-berlin.de/DMII-2015-16/kruskal.pdf
## Tags
shadow, set family
-/
open Finset Nat
variable {α : Type*}
namespace Finset
section Shadow
variable [DecidableEq α] {𝒜 ℬ : Finset (Finset α)} {s t : Finset α} {a : α} {k r : ℕ}
/-- The shadow of a set family `𝒜` is all sets we can get by removing one element from any set in
`𝒜`, and the (`k` times) iterated shadow (`shadow^[k]`) is all sets we can get by removing `k`
elements from any set in `𝒜`. -/
def shadow (𝒜 : Finset (Finset α)) : Finset (Finset α) :=
𝒜.sup fun s => s.image (erase s)
@[inherit_doc] scoped[FinsetFamily] notation:max "∂ " => Finset.shadow
open FinsetFamily
/-- The shadow of the empty set is empty. -/
@[simp]
theorem shadow_empty : ∂ (∅ : Finset (Finset α)) = ∅ :=
rfl
@[simp] lemma shadow_iterate_empty (k : ℕ) : ∂^[k] (∅ : Finset (Finset α)) = ∅ := by
induction k <;> simp [*, shadow_empty]
@[simp]
theorem shadow_singleton_empty : ∂ ({∅} : Finset (Finset α)) = ∅ :=
rfl
@[simp]
theorem shadow_singleton (a : α) : ∂ {{a}} = {∅} := by
simp [shadow]
/-- The shadow is monotone. -/
@[mono]
theorem shadow_monotone : Monotone (shadow : Finset (Finset α) → Finset (Finset α)) := fun _ _ =>
sup_mono
@[gcongr] lemma shadow_mono (h𝒜ℬ : 𝒜 ⊆ ℬ) : ∂ 𝒜 ⊆ ∂ ℬ := shadow_monotone h𝒜ℬ
/-- `t` is in the shadow of `𝒜` iff there is a `s ∈ 𝒜` from which we can remove one element to
get `t`. -/
lemma mem_shadow_iff : t ∈ ∂ 𝒜 ↔ ∃ s ∈ 𝒜, ∃ a ∈ s, erase s a = t := by
simp only [shadow, mem_sup, mem_image]
theorem erase_mem_shadow (hs : s ∈ 𝒜) (ha : a ∈ s) : erase s a ∈ ∂ 𝒜 :=
mem_shadow_iff.2 ⟨s, hs, a, ha, rfl⟩
/-- `t ∈ ∂𝒜` iff `t` is exactly one element less than something from `𝒜`.
See also `Finset.mem_shadow_iff_exists_mem_card_add_one`. -/
lemma mem_shadow_iff_exists_sdiff : t ∈ ∂ 𝒜 ↔ ∃ s ∈ 𝒜, t ⊆ s ∧ #(s \ t) = 1 := by
simp_rw [mem_shadow_iff, ← covBy_iff_card_sdiff_eq_one, covBy_iff_exists_erase]
/-- `t` is in the shadow of `𝒜` iff we can add an element to it so that the resulting finset is in
`𝒜`. -/
lemma mem_shadow_iff_insert_mem : t ∈ ∂ 𝒜 ↔ ∃ a ∉ t, insert a t ∈ 𝒜 := by
simp_rw [mem_shadow_iff_exists_sdiff, ← covBy_iff_card_sdiff_eq_one, covBy_iff_exists_insert]
aesop
/-- `s ∈ ∂ 𝒜` iff `s` is exactly one element less than something from `𝒜`.
See also `Finset.mem_shadow_iff_exists_sdiff`. -/
lemma mem_shadow_iff_exists_mem_card_add_one : t ∈ ∂ 𝒜 ↔ ∃ s ∈ 𝒜, t ⊆ s ∧ #s = #t + 1 := by
refine mem_shadow_iff_exists_sdiff.trans <| exists_congr fun t ↦ and_congr_right fun _ ↦
and_congr_right fun hst ↦ ?_
rw [card_sdiff hst, tsub_eq_iff_eq_add_of_le, add_comm]
exact card_mono hst
lemma mem_shadow_iterate_iff_exists_card :
t ∈ ∂^[k] 𝒜 ↔ ∃ u : Finset α, #u = k ∧ Disjoint t u ∧ t ∪ u ∈ 𝒜 := by
induction k generalizing t with
| zero => simp
| succ k ih =>
simp only [mem_shadow_iff_insert_mem, ih, Function.iterate_succ_apply', card_eq_succ]
aesop
/-- `t ∈ ∂^k 𝒜` iff `t` is exactly `k` elements less than something from `𝒜`.
See also `Finset.mem_shadow_iff_exists_mem_card_add`. -/
lemma mem_shadow_iterate_iff_exists_sdiff : t ∈ ∂^[k] 𝒜 ↔ ∃ s ∈ 𝒜, t ⊆ s ∧ #(s \ t) = k := by
rw [mem_shadow_iterate_iff_exists_card]
constructor
· rintro ⟨u, rfl, htu, hsuA⟩
exact ⟨_, hsuA, subset_union_left, by rw [union_sdiff_cancel_left htu]⟩
· rintro ⟨s, hs, hts, rfl⟩
refine ⟨s \ t, rfl, disjoint_sdiff, ?_⟩
rwa [union_sdiff_self_eq_union, union_eq_right.2 hts]
/-- `t ∈ ∂^k 𝒜` iff `t` is exactly `k` elements less than something in `𝒜`.
See also `Finset.mem_shadow_iterate_iff_exists_sdiff`. -/
lemma mem_shadow_iterate_iff_exists_mem_card_add :
t ∈ ∂^[k] 𝒜 ↔ ∃ s ∈ 𝒜, t ⊆ s ∧ #s = #t + k := by
refine mem_shadow_iterate_iff_exists_sdiff.trans <| exists_congr fun t ↦ and_congr_right fun _ ↦
and_congr_right fun hst ↦ ?_
| rw [card_sdiff hst, tsub_eq_iff_eq_add_of_le, add_comm]
exact card_mono hst
/-- The shadow of a family of `r`-sets is a family of `r - 1`-sets. -/
protected theorem _root_.Set.Sized.shadow (h𝒜 : (𝒜 : Set (Finset α)).Sized r) :
(∂ 𝒜 : Set (Finset α)).Sized (r - 1) := by
intro A h
obtain ⟨A, hA, i, hi, rfl⟩ := mem_shadow_iff.1 h
rw [card_erase_of_mem hi, h𝒜 hA]
| Mathlib/Combinatorics/SetFamily/Shadow.lean | 144 | 152 |
/-
Copyright (c) 2020 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Kim Morrison, Ainsley Pahljina
-/
import Mathlib.RingTheory.Fintype
import Mathlib.Tactic.NormNum
import Mathlib.Tactic.Ring
import Mathlib.Tactic.Zify
/-!
# The Lucas-Lehmer test for Mersenne primes.
We define `lucasLehmerResidue : Π p : ℕ, ZMod (2^p - 1)`, and
prove `lucasLehmerResidue p = 0 → Prime (mersenne p)`.
We construct a `norm_num` extension to calculate this residue to certify primality of Mersenne
primes using `lucas_lehmer_sufficiency`.
## TODO
- Show reverse implication.
- Speed up the calculations using `n ≡ (n % 2^p) + (n / 2^p) [MOD 2^p - 1]`.
- Find some bigger primes!
## History
This development began as a student project by Ainsley Pahljina,
and was then cleaned up for mathlib by Kim Morrison.
The tactic for certified computation of Lucas-Lehmer residues was provided by Mario Carneiro.
This tactic was ported by Thomas Murrills to Lean 4, and then it was converted to a `norm_num`
extension and made to use kernel reductions by Kyle Miller.
-/
assert_not_exists TwoSidedIdeal
/-- The Mersenne numbers, 2^p - 1. -/
def mersenne (p : ℕ) : ℕ :=
2 ^ p - 1
theorem strictMono_mersenne : StrictMono mersenne := fun m n h ↦
(Nat.sub_lt_sub_iff_right <| Nat.one_le_pow _ _ two_pos).2 <| by gcongr; norm_num1
@[simp]
theorem mersenne_lt_mersenne {p q : ℕ} : mersenne p < mersenne q ↔ p < q :=
strictMono_mersenne.lt_iff_lt
@[gcongr] protected alias ⟨_, GCongr.mersenne_lt_mersenne⟩ := mersenne_lt_mersenne
@[simp]
theorem mersenne_le_mersenne {p q : ℕ} : mersenne p ≤ mersenne q ↔ p ≤ q :=
strictMono_mersenne.le_iff_le
@[gcongr] protected alias ⟨_, GCongr.mersenne_le_mersenne⟩ := mersenne_le_mersenne
@[simp] theorem mersenne_zero : mersenne 0 = 0 := rfl
@[simp] lemma mersenne_odd : ∀ {p : ℕ}, Odd (mersenne p) ↔ p ≠ 0
| 0 => by simp
| p + 1 => by
simpa using Nat.Even.sub_odd (one_le_pow₀ one_le_two)
(even_two.pow_of_ne_zero p.succ_ne_zero) odd_one
@[simp] theorem mersenne_pos {p : ℕ} : 0 < mersenne p ↔ 0 < p := mersenne_lt_mersenne (p := 0)
namespace Mathlib.Meta.Positivity
open Lean Meta Qq Function
alias ⟨_, mersenne_pos_of_pos⟩ := mersenne_pos
/-- Extension for the `positivity` tactic: `mersenne`. -/
@[positivity mersenne _]
def evalMersenne : PositivityExt where eval {u α} _zα _pα e := do
match u, α, e with
| 0, ~q(ℕ), ~q(mersenne $a) =>
let ra ← core q(inferInstance) q(inferInstance) a
assertInstancesCommute
match ra with
| .positive pa => pure (.positive q(mersenne_pos_of_pos $pa))
| _ => pure (.nonnegative q(Nat.zero_le (mersenne $a)))
| _, _, _ => throwError "not mersenne"
end Mathlib.Meta.Positivity
@[simp]
theorem one_lt_mersenne {p : ℕ} : 1 < mersenne p ↔ 1 < p :=
mersenne_lt_mersenne (p := 1)
@[simp]
theorem succ_mersenne (k : ℕ) : mersenne k + 1 = 2 ^ k := by
rw [mersenne, tsub_add_cancel_of_le]
exact one_le_pow₀ (by norm_num)
namespace LucasLehmer
open Nat
/-!
We now define three(!) different versions of the recurrence
`s (i+1) = (s i)^2 - 2`.
These versions take values either in `ℤ`, in `ZMod (2^p - 1)`, or
in `ℤ` but applying `% (2^p - 1)` at each step.
They are each useful at different points in the proof,
so we take a moment setting up the lemmas relating them.
-/
/-- The recurrence `s (i+1) = (s i)^2 - 2` in `ℤ`. -/
def s : ℕ → ℤ
| 0 => 4
| i + 1 => s i ^ 2 - 2
/-- The recurrence `s (i+1) = (s i)^2 - 2` in `ZMod (2^p - 1)`. -/
def sZMod (p : ℕ) : ℕ → ZMod (2 ^ p - 1)
| 0 => 4
| i + 1 => sZMod p i ^ 2 - 2
/-- The recurrence `s (i+1) = ((s i)^2 - 2) % (2^p - 1)` in `ℤ`. -/
def sMod (p : ℕ) : ℕ → ℤ
| 0 => 4 % (2 ^ p - 1)
| i + 1 => (sMod p i ^ 2 - 2) % (2 ^ p - 1)
theorem mersenne_int_pos {p : ℕ} (hp : p ≠ 0) : (0 : ℤ) < 2 ^ p - 1 :=
sub_pos.2 <| mod_cast Nat.one_lt_two_pow hp
theorem mersenne_int_ne_zero (p : ℕ) (hp : p ≠ 0) : (2 ^ p - 1 : ℤ) ≠ 0 :=
(mersenne_int_pos hp).ne'
theorem sMod_nonneg (p : ℕ) (hp : p ≠ 0) (i : ℕ) : 0 ≤ sMod p i := by
cases i <;> dsimp [sMod]
· exact sup_eq_right.mp rfl
· apply Int.emod_nonneg
exact mersenne_int_ne_zero p hp
theorem sMod_mod (p i : ℕ) : sMod p i % (2 ^ p - 1) = sMod p i := by cases i <;> simp [sMod]
theorem sMod_lt (p : ℕ) (hp : p ≠ 0) (i : ℕ) : sMod p i < 2 ^ p - 1 := by
rw [← sMod_mod]
refine (Int.emod_lt_abs _ (mersenne_int_ne_zero p hp)).trans_eq ?_
exact abs_of_nonneg (mersenne_int_pos hp).le
theorem sZMod_eq_s (p' : ℕ) (i : ℕ) : sZMod (p' + 2) i = (s i : ZMod (2 ^ (p' + 2) - 1)) := by
induction i with
| zero => dsimp [s, sZMod]; norm_num
| succ i ih => push_cast [s, sZMod, ih]; rfl
-- These next two don't make good `norm_cast` lemmas.
theorem Int.natCast_pow_pred (b p : ℕ) (w : 0 < b) : ((b ^ p - 1 : ℕ) : ℤ) = (b : ℤ) ^ p - 1 := by
have : 1 ≤ b ^ p := Nat.one_le_pow p b w
norm_cast
theorem Int.coe_nat_two_pow_pred (p : ℕ) : ((2 ^ p - 1 : ℕ) : ℤ) = (2 ^ p - 1 : ℤ) :=
Int.natCast_pow_pred 2 p (by decide)
theorem sZMod_eq_sMod (p : ℕ) (i : ℕ) : sZMod p i = (sMod p i : ZMod (2 ^ p - 1)) := by
induction i <;> push_cast [← Int.coe_nat_two_pow_pred p, sMod, sZMod, *] <;> rfl
/-- The Lucas-Lehmer residue is `s p (p-2)` in `ZMod (2^p - 1)`. -/
def lucasLehmerResidue (p : ℕ) : ZMod (2 ^ p - 1) :=
sZMod p (p - 2)
theorem residue_eq_zero_iff_sMod_eq_zero (p : ℕ) (w : 1 < p) :
lucasLehmerResidue p = 0 ↔ sMod p (p - 2) = 0 := by
dsimp [lucasLehmerResidue]
rw [sZMod_eq_sMod p]
constructor
· -- We want to use that fact that `0 ≤ s_mod p (p-2) < 2^p - 1`
-- and `lucas_lehmer_residue p = 0 → 2^p - 1 ∣ s_mod p (p-2)`.
intro h
simp? [ZMod.intCast_zmod_eq_zero_iff_dvd] at h says
simp only [ZMod.intCast_zmod_eq_zero_iff_dvd, ofNat_pos, pow_pos, cast_pred,
cast_pow, cast_ofNat] at h
apply Int.eq_zero_of_dvd_of_nonneg_of_lt _ _ h <;> clear h
· exact sMod_nonneg _ (by positivity) _
· exact sMod_lt _ (by positivity) _
· intro h
rw [h]
simp
/-- **Lucas-Lehmer Test**: a Mersenne number `2^p-1` is prime if and only if
the Lucas-Lehmer residue `s p (p-2) % (2^p - 1)` is zero.
-/
def LucasLehmerTest (p : ℕ) : Prop :=
lucasLehmerResidue p = 0
/-- `q` is defined as the minimum factor of `mersenne p`, bundled as an `ℕ+`. -/
def q (p : ℕ) : ℕ+ :=
⟨Nat.minFac (mersenne p), Nat.minFac_pos (mersenne p)⟩
-- It would be nice to define this as (ℤ/qℤ)[x] / (x^2 - 3),
-- obtaining the ring structure for free,
-- but that seems to be more trouble than it's worth;
-- if it were easy to make the definition,
-- cardinality calculations would be somewhat more involved, too.
/-- We construct the ring `X q` as ℤ/qℤ + √3 ℤ/qℤ. -/
def X (q : ℕ+) : Type :=
ZMod q × ZMod q
namespace X
variable {q : ℕ+}
instance : Inhabited (X q) := inferInstanceAs (Inhabited (ZMod q × ZMod q))
instance : Fintype (X q) := inferInstanceAs (Fintype (ZMod q × ZMod q))
instance : DecidableEq (X q) := inferInstanceAs (DecidableEq (ZMod q × ZMod q))
instance : AddCommGroup (X q) := inferInstanceAs (AddCommGroup (ZMod q × ZMod q))
@[ext]
theorem ext {x y : X q} (h₁ : x.1 = y.1) (h₂ : x.2 = y.2) : x = y := by
cases x; cases y; congr
@[simp] theorem zero_fst : (0 : X q).1 = 0 := rfl
@[simp] theorem zero_snd : (0 : X q).2 = 0 := rfl
@[simp]
theorem add_fst (x y : X q) : (x + y).1 = x.1 + y.1 :=
rfl
@[simp]
theorem add_snd (x y : X q) : (x + y).2 = x.2 + y.2 :=
rfl
@[simp]
theorem neg_fst (x : X q) : (-x).1 = -x.1 :=
rfl
@[simp]
theorem neg_snd (x : X q) : (-x).2 = -x.2 :=
rfl
instance : Mul (X q) where mul x y := (x.1 * y.1 + 3 * x.2 * y.2, x.1 * y.2 + x.2 * y.1)
@[simp]
theorem mul_fst (x y : X q) : (x * y).1 = x.1 * y.1 + 3 * x.2 * y.2 :=
rfl
@[simp]
theorem mul_snd (x y : X q) : (x * y).2 = x.1 * y.2 + x.2 * y.1 :=
rfl
instance : One (X q) where one := ⟨1, 0⟩
@[simp]
theorem one_fst : (1 : X q).1 = 1 :=
rfl
@[simp]
theorem one_snd : (1 : X q).2 = 0 :=
rfl
instance : Monoid (X q) :=
{ inferInstanceAs (Mul (X q)), inferInstanceAs (One (X q)) with
mul_assoc := fun x y z => by ext <;> dsimp <;> ring
one_mul := fun x => by ext <;> simp
mul_one := fun x => by ext <;> simp }
instance : NatCast (X q) where
natCast := fun n => ⟨n, 0⟩
@[simp] theorem fst_natCast (n : ℕ) : (n : X q).fst = (n : ZMod q) := rfl
@[simp] theorem snd_natCast (n : ℕ) : (n : X q).snd = (0 : ZMod q) := rfl
@[simp] theorem ofNat_fst (n : ℕ) [n.AtLeastTwo] :
(ofNat(n) : X q).fst = OfNat.ofNat n :=
rfl
@[simp] theorem ofNat_snd (n : ℕ) [n.AtLeastTwo] :
(ofNat(n) : X q).snd = 0 :=
rfl
instance : AddGroupWithOne (X q) :=
{ inferInstanceAs (Monoid (X q)), inferInstanceAs (AddCommGroup (X q)),
inferInstanceAs (NatCast (X q)) with
natCast_zero := by ext <;> simp
natCast_succ := fun _ ↦ by ext <;> simp
intCast := fun n => ⟨n, 0⟩
intCast_ofNat := fun n => by ext <;> simp
intCast_negSucc := fun n => by ext <;> simp }
theorem left_distrib (x y z : X q) : x * (y + z) = x * y + x * z := by
ext <;> dsimp <;> ring
theorem right_distrib (x y z : X q) : (x + y) * z = x * z + y * z := by
ext <;> dsimp <;> ring
instance : Ring (X q) :=
{ inferInstanceAs (AddGroupWithOne (X q)), inferInstanceAs (AddCommGroup (X q)),
inferInstanceAs (Monoid (X q)) with
left_distrib := left_distrib
right_distrib := right_distrib
mul_zero := fun _ ↦ by ext <;> simp
zero_mul := fun _ ↦ by ext <;> simp }
instance : CommRing (X q) :=
{ inferInstanceAs (Ring (X q)) with
mul_comm := fun _ _ ↦ by ext <;> dsimp <;> ring }
instance [Fact (1 < (q : ℕ))] : Nontrivial (X q) :=
⟨⟨0, 1, ne_of_apply_ne Prod.fst zero_ne_one⟩⟩
@[simp]
theorem fst_intCast (n : ℤ) : (n : X q).fst = (n : ZMod q) :=
rfl
@[simp]
theorem snd_intCast (n : ℤ) : (n : X q).snd = (0 : ZMod q) :=
rfl
@[norm_cast]
theorem coe_mul (n m : ℤ) : ((n * m : ℤ) : X q) = (n : X q) * (m : X q) := by ext <;> simp
@[norm_cast]
theorem coe_natCast (n : ℕ) : ((n : ℤ) : X q) = (n : X q) := by ext <;> simp
/-- The cardinality of `X` is `q^2`. -/
theorem card_eq : Fintype.card (X q) = q ^ 2 := by
dsimp [X]
rw [Fintype.card_prod, ZMod.card q, sq]
/-- There are strictly fewer than `q^2` units, since `0` is not a unit. -/
nonrec theorem card_units_lt (w : 1 < q) : Fintype.card (X q)ˣ < q ^ 2 := by
have : Fact (1 < (q : ℕ)) := ⟨w⟩
convert card_units_lt (X q)
rw [card_eq]
/-- We define `ω = 2 + √3`. -/
def ω : X q := (2, 1)
/-- We define `ωb = 2 - √3`, which is the inverse of `ω`. -/
def ωb : X q := (2, -1)
theorem ω_mul_ωb (q : ℕ+) : (ω : X q) * ωb = 1 := by
dsimp [ω, ωb]
ext <;> simp; ring
theorem ωb_mul_ω (q : ℕ+) : (ωb : X q) * ω = 1 := by
rw [mul_comm, ω_mul_ωb]
/-- A closed form for the recurrence relation. -/
theorem closed_form (i : ℕ) : (s i : X q) = (ω : X q) ^ 2 ^ i + (ωb : X q) ^ 2 ^ i := by
induction i with
| zero =>
dsimp [s, ω, ωb]
ext <;> norm_num
| succ i ih =>
calc
(s (i + 1) : X q) = (s i ^ 2 - 2 : ℤ) := rfl
_ = (s i : X q) ^ 2 - 2 := by push_cast; rfl
_ = (ω ^ 2 ^ i + ωb ^ 2 ^ i) ^ 2 - 2 := by rw [ih]
_ = (ω ^ 2 ^ i) ^ 2 + (ωb ^ 2 ^ i) ^ 2 + 2 * (ωb ^ 2 ^ i * ω ^ 2 ^ i) - 2 := by ring
_ = (ω ^ 2 ^ i) ^ 2 + (ωb ^ 2 ^ i) ^ 2 := by
rw [← mul_pow ωb ω, ωb_mul_ω, one_pow, mul_one, add_sub_cancel_right]
_ = ω ^ 2 ^ (i + 1) + ωb ^ 2 ^ (i + 1) := by rw [← pow_mul, ← pow_mul, _root_.pow_succ]
end X
open X
/-!
Here and below, we introduce `p' = p - 2`, in order to avoid using subtraction in `ℕ`.
-/
/-- If `1 < p`, then `q p`, the smallest prime factor of `mersenne p`, is more than 2. -/
theorem two_lt_q (p' : ℕ) : 2 < q (p' + 2) := by
refine (minFac_prime (one_lt_mersenne.2 ?_).ne').two_le.lt_of_ne' ?_
· exact le_add_left _ _
· rw [Ne, minFac_eq_two_iff, mersenne, Nat.pow_succ']
exact Nat.two_not_dvd_two_mul_sub_one Nat.one_le_two_pow
theorem ω_pow_formula (p' : ℕ) (h : lucasLehmerResidue (p' + 2) = 0) :
∃ k : ℤ,
(ω : X (q (p' + 2))) ^ 2 ^ (p' + 1) =
k * mersenne (p' + 2) * (ω : X (q (p' + 2))) ^ 2 ^ p' - 1 := by
dsimp [lucasLehmerResidue] at h
rw [sZMod_eq_s p'] at h
simp? [ZMod.intCast_zmod_eq_zero_iff_dvd] at h says
simp only [add_tsub_cancel_right, ZMod.intCast_zmod_eq_zero_iff_dvd, ofNat_pos,
pow_pos, cast_pred, cast_pow, cast_ofNat] at h
obtain ⟨k, h⟩ := h
use k
replace h := congr_arg (fun n : ℤ => (n : X (q (p' + 2)))) h
-- coercion from ℤ to X q
dsimp at h
rw [closed_form] at h
replace h := congr_arg (fun x => ω ^ 2 ^ p' * x) h
dsimp at h
have t : 2 ^ p' + 2 ^ p' = 2 ^ (p' + 1) := by ring
rw [mul_add, ← pow_add ω, t, ← mul_pow ω ωb (2 ^ p'), ω_mul_ωb, one_pow] at h
rw [mul_comm, coe_mul] at h
rw [mul_comm _ (k : X (q (p' + 2)))] at h
replace h := eq_sub_of_add_eq h
have : 1 ≤ 2 ^ (p' + 2) := Nat.one_le_pow _ _ (by decide)
exact mod_cast h
/-- `q` is the minimum factor of `mersenne p`, so `M p = 0` in `X q`. -/
theorem mersenne_coe_X (p : ℕ) : (mersenne p : X (q p)) = 0 := by
ext <;> simp [mersenne, q, ZMod.natCast_zmod_eq_zero_iff_dvd, -pow_pos]
apply Nat.minFac_dvd
theorem ω_pow_eq_neg_one (p' : ℕ) (h : lucasLehmerResidue (p' + 2) = 0) :
(ω : X (q (p' + 2))) ^ 2 ^ (p' + 1) = -1 := by
obtain ⟨k, w⟩ := ω_pow_formula p' h
rw [mersenne_coe_X] at w
simpa using w
theorem ω_pow_eq_one (p' : ℕ) (h : lucasLehmerResidue (p' + 2) = 0) :
(ω : X (q (p' + 2))) ^ 2 ^ (p' + 2) = 1 :=
calc
(ω : X (q (p' + 2))) ^ 2 ^ (p' + 2) = (ω ^ 2 ^ (p' + 1)) ^ 2 := by
rw [← pow_mul, ← Nat.pow_succ]
_ = (-1) ^ 2 := by rw [ω_pow_eq_neg_one p' h]
_ = 1 := by simp
/-- `ω` as an element of the group of units. -/
def ωUnit (p : ℕ) : Units (X (q p)) where
val := ω
inv := ωb
val_inv := ω_mul_ωb _
inv_val := ωb_mul_ω _
@[simp]
theorem ωUnit_coe (p : ℕ) : (ωUnit p : X (q p)) = ω :=
rfl
/-- The order of `ω` in the unit group is exactly `2^p`. -/
theorem order_ω (p' : ℕ) (h : lucasLehmerResidue (p' + 2) = 0) :
orderOf (ωUnit (p' + 2)) = 2 ^ (p' + 2) := by
apply Nat.eq_prime_pow_of_dvd_least_prime_pow
-- the order of ω divides 2^p
· exact Nat.prime_two
· intro o
have ω_pow := orderOf_dvd_iff_pow_eq_one.1 o
replace ω_pow :=
congr_arg (Units.coeHom (X (q (p' + 2))) : Units (X (q (p' + 2))) → X (q (p' + 2))) ω_pow
simp? at ω_pow says
simp only [Units.coeHom_apply, Units.val_pow_eq_pow_val, ωUnit_coe, Units.val_one] at ω_pow
have h : (1 : ZMod (q (p' + 2))) = -1 :=
congr_arg Prod.fst (ω_pow.symm.trans (ω_pow_eq_neg_one p' h))
haveI : Fact (2 < (q (p' + 2) : ℕ)) := ⟨two_lt_q _⟩
apply ZMod.neg_one_ne_one h.symm
· apply orderOf_dvd_iff_pow_eq_one.2
apply Units.ext
push_cast
exact ω_pow_eq_one p' h
theorem order_ineq (p' : ℕ) (h : lucasLehmerResidue (p' + 2) = 0) :
2 ^ (p' + 2) < (q (p' + 2) : ℕ) ^ 2 :=
calc
2 ^ (p' + 2) = orderOf (ωUnit (p' + 2)) := (order_ω p' h).symm
_ ≤ Fintype.card (X (q (p' + 2)))ˣ := orderOf_le_card_univ
_ < (q (p' + 2) : ℕ) ^ 2 := card_units_lt (Nat.lt_of_succ_lt (two_lt_q _))
end LucasLehmer
export LucasLehmer (LucasLehmerTest lucasLehmerResidue)
open LucasLehmer
theorem lucas_lehmer_sufficiency (p : ℕ) (w : 1 < p) : LucasLehmerTest p → (mersenne p).Prime := by
let p' := p - 2
have z : p = p' + 2 := (tsub_eq_iff_eq_add_of_le w.nat_succ_le).mp rfl
have w : 1 < p' + 2 := Nat.lt_of_sub_eq_succ rfl
contrapose
intro a t
rw [z] at a
rw [z] at t
have h₁ := order_ineq p' t
have h₂ := Nat.minFac_sq_le_self (mersenne_pos.2 (Nat.lt_of_succ_lt w)) a
have h := lt_of_lt_of_le h₁ h₂
exact not_lt_of_ge (Nat.sub_le _ _) h
namespace LucasLehmer
/-!
### `norm_num` extension
Next we define a `norm_num` extension that calculates `LucasLehmerTest p` for `1 < p`.
It makes use of a version of `sMod` that is specifically written to be reducible by the
Lean 4 kernel, which has the capability of efficiently reducing natural number expressions.
With this reduction in hand, it's a simple matter of applying the lemma
`LucasLehmer.residue_eq_zero_iff_sMod_eq_zero`.
See [Archive/Examples/MersennePrimes.lean] for certifications of all Mersenne primes
up through `mersenne 4423`.
-/
| namespace norm_num_ext
open Qq Lean Elab.Tactic Mathlib.Meta.NormNum
| Mathlib/NumberTheory/LucasLehmer.lean | 491 | 493 |
/-
Copyright (c) 2021 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Algebra.GroupWithZero.Indicator
import Mathlib.Topology.Piecewise
import Mathlib.Topology.Instances.ENNReal.Lemmas
/-!
# Semicontinuous maps
A function `f` from a topological space `α` to an ordered space `β` is lower semicontinuous at a
point `x` if, for any `y < f x`, for any `x'` close enough to `x`, one has `f x' > y`. In other
words, `f` can jump up, but it can not jump down.
Upper semicontinuous functions are defined similarly.
This file introduces these notions, and a basic API around them mimicking the API for continuous
functions.
## Main definitions and results
We introduce 4 definitions related to lower semicontinuity:
* `LowerSemicontinuousWithinAt f s x`
* `LowerSemicontinuousAt f x`
* `LowerSemicontinuousOn f s`
* `LowerSemicontinuous f`
We build a basic API using dot notation around these notions, and we prove that
* constant functions are lower semicontinuous;
* `indicator s (fun _ ↦ y)` is lower semicontinuous when `s` is open and `0 ≤ y`,
or when `s` is closed and `y ≤ 0`;
* continuous functions are lower semicontinuous;
* left composition with a continuous monotone functions maps lower semicontinuous functions to lower
semicontinuous functions. If the function is anti-monotone, it instead maps lower semicontinuous
functions to upper semicontinuous functions;
* right composition with continuous functions preserves lower and upper semicontinuity;
* a sum of two (or finitely many) lower semicontinuous functions is lower semicontinuous;
* a supremum of a family of lower semicontinuous functions is lower semicontinuous;
* An infinite sum of `ℝ≥0∞`-valued lower semicontinuous functions is lower semicontinuous.
Similar results are stated and proved for upper semicontinuity.
We also prove that a function is continuous if and only if it is both lower and upper
semicontinuous.
We have some equivalent definitions of lower- and upper-semicontinuity (under certain
restrictions on the order on the codomain):
* `lowerSemicontinuous_iff_isOpen_preimage` in a linear order;
* `lowerSemicontinuous_iff_isClosed_preimage` in a linear order;
* `lowerSemicontinuousAt_iff_le_liminf` in a dense complete linear order;
* `lowerSemicontinuous_iff_isClosed_epigraph` in a dense complete linear order with the order
topology.
## Implementation details
All the nontrivial results for upper semicontinuous functions are deduced from the corresponding
ones for lower semicontinuous functions using `OrderDual`.
## References
* <https://en.wikipedia.org/wiki/Closed_convex_function>
* <https://en.wikipedia.org/wiki/Semi-continuity>
-/
open Topology ENNReal
open Set Function Filter
variable {α : Type*} [TopologicalSpace α] {β : Type*} [Preorder β] {f g : α → β} {x : α}
{s t : Set α} {y z : β}
/-! ### Main definitions -/
/-- A real function `f` is lower semicontinuous at `x` within a set `s` if, for any `ε > 0`, for all
`x'` close enough to `x` in `s`, then `f x'` is at least `f x - ε`. We formulate this in a general
preordered space, using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuousWithinAt (f : α → β) (s : Set α) (x : α) :=
∀ y < f x, ∀ᶠ x' in 𝓝[s] x, y < f x'
/-- A real function `f` is lower semicontinuous on a set `s` if, for any `ε > 0`, for any `x ∈ s`,
for all `x'` close enough to `x` in `s`, then `f x'` is at least `f x - ε`. We formulate this in
a general preordered space, using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuousOn (f : α → β) (s : Set α) :=
∀ x ∈ s, LowerSemicontinuousWithinAt f s x
/-- A real function `f` is lower semicontinuous at `x` if, for any `ε > 0`, for all `x'` close
enough to `x`, then `f x'` is at least `f x - ε`. We formulate this in a general preordered space,
using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuousAt (f : α → β) (x : α) :=
∀ y < f x, ∀ᶠ x' in 𝓝 x, y < f x'
/-- A real function `f` is lower semicontinuous if, for any `ε > 0`, for any `x`, for all `x'` close
enough to `x`, then `f x'` is at least `f x - ε`. We formulate this in a general preordered space,
using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuous (f : α → β) :=
∀ x, LowerSemicontinuousAt f x
/-- A real function `f` is upper semicontinuous at `x` within a set `s` if, for any `ε > 0`, for all
`x'` close enough to `x` in `s`, then `f x'` is at most `f x + ε`. We formulate this in a general
preordered space, using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuousWithinAt (f : α → β) (s : Set α) (x : α) :=
∀ y, f x < y → ∀ᶠ x' in 𝓝[s] x, f x' < y
/-- A real function `f` is upper semicontinuous on a set `s` if, for any `ε > 0`, for any `x ∈ s`,
for all `x'` close enough to `x` in `s`, then `f x'` is at most `f x + ε`. We formulate this in a
general preordered space, using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuousOn (f : α → β) (s : Set α) :=
∀ x ∈ s, UpperSemicontinuousWithinAt f s x
/-- A real function `f` is upper semicontinuous at `x` if, for any `ε > 0`, for all `x'` close
enough to `x`, then `f x'` is at most `f x + ε`. We formulate this in a general preordered space,
using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuousAt (f : α → β) (x : α) :=
∀ y, f x < y → ∀ᶠ x' in 𝓝 x, f x' < y
/-- A real function `f` is upper semicontinuous if, for any `ε > 0`, for any `x`, for all `x'`
close enough to `x`, then `f x'` is at most `f x + ε`. We formulate this in a general preordered
space, using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuous (f : α → β) :=
∀ x, UpperSemicontinuousAt f x
/-!
### Lower semicontinuous functions
-/
/-! #### Basic dot notation interface for lower semicontinuity -/
theorem LowerSemicontinuousWithinAt.mono (h : LowerSemicontinuousWithinAt f s x) (hst : t ⊆ s) :
LowerSemicontinuousWithinAt f t x := fun y hy =>
Filter.Eventually.filter_mono (nhdsWithin_mono _ hst) (h y hy)
theorem lowerSemicontinuousWithinAt_univ_iff :
LowerSemicontinuousWithinAt f univ x ↔ LowerSemicontinuousAt f x := by
simp [LowerSemicontinuousWithinAt, LowerSemicontinuousAt, nhdsWithin_univ]
theorem LowerSemicontinuousAt.lowerSemicontinuousWithinAt (s : Set α)
(h : LowerSemicontinuousAt f x) : LowerSemicontinuousWithinAt f s x := fun y hy =>
Filter.Eventually.filter_mono nhdsWithin_le_nhds (h y hy)
theorem LowerSemicontinuousOn.lowerSemicontinuousWithinAt (h : LowerSemicontinuousOn f s)
(hx : x ∈ s) : LowerSemicontinuousWithinAt f s x :=
h x hx
theorem LowerSemicontinuousOn.mono (h : LowerSemicontinuousOn f s) (hst : t ⊆ s) :
LowerSemicontinuousOn f t := fun x hx => (h x (hst hx)).mono hst
theorem lowerSemicontinuousOn_univ_iff : LowerSemicontinuousOn f univ ↔ LowerSemicontinuous f := by
simp [LowerSemicontinuousOn, LowerSemicontinuous, lowerSemicontinuousWithinAt_univ_iff]
theorem LowerSemicontinuous.lowerSemicontinuousAt (h : LowerSemicontinuous f) (x : α) :
LowerSemicontinuousAt f x :=
h x
theorem LowerSemicontinuous.lowerSemicontinuousWithinAt (h : LowerSemicontinuous f) (s : Set α)
(x : α) : LowerSemicontinuousWithinAt f s x :=
(h x).lowerSemicontinuousWithinAt s
theorem LowerSemicontinuous.lowerSemicontinuousOn (h : LowerSemicontinuous f) (s : Set α) :
LowerSemicontinuousOn f s := fun x _hx => h.lowerSemicontinuousWithinAt s x
/-! #### Constants -/
theorem lowerSemicontinuousWithinAt_const : LowerSemicontinuousWithinAt (fun _x => z) s x :=
fun _y hy => Filter.Eventually.of_forall fun _x => hy
theorem lowerSemicontinuousAt_const : LowerSemicontinuousAt (fun _x => z) x := fun _y hy =>
Filter.Eventually.of_forall fun _x => hy
theorem lowerSemicontinuousOn_const : LowerSemicontinuousOn (fun _x => z) s := fun _x _hx =>
lowerSemicontinuousWithinAt_const
theorem lowerSemicontinuous_const : LowerSemicontinuous fun _x : α => z := fun _x =>
lowerSemicontinuousAt_const
/-! #### Indicators -/
section
variable [Zero β]
theorem IsOpen.lowerSemicontinuous_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuous (indicator s fun _x => y) := by
intro x z hz
by_cases h : x ∈ s <;> simp [h] at hz
· filter_upwards [hs.mem_nhds h]
simp +contextual [hz]
· refine Filter.Eventually.of_forall fun x' => ?_
by_cases h' : x' ∈ s <;> simp [h', hz.trans_le hy, hz]
theorem IsOpen.lowerSemicontinuousOn_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuousOn (indicator s fun _x => y) t :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousOn t
theorem IsOpen.lowerSemicontinuousAt_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuousAt (indicator s fun _x => y) x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousAt x
theorem IsOpen.lowerSemicontinuousWithinAt_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuousWithinAt (indicator s fun _x => y) t x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousWithinAt t x
theorem IsClosed.lowerSemicontinuous_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuous (indicator s fun _x => y) := by
intro x z hz
by_cases h : x ∈ s <;> simp [h] at hz
· refine Filter.Eventually.of_forall fun x' => ?_
by_cases h' : x' ∈ s <;> simp [h', hz, hz.trans_le hy]
· filter_upwards [hs.isOpen_compl.mem_nhds h]
simp +contextual [hz]
theorem IsClosed.lowerSemicontinuousOn_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuousOn (indicator s fun _x => y) t :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousOn t
theorem IsClosed.lowerSemicontinuousAt_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuousAt (indicator s fun _x => y) x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousAt x
theorem IsClosed.lowerSemicontinuousWithinAt_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuousWithinAt (indicator s fun _x => y) t x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousWithinAt t x
end
/-! #### Relationship with continuity -/
theorem lowerSemicontinuous_iff_isOpen_preimage :
LowerSemicontinuous f ↔ ∀ y, IsOpen (f ⁻¹' Ioi y) :=
⟨fun H y => isOpen_iff_mem_nhds.2 fun x hx => H x y hx, fun H _x y y_lt =>
IsOpen.mem_nhds (H y) y_lt⟩
theorem LowerSemicontinuous.isOpen_preimage (hf : LowerSemicontinuous f) (y : β) :
IsOpen (f ⁻¹' Ioi y) :=
lowerSemicontinuous_iff_isOpen_preimage.1 hf y
section
variable {γ : Type*} [LinearOrder γ]
theorem lowerSemicontinuous_iff_isClosed_preimage {f : α → γ} :
LowerSemicontinuous f ↔ ∀ y, IsClosed (f ⁻¹' Iic y) := by
rw [lowerSemicontinuous_iff_isOpen_preimage]
simp only [← isOpen_compl_iff, ← preimage_compl, compl_Iic]
theorem LowerSemicontinuous.isClosed_preimage {f : α → γ} (hf : LowerSemicontinuous f) (y : γ) :
IsClosed (f ⁻¹' Iic y) :=
lowerSemicontinuous_iff_isClosed_preimage.1 hf y
variable [TopologicalSpace γ] [OrderTopology γ]
theorem ContinuousWithinAt.lowerSemicontinuousWithinAt {f : α → γ} (h : ContinuousWithinAt f s x) :
LowerSemicontinuousWithinAt f s x := fun _y hy => h (Ioi_mem_nhds hy)
theorem ContinuousAt.lowerSemicontinuousAt {f : α → γ} (h : ContinuousAt f x) :
LowerSemicontinuousAt f x := fun _y hy => h (Ioi_mem_nhds hy)
theorem ContinuousOn.lowerSemicontinuousOn {f : α → γ} (h : ContinuousOn f s) :
LowerSemicontinuousOn f s := fun x hx => (h x hx).lowerSemicontinuousWithinAt
theorem Continuous.lowerSemicontinuous {f : α → γ} (h : Continuous f) : LowerSemicontinuous f :=
fun _x => h.continuousAt.lowerSemicontinuousAt
end
/-! #### Equivalent definitions -/
section
variable {γ : Type*} [CompleteLinearOrder γ] [DenselyOrdered γ]
theorem lowerSemicontinuousWithinAt_iff_le_liminf {f : α → γ} :
LowerSemicontinuousWithinAt f s x ↔ f x ≤ liminf f (𝓝[s] x) := by
constructor
· intro hf; unfold LowerSemicontinuousWithinAt at hf
contrapose! hf
obtain ⟨y, lty, ylt⟩ := exists_between hf; use y
exact ⟨ylt, fun h => lty.not_le
(le_liminf_of_le (by isBoundedDefault) (h.mono fun _ hx => le_of_lt hx))⟩
exact fun hf y ylt => eventually_lt_of_lt_liminf (ylt.trans_le hf)
alias ⟨LowerSemicontinuousWithinAt.le_liminf, _⟩ := lowerSemicontinuousWithinAt_iff_le_liminf
theorem lowerSemicontinuousAt_iff_le_liminf {f : α → γ} :
LowerSemicontinuousAt f x ↔ f x ≤ liminf f (𝓝 x) := by
rw [← lowerSemicontinuousWithinAt_univ_iff, lowerSemicontinuousWithinAt_iff_le_liminf,
← nhdsWithin_univ]
alias ⟨LowerSemicontinuousAt.le_liminf, _⟩ := lowerSemicontinuousAt_iff_le_liminf
theorem lowerSemicontinuous_iff_le_liminf {f : α → γ} :
LowerSemicontinuous f ↔ ∀ x, f x ≤ liminf f (𝓝 x) := by
simp only [← lowerSemicontinuousAt_iff_le_liminf, LowerSemicontinuous]
alias ⟨LowerSemicontinuous.le_liminf, _⟩ := lowerSemicontinuous_iff_le_liminf
theorem lowerSemicontinuousOn_iff_le_liminf {f : α → γ} :
LowerSemicontinuousOn f s ↔ ∀ x ∈ s, f x ≤ liminf f (𝓝[s] x) := by
simp only [← lowerSemicontinuousWithinAt_iff_le_liminf, LowerSemicontinuousOn]
alias ⟨LowerSemicontinuousOn.le_liminf, _⟩ := lowerSemicontinuousOn_iff_le_liminf
variable [TopologicalSpace γ] [OrderTopology γ]
theorem lowerSemicontinuous_iff_isClosed_epigraph {f : α → γ} :
LowerSemicontinuous f ↔ IsClosed {p : α × γ | f p.1 ≤ p.2} := by
constructor
· rw [lowerSemicontinuous_iff_le_liminf, isClosed_iff_forall_filter]
rintro hf ⟨x, y⟩ F F_ne h h'
rw [nhds_prod_eq, le_prod] at h'
calc f x ≤ liminf f (𝓝 x) := hf x
_ ≤ liminf f (map Prod.fst F) := liminf_le_liminf_of_le h'.1
_ = liminf (f ∘ Prod.fst) F := (Filter.liminf_comp _ _ _).symm
_ ≤ liminf Prod.snd F := liminf_le_liminf <| by
simpa using (eventually_principal.2 fun (_ : α × γ) ↦ id).filter_mono h
_ = y := h'.2.liminf_eq
· rw [lowerSemicontinuous_iff_isClosed_preimage]
exact fun hf y ↦ hf.preimage (.prodMk_left y)
alias ⟨LowerSemicontinuous.isClosed_epigraph, _⟩ := lowerSemicontinuous_iff_isClosed_epigraph
end
/-! ### Composition -/
section
variable {γ : Type*} [LinearOrder γ] [TopologicalSpace γ] [OrderTopology γ]
variable {δ : Type*} [LinearOrder δ] [TopologicalSpace δ] [OrderTopology δ]
variable {ι : Type*} [TopologicalSpace ι]
theorem ContinuousAt.comp_lowerSemicontinuousWithinAt {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : LowerSemicontinuousWithinAt f s x) (gmon : Monotone g) :
LowerSemicontinuousWithinAt (g ∘ f) s x := by
intro y hy
by_cases h : ∃ l, l < f x
· obtain ⟨z, zlt, hz⟩ : ∃ z < f x, Ioc z (f x) ⊆ g ⁻¹' Ioi y :=
exists_Ioc_subset_of_mem_nhds (hg (Ioi_mem_nhds hy)) h
filter_upwards [hf z zlt] with a ha
calc
y < g (min (f x) (f a)) := hz (by simp [zlt, ha, le_refl])
_ ≤ g (f a) := gmon (min_le_right _ _)
· simp only [not_exists, not_lt] at h
exact Filter.Eventually.of_forall fun a => hy.trans_le (gmon (h (f a)))
theorem ContinuousAt.comp_lowerSemicontinuousAt {g : γ → δ} {f : α → γ} (hg : ContinuousAt g (f x))
(hf : LowerSemicontinuousAt f x) (gmon : Monotone g) : LowerSemicontinuousAt (g ∘ f) x := by
simp only [← lowerSemicontinuousWithinAt_univ_iff] at hf ⊢
exact hg.comp_lowerSemicontinuousWithinAt hf gmon
theorem Continuous.comp_lowerSemicontinuousOn {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuousOn f s) (gmon : Monotone g) : LowerSemicontinuousOn (g ∘ f) s :=
fun x hx => hg.continuousAt.comp_lowerSemicontinuousWithinAt (hf x hx) gmon
theorem Continuous.comp_lowerSemicontinuous {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuous f) (gmon : Monotone g) : LowerSemicontinuous (g ∘ f) := fun x =>
hg.continuousAt.comp_lowerSemicontinuousAt (hf x) gmon
theorem ContinuousAt.comp_lowerSemicontinuousWithinAt_antitone {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : LowerSemicontinuousWithinAt f s x) (gmon : Antitone g) :
UpperSemicontinuousWithinAt (g ∘ f) s x :=
@ContinuousAt.comp_lowerSemicontinuousWithinAt α _ x s γ _ _ _ δᵒᵈ _ _ _ g f hg hf gmon
theorem ContinuousAt.comp_lowerSemicontinuousAt_antitone {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : LowerSemicontinuousAt f x) (gmon : Antitone g) :
UpperSemicontinuousAt (g ∘ f) x :=
@ContinuousAt.comp_lowerSemicontinuousAt α _ x γ _ _ _ δᵒᵈ _ _ _ g f hg hf gmon
theorem Continuous.comp_lowerSemicontinuousOn_antitone {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuousOn f s) (gmon : Antitone g) : UpperSemicontinuousOn (g ∘ f) s :=
fun x hx => hg.continuousAt.comp_lowerSemicontinuousWithinAt_antitone (hf x hx) gmon
theorem Continuous.comp_lowerSemicontinuous_antitone {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuous f) (gmon : Antitone g) : UpperSemicontinuous (g ∘ f) := fun x =>
hg.continuousAt.comp_lowerSemicontinuousAt_antitone (hf x) gmon
theorem LowerSemicontinuousAt.comp_continuousAt {f : α → β} {g : ι → α} {x : ι}
(hf : LowerSemicontinuousAt f (g x)) (hg : ContinuousAt g x) :
LowerSemicontinuousAt (fun x ↦ f (g x)) x :=
fun _ lt ↦ hg.eventually (hf _ lt)
theorem LowerSemicontinuousAt.comp_continuousAt_of_eq {f : α → β} {g : ι → α} {y : α} {x : ι}
(hf : LowerSemicontinuousAt f y) (hg : ContinuousAt g x) (hy : g x = y) :
LowerSemicontinuousAt (fun x ↦ f (g x)) x := by
rw [← hy] at hf
exact comp_continuousAt hf hg
theorem LowerSemicontinuous.comp_continuous {f : α → β} {g : ι → α}
(hf : LowerSemicontinuous f) (hg : Continuous g) : LowerSemicontinuous fun x ↦ f (g x) :=
fun x ↦ (hf (g x)).comp_continuousAt hg.continuousAt
end
/-! #### Addition -/
section
variable {ι : Type*} {γ : Type*} [AddCommMonoid γ] [LinearOrder γ] [IsOrderedAddMonoid γ]
[TopologicalSpace γ] [OrderTopology γ]
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuousWithinAt.add' {f g : α → γ} (hf : LowerSemicontinuousWithinAt f s x)
(hg : LowerSemicontinuousWithinAt g s x)
(hcont : ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuousWithinAt (fun z => f z + g z) s x := by
intro y hy
obtain ⟨u, v, u_open, xu, v_open, xv, h⟩ :
∃ u v : Set γ,
IsOpen u ∧ f x ∈ u ∧ IsOpen v ∧ g x ∈ v ∧ u ×ˢ v ⊆ { p : γ × γ | y < p.fst + p.snd } :=
mem_nhds_prod_iff'.1 (hcont (isOpen_Ioi.mem_nhds hy))
by_cases hx₁ : ∃ l, l < f x
· obtain ⟨z₁, z₁lt, h₁⟩ : ∃ z₁ < f x, Ioc z₁ (f x) ⊆ u :=
exists_Ioc_subset_of_mem_nhds (u_open.mem_nhds xu) hx₁
by_cases hx₂ : ∃ l, l < g x
· obtain ⟨z₂, z₂lt, h₂⟩ : ∃ z₂ < g x, Ioc z₂ (g x) ⊆ v :=
exists_Ioc_subset_of_mem_nhds (v_open.mem_nhds xv) hx₂
filter_upwards [hf z₁ z₁lt, hg z₂ z₂lt] with z h₁z h₂z
have A1 : min (f z) (f x) ∈ u := by
by_cases H : f z ≤ f x
· simpa [H] using h₁ ⟨h₁z, H⟩
· simpa [le_of_not_le H]
have A2 : min (g z) (g x) ∈ v := by
by_cases H : g z ≤ g x
· simpa [H] using h₂ ⟨h₂z, H⟩
· simpa [le_of_not_le H]
have : (min (f z) (f x), min (g z) (g x)) ∈ u ×ˢ v := ⟨A1, A2⟩
calc
y < min (f z) (f x) + min (g z) (g x) := h this
_ ≤ f z + g z := add_le_add (min_le_left _ _) (min_le_left _ _)
· simp only [not_exists, not_lt] at hx₂
filter_upwards [hf z₁ z₁lt] with z h₁z
have A1 : min (f z) (f x) ∈ u := by
by_cases H : f z ≤ f x
· simpa [H] using h₁ ⟨h₁z, H⟩
· simpa [le_of_not_le H]
have : (min (f z) (f x), g x) ∈ u ×ˢ v := ⟨A1, xv⟩
calc
y < min (f z) (f x) + g x := h this
_ ≤ f z + g z := add_le_add (min_le_left _ _) (hx₂ (g z))
· simp only [not_exists, not_lt] at hx₁
by_cases hx₂ : ∃ l, l < g x
· obtain ⟨z₂, z₂lt, h₂⟩ : ∃ z₂ < g x, Ioc z₂ (g x) ⊆ v :=
exists_Ioc_subset_of_mem_nhds (v_open.mem_nhds xv) hx₂
filter_upwards [hg z₂ z₂lt] with z h₂z
have A2 : min (g z) (g x) ∈ v := by
by_cases H : g z ≤ g x
· simpa [H] using h₂ ⟨h₂z, H⟩
· simpa [le_of_not_le H] using h₂ ⟨z₂lt, le_rfl⟩
have : (f x, min (g z) (g x)) ∈ u ×ˢ v := ⟨xu, A2⟩
calc
y < f x + min (g z) (g x) := h this
_ ≤ f z + g z := add_le_add (hx₁ (f z)) (min_le_left _ _)
· simp only [not_exists, not_lt] at hx₁ hx₂
apply Filter.Eventually.of_forall
intro z
have : (f x, g x) ∈ u ×ˢ v := ⟨xu, xv⟩
calc
y < f x + g x := h this
_ ≤ f z + g z := add_le_add (hx₁ (f z)) (hx₂ (g z))
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuousAt.add' {f g : α → γ} (hf : LowerSemicontinuousAt f x)
(hg : LowerSemicontinuousAt g x)
(hcont : ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuousAt (fun z => f z + g z) x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
exact hf.add' hg hcont
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuousOn.add' {f g : α → γ} (hf : LowerSemicontinuousOn f s)
(hg : LowerSemicontinuousOn g s)
(hcont : ∀ x ∈ s, ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuousOn (fun z => f z + g z) s := fun x hx =>
(hf x hx).add' (hg x hx) (hcont x hx)
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuous.add' {f g : α → γ} (hf : LowerSemicontinuous f)
(hg : LowerSemicontinuous g)
(hcont : ∀ x, ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuous fun z => f z + g z := fun x => (hf x).add' (hg x) (hcont x)
variable [ContinuousAdd γ]
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuousWithinAt.add {f g : α → γ} (hf : LowerSemicontinuousWithinAt f s x)
(hg : LowerSemicontinuousWithinAt g s x) :
LowerSemicontinuousWithinAt (fun z => f z + g z) s x :=
hf.add' hg continuous_add.continuousAt
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuousAt.add {f g : α → γ} (hf : LowerSemicontinuousAt f x)
(hg : LowerSemicontinuousAt g x) : LowerSemicontinuousAt (fun z => f z + g z) x :=
hf.add' hg continuous_add.continuousAt
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuousOn.add {f g : α → γ} (hf : LowerSemicontinuousOn f s)
(hg : LowerSemicontinuousOn g s) : LowerSemicontinuousOn (fun z => f z + g z) s :=
hf.add' hg fun _x _hx => continuous_add.continuousAt
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuous.add {f g : α → γ} (hf : LowerSemicontinuous f)
(hg : LowerSemicontinuous g) : LowerSemicontinuous fun z => f z + g z :=
hf.add' hg fun _x => continuous_add.continuousAt
theorem lowerSemicontinuousWithinAt_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun z => ∑ i ∈ a, f i z) s x := by
classical
induction a using Finset.induction_on with
| empty => exact lowerSemicontinuousWithinAt_const
| insert _ _ ia IH =>
simp only [ia, Finset.sum_insert, not_false_iff]
exact
LowerSemicontinuousWithinAt.add (ha _ (Finset.mem_insert_self ..))
(IH fun j ja => ha j (Finset.mem_insert_of_mem ja))
theorem lowerSemicontinuousAt_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun z => ∑ i ∈ a, f i z) x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
exact lowerSemicontinuousWithinAt_sum ha
theorem lowerSemicontinuousOn_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun z => ∑ i ∈ a, f i z) s := fun x hx =>
lowerSemicontinuousWithinAt_sum fun i hi => ha i hi x hx
theorem lowerSemicontinuous_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuous (f i)) : LowerSemicontinuous fun z => ∑ i ∈ a, f i z :=
fun x => lowerSemicontinuousAt_sum fun i hi => ha i hi x
end
/-! #### Supremum -/
section
variable {ι : Sort*} {δ δ' : Type*} [CompleteLinearOrder δ] [ConditionallyCompleteLinearOrder δ']
theorem lowerSemicontinuousWithinAt_ciSup {f : ι → α → δ'}
(bdd : ∀ᶠ y in 𝓝[s] x, BddAbove (range fun i => f i y))
(h : ∀ i, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun x' => ⨆ i, f i x') s x := by
cases isEmpty_or_nonempty ι
· simpa only [iSup_of_empty'] using lowerSemicontinuousWithinAt_const
· intro y hy
rcases exists_lt_of_lt_ciSup hy with ⟨i, hi⟩
filter_upwards [h i y hi, bdd] with y hy hy' using hy.trans_le (le_ciSup hy' i)
theorem lowerSemicontinuousWithinAt_iSup {f : ι → α → δ}
(h : ∀ i, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun x' => ⨆ i, f i x') s x :=
lowerSemicontinuousWithinAt_ciSup (by simp) h
theorem lowerSemicontinuousWithinAt_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuousWithinAt (f i hi) s x) :
LowerSemicontinuousWithinAt (fun x' => ⨆ (i) (hi), f i hi x') s x :=
lowerSemicontinuousWithinAt_iSup fun i => lowerSemicontinuousWithinAt_iSup fun hi => h i hi
theorem lowerSemicontinuousAt_ciSup {f : ι → α → δ'}
(bdd : ∀ᶠ y in 𝓝 x, BddAbove (range fun i => f i y)) (h : ∀ i, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun x' => ⨆ i, f i x') x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
rw [← nhdsWithin_univ] at bdd
exact lowerSemicontinuousWithinAt_ciSup bdd h
theorem lowerSemicontinuousAt_iSup {f : ι → α → δ} (h : ∀ i, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun x' => ⨆ i, f i x') x :=
lowerSemicontinuousAt_ciSup (by simp) h
theorem lowerSemicontinuousAt_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuousAt (f i hi) x) :
LowerSemicontinuousAt (fun x' => ⨆ (i) (hi), f i hi x') x :=
lowerSemicontinuousAt_iSup fun i => lowerSemicontinuousAt_iSup fun hi => h i hi
theorem lowerSemicontinuousOn_ciSup {f : ι → α → δ'}
(bdd : ∀ x ∈ s, BddAbove (range fun i => f i x)) (h : ∀ i, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun x' => ⨆ i, f i x') s := fun x hx =>
lowerSemicontinuousWithinAt_ciSup (eventually_nhdsWithin_of_forall bdd) fun i => h i x hx
theorem lowerSemicontinuousOn_iSup {f : ι → α → δ} (h : ∀ i, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun x' => ⨆ i, f i x') s :=
lowerSemicontinuousOn_ciSup (by simp) h
theorem lowerSemicontinuousOn_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuousOn (f i hi) s) :
LowerSemicontinuousOn (fun x' => ⨆ (i) (hi), f i hi x') s :=
lowerSemicontinuousOn_iSup fun i => lowerSemicontinuousOn_iSup fun hi => h i hi
theorem lowerSemicontinuous_ciSup {f : ι → α → δ'} (bdd : ∀ x, BddAbove (range fun i => f i x))
(h : ∀ i, LowerSemicontinuous (f i)) : LowerSemicontinuous fun x' => ⨆ i, f i x' := fun x =>
lowerSemicontinuousAt_ciSup (Eventually.of_forall bdd) fun i => h i x
theorem lowerSemicontinuous_iSup {f : ι → α → δ} (h : ∀ i, LowerSemicontinuous (f i)) :
LowerSemicontinuous fun x' => ⨆ i, f i x' :=
lowerSemicontinuous_ciSup (by simp) h
theorem lowerSemicontinuous_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuous (f i hi)) :
LowerSemicontinuous fun x' => ⨆ (i) (hi), f i hi x' :=
lowerSemicontinuous_iSup fun i => lowerSemicontinuous_iSup fun hi => h i hi
end
/-! #### Infinite sums -/
section
variable {ι : Type*}
theorem lowerSemicontinuousWithinAt_tsum {f : ι → α → ℝ≥0∞}
(h : ∀ i, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun x' => ∑' i, f i x') s x := by
simp_rw [ENNReal.tsum_eq_iSup_sum]
refine lowerSemicontinuousWithinAt_iSup fun b => ?_
exact lowerSemicontinuousWithinAt_sum fun i _hi => h i
theorem lowerSemicontinuousAt_tsum {f : ι → α → ℝ≥0∞} (h : ∀ i, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun x' => ∑' i, f i x') x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
exact lowerSemicontinuousWithinAt_tsum h
theorem lowerSemicontinuousOn_tsum {f : ι → α → ℝ≥0∞} (h : ∀ i, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun x' => ∑' i, f i x') s := fun x hx =>
lowerSemicontinuousWithinAt_tsum fun i => h i x hx
theorem lowerSemicontinuous_tsum {f : ι → α → ℝ≥0∞} (h : ∀ i, LowerSemicontinuous (f i)) :
LowerSemicontinuous fun x' => ∑' i, f i x' := fun x => lowerSemicontinuousAt_tsum fun i => h i x
end
/-!
### Upper semicontinuous functions
-/
/-! #### Basic dot notation interface for upper semicontinuity -/
theorem UpperSemicontinuousWithinAt.mono (h : UpperSemicontinuousWithinAt f s x) (hst : t ⊆ s) :
UpperSemicontinuousWithinAt f t x := fun y hy =>
Filter.Eventually.filter_mono (nhdsWithin_mono _ hst) (h y hy)
theorem upperSemicontinuousWithinAt_univ_iff :
UpperSemicontinuousWithinAt f univ x ↔ UpperSemicontinuousAt f x := by
simp [UpperSemicontinuousWithinAt, UpperSemicontinuousAt, nhdsWithin_univ]
theorem UpperSemicontinuousAt.upperSemicontinuousWithinAt (s : Set α)
(h : UpperSemicontinuousAt f x) : UpperSemicontinuousWithinAt f s x := fun y hy =>
Filter.Eventually.filter_mono nhdsWithin_le_nhds (h y hy)
theorem UpperSemicontinuousOn.upperSemicontinuousWithinAt (h : UpperSemicontinuousOn f s)
(hx : x ∈ s) : UpperSemicontinuousWithinAt f s x :=
h x hx
theorem UpperSemicontinuousOn.mono (h : UpperSemicontinuousOn f s) (hst : t ⊆ s) :
UpperSemicontinuousOn f t := fun x hx => (h x (hst hx)).mono hst
theorem upperSemicontinuousOn_univ_iff : UpperSemicontinuousOn f univ ↔ UpperSemicontinuous f := by
simp [UpperSemicontinuousOn, UpperSemicontinuous, upperSemicontinuousWithinAt_univ_iff]
theorem UpperSemicontinuous.upperSemicontinuousAt (h : UpperSemicontinuous f) (x : α) :
UpperSemicontinuousAt f x :=
h x
theorem UpperSemicontinuous.upperSemicontinuousWithinAt (h : UpperSemicontinuous f) (s : Set α)
(x : α) : UpperSemicontinuousWithinAt f s x :=
(h x).upperSemicontinuousWithinAt s
theorem UpperSemicontinuous.upperSemicontinuousOn (h : UpperSemicontinuous f) (s : Set α) :
UpperSemicontinuousOn f s := fun x _hx => h.upperSemicontinuousWithinAt s x
/-! #### Constants -/
theorem upperSemicontinuousWithinAt_const : UpperSemicontinuousWithinAt (fun _x => z) s x :=
fun _y hy => Filter.Eventually.of_forall fun _x => hy
theorem upperSemicontinuousAt_const : UpperSemicontinuousAt (fun _x => z) x := fun _y hy =>
Filter.Eventually.of_forall fun _x => hy
theorem upperSemicontinuousOn_const : UpperSemicontinuousOn (fun _x => z) s := fun _x _hx =>
upperSemicontinuousWithinAt_const
theorem upperSemicontinuous_const : UpperSemicontinuous fun _x : α => z := fun _x =>
upperSemicontinuousAt_const
/-! #### Indicators -/
section
variable [Zero β]
theorem IsOpen.upperSemicontinuous_indicator (hs : IsOpen s) (hy : y ≤ 0) :
UpperSemicontinuous (indicator s fun _x => y) :=
@IsOpen.lowerSemicontinuous_indicator α _ βᵒᵈ _ s y _ hs hy
theorem IsOpen.upperSemicontinuousOn_indicator (hs : IsOpen s) (hy : y ≤ 0) :
UpperSemicontinuousOn (indicator s fun _x => y) t :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousOn t
theorem IsOpen.upperSemicontinuousAt_indicator (hs : IsOpen s) (hy : y ≤ 0) :
UpperSemicontinuousAt (indicator s fun _x => y) x :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousAt x
theorem IsOpen.upperSemicontinuousWithinAt_indicator (hs : IsOpen s) (hy : y ≤ 0) :
UpperSemicontinuousWithinAt (indicator s fun _x => y) t x :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousWithinAt t x
theorem IsClosed.upperSemicontinuous_indicator (hs : IsClosed s) (hy : 0 ≤ y) :
UpperSemicontinuous (indicator s fun _x => y) :=
@IsClosed.lowerSemicontinuous_indicator α _ βᵒᵈ _ s y _ hs hy
theorem IsClosed.upperSemicontinuousOn_indicator (hs : IsClosed s) (hy : 0 ≤ y) :
UpperSemicontinuousOn (indicator s fun _x => y) t :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousOn t
theorem IsClosed.upperSemicontinuousAt_indicator (hs : IsClosed s) (hy : 0 ≤ y) :
UpperSemicontinuousAt (indicator s fun _x => y) x :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousAt x
theorem IsClosed.upperSemicontinuousWithinAt_indicator (hs : IsClosed s) (hy : 0 ≤ y) :
UpperSemicontinuousWithinAt (indicator s fun _x => y) t x :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousWithinAt t x
end
/-! #### Relationship with continuity -/
theorem upperSemicontinuous_iff_isOpen_preimage :
UpperSemicontinuous f ↔ ∀ y, IsOpen (f ⁻¹' Iio y) :=
⟨fun H y => isOpen_iff_mem_nhds.2 fun x hx => H x y hx, fun H _x y y_lt =>
IsOpen.mem_nhds (H y) y_lt⟩
theorem UpperSemicontinuous.isOpen_preimage (hf : UpperSemicontinuous f) (y : β) :
IsOpen (f ⁻¹' Iio y) :=
upperSemicontinuous_iff_isOpen_preimage.1 hf y
section
variable {γ : Type*} [LinearOrder γ]
theorem upperSemicontinuous_iff_isClosed_preimage {f : α → γ} :
UpperSemicontinuous f ↔ ∀ y, IsClosed (f ⁻¹' Ici y) := by
rw [upperSemicontinuous_iff_isOpen_preimage]
simp only [← isOpen_compl_iff, ← preimage_compl, compl_Ici]
theorem UpperSemicontinuous.isClosed_preimage {f : α → γ} (hf : UpperSemicontinuous f) (y : γ) :
IsClosed (f ⁻¹' Ici y) :=
upperSemicontinuous_iff_isClosed_preimage.1 hf y
variable [TopologicalSpace γ] [OrderTopology γ]
theorem ContinuousWithinAt.upperSemicontinuousWithinAt {f : α → γ} (h : ContinuousWithinAt f s x) :
UpperSemicontinuousWithinAt f s x := fun _y hy => h (Iio_mem_nhds hy)
theorem ContinuousAt.upperSemicontinuousAt {f : α → γ} (h : ContinuousAt f x) :
UpperSemicontinuousAt f x := fun _y hy => h (Iio_mem_nhds hy)
theorem ContinuousOn.upperSemicontinuousOn {f : α → γ} (h : ContinuousOn f s) :
UpperSemicontinuousOn f s := fun x hx => (h x hx).upperSemicontinuousWithinAt
theorem Continuous.upperSemicontinuous {f : α → γ} (h : Continuous f) : UpperSemicontinuous f :=
fun _x => h.continuousAt.upperSemicontinuousAt
end
/-! #### Equivalent definitions -/
section
variable {γ : Type*} [CompleteLinearOrder γ] [DenselyOrdered γ]
theorem upperSemicontinuousWithinAt_iff_limsup_le {f : α → γ} :
UpperSemicontinuousWithinAt f s x ↔ limsup f (𝓝[s] x) ≤ f x :=
lowerSemicontinuousWithinAt_iff_le_liminf (γ := γᵒᵈ)
alias ⟨UpperSemicontinuousWithinAt.limsup_le, _⟩ := upperSemicontinuousWithinAt_iff_limsup_le
theorem upperSemicontinuousAt_iff_limsup_le {f : α → γ} :
UpperSemicontinuousAt f x ↔ limsup f (𝓝 x) ≤ f x :=
lowerSemicontinuousAt_iff_le_liminf (γ := γᵒᵈ)
alias ⟨UpperSemicontinuousAt.limsup_le, _⟩ := upperSemicontinuousAt_iff_limsup_le
theorem upperSemicontinuous_iff_limsup_le {f : α → γ} :
UpperSemicontinuous f ↔ ∀ x, limsup f (𝓝 x) ≤ f x :=
lowerSemicontinuous_iff_le_liminf (γ := γᵒᵈ)
alias ⟨UpperSemicontinuous.limsup_le, _⟩ := upperSemicontinuous_iff_limsup_le
theorem upperSemicontinuousOn_iff_limsup_le {f : α → γ} :
UpperSemicontinuousOn f s ↔ ∀ x ∈ s, limsup f (𝓝[s] x) ≤ f x :=
lowerSemicontinuousOn_iff_le_liminf (γ := γᵒᵈ)
alias ⟨UpperSemicontinuousOn.limsup_le, _⟩ := upperSemicontinuousOn_iff_limsup_le
variable [TopologicalSpace γ] [OrderTopology γ]
theorem upperSemicontinuous_iff_IsClosed_hypograph {f : α → γ} :
UpperSemicontinuous f ↔ IsClosed {p : α × γ | p.2 ≤ f p.1} :=
lowerSemicontinuous_iff_isClosed_epigraph (γ := γᵒᵈ)
alias ⟨UpperSemicontinuous.IsClosed_hypograph, _⟩ := upperSemicontinuous_iff_IsClosed_hypograph
end
/-! ### Composition -/
section
variable {γ : Type*} [LinearOrder γ] [TopologicalSpace γ] [OrderTopology γ]
variable {δ : Type*} [LinearOrder δ] [TopologicalSpace δ] [OrderTopology δ]
variable {ι : Type*} [TopologicalSpace ι]
theorem ContinuousAt.comp_upperSemicontinuousWithinAt {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : UpperSemicontinuousWithinAt f s x) (gmon : Monotone g) :
UpperSemicontinuousWithinAt (g ∘ f) s x :=
@ContinuousAt.comp_lowerSemicontinuousWithinAt α _ x s γᵒᵈ _ _ _ δᵒᵈ _ _ _ g f hg hf gmon.dual
theorem ContinuousAt.comp_upperSemicontinuousAt {g : γ → δ} {f : α → γ} (hg : ContinuousAt g (f x))
(hf : UpperSemicontinuousAt f x) (gmon : Monotone g) : UpperSemicontinuousAt (g ∘ f) x :=
@ContinuousAt.comp_lowerSemicontinuousAt α _ x γᵒᵈ _ _ _ δᵒᵈ _ _ _ g f hg hf gmon.dual
theorem Continuous.comp_upperSemicontinuousOn {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : UpperSemicontinuousOn f s) (gmon : Monotone g) : UpperSemicontinuousOn (g ∘ f) s :=
fun x hx => hg.continuousAt.comp_upperSemicontinuousWithinAt (hf x hx) gmon
theorem Continuous.comp_upperSemicontinuous {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : UpperSemicontinuous f) (gmon : Monotone g) : UpperSemicontinuous (g ∘ f) := fun x =>
hg.continuousAt.comp_upperSemicontinuousAt (hf x) gmon
theorem ContinuousAt.comp_upperSemicontinuousWithinAt_antitone {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : UpperSemicontinuousWithinAt f s x) (gmon : Antitone g) :
LowerSemicontinuousWithinAt (g ∘ f) s x :=
@ContinuousAt.comp_upperSemicontinuousWithinAt α _ x s γ _ _ _ δᵒᵈ _ _ _ g f hg hf gmon
theorem ContinuousAt.comp_upperSemicontinuousAt_antitone {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : UpperSemicontinuousAt f x) (gmon : Antitone g) :
LowerSemicontinuousAt (g ∘ f) x :=
@ContinuousAt.comp_upperSemicontinuousAt α _ x γ _ _ _ δᵒᵈ _ _ _ g f hg hf gmon
theorem Continuous.comp_upperSemicontinuousOn_antitone {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : UpperSemicontinuousOn f s) (gmon : Antitone g) : LowerSemicontinuousOn (g ∘ f) s :=
fun x hx => hg.continuousAt.comp_upperSemicontinuousWithinAt_antitone (hf x hx) gmon
theorem Continuous.comp_upperSemicontinuous_antitone {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : UpperSemicontinuous f) (gmon : Antitone g) : LowerSemicontinuous (g ∘ f) := fun x =>
hg.continuousAt.comp_upperSemicontinuousAt_antitone (hf x) gmon
theorem UpperSemicontinuousAt.comp_continuousAt {f : α → β} {g : ι → α} {x : ι}
(hf : UpperSemicontinuousAt f (g x)) (hg : ContinuousAt g x) :
UpperSemicontinuousAt (fun x ↦ f (g x)) x :=
| fun _ lt ↦ hg.eventually (hf _ lt)
theorem UpperSemicontinuousAt.comp_continuousAt_of_eq {f : α → β} {g : ι → α} {y : α} {x : ι}
(hf : UpperSemicontinuousAt f y) (hg : ContinuousAt g x) (hy : g x = y) :
| Mathlib/Topology/Semicontinuous.lean | 888 | 891 |
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.Homotopy
import Mathlib.Algebra.Ring.NegOnePow
import Mathlib.Algebra.Category.Grp.Preadditive
import Mathlib.Tactic.Linarith
import Mathlib.CategoryTheory.Linear.LinearFunctor
/-! The cochain complex of homomorphisms between cochain complexes
If `F` and `G` are cochain complexes (indexed by `ℤ`) in a preadditive category,
there is a cochain complex of abelian groups whose `0`-cocycles identify to
morphisms `F ⟶ G`. Informally, in degree `n`, this complex shall consist of
cochains of degree `n` from `F` to `G`, i.e. arbitrary families for morphisms
`F.X p ⟶ G.X (p + n)`. This complex shall be denoted `HomComplex F G`.
In order to avoid type theoretic issues, a cochain of degree `n : ℤ`
(i.e. a term of type of `Cochain F G n`) shall be defined here
as the data of a morphism `F.X p ⟶ G.X q` for all triplets
`⟨p, q, hpq⟩` where `p` and `q` are integers and `hpq : p + n = q`.
If `α : Cochain F G n`, we shall define `α.v p q hpq : F.X p ⟶ G.X q`.
We follow the signs conventions appearing in the introduction of
[Brian Conrad's book *Grothendieck duality and base change*][conrad2000].
## References
* [Brian Conrad, Grothendieck duality and base change][conrad2000]
-/
assert_not_exists TwoSidedIdeal
open CategoryTheory Category Limits Preadditive
universe v u
variable {C : Type u} [Category.{v} C] [Preadditive C] {R : Type*} [Ring R] [Linear R C]
namespace CochainComplex
variable {F G K L : CochainComplex C ℤ} (n m : ℤ)
namespace HomComplex
/-- A term of type `HomComplex.Triplet n` consists of two integers `p` and `q`
such that `p + n = q`. (This type is introduced so that the instance
`AddCommGroup (Cochain F G n)` defined below can be found automatically.) -/
structure Triplet (n : ℤ) where
/-- a first integer -/
p : ℤ
/-- a second integer -/
q : ℤ
/-- the condition on the two integers -/
hpq : p + n = q
variable (F G)
/-- A cochain of degree `n : ℤ` between to cochain complexes `F` and `G` consists
of a family of morphisms `F.X p ⟶ G.X q` whenever `p + n = q`, i.e. for all
triplets in `HomComplex.Triplet n`. -/
def Cochain := ∀ (T : Triplet n), F.X T.p ⟶ G.X T.q
instance : AddCommGroup (Cochain F G n) := by
dsimp only [Cochain]
infer_instance
instance : Module R (Cochain F G n) := by
dsimp only [Cochain]
infer_instance
namespace Cochain
variable {F G n}
/-- A practical constructor for cochains. -/
def mk (v : ∀ (p q : ℤ) (_ : p + n = q), F.X p ⟶ G.X q) : Cochain F G n :=
fun ⟨p, q, hpq⟩ => v p q hpq
/-- The value of a cochain on a triplet `⟨p, q, hpq⟩`. -/
def v (γ : Cochain F G n) (p q : ℤ) (hpq : p + n = q) :
F.X p ⟶ G.X q := γ ⟨p, q, hpq⟩
@[simp]
lemma mk_v (v : ∀ (p q : ℤ) (_ : p + n = q), F.X p ⟶ G.X q) (p q : ℤ) (hpq : p + n = q) :
(Cochain.mk v).v p q hpq = v p q hpq := rfl
lemma congr_v {z₁ z₂ : Cochain F G n} (h : z₁ = z₂) (p q : ℤ) (hpq : p + n = q) :
z₁.v p q hpq = z₂.v p q hpq := by subst h; rfl
@[ext]
lemma ext (z₁ z₂ : Cochain F G n)
(h : ∀ (p q hpq), z₁.v p q hpq = z₂.v p q hpq) : z₁ = z₂ := by
funext ⟨p, q, hpq⟩
apply h
@[ext 1100]
lemma ext₀ (z₁ z₂ : Cochain F G 0)
(h : ∀ (p : ℤ), z₁.v p p (add_zero p) = z₂.v p p (add_zero p)) : z₁ = z₂ := by
ext p q hpq
obtain rfl : q = p := by rw [← hpq, add_zero]
exact h q
@[simp]
lemma zero_v {n : ℤ} (p q : ℤ) (hpq : p + n = q) :
(0 : Cochain F G n).v p q hpq = 0 := rfl
@[simp]
lemma add_v {n : ℤ} (z₁ z₂ : Cochain F G n) (p q : ℤ) (hpq : p + n = q) :
(z₁ + z₂).v p q hpq = z₁.v p q hpq + z₂.v p q hpq := rfl
@[simp]
lemma sub_v {n : ℤ} (z₁ z₂ : Cochain F G n) (p q : ℤ) (hpq : p + n = q) :
(z₁ - z₂).v p q hpq = z₁.v p q hpq - z₂.v p q hpq := rfl
@[simp]
lemma neg_v {n : ℤ} (z : Cochain F G n) (p q : ℤ) (hpq : p + n = q) :
(-z).v p q hpq = - (z.v p q hpq) := rfl
@[simp]
lemma smul_v {n : ℤ} (k : R) (z : Cochain F G n) (p q : ℤ) (hpq : p + n = q) :
(k • z).v p q hpq = k • (z.v p q hpq) := rfl
@[simp]
lemma units_smul_v {n : ℤ} (k : Rˣ) (z : Cochain F G n) (p q : ℤ) (hpq : p + n = q) :
(k • z).v p q hpq = k • (z.v p q hpq) := rfl
/-- A cochain of degree `0` from `F` to `G` can be constructed from a family
of morphisms `F.X p ⟶ G.X p` for all `p : ℤ`. -/
def ofHoms (ψ : ∀ (p : ℤ), F.X p ⟶ G.X p) : Cochain F G 0 :=
Cochain.mk (fun p q hpq => ψ p ≫ eqToHom (by rw [← hpq, add_zero]))
@[simp]
lemma ofHoms_v (ψ : ∀ (p : ℤ), F.X p ⟶ G.X p) (p : ℤ) :
(ofHoms ψ).v p p (add_zero p) = ψ p := by
simp only [ofHoms, mk_v, eqToHom_refl, comp_id]
@[simp]
lemma ofHoms_zero : ofHoms (fun p => (0 : F.X p ⟶ G.X p)) = 0 := by aesop_cat
@[simp]
lemma ofHoms_v_comp_d (ψ : ∀ (p : ℤ), F.X p ⟶ G.X p) (p q q' : ℤ) (hpq : p + 0 = q) :
(ofHoms ψ).v p q hpq ≫ G.d q q' = ψ p ≫ G.d p q' := by
rw [add_zero] at hpq
subst hpq
rw [ofHoms_v]
@[simp]
lemma d_comp_ofHoms_v (ψ : ∀ (p : ℤ), F.X p ⟶ G.X p) (p' p q : ℤ) (hpq : p + 0 = q) :
F.d p' p ≫ (ofHoms ψ).v p q hpq = F.d p' q ≫ ψ q := by
rw [add_zero] at hpq
subst hpq
rw [ofHoms_v]
/-- The `0`-cochain attached to a morphism of cochain complexes. -/
def ofHom (φ : F ⟶ G) : Cochain F G 0 := ofHoms (fun p => φ.f p)
variable (F G)
@[simp]
lemma ofHom_zero : ofHom (0 : F ⟶ G) = 0 := by
simp only [ofHom, HomologicalComplex.zero_f_apply, ofHoms_zero]
variable {F G}
@[simp]
lemma ofHom_v (φ : F ⟶ G) (p : ℤ) : (ofHom φ).v p p (add_zero p) = φ.f p := by
simp only [ofHom, ofHoms_v]
@[simp]
lemma ofHom_v_comp_d (φ : F ⟶ G) (p q q' : ℤ) (hpq : p + 0 = q) :
(ofHom φ).v p q hpq ≫ G.d q q' = φ.f p ≫ G.d p q' := by
simp only [ofHom, ofHoms_v_comp_d]
@[simp]
lemma d_comp_ofHom_v (φ : F ⟶ G) (p' p q : ℤ) (hpq : p + 0 = q) :
F.d p' p ≫ (ofHom φ).v p q hpq = F.d p' q ≫ φ.f q := by
simp only [ofHom, d_comp_ofHoms_v]
@[simp]
lemma ofHom_add (φ₁ φ₂ : F ⟶ G) :
Cochain.ofHom (φ₁ + φ₂) = Cochain.ofHom φ₁ + Cochain.ofHom φ₂ := by aesop_cat
@[simp]
lemma ofHom_sub (φ₁ φ₂ : F ⟶ G) :
Cochain.ofHom (φ₁ - φ₂) = Cochain.ofHom φ₁ - Cochain.ofHom φ₂ := by aesop_cat
@[simp]
lemma ofHom_neg (φ : F ⟶ G) :
Cochain.ofHom (-φ) = -Cochain.ofHom φ := by aesop_cat
/-- The cochain of degree `-1` given by an homotopy between two morphism of complexes. -/
def ofHomotopy {φ₁ φ₂ : F ⟶ G} (ho : Homotopy φ₁ φ₂) : Cochain F G (-1) :=
Cochain.mk (fun p q _ => ho.hom p q)
@[simp]
lemma ofHomotopy_ofEq {φ₁ φ₂ : F ⟶ G} (h : φ₁ = φ₂) :
ofHomotopy (Homotopy.ofEq h) = 0 := rfl
@[simp]
lemma ofHomotopy_refl (φ : F ⟶ G) :
ofHomotopy (Homotopy.refl φ) = 0 := rfl
@[reassoc]
lemma v_comp_XIsoOfEq_hom
(γ : Cochain F G n) (p q q' : ℤ) (hpq : p + n = q) (hq' : q = q') :
γ.v p q hpq ≫ (HomologicalComplex.XIsoOfEq G hq').hom = γ.v p q' (by rw [← hq', hpq]) := by
subst hq'
simp only [HomologicalComplex.XIsoOfEq, eqToIso_refl, Iso.refl_hom, comp_id]
@[reassoc]
lemma v_comp_XIsoOfEq_inv
(γ : Cochain F G n) (p q q' : ℤ) (hpq : p + n = q) (hq' : q' = q) :
γ.v p q hpq ≫ (HomologicalComplex.XIsoOfEq G hq').inv = γ.v p q' (by rw [hq', hpq]) := by
subst hq'
simp only [HomologicalComplex.XIsoOfEq, eqToIso_refl, Iso.refl_inv, comp_id]
/-- The composition of cochains. -/
def comp {n₁ n₂ n₁₂ : ℤ} (z₁ : Cochain F G n₁) (z₂ : Cochain G K n₂) (h : n₁ + n₂ = n₁₂) :
Cochain F K n₁₂ :=
Cochain.mk (fun p q hpq => z₁.v p (p + n₁) rfl ≫ z₂.v (p + n₁) q (by omega))
/-! If `z₁` is a cochain of degree `n₁` and `z₂` is a cochain of degree `n₂`, and that
we have a relation `h : n₁ + n₂ = n₁₂`, then `z₁.comp z₂ h` is a cochain of degree `n₁₂`.
The following lemma `comp_v` computes the value of this composition `z₁.comp z₂ h`
on a triplet `⟨p₁, p₃, _⟩` (with `p₁ + n₁₂ = p₃`). In order to use this lemma,
we need to provide an intermediate integer `p₂` such that `p₁ + n₁ = p₂`.
It is advisable to use a `p₂` that has good definitional properties
(i.e. `p₁ + n₁` is not always the best choice.)
When `z₁` or `z₂` is a `0`-cochain, there is a better choice of `p₂`, and this leads
to the two simplification lemmas `comp_zero_cochain_v` and `zero_cochain_comp_v`.
-/
lemma comp_v {n₁ n₂ n₁₂ : ℤ} (z₁ : Cochain F G n₁) (z₂ : Cochain G K n₂) (h : n₁ + n₂ = n₁₂)
(p₁ p₂ p₃ : ℤ) (h₁ : p₁ + n₁ = p₂) (h₂ : p₂ + n₂ = p₃) :
(z₁.comp z₂ h).v p₁ p₃ (by rw [← h₂, ← h₁, ← h, add_assoc]) =
z₁.v p₁ p₂ h₁ ≫ z₂.v p₂ p₃ h₂ := by
subst h₁; rfl
@[simp]
lemma comp_zero_cochain_v (z₁ : Cochain F G n) (z₂ : Cochain G K 0) (p q : ℤ) (hpq : p + n = q) :
(z₁.comp z₂ (add_zero n)).v p q hpq = z₁.v p q hpq ≫ z₂.v q q (add_zero q) :=
comp_v z₁ z₂ (add_zero n) p q q hpq (add_zero q)
@[simp]
lemma zero_cochain_comp_v (z₁ : Cochain F G 0) (z₂ : Cochain G K n) (p q : ℤ) (hpq : p + n = q) :
(z₁.comp z₂ (zero_add n)).v p q hpq = z₁.v p p (add_zero p) ≫ z₂.v p q hpq :=
comp_v z₁ z₂ (zero_add n) p p q (add_zero p) hpq
/-- The associativity of the composition of cochains. -/
lemma comp_assoc {n₁ n₂ n₃ n₁₂ n₂₃ n₁₂₃ : ℤ}
(z₁ : Cochain F G n₁) (z₂ : Cochain G K n₂) (z₃ : Cochain K L n₃)
(h₁₂ : n₁ + n₂ = n₁₂) (h₂₃ : n₂ + n₃ = n₂₃) (h₁₂₃ : n₁ + n₂ + n₃ = n₁₂₃) :
(z₁.comp z₂ h₁₂).comp z₃ (show n₁₂ + n₃ = n₁₂₃ by rw [← h₁₂, h₁₂₃]) =
z₁.comp (z₂.comp z₃ h₂₃) (by rw [← h₂₃, ← h₁₂₃, add_assoc]) := by
substs h₁₂ h₂₃ h₁₂₃
ext p q hpq
rw [comp_v _ _ rfl p (p + n₁ + n₂) q (add_assoc _ _ _).symm (by omega),
comp_v z₁ z₂ rfl p (p + n₁) (p + n₁ + n₂) (by omega) (by omega),
comp_v z₁ (z₂.comp z₃ rfl) (add_assoc n₁ n₂ n₃).symm p (p + n₁) q (by omega) (by omega),
comp_v z₂ z₃ rfl (p + n₁) (p + n₁ + n₂) q (by omega) (by omega), assoc]
/-! The formulation of the associativity of the composition of cochains given by the
lemma `comp_assoc` often requires a careful selection of degrees with good definitional
properties. In a few cases, like when one of the three cochains is a `0`-cochain,
there are better choices, which provides the following simplification lemmas. -/
@[simp]
lemma comp_assoc_of_first_is_zero_cochain {n₂ n₃ n₂₃ : ℤ}
(z₁ : Cochain F G 0) (z₂ : Cochain G K n₂) (z₃ : Cochain K L n₃)
(h₂₃ : n₂ + n₃ = n₂₃) :
(z₁.comp z₂ (zero_add n₂)).comp z₃ h₂₃ = z₁.comp (z₂.comp z₃ h₂₃) (zero_add n₂₃) :=
comp_assoc _ _ _ _ _ (by omega)
@[simp]
lemma comp_assoc_of_second_is_zero_cochain {n₁ n₃ n₁₃ : ℤ}
(z₁ : Cochain F G n₁) (z₂ : Cochain G K 0) (z₃ : Cochain K L n₃) (h₁₃ : n₁ + n₃ = n₁₃) :
(z₁.comp z₂ (add_zero n₁)).comp z₃ h₁₃ = z₁.comp (z₂.comp z₃ (zero_add n₃)) h₁₃ :=
comp_assoc _ _ _ _ _ (by omega)
@[simp]
lemma comp_assoc_of_third_is_zero_cochain {n₁ n₂ n₁₂ : ℤ}
(z₁ : Cochain F G n₁) (z₂ : Cochain G K n₂) (z₃ : Cochain K L 0) (h₁₂ : n₁ + n₂ = n₁₂) :
(z₁.comp z₂ h₁₂).comp z₃ (add_zero n₁₂) = z₁.comp (z₂.comp z₃ (add_zero n₂)) h₁₂ :=
comp_assoc _ _ _ _ _ (by omega)
@[simp]
lemma comp_assoc_of_second_degree_eq_neg_third_degree {n₁ n₂ n₁₂ : ℤ}
(z₁ : Cochain F G n₁) (z₂ : Cochain G K (-n₂)) (z₃ : Cochain K L n₂) (h₁₂ : n₁ + (-n₂) = n₁₂) :
(z₁.comp z₂ h₁₂).comp z₃
(show n₁₂ + n₂ = n₁ by rw [← h₁₂, add_assoc, neg_add_cancel, add_zero]) =
z₁.comp (z₂.comp z₃ (neg_add_cancel n₂)) (add_zero n₁) :=
comp_assoc _ _ _ _ _ (by omega)
@[simp]
protected lemma zero_comp {n₁ n₂ n₁₂ : ℤ} (z₂ : Cochain G K n₂)
(h : n₁ + n₂ = n₁₂) : (0 : Cochain F G n₁).comp z₂ h = 0 := by
ext p q hpq
simp only [comp_v _ _ h p _ q rfl (by omega), zero_v, zero_comp]
@[simp]
protected lemma add_comp {n₁ n₂ n₁₂ : ℤ} (z₁ z₁' : Cochain F G n₁) (z₂ : Cochain G K n₂)
(h : n₁ + n₂ = n₁₂) : (z₁ + z₁').comp z₂ h = z₁.comp z₂ h + z₁'.comp z₂ h := by
ext p q hpq
simp only [comp_v _ _ h p _ q rfl (by omega), add_v, add_comp]
@[simp]
protected lemma sub_comp {n₁ n₂ n₁₂ : ℤ} (z₁ z₁' : Cochain F G n₁) (z₂ : Cochain G K n₂)
(h : n₁ + n₂ = n₁₂) : (z₁ - z₁').comp z₂ h = z₁.comp z₂ h - z₁'.comp z₂ h := by
ext p q hpq
simp only [comp_v _ _ h p _ q rfl (by omega), sub_v, sub_comp]
@[simp]
protected lemma neg_comp {n₁ n₂ n₁₂ : ℤ} (z₁ : Cochain F G n₁) (z₂ : Cochain G K n₂)
(h : n₁ + n₂ = n₁₂) : (-z₁).comp z₂ h = -z₁.comp z₂ h := by
ext p q hpq
simp only [comp_v _ _ h p _ q rfl (by omega), neg_v, neg_comp]
@[simp]
protected lemma smul_comp {n₁ n₂ n₁₂ : ℤ} (k : R) (z₁ : Cochain F G n₁) (z₂ : Cochain G K n₂)
(h : n₁ + n₂ = n₁₂) : (k • z₁).comp z₂ h = k • (z₁.comp z₂ h) := by
ext p q hpq
simp only [comp_v _ _ h p _ q rfl (by omega), smul_v, Linear.smul_comp]
@[simp]
lemma units_smul_comp {n₁ n₂ n₁₂ : ℤ} (k : Rˣ) (z₁ : Cochain F G n₁) (z₂ : Cochain G K n₂)
(h : n₁ + n₂ = n₁₂) : (k • z₁).comp z₂ h = k • (z₁.comp z₂ h) := by
apply Cochain.smul_comp
@[simp]
protected lemma id_comp {n : ℤ} (z₂ : Cochain F G n) :
(Cochain.ofHom (𝟙 F)).comp z₂ (zero_add n) = z₂ := by
ext p q hpq
simp only [zero_cochain_comp_v, ofHom_v, HomologicalComplex.id_f, id_comp]
@[simp]
protected lemma comp_zero {n₁ n₂ n₁₂ : ℤ} (z₁ : Cochain F G n₁)
(h : n₁ + n₂ = n₁₂) : z₁.comp (0 : Cochain G K n₂) h = 0 := by
ext p q hpq
simp only [comp_v _ _ h p _ q rfl (by omega), zero_v, comp_zero]
@[simp]
protected lemma comp_add {n₁ n₂ n₁₂ : ℤ} (z₁ : Cochain F G n₁) (z₂ z₂' : Cochain G K n₂)
(h : n₁ + n₂ = n₁₂) : z₁.comp (z₂ + z₂') h = z₁.comp z₂ h + z₁.comp z₂' h := by
ext p q hpq
simp only [comp_v _ _ h p _ q rfl (by omega), add_v, comp_add]
@[simp]
protected lemma comp_sub {n₁ n₂ n₁₂ : ℤ} (z₁ : Cochain F G n₁) (z₂ z₂' : Cochain G K n₂)
(h : n₁ + n₂ = n₁₂) : z₁.comp (z₂ - z₂') h = z₁.comp z₂ h - z₁.comp z₂' h := by
ext p q hpq
simp only [comp_v _ _ h p _ q rfl (by omega), sub_v, comp_sub]
@[simp]
protected lemma comp_neg {n₁ n₂ n₁₂ : ℤ} (z₁ : Cochain F G n₁) (z₂ : Cochain G K n₂)
(h : n₁ + n₂ = n₁₂) : z₁.comp (-z₂) h = -z₁.comp z₂ h := by
ext p q hpq
simp only [comp_v _ _ h p _ q rfl (by omega), neg_v, comp_neg]
@[simp]
protected lemma comp_smul {n₁ n₂ n₁₂ : ℤ} (z₁ : Cochain F G n₁) (k : R) (z₂ : Cochain G K n₂)
(h : n₁ + n₂ = n₁₂ ) : z₁.comp (k • z₂) h = k • (z₁.comp z₂ h) := by
ext p q hpq
simp only [comp_v _ _ h p _ q rfl (by omega), smul_v, Linear.comp_smul]
@[simp]
lemma comp_units_smul {n₁ n₂ n₁₂ : ℤ} (z₁ : Cochain F G n₁) (k : Rˣ) (z₂ : Cochain G K n₂)
(h : n₁ + n₂ = n₁₂ ) : z₁.comp (k • z₂) h = k • (z₁.comp z₂ h) := by
apply Cochain.comp_smul
@[simp]
protected lemma comp_id {n : ℤ} (z₁ : Cochain F G n) :
z₁.comp (Cochain.ofHom (𝟙 G)) (add_zero n) = z₁ := by
ext p q hpq
simp only [comp_zero_cochain_v, ofHom_v, HomologicalComplex.id_f, comp_id]
@[simp]
lemma ofHoms_comp (φ : ∀ (p : ℤ), F.X p ⟶ G.X p) (ψ : ∀ (p : ℤ), G.X p ⟶ K.X p) :
(ofHoms φ).comp (ofHoms ψ) (zero_add 0) = ofHoms (fun p => φ p ≫ ψ p) := by aesop_cat
@[simp]
lemma ofHom_comp (f : F ⟶ G) (g : G ⟶ K) :
ofHom (f ≫ g) = (ofHom f).comp (ofHom g) (zero_add 0) := by
simp only [ofHom, HomologicalComplex.comp_f, ofHoms_comp]
variable (K)
/-- The differential on a cochain complex, as a cochain of degree `1`. -/
def diff : Cochain K K 1 := Cochain.mk (fun p q _ => K.d p q)
@[simp]
lemma diff_v (p q : ℤ) (hpq : p + 1 = q) : (diff K).v p q hpq = K.d p q := rfl
end Cochain
variable {F G}
/-- The differential on the complex of morphisms between cochain complexes. -/
def δ (z : Cochain F G n) : Cochain F G m :=
Cochain.mk (fun p q hpq => z.v p (p + n) rfl ≫ G.d (p + n) q +
m.negOnePow • F.d p (p + m - n) ≫ z.v (p + m - n) q (by rw [hpq, sub_add_cancel]))
/-! Similarly as for the composition of cochains, if `z : Cochain F G n`,
we usually need to carefully select intermediate indices with
good definitional properties in order to obtain a suitable expansion of the
morphisms which constitute `δ n m z : Cochain F G m` (when `n + 1 = m`, otherwise
it shall be zero). The basic equational lemma is `δ_v` below. -/
lemma δ_v (hnm : n + 1 = m) (z : Cochain F G n) (p q : ℤ) (hpq : p + m = q) (q₁ q₂ : ℤ)
(hq₁ : q₁ = q - 1) (hq₂ : p + 1 = q₂) : (δ n m z).v p q hpq =
z.v p q₁ (by rw [hq₁, ← hpq, ← hnm, ← add_assoc, add_sub_cancel_right]) ≫ G.d q₁ q
+ m.negOnePow • F.d p q₂ ≫ z.v q₂ q
(by rw [← hq₂, add_assoc, add_comm 1, hnm, hpq]) := by
obtain rfl : q₁ = p + n := by omega
obtain rfl : q₂ = p + m - n := by omega
rfl
lemma δ_shape (hnm : ¬ n + 1 = m) (z : Cochain F G n) : δ n m z = 0 := by
ext p q hpq
dsimp only [δ]
rw [Cochain.mk_v, Cochain.zero_v, F.shape, G.shape, comp_zero, zero_add, zero_comp, smul_zero]
all_goals
simp only [ComplexShape.up_Rel]
exact fun _ => hnm (by omega)
variable (F G) (R)
/-- The differential on the complex of morphisms between cochain complexes, as a linear map. -/
@[simps!]
def δ_hom : Cochain F G n →ₗ[R] Cochain F G m where
toFun := δ n m
map_add' α β := by
by_cases h : n + 1 = m
· ext p q hpq
dsimp
simp only [δ_v n m h _ p q hpq _ _ rfl rfl, Cochain.add_v, add_comp, comp_add, smul_add]
abel
· simp only [δ_shape _ _ h, add_zero]
map_smul' r a := by
by_cases h : n + 1 = m
· ext p q hpq
dsimp
simp only [δ_v n m h _ p q hpq _ _ rfl rfl, Cochain.smul_v, Linear.comp_smul,
Linear.smul_comp, smul_add, add_right_inj, smul_comm m.negOnePow r]
· simp only [δ_shape _ _ h, smul_zero]
variable {F G R}
@[simp] lemma δ_add (z₁ z₂ : Cochain F G n) : δ n m (z₁ + z₂) = δ n m z₁ + δ n m z₂ :=
(δ_hom ℤ F G n m).map_add z₁ z₂
@[simp] lemma δ_sub (z₁ z₂ : Cochain F G n) : δ n m (z₁ - z₂) = δ n m z₁ - δ n m z₂ :=
(δ_hom ℤ F G n m).map_sub z₁ z₂
@[simp] lemma δ_zero : δ n m (0 : Cochain F G n) = 0 := (δ_hom ℤ F G n m).map_zero
@[simp] lemma δ_neg (z : Cochain F G n) : δ n m (-z) = - δ n m z :=
(δ_hom ℤ F G n m).map_neg z
@[simp] lemma δ_smul (k : R) (z : Cochain F G n) : δ n m (k • z) = k • δ n m z :=
(δ_hom R F G n m).map_smul k z
@[simp] lemma δ_units_smul (k : Rˣ) (z : Cochain F G n) : δ n m (k • z) = k • δ n m z :=
δ_smul ..
lemma δ_δ (n₀ n₁ n₂ : ℤ) (z : Cochain F G n₀) : δ n₁ n₂ (δ n₀ n₁ z) = 0 := by
by_cases h₁₂ : n₁ + 1 = n₂; swap
· rw [δ_shape _ _ h₁₂]
by_cases h₀₁ : n₀ + 1 = n₁; swap
· rw [δ_shape _ _ h₀₁, δ_zero]
ext p q hpq
dsimp
simp only [δ_v n₁ n₂ h₁₂ _ p q hpq _ _ rfl rfl,
δ_v n₀ n₁ h₀₁ z p (q-1) (by omega) (q-2) _ (by omega) rfl,
δ_v n₀ n₁ h₀₁ z (p+1) q (by omega) _ (p+2) rfl (by omega),
← h₁₂, Int.negOnePow_succ, add_comp, assoc,
HomologicalComplex.d_comp_d, comp_zero, zero_add, comp_add,
HomologicalComplex.d_comp_d_assoc, zero_comp, smul_zero,
add_zero, add_neg_cancel, Units.neg_smul,
Linear.units_smul_comp, Linear.comp_units_smul]
lemma δ_comp {n₁ n₂ n₁₂ : ℤ} (z₁ : Cochain F G n₁) (z₂ : Cochain G K n₂) (h : n₁ + n₂ = n₁₂)
(m₁ m₂ m₁₂ : ℤ) (h₁₂ : n₁₂ + 1 = m₁₂) (h₁ : n₁ + 1 = m₁) (h₂ : n₂ + 1 = m₂) :
δ n₁₂ m₁₂ (z₁.comp z₂ h) = z₁.comp (δ n₂ m₂ z₂) (by rw [← h₁₂, ← h₂, ← h, add_assoc]) +
n₂.negOnePow • (δ n₁ m₁ z₁).comp z₂
(by rw [← h₁₂, ← h₁, ← h, add_assoc, add_comm 1, add_assoc]) := by
subst h₁₂ h₁ h₂ h
ext p q hpq
dsimp
rw [z₁.comp_v _ (add_assoc n₁ n₂ 1).symm p _ q rfl (by omega),
Cochain.comp_v _ _ (show n₁ + 1 + n₂ = n₁ + n₂ + 1 by omega) p (p+n₁+1) q
(by omega) (by omega),
δ_v (n₁ + n₂) _ rfl (z₁.comp z₂ rfl) p q hpq (p + n₁ + n₂) _ (by omega) rfl,
z₁.comp_v z₂ rfl p _ _ rfl rfl,
z₁.comp_v z₂ rfl (p+1) (p+n₁+1) q (by omega) (by omega),
δ_v n₂ (n₂+1) rfl z₂ (p+n₁) q (by omega) (p+n₁+n₂) _ (by omega) rfl,
δ_v n₁ (n₁+1) rfl z₁ p (p+n₁+1) (by omega) (p+n₁) _ (by omega) rfl]
simp only [assoc, comp_add, add_comp, Int.negOnePow_succ, Int.negOnePow_add n₁ n₂,
Units.neg_smul, comp_neg, neg_comp, smul_neg, smul_smul, Linear.units_smul_comp,
mul_comm n₁.negOnePow n₂.negOnePow, Linear.comp_units_smul, smul_add]
abel
lemma δ_zero_cochain_comp {n₂ : ℤ} (z₁ : Cochain F G 0) (z₂ : Cochain G K n₂)
(m₂ : ℤ) (h₂ : n₂ + 1 = m₂) :
δ n₂ m₂ (z₁.comp z₂ (zero_add n₂)) =
z₁.comp (δ n₂ m₂ z₂) (zero_add m₂) +
n₂.negOnePow • ((δ 0 1 z₁).comp z₂ (by rw [add_comm, h₂])) :=
δ_comp z₁ z₂ (zero_add n₂) 1 m₂ m₂ h₂ (zero_add 1) h₂
lemma δ_comp_zero_cochain {n₁ : ℤ} (z₁ : Cochain F G n₁) (z₂ : Cochain G K 0)
(m₁ : ℤ) (h₁ : n₁ + 1 = m₁) :
δ n₁ m₁ (z₁.comp z₂ (add_zero n₁)) =
z₁.comp (δ 0 1 z₂) h₁ + (δ n₁ m₁ z₁).comp z₂ (add_zero m₁) := by
simp only [δ_comp z₁ z₂ (add_zero n₁) m₁ 1 m₁ h₁ h₁ (zero_add 1), one_smul,
Int.negOnePow_zero]
@[simp]
lemma δ_zero_cochain_v (z : Cochain F G 0) (p q : ℤ) (hpq : p + 1 = q) :
(δ 0 1 z).v p q hpq = z.v p p (add_zero p) ≫ G.d p q - F.d p q ≫ z.v q q (add_zero q) := by
simp only [δ_v 0 1 (zero_add 1) z p q hpq p q (by omega) hpq, zero_add,
Int.negOnePow_one, Units.neg_smul, one_smul, sub_eq_add_neg]
@[simp]
lemma δ_ofHom {p : ℤ} (φ : F ⟶ G) : δ 0 p (Cochain.ofHom φ) = 0 := by
by_cases h : p = 1
· subst h
ext
simp
· rw [δ_shape]
omega
@[simp]
lemma δ_ofHomotopy {φ₁ φ₂ : F ⟶ G} (h : Homotopy φ₁ φ₂) :
δ (-1) 0 (Cochain.ofHomotopy h) = Cochain.ofHom φ₁ - Cochain.ofHom φ₂ := by
ext p
have eq := h.comm p
rw [dNext_eq h.hom (show (ComplexShape.up ℤ).Rel p (p+1) by simp),
prevD_eq h.hom (show (ComplexShape.up ℤ).Rel (p-1) p by simp)] at eq
rw [Cochain.ofHomotopy, δ_v (-1) 0 (neg_add_cancel 1) _ p p (add_zero p) (p-1) (p+1) rfl rfl]
simp only [Cochain.mk_v, neg_add_cancel, one_smul, Int.negOnePow_zero,
Cochain.sub_v, Cochain.ofHom_v, eq]
abel
lemma δ_neg_one_cochain (z : Cochain F G (-1)) :
δ (-1) 0 z = Cochain.ofHom (Homotopy.nullHomotopicMap'
(fun i j hij => z.v i j (by dsimp at hij; rw [← hij, add_neg_cancel_right]))) := by
ext p
rw [δ_v (-1) 0 (neg_add_cancel 1) _ p p (add_zero p) (p-1) (p+1) rfl rfl]
simp only [neg_add_cancel, one_smul, Cochain.ofHom_v, Int.negOnePow_zero]
rw [Homotopy.nullHomotopicMap'_f (show (ComplexShape.up ℤ).Rel (p-1) p by simp)
(show (ComplexShape.up ℤ).Rel p (p+1) by simp)]
abel
end HomComplex
variable (F G)
open HomComplex
/-- The cochain complex of homomorphisms between two cochain complexes `F` and `G`.
In degree `n : ℤ`, it consists of the abelian group `HomComplex.Cochain F G n`. -/
@[simps! X d_hom_apply]
def HomComplex : CochainComplex AddCommGrp ℤ where
X i := AddCommGrp.of (Cochain F G i)
d i j := AddCommGrp.ofHom (δ_hom ℤ F G i j)
shape _ _ hij := by ext; simp [δ_shape _ _ hij]
d_comp_d' _ _ _ _ _ := by ext; simp [δ_δ]
namespace HomComplex
/-- The subgroup of cocycles in `Cochain F G n`. -/
def cocycle : AddSubgroup (Cochain F G n) :=
AddMonoidHom.ker (δ_hom ℤ F G n (n + 1)).toAddMonoidHom
/-- The type of `n`-cocycles, as a subtype of `Cochain F G n`. -/
def Cocycle : Type v := cocycle F G n
instance : AddCommGroup (Cocycle F G n) := by
dsimp only [Cocycle]
infer_instance
namespace Cocycle
variable {F G}
lemma mem_iff (hnm : n + 1 = m) (z : Cochain F G n) :
z ∈ cocycle F G n ↔ δ n m z = 0 := by subst hnm; rfl
variable {n}
instance : Coe (Cocycle F G n) (Cochain F G n) where
coe x := x.1
@[ext]
lemma ext (z₁ z₂ : Cocycle F G n) (h : (z₁ : Cochain F G n) = z₂) : z₁ = z₂ :=
Subtype.ext h
instance : SMul R (Cocycle F G n) where
smul r z := ⟨r • z.1, by
have hz := z.2
rw [mem_iff n (n + 1) rfl] at hz ⊢
simp only [δ_smul, hz, smul_zero]⟩
variable (F G n)
@[simp]
lemma coe_zero : (↑(0 : Cocycle F G n) : Cochain F G n) = 0 := by rfl
variable {F G n}
@[simp]
lemma coe_add (z₁ z₂ : Cocycle F G n) :
(↑(z₁ + z₂) : Cochain F G n) = (z₁ : Cochain F G n) + (z₂ : Cochain F G n) := rfl
@[simp]
lemma coe_neg (z : Cocycle F G n) :
(↑(-z) : Cochain F G n) = -(z : Cochain F G n) := rfl
@[simp]
lemma coe_smul (z : Cocycle F G n) (x : R) :
(↑(x • z) : Cochain F G n) = x • (z : Cochain F G n) := rfl
@[simp]
lemma coe_units_smul (z : Cocycle F G n) (x : Rˣ) :
(↑(x • z) : Cochain F G n) = x • (z : Cochain F G n) := rfl
@[simp]
lemma coe_sub (z₁ z₂ : Cocycle F G n) :
(↑(z₁ - z₂) : Cochain F G n) = (z₁ : Cochain F G n) - (z₂ : Cochain F G n) := rfl
instance : Module R (Cocycle F G n) where
one_smul _ := by aesop
mul_smul _ _ _ := by ext; dsimp; rw [smul_smul]
smul_zero _ := by aesop
smul_add _ _ _ := by aesop
add_smul _ _ _ := by ext; dsimp; rw [add_smul]
zero_smul := by aesop
/-- Constructor for `Cocycle F G n`, taking as inputs `z : Cochain F G n`, an integer
`m : ℤ` such that `n + 1 = m`, and the relation `δ n m z = 0`. -/
@[simps]
def mk (z : Cochain F G n) (m : ℤ) (hnm : n + 1 = m) (h : δ n m z = 0) : Cocycle F G n :=
⟨z, by simpa only [mem_iff n m hnm z] using h⟩
@[simp]
lemma δ_eq_zero {n : ℤ} (z : Cocycle F G n) (m : ℤ) : δ n m (z : Cochain F G n) = 0 := by
by_cases h : n + 1 = m
· rw [← mem_iff n m h]
exact z.2
· exact δ_shape n m h _
/-- The `0`-cocycle associated to a morphism in `CochainComplex C ℤ`. -/
@[simps!]
def ofHom (φ : F ⟶ G) : Cocycle F G 0 := mk (Cochain.ofHom φ) 1 (zero_add 1) (by simp)
/-- The morphism in `CochainComplex C ℤ` associated to a `0`-cocycle. -/
@[simps]
def homOf (z : Cocycle F G 0) : F ⟶ G where
f i := (z : Cochain _ _ _).v i i (add_zero i)
comm' := by
rintro i j rfl
rcases z with ⟨z, hz⟩
dsimp
rw [mem_iff 0 1 (zero_add 1)] at hz
simpa only [δ_zero_cochain_v, Cochain.zero_v, sub_eq_zero]
using Cochain.congr_v hz i (i + 1) rfl
@[simp]
lemma homOf_ofHom_eq_self (φ : F ⟶ G) : homOf (ofHom φ) = φ := by aesop_cat
@[simp]
lemma ofHom_homOf_eq_self (z : Cocycle F G 0) : ofHom (homOf z) = z := by aesop_cat
@[simp]
lemma cochain_ofHom_homOf_eq_coe (z : Cocycle F G 0) :
Cochain.ofHom (homOf z) = (z : Cochain F G 0) := by
simpa only [Cocycle.ext_iff] using ofHom_homOf_eq_self z
variable (F G)
/-- The additive equivalence between morphisms in `CochainComplex C ℤ` and `0`-cocycles. -/
@[simps]
def equivHom : (F ⟶ G) ≃+ Cocycle F G 0 where
toFun := ofHom
invFun := homOf
left_inv := homOf_ofHom_eq_self
right_inv := ofHom_homOf_eq_self
map_add' := by aesop_cat
variable (K)
/-- The `1`-cocycle given by the differential on a cochain complex. -/
@[simps!]
def diff : Cocycle K K 1 :=
Cocycle.mk (Cochain.diff K) 2 rfl (by
ext p q hpq
simp only [Cochain.zero_v, δ_v 1 2 rfl _ p q hpq _ _ rfl rfl, Cochain.diff_v,
HomologicalComplex.d_comp_d, smul_zero, add_zero])
end Cocycle
variable {F G}
@[simp]
lemma δ_comp_zero_cocycle {n : ℤ} (z₁ : Cochain F G n) (z₂ : Cocycle G K 0) (m : ℤ) :
δ n m (z₁.comp z₂.1 (add_zero n)) =
(δ n m z₁).comp z₂.1 (add_zero m) := by
by_cases hnm : n + 1 = m
· simp [δ_comp_zero_cochain _ _ _ hnm]
· simp [δ_shape _ _ hnm]
@[simp]
lemma δ_comp_ofHom {n : ℤ} (z₁ : Cochain F G n) (f : G ⟶ K) (m : ℤ) :
δ n m (z₁.comp (Cochain.ofHom f) (add_zero n)) =
(δ n m z₁).comp (Cochain.ofHom f) (add_zero m) := by
rw [← Cocycle.ofHom_coe, δ_comp_zero_cocycle]
@[simp]
lemma δ_zero_cocycle_comp {n : ℤ} (z₁ : Cocycle F G 0) (z₂ : Cochain G K n) (m : ℤ) :
δ n m (z₁.1.comp z₂ (zero_add n)) =
z₁.1.comp (δ n m z₂) (zero_add m) := by
by_cases hnm : n + 1 = m
· simp [δ_zero_cochain_comp _ _ _ hnm]
· simp [δ_shape _ _ hnm]
@[simp]
lemma δ_ofHom_comp {n : ℤ} (f : F ⟶ G) (z : Cochain G K n) (m : ℤ) :
δ n m ((Cochain.ofHom f).comp z (zero_add n)) =
(Cochain.ofHom f).comp (δ n m z) (zero_add m) := by
rw [← Cocycle.ofHom_coe, δ_zero_cocycle_comp]
namespace Cochain
| /-- Given two morphisms of complexes `φ₁ φ₂ : F ⟶ G`, the datum of an homotopy between `φ₁` and
`φ₂` is equivalent to the datum of a `1`-cochain `z` such that `δ (-1) 0 z` is the difference
of the zero cochains associated to `φ₂` and `φ₁`. -/
@[simps]
def equivHomotopy (φ₁ φ₂ : F ⟶ G) :
| Mathlib/Algebra/Homology/HomotopyCategory/HomComplex.lean | 739 | 743 |
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Frédéric Dupuis, Heather Macbeth
-/
import Mathlib.Analysis.Convex.Basic
import Mathlib.Analysis.InnerProductSpace.Orthogonal
import Mathlib.Analysis.InnerProductSpace.Symmetric
import Mathlib.Analysis.NormedSpace.RCLike
import Mathlib.Analysis.RCLike.Lemmas
import Mathlib.Algebra.DirectSum.Decomposition
/-!
# The orthogonal projection
Given a nonempty complete subspace `K` of an inner product space `E`, this file constructs
`K.orthogonalProjection : E →L[𝕜] K`, the orthogonal projection of `E` onto `K`. This map
satisfies: for any point `u` in `E`, the point `v = K.orthogonalProjection u` in `K` minimizes the
distance `‖u - v‖` to `u`.
Also a linear isometry equivalence `K.reflection : E ≃ₗᵢ[𝕜] E` is constructed, by choosing, for
each `u : E`, the point `K.reflection u` to satisfy
`u + (K.reflection u) = 2 • K.orthogonalProjection u`.
Basic API for `orthogonalProjection` and `reflection` is developed.
Next, the orthogonal projection is used to prove a series of more subtle lemmas about the
orthogonal complement of complete subspaces of `E` (the orthogonal complement itself was
defined in `Analysis.InnerProductSpace.Orthogonal`); the lemma
`Submodule.sup_orthogonal_of_completeSpace`, stating that for a complete subspace `K` of `E` we have
`K ⊔ Kᗮ = ⊤`, is a typical example.
## References
The orthogonal projection construction is adapted from
* [Clément & Martin, *The Lax-Milgram Theorem. A detailed proof to be formalized in Coq*]
* [Clément & Martin, *A Coq formal proof of the Lax–Milgram theorem*]
The Coq code is available at the following address: <http://www.lri.fr/~sboldo/elfic/index.html>
-/
noncomputable section
open InnerProductSpace
open RCLike Real Filter
open LinearMap (ker range)
open Topology Finsupp
variable {𝕜 E F : Type*} [RCLike 𝕜]
variable [NormedAddCommGroup E] [NormedAddCommGroup F]
variable [InnerProductSpace 𝕜 E] [InnerProductSpace ℝ F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
local notation "absR" => abs
/-! ### Orthogonal projection in inner product spaces -/
-- FIXME this monolithic proof causes a deterministic timeout with `-T50000`
-- It should be broken in a sequence of more manageable pieces,
-- perhaps with individual statements for the three steps below.
/-- **Existence of minimizers**, aka the **Hilbert projection theorem**.
Let `u` be a point in a real inner product space, and let `K` be a nonempty complete convex subset.
Then there exists a (unique) `v` in `K` that minimizes the distance `‖u - v‖` to `u`. -/
theorem exists_norm_eq_iInf_of_complete_convex {K : Set F} (ne : K.Nonempty) (h₁ : IsComplete K)
(h₂ : Convex ℝ K) : ∀ u : F, ∃ v ∈ K, ‖u - v‖ = ⨅ w : K, ‖u - w‖ := fun u => by
let δ := ⨅ w : K, ‖u - w‖
letI : Nonempty K := ne.to_subtype
have zero_le_δ : 0 ≤ δ := le_ciInf fun _ => norm_nonneg _
have δ_le : ∀ w : K, δ ≤ ‖u - w‖ := ciInf_le ⟨0, Set.forall_mem_range.2 fun _ => norm_nonneg _⟩
have δ_le' : ∀ w ∈ K, δ ≤ ‖u - w‖ := fun w hw => δ_le ⟨w, hw⟩
-- Step 1: since `δ` is the infimum, can find a sequence `w : ℕ → K` in `K`
-- such that `‖u - w n‖ < δ + 1 / (n + 1)` (which implies `‖u - w n‖ --> δ`);
-- maybe this should be a separate lemma
have exists_seq : ∃ w : ℕ → K, ∀ n, ‖u - w n‖ < δ + 1 / (n + 1) := by
have hδ : ∀ n : ℕ, δ < δ + 1 / (n + 1) := fun n =>
lt_add_of_le_of_pos le_rfl Nat.one_div_pos_of_nat
have h := fun n => exists_lt_of_ciInf_lt (hδ n)
let w : ℕ → K := fun n => Classical.choose (h n)
exact ⟨w, fun n => Classical.choose_spec (h n)⟩
rcases exists_seq with ⟨w, hw⟩
have norm_tendsto : Tendsto (fun n => ‖u - w n‖) atTop (𝓝 δ) := by
have h : Tendsto (fun _ : ℕ => δ) atTop (𝓝 δ) := tendsto_const_nhds
have h' : Tendsto (fun n : ℕ => δ + 1 / (n + 1)) atTop (𝓝 δ) := by
convert h.add tendsto_one_div_add_atTop_nhds_zero_nat
simp only [add_zero]
exact tendsto_of_tendsto_of_tendsto_of_le_of_le h h' (fun x => δ_le _) fun x => le_of_lt (hw _)
-- Step 2: Prove that the sequence `w : ℕ → K` is a Cauchy sequence
have seq_is_cauchy : CauchySeq fun n => (w n : F) := by
rw [cauchySeq_iff_le_tendsto_0]
-- splits into three goals
let b := fun n : ℕ => 8 * δ * (1 / (n + 1)) + 4 * (1 / (n + 1)) * (1 / (n + 1))
use fun n => √(b n)
constructor
-- first goal : `∀ (n : ℕ), 0 ≤ √(b n)`
· intro n
exact sqrt_nonneg _
constructor
-- second goal : `∀ (n m N : ℕ), N ≤ n → N ≤ m → dist ↑(w n) ↑(w m) ≤ √(b N)`
· intro p q N hp hq
let wp := (w p : F)
let wq := (w q : F)
let a := u - wq
let b := u - wp
let half := 1 / (2 : ℝ)
let div := 1 / ((N : ℝ) + 1)
have :
4 * ‖u - half • (wq + wp)‖ * ‖u - half • (wq + wp)‖ + ‖wp - wq‖ * ‖wp - wq‖ =
2 * (‖a‖ * ‖a‖ + ‖b‖ * ‖b‖) :=
calc
4 * ‖u - half • (wq + wp)‖ * ‖u - half • (wq + wp)‖ + ‖wp - wq‖ * ‖wp - wq‖ =
2 * ‖u - half • (wq + wp)‖ * (2 * ‖u - half • (wq + wp)‖) + ‖wp - wq‖ * ‖wp - wq‖ :=
by ring
_ =
absR (2 : ℝ) * ‖u - half • (wq + wp)‖ * (absR (2 : ℝ) * ‖u - half • (wq + wp)‖) +
‖wp - wq‖ * ‖wp - wq‖ := by
rw [abs_of_nonneg]
exact zero_le_two
_ =
‖(2 : ℝ) • (u - half • (wq + wp))‖ * ‖(2 : ℝ) • (u - half • (wq + wp))‖ +
‖wp - wq‖ * ‖wp - wq‖ := by simp [norm_smul]
_ = ‖a + b‖ * ‖a + b‖ + ‖a - b‖ * ‖a - b‖ := by
rw [smul_sub, smul_smul, mul_one_div_cancel (_root_.two_ne_zero : (2 : ℝ) ≠ 0), ←
one_add_one_eq_two, add_smul]
simp only [one_smul]
have eq₁ : wp - wq = a - b := (sub_sub_sub_cancel_left _ _ _).symm
have eq₂ : u + u - (wq + wp) = a + b := by
show u + u - (wq + wp) = u - wq + (u - wp)
abel
rw [eq₁, eq₂]
_ = 2 * (‖a‖ * ‖a‖ + ‖b‖ * ‖b‖) := parallelogram_law_with_norm ℝ _ _
have eq : δ ≤ ‖u - half • (wq + wp)‖ := by
rw [smul_add]
apply δ_le'
apply h₂
repeat' exact Subtype.mem _
repeat' exact le_of_lt one_half_pos
exact add_halves 1
have eq₁ : 4 * δ * δ ≤ 4 * ‖u - half • (wq + wp)‖ * ‖u - half • (wq + wp)‖ := by
simp_rw [mul_assoc]
gcongr
have eq₂ : ‖a‖ ≤ δ + div :=
le_trans (le_of_lt <| hw q) (add_le_add_left (Nat.one_div_le_one_div hq) _)
have eq₂' : ‖b‖ ≤ δ + div :=
le_trans (le_of_lt <| hw p) (add_le_add_left (Nat.one_div_le_one_div hp) _)
rw [dist_eq_norm]
apply nonneg_le_nonneg_of_sq_le_sq
· exact sqrt_nonneg _
rw [mul_self_sqrt]
· calc
‖wp - wq‖ * ‖wp - wq‖ =
2 * (‖a‖ * ‖a‖ + ‖b‖ * ‖b‖) - 4 * ‖u - half • (wq + wp)‖ * ‖u - half • (wq + wp)‖ := by
simp [← this]
_ ≤ 2 * (‖a‖ * ‖a‖ + ‖b‖ * ‖b‖) - 4 * δ * δ := by gcongr
_ ≤ 2 * ((δ + div) * (δ + div) + (δ + div) * (δ + div)) - 4 * δ * δ := by gcongr
_ = 8 * δ * div + 4 * div * div := by ring
positivity
-- third goal : `Tendsto (fun (n : ℕ) => √(b n)) atTop (𝓝 0)`
suffices Tendsto (fun x ↦ √(8 * δ * x + 4 * x * x) : ℝ → ℝ) (𝓝 0) (𝓝 0)
from this.comp tendsto_one_div_add_atTop_nhds_zero_nat
exact Continuous.tendsto' (by fun_prop) _ _ (by simp)
-- Step 3: By completeness of `K`, let `w : ℕ → K` converge to some `v : K`.
-- Prove that it satisfies all requirements.
rcases cauchySeq_tendsto_of_isComplete h₁ (fun n => Subtype.mem _) seq_is_cauchy with
⟨v, hv, w_tendsto⟩
use v
use hv
have h_cont : Continuous fun v => ‖u - v‖ :=
Continuous.comp continuous_norm (Continuous.sub continuous_const continuous_id)
have : Tendsto (fun n => ‖u - w n‖) atTop (𝓝 ‖u - v‖) := by
convert Tendsto.comp h_cont.continuousAt w_tendsto
exact tendsto_nhds_unique this norm_tendsto
/-- Characterization of minimizers for the projection on a convex set in a real inner product
space. -/
theorem norm_eq_iInf_iff_real_inner_le_zero {K : Set F} (h : Convex ℝ K) {u : F} {v : F}
(hv : v ∈ K) : (‖u - v‖ = ⨅ w : K, ‖u - w‖) ↔ ∀ w ∈ K, ⟪u - v, w - v⟫_ℝ ≤ 0 := by
letI : Nonempty K := ⟨⟨v, hv⟩⟩
constructor
· intro eq w hw
let δ := ⨅ w : K, ‖u - w‖
let p := ⟪u - v, w - v⟫_ℝ
let q := ‖w - v‖ ^ 2
have δ_le (w : K) : δ ≤ ‖u - w‖ := ciInf_le ⟨0, fun _ ⟨_, h⟩ => h ▸ norm_nonneg _⟩ _
have δ_le' (w) (hw : w ∈ K) : δ ≤ ‖u - w‖ := δ_le ⟨w, hw⟩
have (θ : ℝ) (hθ₁ : 0 < θ) (hθ₂ : θ ≤ 1) : 2 * p ≤ θ * q := by
have : ‖u - v‖ ^ 2 ≤ ‖u - v‖ ^ 2 - 2 * θ * ⟪u - v, w - v⟫_ℝ + θ * θ * ‖w - v‖ ^ 2 :=
calc ‖u - v‖ ^ 2
_ ≤ ‖u - (θ • w + (1 - θ) • v)‖ ^ 2 := by
simp only [sq]; apply mul_self_le_mul_self (norm_nonneg _)
rw [eq]; apply δ_le'
apply h hw hv
exacts [le_of_lt hθ₁, sub_nonneg.2 hθ₂, add_sub_cancel _ _]
_ = ‖u - v - θ • (w - v)‖ ^ 2 := by
have : u - (θ • w + (1 - θ) • v) = u - v - θ • (w - v) := by
rw [smul_sub, sub_smul, one_smul]
simp only [sub_eq_add_neg, add_comm, add_left_comm, add_assoc, neg_add_rev]
rw [this]
_ = ‖u - v‖ ^ 2 - 2 * θ * inner (u - v) (w - v) + θ * θ * ‖w - v‖ ^ 2 := by
rw [@norm_sub_sq ℝ, inner_smul_right, norm_smul]
simp only [sq]
show
‖u - v‖ * ‖u - v‖ - 2 * (θ * inner (u - v) (w - v)) +
absR θ * ‖w - v‖ * (absR θ * ‖w - v‖) =
‖u - v‖ * ‖u - v‖ - 2 * θ * inner (u - v) (w - v) + θ * θ * (‖w - v‖ * ‖w - v‖)
rw [abs_of_pos hθ₁]; ring
have eq₁ :
‖u - v‖ ^ 2 - 2 * θ * inner (u - v) (w - v) + θ * θ * ‖w - v‖ ^ 2 =
‖u - v‖ ^ 2 + (θ * θ * ‖w - v‖ ^ 2 - 2 * θ * inner (u - v) (w - v)) := by
abel
rw [eq₁, le_add_iff_nonneg_right] at this
have eq₂ :
θ * θ * ‖w - v‖ ^ 2 - 2 * θ * inner (u - v) (w - v) =
θ * (θ * ‖w - v‖ ^ 2 - 2 * inner (u - v) (w - v)) := by ring
rw [eq₂] at this
exact le_of_sub_nonneg (nonneg_of_mul_nonneg_right this hθ₁)
by_cases hq : q = 0
· rw [hq] at this
have : p ≤ 0 := by
have := this (1 : ℝ) (by norm_num) (by norm_num)
linarith
exact this
· have q_pos : 0 < q := lt_of_le_of_ne (sq_nonneg _) fun h ↦ hq h.symm
by_contra hp
rw [not_le] at hp
let θ := min (1 : ℝ) (p / q)
have eq₁ : θ * q ≤ p :=
calc
θ * q ≤ p / q * q := mul_le_mul_of_nonneg_right (min_le_right _ _) (sq_nonneg _)
_ = p := div_mul_cancel₀ _ hq
have : 2 * p ≤ p :=
calc
2 * p ≤ θ * q := by
exact this θ (lt_min (by norm_num) (div_pos hp q_pos)) (by norm_num [θ])
_ ≤ p := eq₁
linarith
· intro h
apply le_antisymm
· apply le_ciInf
intro w
apply nonneg_le_nonneg_of_sq_le_sq (norm_nonneg _)
have := h w w.2
calc
‖u - v‖ * ‖u - v‖ ≤ ‖u - v‖ * ‖u - v‖ - 2 * inner (u - v) ((w : F) - v) := by linarith
_ ≤ ‖u - v‖ ^ 2 - 2 * inner (u - v) ((w : F) - v) + ‖(w : F) - v‖ ^ 2 := by
rw [sq]
refine le_add_of_nonneg_right ?_
exact sq_nonneg _
_ = ‖u - v - (w - v)‖ ^ 2 := (@norm_sub_sq ℝ _ _ _ _ _ _).symm
_ = ‖u - w‖ * ‖u - w‖ := by
have : u - v - (w - v) = u - w := by abel
rw [this, sq]
· show ⨅ w : K, ‖u - w‖ ≤ (fun w : K => ‖u - w‖) ⟨v, hv⟩
apply ciInf_le
use 0
rintro y ⟨z, rfl⟩
exact norm_nonneg _
variable (K : Submodule 𝕜 E)
namespace Submodule
/-- Existence of projections on complete subspaces.
Let `u` be a point in an inner product space, and let `K` be a nonempty complete subspace.
Then there exists a (unique) `v` in `K` that minimizes the distance `‖u - v‖` to `u`.
This point `v` is usually called the orthogonal projection of `u` onto `K`.
-/
theorem exists_norm_eq_iInf_of_complete_subspace (h : IsComplete (↑K : Set E)) :
∀ u : E, ∃ v ∈ K, ‖u - v‖ = ⨅ w : (K : Set E), ‖u - w‖ := by
letI : InnerProductSpace ℝ E := InnerProductSpace.rclikeToReal 𝕜 E
letI : Module ℝ E := RestrictScalars.module ℝ 𝕜 E
let K' : Submodule ℝ E := Submodule.restrictScalars ℝ K
exact exists_norm_eq_iInf_of_complete_convex ⟨0, K'.zero_mem⟩ h K'.convex
/-- Characterization of minimizers in the projection on a subspace, in the real case.
Let `u` be a point in a real inner product space, and let `K` be a nonempty subspace.
Then point `v` minimizes the distance `‖u - v‖` over points in `K` if and only if
for all `w ∈ K`, `⟪u - v, w⟫ = 0` (i.e., `u - v` is orthogonal to the subspace `K`).
This is superseded by `norm_eq_iInf_iff_inner_eq_zero` that gives the same conclusion over
any `RCLike` field.
-/
theorem norm_eq_iInf_iff_real_inner_eq_zero (K : Submodule ℝ F) {u : F} {v : F} (hv : v ∈ K) :
(‖u - v‖ = ⨅ w : (↑K : Set F), ‖u - w‖) ↔ ∀ w ∈ K, ⟪u - v, w⟫_ℝ = 0 :=
Iff.intro
(by
intro h
have h : ∀ w ∈ K, ⟪u - v, w - v⟫_ℝ ≤ 0 := by
rwa [norm_eq_iInf_iff_real_inner_le_zero] at h
exacts [K.convex, hv]
intro w hw
have le : ⟪u - v, w⟫_ℝ ≤ 0 := by
let w' := w + v
have : w' ∈ K := Submodule.add_mem _ hw hv
have h₁ := h w' this
have h₂ : w' - v = w := by
simp only [w', add_neg_cancel_right, sub_eq_add_neg]
rw [h₂] at h₁
exact h₁
have ge : ⟪u - v, w⟫_ℝ ≥ 0 := by
let w'' := -w + v
have : w'' ∈ K := Submodule.add_mem _ (Submodule.neg_mem _ hw) hv
have h₁ := h w'' this
have h₂ : w'' - v = -w := by
simp only [w'', neg_inj, add_neg_cancel_right, sub_eq_add_neg]
rw [h₂, inner_neg_right] at h₁
linarith
exact le_antisymm le ge)
(by
intro h
have : ∀ w ∈ K, ⟪u - v, w - v⟫_ℝ ≤ 0 := by
intro w hw
let w' := w - v
have : w' ∈ K := Submodule.sub_mem _ hw hv
have h₁ := h w' this
exact le_of_eq h₁
rwa [norm_eq_iInf_iff_real_inner_le_zero]
exacts [Submodule.convex _, hv])
/-- Characterization of minimizers in the projection on a subspace.
Let `u` be a point in an inner product space, and let `K` be a nonempty subspace.
Then point `v` minimizes the distance `‖u - v‖` over points in `K` if and only if
for all `w ∈ K`, `⟪u - v, w⟫ = 0` (i.e., `u - v` is orthogonal to the subspace `K`)
-/
theorem norm_eq_iInf_iff_inner_eq_zero {u : E} {v : E} (hv : v ∈ K) :
(‖u - v‖ = ⨅ w : K, ‖u - w‖) ↔ ∀ w ∈ K, ⟪u - v, w⟫ = 0 := by
letI : InnerProductSpace ℝ E := InnerProductSpace.rclikeToReal 𝕜 E
letI : Module ℝ E := RestrictScalars.module ℝ 𝕜 E
let K' : Submodule ℝ E := K.restrictScalars ℝ
constructor
· intro H
have A : ∀ w ∈ K, re ⟪u - v, w⟫ = 0 := (K'.norm_eq_iInf_iff_real_inner_eq_zero hv).1 H
intro w hw
apply RCLike.ext
· simp [A w hw]
· symm
calc
im (0 : 𝕜) = 0 := im.map_zero
_ = re ⟪u - v, (-I : 𝕜) • w⟫ := (A _ (K.smul_mem (-I) hw)).symm
_ = re (-I * ⟪u - v, w⟫) := by rw [inner_smul_right]
_ = im ⟪u - v, w⟫ := by simp
· intro H
have : ∀ w ∈ K', ⟪u - v, w⟫_ℝ = 0 := by
intro w hw
rw [real_inner_eq_re_inner, H w hw]
exact zero_re'
exact (K'.norm_eq_iInf_iff_real_inner_eq_zero hv).2 this
/-- A subspace `K : Submodule 𝕜 E` has an orthogonal projection if every vector `v : E` admits an
orthogonal projection to `K`. -/
class HasOrthogonalProjection (K : Submodule 𝕜 E) : Prop where
exists_orthogonal (v : E) : ∃ w ∈ K, v - w ∈ Kᗮ
instance (priority := 100) HasOrthogonalProjection.ofCompleteSpace [CompleteSpace K] :
K.HasOrthogonalProjection where
exists_orthogonal v := by
rcases K.exists_norm_eq_iInf_of_complete_subspace (completeSpace_coe_iff_isComplete.mp ‹_›) v
with ⟨w, hwK, hw⟩
refine ⟨w, hwK, (K.mem_orthogonal' _).2 ?_⟩
rwa [← K.norm_eq_iInf_iff_inner_eq_zero hwK]
instance [K.HasOrthogonalProjection] : Kᗮ.HasOrthogonalProjection where
exists_orthogonal v := by
rcases HasOrthogonalProjection.exists_orthogonal (K := K) v with ⟨w, hwK, hw⟩
refine ⟨_, hw, ?_⟩
rw [sub_sub_cancel]
exact K.le_orthogonal_orthogonal hwK
instance HasOrthogonalProjection.map_linearIsometryEquiv [K.HasOrthogonalProjection]
{E' : Type*} [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E'] (f : E ≃ₗᵢ[𝕜] E') :
(K.map (f.toLinearEquiv : E →ₗ[𝕜] E')).HasOrthogonalProjection where
exists_orthogonal v := by
rcases HasOrthogonalProjection.exists_orthogonal (K := K) (f.symm v) with ⟨w, hwK, hw⟩
refine ⟨f w, Submodule.mem_map_of_mem hwK, Set.forall_mem_image.2 fun u hu ↦ ?_⟩
erw [← f.symm.inner_map_map, f.symm_apply_apply, map_sub, f.symm_apply_apply, hw u hu]
instance HasOrthogonalProjection.map_linearIsometryEquiv' [K.HasOrthogonalProjection]
{E' : Type*} [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E'] (f : E ≃ₗᵢ[𝕜] E') :
(K.map f.toLinearIsometry).HasOrthogonalProjection :=
HasOrthogonalProjection.map_linearIsometryEquiv K f
instance : (⊤ : Submodule 𝕜 E).HasOrthogonalProjection := ⟨fun v ↦ ⟨v, trivial, by simp⟩⟩
section orthogonalProjection
variable [K.HasOrthogonalProjection]
/-- The orthogonal projection onto a complete subspace, as an
unbundled function. This definition is only intended for use in
setting up the bundled version `orthogonalProjection` and should not
be used once that is defined. -/
def orthogonalProjectionFn (v : E) :=
(HasOrthogonalProjection.exists_orthogonal (K := K) v).choose
variable {K}
/-- The unbundled orthogonal projection is in the given subspace.
This lemma is only intended for use in setting up the bundled version
and should not be used once that is defined. -/
theorem orthogonalProjectionFn_mem (v : E) : K.orthogonalProjectionFn v ∈ K :=
(HasOrthogonalProjection.exists_orthogonal (K := K) v).choose_spec.left
/-- The characterization of the unbundled orthogonal projection. This
lemma is only intended for use in setting up the bundled version
and should not be used once that is defined. -/
theorem orthogonalProjectionFn_inner_eq_zero (v : E) :
∀ w ∈ K, ⟪v - K.orthogonalProjectionFn v, w⟫ = 0 :=
(K.mem_orthogonal' _).1 (HasOrthogonalProjection.exists_orthogonal (K := K) v).choose_spec.right
/-- The unbundled orthogonal projection is the unique point in `K`
with the orthogonality property. This lemma is only intended for use
in setting up the bundled version and should not be used once that is
defined. -/
theorem eq_orthogonalProjectionFn_of_mem_of_inner_eq_zero {u v : E} (hvm : v ∈ K)
(hvo : ∀ w ∈ K, ⟪u - v, w⟫ = 0) : K.orthogonalProjectionFn u = v := by
rw [← sub_eq_zero, ← @inner_self_eq_zero 𝕜]
have hvs : K.orthogonalProjectionFn u - v ∈ K :=
Submodule.sub_mem K (orthogonalProjectionFn_mem u) hvm
have huo : ⟪u - K.orthogonalProjectionFn u, K.orthogonalProjectionFn u - v⟫ = 0 :=
orthogonalProjectionFn_inner_eq_zero u _ hvs
have huv : ⟪u - v, K.orthogonalProjectionFn u - v⟫ = 0 := hvo _ hvs
have houv : ⟪u - v - (u - K.orthogonalProjectionFn u), K.orthogonalProjectionFn u - v⟫ = 0 := by
rw [inner_sub_left, huo, huv, sub_zero]
rwa [sub_sub_sub_cancel_left] at houv
variable (K)
theorem orthogonalProjectionFn_norm_sq (v : E) :
‖v‖ * ‖v‖ =
‖v - K.orthogonalProjectionFn v‖ * ‖v - K.orthogonalProjectionFn v‖ +
‖K.orthogonalProjectionFn v‖ * ‖K.orthogonalProjectionFn v‖ := by
set p := K.orthogonalProjectionFn v
have h' : ⟪v - p, p⟫ = 0 :=
orthogonalProjectionFn_inner_eq_zero _ _ (orthogonalProjectionFn_mem v)
convert norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero (v - p) p h' using 2 <;> simp
/-- The orthogonal projection onto a complete subspace. -/
def orthogonalProjection : E →L[𝕜] K :=
LinearMap.mkContinuous
{ toFun := fun v => ⟨K.orthogonalProjectionFn v, orthogonalProjectionFn_mem v⟩
map_add' := fun x y => by
have hm : K.orthogonalProjectionFn x + K.orthogonalProjectionFn y ∈ K :=
Submodule.add_mem K (orthogonalProjectionFn_mem x) (orthogonalProjectionFn_mem y)
have ho :
∀ w ∈ K, ⟪x + y - (K.orthogonalProjectionFn x + K.orthogonalProjectionFn y), w⟫ = 0 := by
intro w hw
rw [add_sub_add_comm, inner_add_left, orthogonalProjectionFn_inner_eq_zero _ w hw,
orthogonalProjectionFn_inner_eq_zero _ w hw, add_zero]
ext
simp [eq_orthogonalProjectionFn_of_mem_of_inner_eq_zero hm ho]
map_smul' := fun c x => by
have hm : c • K.orthogonalProjectionFn x ∈ K :=
Submodule.smul_mem K _ (orthogonalProjectionFn_mem x)
have ho : ∀ w ∈ K, ⟪c • x - c • K.orthogonalProjectionFn x, w⟫ = 0 := by
intro w hw
rw [← smul_sub, inner_smul_left, orthogonalProjectionFn_inner_eq_zero _ w hw,
mul_zero]
ext
simp [eq_orthogonalProjectionFn_of_mem_of_inner_eq_zero hm ho] }
1 fun x => by
simp only [one_mul, LinearMap.coe_mk]
refine le_of_pow_le_pow_left₀ two_ne_zero (norm_nonneg _) ?_
change ‖K.orthogonalProjectionFn x‖ ^ 2 ≤ ‖x‖ ^ 2
nlinarith [K.orthogonalProjectionFn_norm_sq x]
variable {K}
@[simp]
theorem orthogonalProjectionFn_eq (v : E) :
K.orthogonalProjectionFn v = (K.orthogonalProjection v : E) :=
rfl
/-- The characterization of the orthogonal projection. -/
@[simp]
theorem orthogonalProjection_inner_eq_zero (v : E) :
∀ w ∈ K, ⟪v - K.orthogonalProjection v, w⟫ = 0 :=
orthogonalProjectionFn_inner_eq_zero v
/-- The difference of `v` from its orthogonal projection onto `K` is in `Kᗮ`. -/
@[simp]
theorem sub_orthogonalProjection_mem_orthogonal (v : E) : v - K.orthogonalProjection v ∈ Kᗮ := by
intro w hw
rw [inner_eq_zero_symm]
exact orthogonalProjection_inner_eq_zero _ _ hw
/-- The orthogonal projection is the unique point in `K` with the
orthogonality property. -/
theorem eq_orthogonalProjection_of_mem_of_inner_eq_zero {u v : E} (hvm : v ∈ K)
(hvo : ∀ w ∈ K, ⟪u - v, w⟫ = 0) : (K.orthogonalProjection u : E) = v :=
eq_orthogonalProjectionFn_of_mem_of_inner_eq_zero hvm hvo
/-- A point in `K` with the orthogonality property (here characterized in terms of `Kᗮ`) must be the
orthogonal projection. -/
theorem eq_orthogonalProjection_of_mem_orthogonal {u v : E} (hv : v ∈ K)
(hvo : u - v ∈ Kᗮ) : (K.orthogonalProjection u : E) = v :=
eq_orthogonalProjectionFn_of_mem_of_inner_eq_zero hv <| (Submodule.mem_orthogonal' _ _).1 hvo
/-- A point in `K` with the orthogonality property (here characterized in terms of `Kᗮ`) must be the
orthogonal projection. -/
theorem eq_orthogonalProjection_of_mem_orthogonal' {u v z : E}
(hv : v ∈ K) (hz : z ∈ Kᗮ) (hu : u = v + z) : (K.orthogonalProjection u : E) = v :=
eq_orthogonalProjection_of_mem_orthogonal hv (by simpa [hu] )
@[simp]
theorem orthogonalProjection_orthogonal_val (u : E) :
(Kᗮ.orthogonalProjection u : E) = u - K.orthogonalProjection u :=
eq_orthogonalProjection_of_mem_orthogonal' (sub_orthogonalProjection_mem_orthogonal _)
(K.le_orthogonal_orthogonal (K.orthogonalProjection u).2) <| by simp
theorem orthogonalProjection_orthogonal (u : E) :
Kᗮ.orthogonalProjection u =
⟨u - K.orthogonalProjection u, sub_orthogonalProjection_mem_orthogonal _⟩ :=
Subtype.eq <| orthogonalProjection_orthogonal_val _
/-- The orthogonal projection of `y` on `U` minimizes the distance `‖y - x‖` for `x ∈ U`. -/
theorem orthogonalProjection_minimal {U : Submodule 𝕜 E} [U.HasOrthogonalProjection] (y : E) :
‖y - U.orthogonalProjection y‖ = ⨅ x : U, ‖y - x‖ := by
rw [U.norm_eq_iInf_iff_inner_eq_zero (Submodule.coe_mem _)]
exact orthogonalProjection_inner_eq_zero _
/-- The orthogonal projections onto equal subspaces are coerced back to the same point in `E`. -/
theorem eq_orthogonalProjection_of_eq_submodule {K' : Submodule 𝕜 E} [K'.HasOrthogonalProjection]
(h : K = K') (u : E) : (K.orthogonalProjection u : E) = (K'.orthogonalProjection u : E) := by
subst h; rfl
/-- The orthogonal projection sends elements of `K` to themselves. -/
@[simp]
theorem orthogonalProjection_mem_subspace_eq_self (v : K) : K.orthogonalProjection v = v := by
ext
apply eq_orthogonalProjection_of_mem_of_inner_eq_zero <;> simp
/-- A point equals its orthogonal projection if and only if it lies in the subspace. -/
theorem orthogonalProjection_eq_self_iff {v : E} : (K.orthogonalProjection v : E) = v ↔ v ∈ K := by
refine ⟨fun h => ?_, fun h => eq_orthogonalProjection_of_mem_of_inner_eq_zero h ?_⟩
· rw [← h]
simp
· simp
@[simp]
theorem orthogonalProjection_eq_zero_iff {v : E} : K.orthogonalProjection v = 0 ↔ v ∈ Kᗮ := by
refine ⟨fun h ↦ ?_, fun h ↦ Subtype.eq <| eq_orthogonalProjection_of_mem_orthogonal
(zero_mem _) ?_⟩
· simpa [h] using sub_orthogonalProjection_mem_orthogonal (K := K) v
· simpa
@[simp]
theorem ker_orthogonalProjection : LinearMap.ker K.orthogonalProjection = Kᗮ := by
ext; exact orthogonalProjection_eq_zero_iff
theorem _root_.LinearIsometry.map_orthogonalProjection {E E' : Type*} [NormedAddCommGroup E]
[NormedAddCommGroup E'] [InnerProductSpace 𝕜 E] [InnerProductSpace 𝕜 E'] (f : E →ₗᵢ[𝕜] E')
(p : Submodule 𝕜 E) [p.HasOrthogonalProjection] [(p.map f.toLinearMap).HasOrthogonalProjection]
(x : E) : f (p.orthogonalProjection x) = (p.map f.toLinearMap).orthogonalProjection (f x) := by
refine (eq_orthogonalProjection_of_mem_of_inner_eq_zero ?_ fun y hy => ?_).symm
· refine Submodule.apply_coe_mem_map _ _
rcases hy with ⟨x', hx', rfl : f x' = y⟩
rw [← f.map_sub, f.inner_map_map, orthogonalProjection_inner_eq_zero x x' hx']
theorem _root_.LinearIsometry.map_orthogonalProjection' {E E' : Type*} [NormedAddCommGroup E]
[NormedAddCommGroup E'] [InnerProductSpace 𝕜 E] [InnerProductSpace 𝕜 E'] (f : E →ₗᵢ[𝕜] E')
(p : Submodule 𝕜 E) [p.HasOrthogonalProjection] [(p.map f).HasOrthogonalProjection] (x : E) :
f (p.orthogonalProjection x) = (p.map f).orthogonalProjection (f x) :=
have : (p.map f.toLinearMap).HasOrthogonalProjection := ‹_›
f.map_orthogonalProjection p x
/-- Orthogonal projection onto the `Submodule.map` of a subspace. -/
theorem orthogonalProjection_map_apply {E E' : Type*} [NormedAddCommGroup E]
[NormedAddCommGroup E'] [InnerProductSpace 𝕜 E] [InnerProductSpace 𝕜 E'] (f : E ≃ₗᵢ[𝕜] E')
(p : Submodule 𝕜 E) [p.HasOrthogonalProjection] (x : E') :
((p.map (f.toLinearEquiv : E →ₗ[𝕜] E')).orthogonalProjection x : E') =
f (p.orthogonalProjection (f.symm x)) := by
simpa only [f.coe_toLinearIsometry, f.apply_symm_apply] using
(f.toLinearIsometry.map_orthogonalProjection' p (f.symm x)).symm
/-- The orthogonal projection onto the trivial submodule is the zero map. -/
@[simp]
theorem orthogonalProjection_bot : (⊥ : Submodule 𝕜 E).orthogonalProjection = 0 := by ext
variable (K)
/-- The orthogonal projection has norm `≤ 1`. -/
theorem orthogonalProjection_norm_le : ‖K.orthogonalProjection‖ ≤ 1 :=
LinearMap.mkContinuous_norm_le _ (by norm_num) _
variable (𝕜)
theorem smul_orthogonalProjection_singleton {v : E} (w : E) :
((‖v‖ ^ 2 : ℝ) : 𝕜) • ((𝕜 ∙ v).orthogonalProjection w : E) = ⟪v, w⟫ • v := by
suffices (((𝕜 ∙ v).orthogonalProjection (((‖v‖ : 𝕜) ^ 2) • w)) : E) = ⟪v, w⟫ • v by
simpa using this
apply eq_orthogonalProjection_of_mem_of_inner_eq_zero
· rw [Submodule.mem_span_singleton]
use ⟪v, w⟫
· rw [← Submodule.mem_orthogonal', Submodule.mem_orthogonal_singleton_iff_inner_left]
simp [inner_sub_left, inner_smul_left, inner_self_eq_norm_sq_to_K, mul_comm]
/-- Formula for orthogonal projection onto a single vector. -/
theorem orthogonalProjection_singleton {v : E} (w : E) :
((𝕜 ∙ v).orthogonalProjection w : E) = (⟪v, w⟫ / ((‖v‖ ^ 2 : ℝ) : 𝕜)) • v := by
by_cases hv : v = 0
· rw [hv, eq_orthogonalProjection_of_eq_submodule (Submodule.span_zero_singleton 𝕜)]
simp
have hv' : ‖v‖ ≠ 0 := ne_of_gt (norm_pos_iff.mpr hv)
have key :
(((‖v‖ ^ 2 : ℝ) : 𝕜)⁻¹ * ((‖v‖ ^ 2 : ℝ) : 𝕜)) • (((𝕜 ∙ v).orthogonalProjection w) : E) =
(((‖v‖ ^ 2 : ℝ) : 𝕜)⁻¹ * ⟪v, w⟫) • v := by
simp [mul_smul, smul_orthogonalProjection_singleton 𝕜 w, -map_pow]
convert key using 1 <;> field_simp [hv']
/-- Formula for orthogonal projection onto a single unit vector. -/
theorem orthogonalProjection_unit_singleton {v : E} (hv : ‖v‖ = 1) (w : E) :
((𝕜 ∙ v).orthogonalProjection w : E) = ⟪v, w⟫ • v := by
rw [← smul_orthogonalProjection_singleton 𝕜 w]
simp [hv]
end orthogonalProjection
section reflection
variable [K.HasOrthogonalProjection]
/-- Auxiliary definition for `reflection`: the reflection as a linear equivalence. -/
def reflectionLinearEquiv : E ≃ₗ[𝕜] E :=
LinearEquiv.ofInvolutive
(2 • (K.subtype.comp K.orthogonalProjection.toLinearMap) - LinearMap.id) fun x => by
simp [two_smul]
/-- Reflection in a complete subspace of an inner product space. The word "reflection" is
sometimes understood to mean specifically reflection in a codimension-one subspace, and sometimes
more generally to cover operations such as reflection in a point. The definition here, of
reflection in a subspace, is a more general sense of the word that includes both those common
cases. -/
def reflection : E ≃ₗᵢ[𝕜] E :=
{ K.reflectionLinearEquiv with
norm_map' := by
intro x
let w : K := K.orthogonalProjection x
let v := x - w
have : ⟪v, w⟫ = 0 := orthogonalProjection_inner_eq_zero x w w.2
convert norm_sub_eq_norm_add this using 2
· rw [LinearEquiv.coe_mk, reflectionLinearEquiv, LinearEquiv.toFun_eq_coe,
LinearEquiv.coe_ofInvolutive, LinearMap.sub_apply, LinearMap.id_apply, two_smul,
LinearMap.add_apply, LinearMap.comp_apply, Submodule.subtype_apply,
ContinuousLinearMap.coe_coe]
dsimp [v]
abel
· simp only [v, add_sub_cancel, eq_self_iff_true] }
variable {K}
/-- The result of reflecting. -/
theorem reflection_apply (p : E) : K.reflection p = 2 • (K.orthogonalProjection p : E) - p :=
rfl
/-- Reflection is its own inverse. -/
@[simp]
theorem reflection_symm : K.reflection.symm = K.reflection :=
rfl
/-- Reflection is its own inverse. -/
@[simp]
theorem reflection_inv : K.reflection⁻¹ = K.reflection :=
rfl
variable (K)
/-- Reflecting twice in the same subspace. -/
@[simp]
theorem reflection_reflection (p : E) : K.reflection (K.reflection p) = p :=
K.reflection.left_inv p
/-- Reflection is involutive. -/
theorem reflection_involutive : Function.Involutive K.reflection :=
K.reflection_reflection
/-- Reflection is involutive. -/
@[simp]
theorem reflection_trans_reflection :
K.reflection.trans K.reflection = LinearIsometryEquiv.refl 𝕜 E :=
LinearIsometryEquiv.ext <| reflection_involutive K
/-- Reflection is involutive. -/
@[simp]
theorem reflection_mul_reflection : K.reflection * K.reflection = 1 :=
reflection_trans_reflection _
theorem reflection_orthogonal_apply (v : E) : Kᗮ.reflection v = -K.reflection v := by
simp [reflection_apply]; abel
theorem reflection_orthogonal : Kᗮ.reflection = .trans K.reflection (.neg _) := by
ext; apply reflection_orthogonal_apply
variable {K}
theorem reflection_singleton_apply (u v : E) :
reflection (𝕜 ∙ u) v = 2 • (⟪u, v⟫ / ((‖u‖ : 𝕜) ^ 2)) • u - v := by
rw [reflection_apply, orthogonalProjection_singleton, ofReal_pow]
/-- A point is its own reflection if and only if it is in the subspace. -/
theorem reflection_eq_self_iff (x : E) : K.reflection x = x ↔ x ∈ K := by
rw [← orthogonalProjection_eq_self_iff, reflection_apply, sub_eq_iff_eq_add', ← two_smul 𝕜,
two_smul ℕ, ← two_smul 𝕜]
refine (smul_right_injective E ?_).eq_iff
exact two_ne_zero
theorem reflection_mem_subspace_eq_self {x : E} (hx : x ∈ K) : K.reflection x = x :=
(reflection_eq_self_iff x).mpr hx
/-- Reflection in the `Submodule.map` of a subspace. -/
theorem reflection_map_apply {E E' : Type*} [NormedAddCommGroup E] [NormedAddCommGroup E']
[InnerProductSpace 𝕜 E] [InnerProductSpace 𝕜 E'] (f : E ≃ₗᵢ[𝕜] E') (K : Submodule 𝕜 E)
[K.HasOrthogonalProjection] (x : E') :
reflection (K.map (f.toLinearEquiv : E →ₗ[𝕜] E')) x = f (K.reflection (f.symm x)) := by
simp [two_smul, reflection_apply, orthogonalProjection_map_apply f K x]
/-- Reflection in the `Submodule.map` of a subspace. -/
theorem reflection_map {E E' : Type*} [NormedAddCommGroup E] [NormedAddCommGroup E']
[InnerProductSpace 𝕜 E] [InnerProductSpace 𝕜 E'] (f : E ≃ₗᵢ[𝕜] E') (K : Submodule 𝕜 E)
[K.HasOrthogonalProjection] :
reflection (K.map (f.toLinearEquiv : E →ₗ[𝕜] E')) = f.symm.trans (K.reflection.trans f) :=
LinearIsometryEquiv.ext <| reflection_map_apply f K
/-- Reflection through the trivial subspace {0} is just negation. -/
@[simp]
theorem reflection_bot : reflection (⊥ : Submodule 𝕜 E) = LinearIsometryEquiv.neg 𝕜 := by
ext; simp [reflection_apply]
end reflection
end Submodule
section Orthogonal
namespace Submodule
/-- If `K₁` is complete and contained in `K₂`, `K₁` and `K₁ᗮ ⊓ K₂` span `K₂`. -/
theorem sup_orthogonal_inf_of_completeSpace {K₁ K₂ : Submodule 𝕜 E} (h : K₁ ≤ K₂)
[K₁.HasOrthogonalProjection] : K₁ ⊔ K₁ᗮ ⊓ K₂ = K₂ := by
ext x
rw [Submodule.mem_sup]
let v : K₁ := orthogonalProjection K₁ x
have hvm : x - v ∈ K₁ᗮ := sub_orthogonalProjection_mem_orthogonal x
constructor
· rintro ⟨y, hy, z, hz, rfl⟩
exact K₂.add_mem (h hy) hz.2
· exact fun hx => ⟨v, v.prop, x - v, ⟨hvm, K₂.sub_mem hx (h v.prop)⟩, add_sub_cancel _ _⟩
variable {K} in
/-- If `K` is complete, `K` and `Kᗮ` span the whole space. -/
theorem sup_orthogonal_of_completeSpace [K.HasOrthogonalProjection] : K ⊔ Kᗮ = ⊤ := by
convert Submodule.sup_orthogonal_inf_of_completeSpace (le_top : K ≤ ⊤) using 2
simp
/-- If `K` is complete, any `v` in `E` can be expressed as a sum of elements of `K` and `Kᗮ`. -/
theorem exists_add_mem_mem_orthogonal [K.HasOrthogonalProjection] (v : E) :
∃ y ∈ K, ∃ z ∈ Kᗮ, v = y + z :=
⟨K.orthogonalProjection v, Subtype.coe_prop _, v - K.orthogonalProjection v,
sub_orthogonalProjection_mem_orthogonal _, by simp⟩
/-- If `K` admits an orthogonal projection, then the orthogonal complement of its orthogonal
complement is itself. -/
@[simp]
theorem orthogonal_orthogonal [K.HasOrthogonalProjection] : Kᗮᗮ = K := by
ext v
constructor
· obtain ⟨y, hy, z, hz, rfl⟩ := K.exists_add_mem_mem_orthogonal v
intro hv
have hz' : z = 0 := by
have hyz : ⟪z, y⟫ = 0 := by simp [hz y hy, inner_eq_zero_symm]
simpa [inner_add_right, hyz] using hv z hz
simp [hy, hz']
· intro hv w hw
rw [inner_eq_zero_symm]
exact hw v hv
/-- In a Hilbert space, the orthogonal complement of the orthogonal complement of a subspace `K`
is the topological closure of `K`.
Note that the completeness assumption is necessary. Let `E` be the space `ℕ →₀ ℝ` with inner space
structure inherited from `PiLp 2 (fun _ : ℕ ↦ ℝ)`. Let `K` be the subspace of sequences with the sum
of all elements equal to zero. Then `Kᗮ = ⊥`, `Kᗮᗮ = ⊤`. -/
theorem orthogonal_orthogonal_eq_closure [CompleteSpace E] :
Kᗮᗮ = K.topologicalClosure := by
refine le_antisymm ?_ ?_
· convert Submodule.orthogonal_orthogonal_monotone K.le_topologicalClosure using 1
rw [K.topologicalClosure.orthogonal_orthogonal]
· exact K.topologicalClosure_minimal K.le_orthogonal_orthogonal Kᗮ.isClosed_orthogonal
variable {K}
/-- If `K` admits an orthogonal projection, `K` and `Kᗮ` are complements of each other. -/
theorem isCompl_orthogonal_of_completeSpace [K.HasOrthogonalProjection] : IsCompl K Kᗮ :=
⟨K.orthogonal_disjoint, codisjoint_iff.2 Submodule.sup_orthogonal_of_completeSpace⟩
@[simp]
theorem orthogonalComplement_eq_orthogonalComplement {L : Submodule 𝕜 E} [K.HasOrthogonalProjection]
[L.HasOrthogonalProjection] : Kᗮ = Lᗮ ↔ K = L :=
⟨fun h ↦ by simpa using congr(Submodule.orthogonal $(h)),
fun h ↦ congr(Submodule.orthogonal $(h))⟩
@[simp]
theorem orthogonal_eq_bot_iff [K.HasOrthogonalProjection] : Kᗮ = ⊥ ↔ K = ⊤ := by
refine ⟨?_, fun h => by rw [h, Submodule.top_orthogonal_eq_bot]⟩
intro h
have : K ⊔ Kᗮ = ⊤ := Submodule.sup_orthogonal_of_completeSpace
rwa [h, sup_comm, bot_sup_eq] at this
/-- The orthogonal projection onto `K` of an element of `Kᗮ` is zero. -/
theorem orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero [K.HasOrthogonalProjection]
{v : E} (hv : v ∈ Kᗮ) : K.orthogonalProjection v = 0 := by
ext
convert eq_orthogonalProjection_of_mem_orthogonal (K := K) _ _ <;> simp [hv]
/-- The projection into `U` from an orthogonal submodule `V` is the zero map. -/
theorem IsOrtho.orthogonalProjection_comp_subtypeL {U V : Submodule 𝕜 E}
[U.HasOrthogonalProjection] (h : U ⟂ V) : U.orthogonalProjection ∘L V.subtypeL = 0 :=
ContinuousLinearMap.ext fun v =>
orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero <| h.symm v.prop
/-- The projection into `U` from `V` is the zero map if and only if `U` and `V` are orthogonal. -/
theorem orthogonalProjection_comp_subtypeL_eq_zero_iff {U V : Submodule 𝕜 E}
[U.HasOrthogonalProjection] : U.orthogonalProjection ∘L V.subtypeL = 0 ↔ U ⟂ V :=
⟨fun h u hu v hv => by
convert orthogonalProjection_inner_eq_zero v u hu using 2
have : U.orthogonalProjection v = 0 := DFunLike.congr_fun h (⟨_, hv⟩ : V)
rw [this, Submodule.coe_zero, sub_zero], Submodule.IsOrtho.orthogonalProjection_comp_subtypeL⟩
theorem orthogonalProjection_eq_linear_proj [K.HasOrthogonalProjection] (x : E) :
K.orthogonalProjection x =
K.linearProjOfIsCompl _ Submodule.isCompl_orthogonal_of_completeSpace x := by
have : IsCompl K Kᗮ := Submodule.isCompl_orthogonal_of_completeSpace
conv_lhs => rw [← Submodule.linear_proj_add_linearProjOfIsCompl_eq_self this x]
rw [map_add, orthogonalProjection_mem_subspace_eq_self,
orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero (Submodule.coe_mem _), add_zero]
theorem orthogonalProjection_coe_linearMap_eq_linearProj [K.HasOrthogonalProjection] :
(K.orthogonalProjection : E →ₗ[𝕜] K) =
K.linearProjOfIsCompl _ Submodule.isCompl_orthogonal_of_completeSpace :=
LinearMap.ext <| orthogonalProjection_eq_linear_proj
/-- The reflection in `K` of an element of `Kᗮ` is its negation. -/
theorem reflection_mem_subspace_orthogonalComplement_eq_neg [K.HasOrthogonalProjection] {v : E}
(hv : v ∈ Kᗮ) : K.reflection v = -v := by
simp [reflection_apply, orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero hv]
/-- The orthogonal projection onto `Kᗮ` of an element of `K` is zero. -/
theorem orthogonalProjection_mem_subspace_orthogonal_precomplement_eq_zero
[Kᗮ.HasOrthogonalProjection] {v : E} (hv : v ∈ K) : Kᗮ.orthogonalProjection v = 0 :=
orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero (K.le_orthogonal_orthogonal hv)
/-- If `U ≤ V`, then projecting on `V` and then on `U` is the same as projecting on `U`. -/
theorem orthogonalProjection_orthogonalProjection_of_le {U V : Submodule 𝕜 E}
[U.HasOrthogonalProjection] [V.HasOrthogonalProjection] (h : U ≤ V) (x : E) :
U.orthogonalProjection (V.orthogonalProjection x) = U.orthogonalProjection x :=
Eq.symm <| by
simpa only [sub_eq_zero, map_sub] using
orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero
(Submodule.orthogonal_le h (sub_orthogonalProjection_mem_orthogonal x))
/-- Given a monotone family `U` of complete submodules of `E` and a fixed `x : E`,
the orthogonal projection of `x` on `U i` tends to the orthogonal projection of `x` on
`(⨆ i, U i).topologicalClosure` along `atTop`. -/
theorem orthogonalProjection_tendsto_closure_iSup {ι : Type*} [Preorder ι]
(U : ι → Submodule 𝕜 E) [∀ i, (U i).HasOrthogonalProjection]
[(⨆ i, U i).topologicalClosure.HasOrthogonalProjection] (hU : Monotone U) (x : E) :
Filter.Tendsto (fun i => ((U i).orthogonalProjection x : E)) atTop
(𝓝 ((⨆ i, U i).topologicalClosure.orthogonalProjection x : E)) := by
refine .of_neBot_imp fun h ↦ ?_
cases atTop_neBot_iff.mp h
let y := ((⨆ i, U i).topologicalClosure.orthogonalProjection x : E)
have proj_x : ∀ i, (U i).orthogonalProjection x = (U i).orthogonalProjection y := fun i =>
(orthogonalProjection_orthogonalProjection_of_le
((le_iSup U i).trans (iSup U).le_topologicalClosure) _).symm
suffices ∀ ε > 0, ∃ I, ∀ i ≥ I, ‖((U i).orthogonalProjection y : E) - y‖ < ε by
simpa only [proj_x, NormedAddCommGroup.tendsto_atTop] using this
intro ε hε
obtain ⟨a, ha, hay⟩ : ∃ a ∈ ⨆ i, U i, dist y a < ε := by
have y_mem : y ∈ (⨆ i, U i).topologicalClosure := Submodule.coe_mem _
rw [← SetLike.mem_coe, Submodule.topologicalClosure_coe, Metric.mem_closure_iff] at y_mem
exact y_mem ε hε
rw [dist_eq_norm] at hay
obtain ⟨I, hI⟩ : ∃ I, a ∈ U I := by rwa [Submodule.mem_iSup_of_directed _ hU.directed_le] at ha
refine ⟨I, fun i (hi : I ≤ i) => ?_⟩
rw [norm_sub_rev, orthogonalProjection_minimal]
refine lt_of_le_of_lt ?_ hay
change _ ≤ ‖y - (⟨a, hU hi hI⟩ : U i)‖
exact ciInf_le ⟨0, Set.forall_mem_range.mpr fun _ => norm_nonneg _⟩ _
/-- Given a monotone family `U` of complete submodules of `E` with dense span supremum,
and a fixed `x : E`, the orthogonal projection of `x` on `U i` tends to `x` along `at_top`. -/
theorem orthogonalProjection_tendsto_self {ι : Type*} [Preorder ι]
(U : ι → Submodule 𝕜 E) [∀ t, (U t).HasOrthogonalProjection] (hU : Monotone U) (x : E)
(hU' : ⊤ ≤ (⨆ t, U t).topologicalClosure) :
Filter.Tendsto (fun t => ((U t).orthogonalProjection x : E)) atTop (𝓝 x) := by
have : (⨆ i, U i).topologicalClosure.HasOrthogonalProjection := by
rw [top_unique hU']
infer_instance
convert orthogonalProjection_tendsto_closure_iSup U hU x
rw [eq_comm, orthogonalProjection_eq_self_iff, top_unique hU']
trivial
/-- The orthogonal complement satisfies `Kᗮᗮᗮ = Kᗮ`. -/
theorem triorthogonal_eq_orthogonal [CompleteSpace E] : Kᗮᗮᗮ = Kᗮ := by
rw [Kᗮ.orthogonal_orthogonal_eq_closure]
exact K.isClosed_orthogonal.submodule_topologicalClosure_eq
/-- The closure of `K` is the full space iff `Kᗮ` is trivial. -/
theorem topologicalClosure_eq_top_iff [CompleteSpace E] :
K.topologicalClosure = ⊤ ↔ Kᗮ = ⊥ := by
rw [← K.orthogonal_orthogonal_eq_closure]
constructor <;> intro h
· rw [← Submodule.triorthogonal_eq_orthogonal, h, Submodule.top_orthogonal_eq_bot]
· rw [h, Submodule.bot_orthogonal_eq_top]
end Submodule
namespace Dense
/- TODO: Move to another file? -/
open Submodule
variable {K} {x y : E}
theorem eq_zero_of_inner_left (hK : Dense (K : Set E)) (h : ∀ v : K, ⟪x, v⟫ = 0) : x = 0 := by
have : (⟪x, ·⟫) = 0 := (continuous_const.inner continuous_id).ext_on
hK continuous_const (Subtype.forall.1 h)
simpa using congr_fun this x
theorem eq_zero_of_mem_orthogonal (hK : Dense (K : Set E)) (h : x ∈ Kᗮ) : x = 0 :=
eq_zero_of_inner_left hK fun v ↦ (mem_orthogonal' _ _).1 h _ v.2
/-- If `S` is dense and `x - y ∈ Kᗮ`, then `x = y`. -/
theorem eq_of_sub_mem_orthogonal (hK : Dense (K : Set E)) (h : x - y ∈ Kᗮ) : x = y :=
sub_eq_zero.1 <| eq_zero_of_mem_orthogonal hK h
theorem eq_of_inner_left (hK : Dense (K : Set E)) (h : ∀ v : K, ⟪x, v⟫ = ⟪y, v⟫) : x = y :=
hK.eq_of_sub_mem_orthogonal (Submodule.sub_mem_orthogonal_of_inner_left h)
theorem eq_of_inner_right (hK : Dense (K : Set E)) (h : ∀ v : K, ⟪(v : E), x⟫ = ⟪(v : E), y⟫) :
x = y :=
hK.eq_of_sub_mem_orthogonal (Submodule.sub_mem_orthogonal_of_inner_right h)
theorem eq_zero_of_inner_right (hK : Dense (K : Set E)) (h : ∀ v : K, ⟪(v : E), x⟫ = 0) : x = 0 :=
hK.eq_of_inner_right fun v => by rw [inner_zero_right, h v]
end Dense
namespace Submodule
variable {K}
/-- The reflection in `Kᗮ` of an element of `K` is its negation. -/
theorem reflection_mem_subspace_orthogonal_precomplement_eq_neg [K.HasOrthogonalProjection] {v : E}
(hv : v ∈ K) : Kᗮ.reflection v = -v :=
reflection_mem_subspace_orthogonalComplement_eq_neg (K.le_orthogonal_orthogonal hv)
/-- The orthogonal projection onto `(𝕜 ∙ v)ᗮ` of `v` is zero. -/
theorem orthogonalProjection_orthogonalComplement_singleton_eq_zero (v : E) :
(𝕜 ∙ v)ᗮ.orthogonalProjection v = 0 :=
orthogonalProjection_mem_subspace_orthogonal_precomplement_eq_zero
(Submodule.mem_span_singleton_self v)
/-- The reflection in `(𝕜 ∙ v)ᗮ` of `v` is `-v`. -/
theorem reflection_orthogonalComplement_singleton_eq_neg (v : E) : reflection (𝕜 ∙ v)ᗮ v = -v :=
reflection_mem_subspace_orthogonal_precomplement_eq_neg (Submodule.mem_span_singleton_self v)
theorem reflection_sub {v w : F} (h : ‖v‖ = ‖w‖) : reflection (ℝ ∙ (v - w))ᗮ v = w := by
set R : F ≃ₗᵢ[ℝ] F := reflection (ℝ ∙ v - w)ᗮ
suffices R v + R v = w + w by
apply smul_right_injective F (by norm_num : (2 : ℝ) ≠ 0)
simpa [two_smul] using this
have h₁ : R (v - w) = -(v - w) := reflection_orthogonalComplement_singleton_eq_neg (v - w)
have h₂ : R (v + w) = v + w := by
apply reflection_mem_subspace_eq_self
rw [Submodule.mem_orthogonal_singleton_iff_inner_left]
rw [real_inner_add_sub_eq_zero_iff]
exact h
convert congr_arg₂ (· + ·) h₂ h₁ using 1
· simp
· abel
variable (K)
section FiniteDimensional
open Module
variable [FiniteDimensional 𝕜 K]
@[simp]
theorem det_reflection : LinearMap.det K.reflection.toLinearMap = (-1) ^ finrank 𝕜 Kᗮ := by
by_cases hK : FiniteDimensional 𝕜 Kᗮ
swap
· rw [finrank_of_infinite_dimensional hK, pow_zero, LinearMap.det_eq_one_of_finrank_eq_zero]
exact finrank_of_infinite_dimensional fun h ↦ hK (h.finiteDimensional_submodule _)
let e := K.prodEquivOfIsCompl _ K.isCompl_orthogonal_of_completeSpace
let b := (finBasis 𝕜 K).prod (finBasis 𝕜 Kᗮ)
have : LinearMap.toMatrix b b (e.symm ∘ₗ K.reflection.toLinearMap ∘ₗ e.symm.symm) =
Matrix.fromBlocks 1 0 0 (-1) := by
ext (_ | _) (_ | _) <;>
simp [LinearMap.toMatrix_apply, b, Matrix.one_apply, Finsupp.single_apply, e, eq_comm,
reflection_mem_subspace_eq_self, reflection_mem_subspace_orthogonalComplement_eq_neg]
rw [← LinearMap.det_conj _ e.symm, ← LinearMap.det_toMatrix b, this, Matrix.det_fromBlocks_zero₂₁,
Matrix.det_one, one_mul, Matrix.det_neg, Fintype.card_fin, Matrix.det_one, mul_one]
@[simp]
theorem linearEquiv_det_reflection : K.reflection.det = (-1) ^ finrank 𝕜 Kᗮ := by
ext
rw [LinearEquiv.coe_det, Units.val_pow_eq_pow_val]
exact K.det_reflection
end FiniteDimensional
/-- If the orthogonal projection to `K` is well-defined, then a vector splits as the sum of its
orthogonal projections onto a complete submodule `K` and onto the orthogonal complement of `K`. -/
theorem orthogonalProjection_add_orthogonalProjection_orthogonal [K.HasOrthogonalProjection]
(w : E) : (K.orthogonalProjection w : E) + (Kᗮ.orthogonalProjection w : E) = w := by
simp
/-- The Pythagorean theorem, for an orthogonal projection. -/
theorem norm_sq_eq_add_norm_sq_projection (x : E) (S : Submodule 𝕜 E) [S.HasOrthogonalProjection] :
‖x‖ ^ 2 = ‖S.orthogonalProjection x‖ ^ 2 + ‖Sᗮ.orthogonalProjection x‖ ^ 2 :=
calc
‖x‖ ^ 2 = ‖(S.orthogonalProjection x : E) + Sᗮ.orthogonalProjection x‖ ^ 2 := by
rw [orthogonalProjection_add_orthogonalProjection_orthogonal]
_ = ‖S.orthogonalProjection x‖ ^ 2 + ‖Sᗮ.orthogonalProjection x‖ ^ 2 := by
simp only [sq]
| exact norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero _ _ <|
(S.mem_orthogonal _).1 (Sᗮ.orthogonalProjection x).2 _ (S.orthogonalProjection x).2
/-- In a complete space `E`, the projection maps onto a complete subspace `K` and its orthogonal
complement sum to the identity. -/
theorem id_eq_sum_orthogonalProjection_self_orthogonalComplement [K.HasOrthogonalProjection] :
ContinuousLinearMap.id 𝕜 E =
K.subtypeL.comp K.orthogonalProjection + Kᗮ.subtypeL.comp Kᗮ.orthogonalProjection := by
ext w
exact (K.orthogonalProjection_add_orthogonalProjection_orthogonal w).symm
-- Porting note: The priority should be higher than `Submodule.coe_inner`.
@[simp high]
theorem inner_orthogonalProjection_eq_of_mem_right [K.HasOrthogonalProjection] (u : K) (v : E) :
| Mathlib/Analysis/InnerProductSpace/Projection.lean | 1,031 | 1,044 |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Kim Morrison, Jens Wagemaker
-/
import Mathlib.Algebra.MonoidAlgebra.Degree
import Mathlib.Algebra.Order.Ring.WithTop
import Mathlib.Algebra.Polynomial.Basic
import Mathlib.Data.Nat.Cast.WithTop
import Mathlib.Data.Nat.SuccPred
import Mathlib.Order.SuccPred.WithBot
/-!
# Degree of univariate polynomials
## Main definitions
* `Polynomial.degree`: the degree of a polynomial, where `0` has degree `⊥`
* `Polynomial.natDegree`: the degree of a polynomial, where `0` has degree `0`
* `Polynomial.leadingCoeff`: the leading coefficient of a polynomial
* `Polynomial.Monic`: a polynomial is monic if its leading coefficient is 0
* `Polynomial.nextCoeff`: the next coefficient after the leading coefficient
## Main results
* `Polynomial.degree_eq_natDegree`: the degree and natDegree coincide for nonzero polynomials
-/
noncomputable section
open Finsupp Finset
open Polynomial
namespace Polynomial
universe u v
variable {R : Type u} {S : Type v} {a b c d : R} {n m : ℕ}
section Semiring
variable [Semiring R] {p q r : R[X]}
/-- `degree p` is the degree of the polynomial `p`, i.e. the largest `X`-exponent in `p`.
`degree p = some n` when `p ≠ 0` and `n` is the highest power of `X` that appears in `p`, otherwise
`degree 0 = ⊥`. -/
def degree (p : R[X]) : WithBot ℕ :=
p.support.max
/-- `natDegree p` forces `degree p` to ℕ, by defining `natDegree 0 = 0`. -/
def natDegree (p : R[X]) : ℕ :=
(degree p).unbotD 0
/-- `leadingCoeff p` gives the coefficient of the highest power of `X` in `p`. -/
def leadingCoeff (p : R[X]) : R :=
coeff p (natDegree p)
/-- a polynomial is `Monic` if its leading coefficient is 1 -/
def Monic (p : R[X]) :=
leadingCoeff p = (1 : R)
theorem Monic.def : Monic p ↔ leadingCoeff p = 1 :=
Iff.rfl
instance Monic.decidable [DecidableEq R] : Decidable (Monic p) := by unfold Monic; infer_instance
@[simp]
theorem Monic.leadingCoeff {p : R[X]} (hp : p.Monic) : leadingCoeff p = 1 :=
hp
theorem Monic.coeff_natDegree {p : R[X]} (hp : p.Monic) : p.coeff p.natDegree = 1 :=
hp
@[simp]
theorem degree_zero : degree (0 : R[X]) = ⊥ :=
rfl
@[simp]
theorem natDegree_zero : natDegree (0 : R[X]) = 0 :=
rfl
@[simp]
theorem coeff_natDegree : coeff p (natDegree p) = leadingCoeff p :=
rfl
@[simp]
theorem degree_eq_bot : degree p = ⊥ ↔ p = 0 :=
⟨fun h => support_eq_empty.1 (Finset.max_eq_bot.1 h), fun h => h.symm ▸ rfl⟩
theorem degree_ne_bot : degree p ≠ ⊥ ↔ p ≠ 0 := degree_eq_bot.not
theorem degree_eq_natDegree (hp : p ≠ 0) : degree p = (natDegree p : WithBot ℕ) := by
let ⟨n, hn⟩ := not_forall.1 (mt Option.eq_none_iff_forall_not_mem.2 (mt degree_eq_bot.1 hp))
have hn : degree p = some n := Classical.not_not.1 hn
rw [natDegree, hn]; rfl
theorem degree_eq_iff_natDegree_eq {p : R[X]} {n : ℕ} (hp : p ≠ 0) :
p.degree = n ↔ p.natDegree = n := by rw [degree_eq_natDegree hp]; exact WithBot.coe_eq_coe
theorem degree_eq_iff_natDegree_eq_of_pos {p : R[X]} {n : ℕ} (hn : 0 < n) :
p.degree = n ↔ p.natDegree = n := by
obtain rfl|h := eq_or_ne p 0
· simp [hn.ne]
· exact degree_eq_iff_natDegree_eq h
theorem natDegree_eq_of_degree_eq_some {p : R[X]} {n : ℕ} (h : degree p = n) : natDegree p = n := by
rw [natDegree, h, Nat.cast_withBot, WithBot.unbotD_coe]
theorem degree_ne_of_natDegree_ne {n : ℕ} : p.natDegree ≠ n → degree p ≠ n :=
mt natDegree_eq_of_degree_eq_some
@[simp]
theorem degree_le_natDegree : degree p ≤ natDegree p :=
WithBot.giUnbotDBot.gc.le_u_l _
theorem natDegree_eq_of_degree_eq [Semiring S] {q : S[X]} (h : degree p = degree q) :
natDegree p = natDegree q := by unfold natDegree; rw [h]
theorem le_degree_of_ne_zero (h : coeff p n ≠ 0) : (n : WithBot ℕ) ≤ degree p := by
rw [Nat.cast_withBot]
exact Finset.le_sup (mem_support_iff.2 h)
theorem degree_mono [Semiring S] {f : R[X]} {g : S[X]} (h : f.support ⊆ g.support) :
f.degree ≤ g.degree :=
Finset.sup_mono h
theorem degree_le_degree (h : coeff q (natDegree p) ≠ 0) : degree p ≤ degree q := by
by_cases hp : p = 0
· rw [hp, degree_zero]
exact bot_le
· rw [degree_eq_natDegree hp]
exact le_degree_of_ne_zero h
theorem natDegree_le_iff_degree_le {n : ℕ} : natDegree p ≤ n ↔ degree p ≤ n :=
WithBot.unbotD_le_iff (fun _ ↦ bot_le)
theorem natDegree_lt_iff_degree_lt (hp : p ≠ 0) : p.natDegree < n ↔ p.degree < ↑n :=
WithBot.unbotD_lt_iff (absurd · (degree_eq_bot.not.mpr hp))
alias ⟨degree_le_of_natDegree_le, natDegree_le_of_degree_le⟩ := natDegree_le_iff_degree_le
theorem natDegree_le_natDegree [Semiring S] {q : S[X]} (hpq : p.degree ≤ q.degree) :
p.natDegree ≤ q.natDegree :=
WithBot.giUnbotDBot.gc.monotone_l hpq
@[simp]
theorem degree_C (ha : a ≠ 0) : degree (C a) = (0 : WithBot ℕ) := by
rw [degree, ← monomial_zero_left, support_monomial 0 ha, max_eq_sup_coe, sup_singleton,
WithBot.coe_zero]
theorem degree_C_le : degree (C a) ≤ 0 := by
by_cases h : a = 0
· rw [h, C_0]
exact bot_le
· rw [degree_C h]
theorem degree_C_lt : degree (C a) < 1 :=
degree_C_le.trans_lt <| WithBot.coe_lt_coe.mpr zero_lt_one
theorem degree_one_le : degree (1 : R[X]) ≤ (0 : WithBot ℕ) := by rw [← C_1]; exact degree_C_le
@[simp]
theorem natDegree_C (a : R) : natDegree (C a) = 0 := by
by_cases ha : a = 0
· have : C a = 0 := by rw [ha, C_0]
rw [natDegree, degree_eq_bot.2 this, WithBot.unbotD_bot]
· rw [natDegree, degree_C ha, WithBot.unbotD_zero]
@[simp]
theorem natDegree_one : natDegree (1 : R[X]) = 0 :=
natDegree_C 1
@[simp]
theorem natDegree_natCast (n : ℕ) : natDegree (n : R[X]) = 0 := by
simp only [← C_eq_natCast, natDegree_C]
@[simp]
theorem natDegree_ofNat (n : ℕ) [Nat.AtLeastTwo n] :
natDegree (ofNat(n) : R[X]) = 0 :=
natDegree_natCast _
theorem degree_natCast_le (n : ℕ) : degree (n : R[X]) ≤ 0 := degree_le_of_natDegree_le (by simp)
@[simp]
theorem degree_monomial (n : ℕ) (ha : a ≠ 0) : degree (monomial n a) = n := by
rw [degree, support_monomial n ha, max_singleton, Nat.cast_withBot]
@[simp]
theorem degree_C_mul_X_pow (n : ℕ) (ha : a ≠ 0) : degree (C a * X ^ n) = n := by
rw [C_mul_X_pow_eq_monomial, degree_monomial n ha]
theorem degree_C_mul_X (ha : a ≠ 0) : degree (C a * X) = 1 := by
simpa only [pow_one] using degree_C_mul_X_pow 1 ha
theorem degree_monomial_le (n : ℕ) (a : R) : degree (monomial n a) ≤ n :=
letI := Classical.decEq R
if h : a = 0 then by rw [h, (monomial n).map_zero, degree_zero]; exact bot_le
else le_of_eq (degree_monomial n h)
theorem degree_C_mul_X_pow_le (n : ℕ) (a : R) : degree (C a * X ^ n) ≤ n := by
rw [C_mul_X_pow_eq_monomial]
apply degree_monomial_le
theorem degree_C_mul_X_le (a : R) : degree (C a * X) ≤ 1 := by
simpa only [pow_one] using degree_C_mul_X_pow_le 1 a
@[simp]
theorem natDegree_C_mul_X_pow (n : ℕ) (a : R) (ha : a ≠ 0) : natDegree (C a * X ^ n) = n :=
natDegree_eq_of_degree_eq_some (degree_C_mul_X_pow n ha)
@[simp]
theorem natDegree_C_mul_X (a : R) (ha : a ≠ 0) : natDegree (C a * X) = 1 := by
simpa only [pow_one] using natDegree_C_mul_X_pow 1 a ha
@[simp]
theorem natDegree_monomial [DecidableEq R] (i : ℕ) (r : R) :
natDegree (monomial i r) = if r = 0 then 0 else i := by
split_ifs with hr
· simp [hr]
· rw [← C_mul_X_pow_eq_monomial, natDegree_C_mul_X_pow i r hr]
theorem natDegree_monomial_le (a : R) {m : ℕ} : (monomial m a).natDegree ≤ m := by
classical
rw [Polynomial.natDegree_monomial]
split_ifs
exacts [Nat.zero_le _, le_rfl]
theorem natDegree_monomial_eq (i : ℕ) {r : R} (r0 : r ≠ 0) : (monomial i r).natDegree = i :=
letI := Classical.decEq R
Eq.trans (natDegree_monomial _ _) (if_neg r0)
theorem coeff_ne_zero_of_eq_degree (hn : degree p = n) : coeff p n ≠ 0 := fun h =>
mem_support_iff.mp (mem_of_max hn) h
theorem degree_X_pow_le (n : ℕ) : degree (X ^ n : R[X]) ≤ n := by
simpa only [C_1, one_mul] using degree_C_mul_X_pow_le n (1 : R)
theorem degree_X_le : degree (X : R[X]) ≤ 1 :=
degree_monomial_le _ _
theorem natDegree_X_le : (X : R[X]).natDegree ≤ 1 :=
natDegree_le_of_degree_le degree_X_le
theorem withBotSucc_degree_eq_natDegree_add_one (h : p ≠ 0) : p.degree.succ = p.natDegree + 1 := by
rw [degree_eq_natDegree h]
exact WithBot.succ_coe p.natDegree
end Semiring
section NonzeroSemiring
variable [Semiring R] [Nontrivial R] {p q : R[X]}
@[simp]
theorem degree_one : degree (1 : R[X]) = (0 : WithBot ℕ) :=
degree_C one_ne_zero
@[simp]
theorem degree_X : degree (X : R[X]) = 1 :=
degree_monomial _ one_ne_zero
@[simp]
theorem natDegree_X : (X : R[X]).natDegree = 1 :=
natDegree_eq_of_degree_eq_some degree_X
end NonzeroSemiring
section Ring
variable [Ring R]
@[simp]
theorem degree_neg (p : R[X]) : degree (-p) = degree p := by unfold degree; rw [support_neg]
theorem degree_neg_le_of_le {a : WithBot ℕ} {p : R[X]} (hp : degree p ≤ a) : degree (-p) ≤ a :=
p.degree_neg.le.trans hp
@[simp]
theorem natDegree_neg (p : R[X]) : natDegree (-p) = natDegree p := by simp [natDegree]
theorem natDegree_neg_le_of_le {p : R[X]} (hp : natDegree p ≤ m) : natDegree (-p) ≤ m :=
(natDegree_neg p).le.trans hp
@[simp]
theorem natDegree_intCast (n : ℤ) : natDegree (n : R[X]) = 0 := by
rw [← C_eq_intCast, natDegree_C]
theorem degree_intCast_le (n : ℤ) : degree (n : R[X]) ≤ 0 := degree_le_of_natDegree_le (by simp)
@[simp]
theorem leadingCoeff_neg (p : R[X]) : (-p).leadingCoeff = -p.leadingCoeff := by
rw [leadingCoeff, leadingCoeff, natDegree_neg, coeff_neg]
end Ring
section Semiring
variable [Semiring R] {p : R[X]}
/-- The second-highest coefficient, or 0 for constants -/
def nextCoeff (p : R[X]) : R :=
if p.natDegree = 0 then 0 else p.coeff (p.natDegree - 1)
lemma nextCoeff_eq_zero :
p.nextCoeff = 0 ↔ p.natDegree = 0 ∨ 0 < p.natDegree ∧ p.coeff (p.natDegree - 1) = 0 := by
simp [nextCoeff, or_iff_not_imp_left, pos_iff_ne_zero]; aesop
lemma nextCoeff_ne_zero : p.nextCoeff ≠ 0 ↔ p.natDegree ≠ 0 ∧ p.coeff (p.natDegree - 1) ≠ 0 := by
simp [nextCoeff]
@[simp]
theorem nextCoeff_C_eq_zero (c : R) : nextCoeff (C c) = 0 := by
rw [nextCoeff]
simp
theorem nextCoeff_of_natDegree_pos (hp : 0 < p.natDegree) :
nextCoeff p = p.coeff (p.natDegree - 1) := by
rw [nextCoeff, if_neg]
contrapose! hp
simpa
variable {p q : R[X]} {ι : Type*}
theorem degree_add_le (p q : R[X]) : degree (p + q) ≤ max (degree p) (degree q) := by
simpa only [degree, ← support_toFinsupp, toFinsupp_add]
using AddMonoidAlgebra.sup_support_add_le _ _ _
theorem degree_add_le_of_degree_le {p q : R[X]} {n : ℕ} (hp : degree p ≤ n) (hq : degree q ≤ n) :
degree (p + q) ≤ n :=
(degree_add_le p q).trans <| max_le hp hq
theorem degree_add_le_of_le {a b : WithBot ℕ} (hp : degree p ≤ a) (hq : degree q ≤ b) :
degree (p + q) ≤ max a b :=
(p.degree_add_le q).trans <| max_le_max ‹_› ‹_›
theorem natDegree_add_le (p q : R[X]) : natDegree (p + q) ≤ max (natDegree p) (natDegree q) := by
rcases le_max_iff.1 (degree_add_le p q) with h | h <;> simp [natDegree_le_natDegree h]
theorem natDegree_add_le_of_degree_le {p q : R[X]} {n : ℕ} (hp : natDegree p ≤ n)
(hq : natDegree q ≤ n) : natDegree (p + q) ≤ n :=
(natDegree_add_le p q).trans <| max_le hp hq
theorem natDegree_add_le_of_le (hp : natDegree p ≤ m) (hq : natDegree q ≤ n) :
natDegree (p + q) ≤ max m n :=
(p.natDegree_add_le q).trans <| max_le_max ‹_› ‹_›
@[simp]
theorem leadingCoeff_zero : leadingCoeff (0 : R[X]) = 0 :=
rfl
@[simp]
theorem leadingCoeff_eq_zero : leadingCoeff p = 0 ↔ p = 0 :=
⟨fun h =>
Classical.by_contradiction fun hp =>
mt mem_support_iff.1 (Classical.not_not.2 h) (mem_of_max (degree_eq_natDegree hp)),
fun h => h.symm ▸ leadingCoeff_zero⟩
theorem leadingCoeff_ne_zero : leadingCoeff p ≠ 0 ↔ p ≠ 0 := by rw [Ne, leadingCoeff_eq_zero]
theorem leadingCoeff_eq_zero_iff_deg_eq_bot : leadingCoeff p = 0 ↔ degree p = ⊥ := by
rw [leadingCoeff_eq_zero, degree_eq_bot]
theorem natDegree_C_mul_X_pow_le (a : R) (n : ℕ) : natDegree (C a * X ^ n) ≤ n :=
natDegree_le_iff_degree_le.2 <| degree_C_mul_X_pow_le _ _
theorem degree_erase_le (p : R[X]) (n : ℕ) : degree (p.erase n) ≤ degree p := by
rcases p with ⟨p⟩
simp only [erase_def, degree, coeff, support]
apply sup_mono
rw [Finsupp.support_erase]
apply Finset.erase_subset
theorem degree_erase_lt (hp : p ≠ 0) : degree (p.erase (natDegree p)) < degree p := by
apply lt_of_le_of_ne (degree_erase_le _ _)
rw [degree_eq_natDegree hp, degree, support_erase]
exact fun h => not_mem_erase _ _ (mem_of_max h)
theorem degree_update_le (p : R[X]) (n : ℕ) (a : R) : degree (p.update n a) ≤ max (degree p) n := by
classical
rw [degree, support_update]
split_ifs
· exact (Finset.max_mono (erase_subset _ _)).trans (le_max_left _ _)
· rw [max_insert, max_comm]
exact le_rfl
theorem degree_sum_le (s : Finset ι) (f : ι → R[X]) :
degree (∑ i ∈ s, f i) ≤ s.sup fun b => degree (f b) :=
Finset.cons_induction_on s (by simp only [sum_empty, sup_empty, degree_zero, le_refl])
fun a s has ih =>
calc
degree (∑ i ∈ cons a s has, f i) ≤ max (degree (f a)) (degree (∑ i ∈ s, f i)) := by
rw [Finset.sum_cons]; exact degree_add_le _ _
_ ≤ _ := by rw [sup_cons]; exact max_le_max le_rfl ih
theorem degree_mul_le (p q : R[X]) : degree (p * q) ≤ degree p + degree q := by
simpa only [degree, ← support_toFinsupp, toFinsupp_mul]
using AddMonoidAlgebra.sup_support_mul_le (WithBot.coe_add _ _).le _ _
theorem degree_mul_le_of_le {a b : WithBot ℕ} (hp : degree p ≤ a) (hq : degree q ≤ b) :
degree (p * q) ≤ a + b :=
(p.degree_mul_le _).trans <| add_le_add ‹_› ‹_›
theorem degree_pow_le (p : R[X]) : ∀ n : ℕ, degree (p ^ n) ≤ n • degree p
| 0 => by rw [pow_zero, zero_nsmul]; exact degree_one_le
| n + 1 =>
calc
degree (p ^ (n + 1)) ≤ degree (p ^ n) + degree p := by
rw [pow_succ]; exact degree_mul_le _ _
_ ≤ _ := by rw [succ_nsmul]; exact add_le_add_right (degree_pow_le _ _) _
theorem degree_pow_le_of_le {a : WithBot ℕ} (b : ℕ) (hp : degree p ≤ a) :
degree (p ^ b) ≤ b * a := by
induction b with
| zero => simp [degree_one_le]
| succ n hn =>
rw [Nat.cast_succ, add_mul, one_mul, pow_succ]
exact degree_mul_le_of_le hn hp
@[simp]
theorem leadingCoeff_monomial (a : R) (n : ℕ) : leadingCoeff (monomial n a) = a := by
classical
by_cases ha : a = 0
· simp only [ha, (monomial n).map_zero, leadingCoeff_zero]
· rw [leadingCoeff, natDegree_monomial, if_neg ha, coeff_monomial]
simp
theorem leadingCoeff_C_mul_X_pow (a : R) (n : ℕ) : leadingCoeff (C a * X ^ n) = a := by
rw [C_mul_X_pow_eq_monomial, leadingCoeff_monomial]
theorem leadingCoeff_C_mul_X (a : R) : leadingCoeff (C a * X) = a := by
simpa only [pow_one] using leadingCoeff_C_mul_X_pow a 1
@[simp]
theorem leadingCoeff_C (a : R) : leadingCoeff (C a) = a :=
leadingCoeff_monomial a 0
theorem leadingCoeff_X_pow (n : ℕ) : leadingCoeff ((X : R[X]) ^ n) = 1 := by
simpa only [C_1, one_mul] using leadingCoeff_C_mul_X_pow (1 : R) n
theorem leadingCoeff_X : leadingCoeff (X : R[X]) = 1 := by
simpa only [pow_one] using @leadingCoeff_X_pow R _ 1
@[simp]
theorem monic_X_pow (n : ℕ) : Monic (X ^ n : R[X]) :=
leadingCoeff_X_pow n
@[simp]
theorem monic_X : Monic (X : R[X]) :=
leadingCoeff_X
theorem leadingCoeff_one : leadingCoeff (1 : R[X]) = 1 :=
leadingCoeff_C 1
@[simp]
theorem monic_one : Monic (1 : R[X]) :=
leadingCoeff_C _
theorem Monic.ne_zero {R : Type*} [Semiring R] [Nontrivial R] {p : R[X]} (hp : p.Monic) :
p ≠ 0 := by
rintro rfl
simp [Monic] at hp
theorem Monic.ne_zero_of_ne (h : (0 : R) ≠ 1) {p : R[X]} (hp : p.Monic) : p ≠ 0 := by
nontriviality R
exact hp.ne_zero
theorem Monic.ne_zero_of_polynomial_ne {r} (hp : Monic p) (hne : q ≠ r) : p ≠ 0 :=
haveI := Nontrivial.of_polynomial_ne hne
hp.ne_zero
theorem natDegree_mul_le {p q : R[X]} : natDegree (p * q) ≤ natDegree p + natDegree q := by
apply natDegree_le_of_degree_le
apply le_trans (degree_mul_le p q)
rw [Nat.cast_add]
apply add_le_add <;> apply degree_le_natDegree
theorem natDegree_mul_le_of_le (hp : natDegree p ≤ m) (hg : natDegree q ≤ n) :
natDegree (p * q) ≤ m + n :=
natDegree_mul_le.trans <| add_le_add ‹_› ‹_›
theorem natDegree_pow_le {p : R[X]} {n : ℕ} : (p ^ n).natDegree ≤ n * p.natDegree := by
induction n with
| zero => simp
| succ i hi =>
rw [pow_succ, Nat.succ_mul]
apply le_trans natDegree_mul_le (add_le_add_right hi _)
theorem natDegree_pow_le_of_le (n : ℕ) (hp : natDegree p ≤ m) :
natDegree (p ^ n) ≤ n * m :=
natDegree_pow_le.trans (Nat.mul_le_mul le_rfl ‹_›)
theorem natDegree_eq_zero_iff_degree_le_zero : p.natDegree = 0 ↔ p.degree ≤ 0 := by
rw [← nonpos_iff_eq_zero, natDegree_le_iff_degree_le, Nat.cast_zero]
theorem degree_zero_le : degree (0 : R[X]) ≤ 0 := natDegree_eq_zero_iff_degree_le_zero.mp rfl
theorem degree_le_iff_coeff_zero (f : R[X]) (n : WithBot ℕ) :
degree f ≤ n ↔ ∀ m : ℕ, n < m → coeff f m = 0 := by
simp only [degree, Finset.max, Finset.sup_le_iff, mem_support_iff, Ne, ← not_le,
not_imp_comm, Nat.cast_withBot]
theorem degree_lt_iff_coeff_zero (f : R[X]) (n : ℕ) :
degree f < n ↔ ∀ m : ℕ, n ≤ m → coeff f m = 0 := by
simp only [degree, Finset.sup_lt_iff (WithBot.bot_lt_coe n), mem_support_iff,
WithBot.coe_lt_coe, ← @not_le ℕ, max_eq_sup_coe, Nat.cast_withBot, Ne, not_imp_not]
theorem natDegree_pos_iff_degree_pos : 0 < natDegree p ↔ 0 < degree p :=
lt_iff_lt_of_le_iff_le natDegree_le_iff_degree_le
end Semiring
section NontrivialSemiring
variable [Semiring R] [Nontrivial R] {p q : R[X]} (n : ℕ)
@[simp]
theorem degree_X_pow : degree ((X : R[X]) ^ n) = n := by
rw [X_pow_eq_monomial, degree_monomial _ (one_ne_zero' R)]
@[simp]
theorem natDegree_X_pow : natDegree ((X : R[X]) ^ n) = n :=
natDegree_eq_of_degree_eq_some (degree_X_pow n)
end NontrivialSemiring
section Ring
variable [Ring R] {p q : R[X]}
theorem degree_sub_le (p q : R[X]) : degree (p - q) ≤ max (degree p) (degree q) := by
simpa only [degree_neg q] using degree_add_le p (-q)
theorem degree_sub_le_of_le {a b : WithBot ℕ} (hp : degree p ≤ a) (hq : degree q ≤ b) :
degree (p - q) ≤ max a b :=
(p.degree_sub_le q).trans <| max_le_max ‹_› ‹_›
theorem natDegree_sub_le (p q : R[X]) : natDegree (p - q) ≤ max (natDegree p) (natDegree q) := by
simpa only [← natDegree_neg q] using natDegree_add_le p (-q)
theorem natDegree_sub_le_of_le (hp : natDegree p ≤ m) (hq : natDegree q ≤ n) :
natDegree (p - q) ≤ max m n :=
(p.natDegree_sub_le q).trans <| max_le_max ‹_› ‹_›
theorem degree_sub_lt (hd : degree p = degree q) (hp0 : p ≠ 0)
(hlc : leadingCoeff p = leadingCoeff q) : degree (p - q) < degree p :=
have hp : monomial (natDegree p) (leadingCoeff p) + p.erase (natDegree p) = p :=
monomial_add_erase _ _
have hq : monomial (natDegree q) (leadingCoeff q) + q.erase (natDegree q) = q :=
monomial_add_erase _ _
have hd' : natDegree p = natDegree q := by unfold natDegree; rw [hd]
have hq0 : q ≠ 0 := mt degree_eq_bot.2 (hd ▸ mt degree_eq_bot.1 hp0)
calc
degree (p - q) = degree (erase (natDegree q) p + -erase (natDegree q) q) := by
conv =>
lhs
rw [← hp, ← hq, hlc, hd', add_sub_add_left_eq_sub, sub_eq_add_neg]
_ ≤ max (degree (erase (natDegree q) p)) (degree (erase (natDegree q) q)) :=
(degree_neg (erase (natDegree q) q) ▸ degree_add_le _ _)
_ < degree p := max_lt_iff.2 ⟨hd' ▸ degree_erase_lt hp0, hd.symm ▸ degree_erase_lt hq0⟩
theorem degree_X_sub_C_le (r : R) : (X - C r).degree ≤ 1 :=
(degree_sub_le _ _).trans (max_le degree_X_le (degree_C_le.trans zero_le_one))
theorem natDegree_X_sub_C_le (r : R) : (X - C r).natDegree ≤ 1 :=
natDegree_le_iff_degree_le.2 <| degree_X_sub_C_le r
end Ring
end Polynomial
| Mathlib/Algebra/Polynomial/Degree/Definitions.lean | 1,218 | 1,219 | |
/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.AlgebraicGeometry.Morphisms.Constructors
import Mathlib.RingTheory.LocalProperties.Basic
import Mathlib.RingTheory.RingHom.Locally
/-!
# Properties of morphisms from properties of ring homs.
We provide the basic framework for talking about properties of morphisms that come from properties
of ring homs. For `P` a property of ring homs, we have two ways of defining a property of scheme
morphisms:
Let `f : X ⟶ Y`,
- `targetAffineLocally (affineAnd P)`: the preimage of an affine open `U = Spec A` is affine
(`= Spec B`) and `A ⟶ B` satisfies `P`. (in `Mathlib/AlgebraicGeometry/Morphisms/AffineAnd.lean`)
- `affineLocally P`: For each pair of affine open `U = Spec A ⊆ X` and `V = Spec B ⊆ f ⁻¹' U`,
the ring hom `A ⟶ B` satisfies `P`.
For these notions to be well defined, we require `P` be a sufficient local property. For the former,
`P` should be local on the source (`RingHom.RespectsIso P`, `RingHom.LocalizationPreserves P`,
`RingHom.OfLocalizationSpan`), and `targetAffineLocally (affine_and P)` will be local on
the target.
For the latter `P` should be local on the target (`RingHom.PropertyIsLocal P`), and
`affineLocally P` will be local on both the source and the target.
We also provide the following interface:
## `HasRingHomProperty`
`HasRingHomProperty P Q` is a type class asserting that `P` is local at the target and the source,
and for `f : Spec B ⟶ Spec A`, it is equivalent to the ring hom property `Q` on `Γ(f)`.
For `HasRingHomProperty P Q` and `f : X ⟶ Y`, we provide these API lemmas:
- `AlgebraicGeometry.HasRingHomProperty.iff_appLE`:
`P f` if and only if `Q (f.appLE U V _)` for all affine `U : Opens Y` and `V : Opens X`.
- `AlgebraicGeometry.HasRingHomProperty.iff_of_source_openCover`:
If `Y` is affine, `P f ↔ ∀ i, Q ((𝒰.map i ≫ f).appTop)` for an affine open cover `𝒰` of `X`.
- `AlgebraicGeometry.HasRingHomProperty.iff_of_isAffine`:
If `X` and `Y` are affine, then `P f ↔ Q (f.appTop)`.
- `AlgebraicGeometry.HasRingHomProperty.Spec_iff`:
`P (Spec.map φ) ↔ Q φ`
- `AlgebraicGeometry.HasRingHomProperty.iff_of_iSup_eq_top`:
If `Y` is affine, `P f ↔ ∀ i, Q (f.appLE ⊤ (U i) _)` for a family `U` of affine opens of `X`.
- `AlgebraicGeometry.HasRingHomProperty.of_isOpenImmersion`:
If `f` is an open immersion then `P f`.
- `AlgebraicGeometry.HasRingHomProperty.isStableUnderBaseChange`:
If `Q` is stable under base change, then so is `P`.
We also provide the instances `P.IsMultiplicative`, `P.IsStableUnderComposition`,
`IsLocalAtTarget P`, `IsLocalAtSource P`.
-/
-- Explicit universe annotations were used in this file to improve performance https://github.com/leanprover-community/mathlib4/issues/12737
universe u
open CategoryTheory Opposite TopologicalSpace CategoryTheory.Limits AlgebraicGeometry
namespace RingHom
variable (P : ∀ {R S : Type u} [CommRing R] [CommRing S], (R →+* S) → Prop)
theorem IsStableUnderBaseChange.pullback_fst_appTop
(hP : IsStableUnderBaseChange P) (hP' : RespectsIso P)
{X Y S : Scheme} [IsAffine X] [IsAffine Y] [IsAffine S] (f : X ⟶ S) (g : Y ⟶ S)
(H : P g.appTop.hom) : P (pullback.fst f g).appTop.hom := by
-- Porting note (https://github.com/leanprover-community/mathlib4/issues/11224): change `rw` to `erw`
erw [← PreservesPullback.iso_inv_fst AffineScheme.forgetToScheme (AffineScheme.ofHom f)
(AffineScheme.ofHom g)]
rw [Scheme.comp_appTop, CommRingCat.hom_comp, hP'.cancel_right_isIso,
AffineScheme.forgetToScheme_map]
have := congr_arg Quiver.Hom.unop
(PreservesPullback.iso_hom_fst AffineScheme.Γ.rightOp (AffineScheme.ofHom f)
(AffineScheme.ofHom g))
simp only [AffineScheme.Γ, Functor.rightOp_obj, Functor.comp_obj, Functor.op_obj, unop_comp,
AffineScheme.forgetToScheme_obj, Scheme.Γ_obj, Functor.rightOp_map, Functor.comp_map,
Functor.op_map, Quiver.Hom.unop_op, AffineScheme.forgetToScheme_map, Scheme.Γ_map] at this
rw [← this, CommRingCat.hom_comp, hP'.cancel_right_isIso, ← pushoutIsoUnopPullback_inl_hom,
CommRingCat.hom_comp, hP'.cancel_right_isIso]
exact hP.pushout_inl _ hP' _ _ H
@[deprecated (since := "2024-11-23")]
alias IsStableUnderBaseChange.pullback_fst_app_top :=
IsStableUnderBaseChange.pullback_fst_appTop
end RingHom
namespace AlgebraicGeometry
section affineLocally
variable (P : ∀ {R S : Type u} [CommRing R] [CommRing S], (R →+* S) → Prop)
/-- For `P` a property of ring homomorphisms, `sourceAffineLocally P` holds for `f : X ⟶ Y`
whenever `P` holds for the restriction of `f` on every affine open subset of `X`. -/
def sourceAffineLocally : AffineTargetMorphismProperty := fun X _ f _ =>
∀ U : X.affineOpens, P (f.appLE ⊤ U le_top).hom
/-- For `P` a property of ring homomorphisms, `affineLocally P` holds for `f : X ⟶ Y` if for each
affine open `U = Spec A ⊆ Y` and `V = Spec B ⊆ f ⁻¹' U`, the ring hom `A ⟶ B` satisfies `P`.
Also see `affineLocally_iff_affineOpens_le`. -/
abbrev affineLocally : MorphismProperty Scheme.{u} :=
targetAffineLocally (sourceAffineLocally P)
theorem sourceAffineLocally_respectsIso (h₁ : RingHom.RespectsIso P) :
(sourceAffineLocally P).toProperty.RespectsIso := by
apply AffineTargetMorphismProperty.respectsIso_mk
· introv H U
have : IsIso (e.hom.appLE (e.hom ''ᵁ U) U.1 (e.hom.preimage_image_eq _).ge) :=
inferInstanceAs (IsIso (e.hom.app _ ≫
X.presheaf.map (eqToHom (e.hom.preimage_image_eq _).symm).op))
rw [← Scheme.appLE_comp_appLE _ _ ⊤ (e.hom ''ᵁ U) U.1 le_top (e.hom.preimage_image_eq _).ge,
CommRingCat.hom_comp, h₁.cancel_right_isIso]
exact H ⟨_, U.prop.image_of_isOpenImmersion e.hom⟩
· introv H U
rw [Scheme.comp_appLE, CommRingCat.hom_comp, h₁.cancel_left_isIso]
exact H U
theorem affineLocally_respectsIso (h : RingHom.RespectsIso P) : (affineLocally P).RespectsIso :=
letI := sourceAffineLocally_respectsIso P h
inferInstance
open Scheme in
theorem sourceAffineLocally_morphismRestrict {X Y : Scheme.{u}} (f : X ⟶ Y)
(U : Y.Opens) (hU : IsAffineOpen U) :
@sourceAffineLocally P _ _ (f ∣_ U) hU ↔
∀ (V : X.affineOpens) (e : V.1 ≤ f ⁻¹ᵁ U), P (f.appLE U V e).hom := by
dsimp only [sourceAffineLocally]
simp only [morphismRestrict_appLE]
rw [(affineOpensRestrict (f ⁻¹ᵁ U)).forall_congr_left, Subtype.forall]
refine forall₂_congr fun V h ↦ ?_
have := (affineOpensRestrict (f ⁻¹ᵁ U)).apply_symm_apply ⟨V, h⟩
exact f.appLE_congr _ (Opens.ι_image_top _) congr($(this).1.1) (fun f => P f.hom)
theorem affineLocally_iff_affineOpens_le {X Y : Scheme.{u}} (f : X ⟶ Y) :
affineLocally.{u} P f ↔
∀ (U : Y.affineOpens) (V : X.affineOpens) (e : V.1 ≤ f ⁻¹ᵁ U.1), P (f.appLE U V e).hom :=
forall_congr' fun U ↦ sourceAffineLocally_morphismRestrict P f U U.2
theorem sourceAffineLocally_isLocal (h₁ : RingHom.RespectsIso P)
(h₂ : RingHom.LocalizationAwayPreserves P) (h₃ : RingHom.OfLocalizationSpan P) :
(sourceAffineLocally P).IsLocal := by
constructor
· exact sourceAffineLocally_respectsIso P h₁
· intro X Y _ f r H
rw [sourceAffineLocally_morphismRestrict]
intro U hU
have : X.basicOpen (f.appLE ⊤ U (by simp) r) = U := by
simp only [Scheme.Hom.appLE, Opens.map_top, CommRingCat.comp_apply, RingHom.coe_comp,
Function.comp_apply]
rw [Scheme.basicOpen_res]
simpa using hU
rw [← f.appLE_congr _ rfl this (fun f => P f.hom),
IsAffineOpen.appLE_eq_away_map f (isAffineOpen_top Y) U.2 _ r]
simp only [CommRingCat.hom_ofHom]
apply (config := { allowSynthFailures := true }) h₂
exact H U
· introv hs hs' U
apply h₃ _ _ hs
intro r
simp_rw [sourceAffineLocally_morphismRestrict] at hs'
have := hs' r ⟨X.basicOpen (f.appLE ⊤ U le_top r.1), U.2.basicOpen (f.appLE ⊤ U le_top r.1)⟩
(by simp [Scheme.Hom.appLE])
rwa [IsAffineOpen.appLE_eq_away_map f (isAffineOpen_top Y) U.2, CommRingCat.hom_ofHom,
← h₁.isLocalization_away_iff] at this
variable {P}
lemma affineLocally_le {Q : ∀ {R S : Type u} [CommRing R] [CommRing S], (R →+* S) → Prop}
(hPQ : ∀ {R S : Type u} [CommRing R] [CommRing S] {f : R →+* S}, P f → Q f) :
affineLocally P ≤ affineLocally Q :=
fun _ _ _ hf U V ↦ hPQ (hf U V)
open RingHom
variable {X Y : Scheme.{u}} {f : X ⟶ Y}
/-- If `P` holds for `f` over affine opens `U₂` of `Y` and `V₂` of `X` and `U₁` (resp. `V₁`) are
open affine neighborhoods of `x` (resp. `f.base x`), then `P` also holds for `f`
over some basic open of `U₁` (resp. `V₁`). -/
lemma exists_basicOpen_le_appLE_of_appLE_of_isAffine
(hPa : StableUnderCompositionWithLocalizationAwayTarget P) (hPl : LocalizationAwayPreserves P)
(x : X) (U₁ : Y.affineOpens) (U₂ : Y.affineOpens) (V₁ : X.affineOpens) (V₂ : X.affineOpens)
(hx₁ : x ∈ V₁.1) (hx₂ : x ∈ V₂.1) (e₂ : V₂.1 ≤ f ⁻¹ᵁ U₂.1) (h₂ : P (f.appLE U₂ V₂ e₂).hom)
(hfx₁ : f.base x ∈ U₁.1) :
∃ (r : Γ(Y, U₁)) (s : Γ(X, V₁)) (_ : x ∈ X.basicOpen s)
(e : X.basicOpen s ≤ f ⁻¹ᵁ Y.basicOpen r),
P (f.appLE (Y.basicOpen r) (X.basicOpen s) e).hom := by
obtain ⟨r, r', hBrr', hBfx⟩ := exists_basicOpen_le_affine_inter U₁.2 U₂.2 (f.base x)
⟨hfx₁, e₂ hx₂⟩
have ha : IsAffineOpen (X.basicOpen (f.appLE U₂ V₂ e₂ r')) := V₂.2.basicOpen _
have hxa : x ∈ X.basicOpen (f.appLE U₂ V₂ e₂ r') := by
simpa [Scheme.Hom.appLE, ← Scheme.preimage_basicOpen] using And.intro hx₂ (hBrr' ▸ hBfx)
obtain ⟨s, s', hBss', hBx⟩ := exists_basicOpen_le_affine_inter V₁.2 ha x ⟨hx₁, hxa⟩
haveI := V₂.2.isLocalization_basicOpen (f.appLE U₂ V₂ e₂ r')
haveI := U₂.2.isLocalization_basicOpen r'
haveI := ha.isLocalization_basicOpen s'
have ers : X.basicOpen s ≤ f ⁻¹ᵁ Y.basicOpen r := by
rw [hBss', hBrr']
apply le_trans (X.basicOpen_le _)
simp [Scheme.Hom.appLE]
have heq : f.appLE (Y.basicOpen r') (X.basicOpen s') (hBrr' ▸ hBss' ▸ ers) =
f.appLE (Y.basicOpen r') (X.basicOpen (f.appLE U₂ V₂ e₂ r')) (by simp [Scheme.Hom.appLE]) ≫
CommRingCat.ofHom (algebraMap _ _) := by
simp only [Scheme.Hom.appLE, homOfLE_leOfHom, CommRingCat.comp_apply, Category.assoc]
congr
apply X.presheaf.map_comp
refine ⟨r, s, hBx, ers, ?_⟩
· rw [f.appLE_congr _ hBrr' hBss' (fun f => P f.hom), heq]
apply hPa _ s' _
rw [U₂.2.appLE_eq_away_map f V₂.2]
exact hPl _ _ _ _ h₂
/-- If `P` holds for `f` over affine opens `U₂` of `Y` and `V₂` of `X` and `U₁` (resp. `V₁`) are
open neighborhoods of `x` (resp. `f.base x`), then `P` also holds for `f` over some affine open
`U'` of `Y` (resp. `V'` of `X`) that is contained in `U₁` (resp. `V₁`). -/
lemma exists_affineOpens_le_appLE_of_appLE
(hPa : StableUnderCompositionWithLocalizationAwayTarget P) (hPl : LocalizationAwayPreserves P)
(x : X) (U₁ : Y.Opens) (U₂ : Y.affineOpens) (V₁ : X.Opens) (V₂ : X.affineOpens)
(hx₁ : x ∈ V₁) (hx₂ : x ∈ V₂.1) (e₂ : V₂.1 ≤ f ⁻¹ᵁ U₂.1) (h₂ : P (f.appLE U₂ V₂ e₂).hom)
(hfx₁ : f.base x ∈ U₁.1) :
∃ (U' : Y.affineOpens) (V' : X.affineOpens) (_ : U'.1 ≤ U₁) (_ : V'.1 ≤ V₁) (_ : x ∈ V'.1)
(e : V'.1 ≤ f⁻¹ᵁ U'.1), P (f.appLE U' V' e).hom := by
obtain ⟨r, hBr, hBfx⟩ := U₂.2.exists_basicOpen_le ⟨f.base x, hfx₁⟩ (e₂ hx₂)
obtain ⟨s, hBs, hBx⟩ := V₂.2.exists_basicOpen_le ⟨x, hx₁⟩ hx₂
obtain ⟨r', s', hBx', e', hf'⟩ := exists_basicOpen_le_appLE_of_appLE_of_isAffine hPa hPl x
⟨Y.basicOpen r, U₂.2.basicOpen _⟩ U₂ ⟨X.basicOpen s, V₂.2.basicOpen _⟩ V₂ hBx hx₂ e₂ h₂ hBfx
exact ⟨⟨Y.basicOpen r', (U₂.2.basicOpen _).basicOpen _⟩,
⟨X.basicOpen s', (V₂.2.basicOpen _).basicOpen _⟩, le_trans (Y.basicOpen_le _) hBr,
le_trans (X.basicOpen_le _) hBs, hBx', e', hf'⟩
end affineLocally
/--
`HasRingHomProperty P Q` is a type class asserting that `P` is local at the target and the source,
and for `f : Spec B ⟶ Spec A`, it is equivalent to the ring hom property `Q`.
To make the proofs easier, we state it instead as
1. `Q` is local (See `RingHom.PropertyIsLocal`)
2. `P f` if and only if `Q` holds for every `Γ(Y, U) ⟶ Γ(X, V)` for all affine `U`, `V`.
See `HasRingHomProperty.iff_appLE`.
-/
class HasRingHomProperty (P : MorphismProperty Scheme.{u})
(Q : outParam (∀ {R S : Type u} [CommRing R] [CommRing S], (R →+* S) → Prop)) : Prop where
isLocal_ringHomProperty : RingHom.PropertyIsLocal Q
eq_affineLocally' : P = affineLocally Q
namespace HasRingHomProperty
variable (P : MorphismProperty Scheme.{u}) {Q} [HasRingHomProperty P Q]
variable {X Y Z : Scheme.{u}} (f : X ⟶ Y) (g : Y ⟶ Z)
lemma copy {P' : MorphismProperty Scheme.{u}}
{Q' : ∀ {R S : Type u} [CommRing R] [CommRing S], (R →+* S) → Prop}
(e : P = P') (e' : ∀ {R S : Type u} [CommRing R] [CommRing S] (f : R →+* S), Q f ↔ Q' f) :
HasRingHomProperty P' Q' := by
subst e
have heq : @Q = @Q' := by
ext R S _ _ f
exact (e' f)
rw [← heq]
infer_instance
lemma eq_affineLocally : P = affineLocally Q := eq_affineLocally'
@[local instance]
lemma HasAffineProperty : HasAffineProperty P (sourceAffineLocally Q) where
isLocal_affineProperty := sourceAffineLocally_isLocal _
(isLocal_ringHomProperty P).respectsIso
(isLocal_ringHomProperty P).localizationAwayPreserves
(isLocal_ringHomProperty P).ofLocalizationSpan
eq_targetAffineLocally' := eq_affineLocally P
/- This is only `inferInstance` because of the `@[local instance]` on `HasAffineProperty` above. -/
instance (priority := 900) : IsLocalAtTarget P := inferInstance
theorem appLE (H : P f) (U : Y.affineOpens) (V : X.affineOpens) (e) : Q (f.appLE U V e).hom := by
rw [eq_affineLocally P, affineLocally_iff_affineOpens_le] at H
exact H _ _ _
theorem appTop (H : P f) [IsAffine X] [IsAffine Y] : Q f.appTop.hom := by
rw [Scheme.Hom.appTop, Scheme.Hom.app_eq_appLE]
exact appLE P f H ⟨_, isAffineOpen_top _⟩ ⟨_, isAffineOpen_top _⟩ _
|
@[deprecated (since := "2024-11-23")] alias app_top := appTop
include Q in
theorem comp_of_isOpenImmersion [IsOpenImmersion f] (H : P g) :
P (f ≫ g) := by
rw [eq_affineLocally P, affineLocally_iff_affineOpens_le] at H ⊢
intro U V e
have : IsIso (f.appLE (f ''ᵁ V) V.1 (f.preimage_image_eq _).ge) :=
inferInstanceAs (IsIso (f.app _ ≫
X.presheaf.map (eqToHom (f.preimage_image_eq _).symm).op))
rw [← Scheme.appLE_comp_appLE _ _ _ (f ''ᵁ V) V.1
(Set.image_subset_iff.mpr e) (f.preimage_image_eq _).ge,
CommRingCat.hom_comp,
(isLocal_ringHomProperty P).respectsIso.cancel_right_isIso]
exact H _ ⟨_, V.2.image_of_isOpenImmersion _⟩ _
variable {P f}
lemma iff_appLE : P f ↔ ∀ (U : Y.affineOpens) (V : X.affineOpens) (e), Q (f.appLE U V e).hom := by
rw [eq_affineLocally P, affineLocally_iff_affineOpens_le]
theorem of_source_openCover [IsAffine Y]
(𝒰 : X.OpenCover) [∀ i, IsAffine (𝒰.obj i)] (H : ∀ i, Q ((𝒰.map i ≫ f).appTop.hom)) :
P f := by
rw [HasAffineProperty.iff_of_isAffine (P := P)]
intro U
let S i : X.affineOpens := ⟨_, isAffineOpen_opensRange (𝒰.map i)⟩
induction U using of_affine_open_cover S 𝒰.iSup_opensRange with
| basicOpen U r H =>
simp_rw [Scheme.affineBasicOpen_coe,
← f.appLE_map (U := ⊤) le_top (homOfLE (X.basicOpen_le r)).op]
have := U.2.isLocalization_basicOpen r
exact (isLocal_ringHomProperty P).StableUnderCompositionWithLocalizationAwayTarget _ r _ H
| openCover U s hs H =>
apply (isLocal_ringHomProperty P).ofLocalizationSpanTarget.ofIsLocalization
(isLocal_ringHomProperty P).respectsIso _ _ hs
rintro r
refine ⟨_, _, _, IsAffineOpen.isLocalization_basicOpen U.2 r, ?_⟩
rw [RingHom.algebraMap_toAlgebra, ← CommRingCat.hom_comp, Scheme.Hom.appLE_map]
exact H r
| hU i =>
specialize H i
rw [← (isLocal_ringHomProperty P).respectsIso.cancel_right_isIso _
((IsOpenImmersion.isoOfRangeEq (𝒰.map i) (S i).1.ι
Subtype.range_coe.symm).inv.app _), ← CommRingCat.hom_comp, ← Scheme.comp_appTop,
IsOpenImmersion.isoOfRangeEq_inv_fac_assoc, Scheme.comp_appTop,
Scheme.Opens.ι_appTop, Scheme.Hom.appTop, Scheme.Hom.app_eq_appLE, Scheme.Hom.appLE_map] at H
exact (f.appLE_congr _ rfl (by simp) (fun f => Q f.hom)).mp H
theorem iff_of_source_openCover [IsAffine Y] (𝒰 : X.OpenCover) [∀ i, IsAffine (𝒰.obj i)] :
P f ↔ ∀ i, Q ((𝒰.map i ≫ f).appTop).hom :=
⟨fun H i ↦ appTop P _ (comp_of_isOpenImmersion P (𝒰.map i) f H), of_source_openCover 𝒰⟩
theorem iff_of_isAffine [IsAffine X] [IsAffine Y] :
| Mathlib/AlgebraicGeometry/Morphisms/RingHomProperties.lean | 289 | 343 |
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Polynomial.Expand
import Mathlib.Algebra.Polynomial.Splits
import Mathlib.Algebra.Squarefree.Basic
import Mathlib.FieldTheory.IntermediateField.Basic
import Mathlib.FieldTheory.Minpoly.Field
import Mathlib.RingTheory.Polynomial.Content
import Mathlib.RingTheory.PowerBasis
import Mathlib.Data.ENat.Lattice
/-!
# Separable polynomials
We define a polynomial to be separable if it is coprime with its derivative. We prove basic
properties about separable polynomials here.
## Main definitions
* `Polynomial.Separable f`: a polynomial `f` is separable iff it is coprime with its derivative.
* `IsSeparable K x`: an element `x` is separable over `K` iff the minimal polynomial of `x`
over `K` is separable.
* `Algebra.IsSeparable K L`: `L` is separable over `K` iff every element in `L` is separable
over `K`.
-/
universe u v w
open Polynomial Finset
namespace Polynomial
section CommSemiring
variable {R : Type u} [CommSemiring R] {S : Type v} [CommSemiring S]
/-- A polynomial is separable iff it is coprime with its derivative. -/
@[stacks 09H1 "first part"]
def Separable (f : R[X]) : Prop :=
IsCoprime f (derivative f)
theorem separable_def (f : R[X]) : f.Separable ↔ IsCoprime f (derivative f) :=
Iff.rfl
theorem separable_def' (f : R[X]) : f.Separable ↔ ∃ a b : R[X], a * f + b * (derivative f) = 1 :=
Iff.rfl
theorem not_separable_zero [Nontrivial R] : ¬Separable (0 : R[X]) := by
rintro ⟨x, y, h⟩
simp only [derivative_zero, mul_zero, add_zero, zero_ne_one] at h
theorem Separable.ne_zero [Nontrivial R] {f : R[X]} (h : f.Separable) : f ≠ 0 :=
(not_separable_zero <| · ▸ h)
@[simp]
theorem separable_one : (1 : R[X]).Separable :=
isCoprime_one_left
@[nontriviality]
theorem separable_of_subsingleton [Subsingleton R] (f : R[X]) : f.Separable := by
simp [Separable, IsCoprime, eq_iff_true_of_subsingleton]
theorem separable_X_add_C (a : R) : (X + C a).Separable := by
rw [separable_def, derivative_add, derivative_X, derivative_C, add_zero]
exact isCoprime_one_right
theorem separable_X : (X : R[X]).Separable := by
rw [separable_def, derivative_X]
exact isCoprime_one_right
theorem separable_C (r : R) : (C r).Separable ↔ IsUnit r := by
rw [separable_def, derivative_C, isCoprime_zero_right, isUnit_C]
theorem Separable.of_mul_left {f g : R[X]} (h : (f * g).Separable) : f.Separable := by
have := h.of_mul_left_left; rw [derivative_mul] at this
exact IsCoprime.of_mul_right_left (IsCoprime.of_add_mul_left_right this)
theorem Separable.of_mul_right {f g : R[X]} (h : (f * g).Separable) : g.Separable := by
rw [mul_comm] at h
exact h.of_mul_left
theorem Separable.of_dvd {f g : R[X]} (hf : f.Separable) (hfg : g ∣ f) : g.Separable := by
rcases hfg with ⟨f', rfl⟩
exact Separable.of_mul_left hf
theorem separable_gcd_left {F : Type*} [Field F] [DecidableEq F[X]]
{f : F[X]} (hf : f.Separable) (g : F[X]) :
(EuclideanDomain.gcd f g).Separable :=
Separable.of_dvd hf (EuclideanDomain.gcd_dvd_left f g)
theorem separable_gcd_right {F : Type*} [Field F] [DecidableEq F[X]]
{g : F[X]} (f : F[X]) (hg : g.Separable) :
(EuclideanDomain.gcd f g).Separable :=
Separable.of_dvd hg (EuclideanDomain.gcd_dvd_right f g)
theorem Separable.isCoprime {f g : R[X]} (h : (f * g).Separable) : IsCoprime f g := by
have := h.of_mul_left_left; rw [derivative_mul] at this
exact IsCoprime.of_mul_right_right (IsCoprime.of_add_mul_left_right this)
theorem Separable.of_pow' {f : R[X]} :
∀ {n : ℕ} (_h : (f ^ n).Separable), IsUnit f ∨ f.Separable ∧ n = 1 ∨ n = 0
| 0 => fun _h => Or.inr <| Or.inr rfl
| 1 => fun h => Or.inr <| Or.inl ⟨pow_one f ▸ h, rfl⟩
| n + 2 => fun h => by
rw [pow_succ, pow_succ] at h
exact Or.inl (isCoprime_self.1 h.isCoprime.of_mul_left_right)
theorem Separable.of_pow {f : R[X]} (hf : ¬IsUnit f) {n : ℕ} (hn : n ≠ 0)
(hfs : (f ^ n).Separable) : f.Separable ∧ n = 1 :=
(hfs.of_pow'.resolve_left hf).resolve_right hn
theorem Separable.map {p : R[X]} (h : p.Separable) {f : R →+* S} : (p.map f).Separable :=
let ⟨a, b, H⟩ := h
⟨a.map f, b.map f, by
rw [derivative_map, ← Polynomial.map_mul, ← Polynomial.map_mul, ← Polynomial.map_add, H,
Polynomial.map_one]⟩
theorem _root_.Associated.separable {f g : R[X]}
(ha : Associated f g) (h : f.Separable) : g.Separable := by
obtain ⟨⟨u, v, h1, h2⟩, ha⟩ := ha
obtain ⟨a, b, h⟩ := h
refine ⟨a * v + b * derivative v, b * v, ?_⟩
replace h := congr($h * $(h1))
have h3 := congr(derivative $(h1))
simp only [← ha, derivative_mul, derivative_one] at h3 ⊢
calc
_ = (a * f + b * derivative f) * (u * v)
+ (b * f) * (derivative u * v + u * derivative v) := by ring1
_ = 1 := by rw [h, h3]; ring1
theorem _root_.Associated.separable_iff {f g : R[X]}
(ha : Associated f g) : f.Separable ↔ g.Separable := ⟨ha.separable, ha.symm.separable⟩
theorem Separable.mul_unit {f g : R[X]} (hf : f.Separable) (hg : IsUnit g) : (f * g).Separable :=
(associated_mul_unit_right f g hg).separable hf
theorem Separable.unit_mul {f g : R[X]} (hf : IsUnit f) (hg : g.Separable) : (f * g).Separable :=
(associated_unit_mul_right g f hf).separable hg
theorem Separable.eval₂_derivative_ne_zero [Nontrivial S] (f : R →+* S) {p : R[X]}
(h : p.Separable) {x : S} (hx : p.eval₂ f x = 0) :
(derivative p).eval₂ f x ≠ 0 := by
intro hx'
obtain ⟨a, b, e⟩ := h
apply_fun Polynomial.eval₂ f x at e
simp only [eval₂_add, eval₂_mul, hx, mul_zero, hx', add_zero, eval₂_one, zero_ne_one] at e
theorem Separable.aeval_derivative_ne_zero [Nontrivial S] [Algebra R S] {p : R[X]}
(h : p.Separable) {x : S} (hx : aeval x p = 0) :
aeval x (derivative p) ≠ 0 :=
h.eval₂_derivative_ne_zero (algebraMap R S) hx
variable (p q : ℕ)
theorem isUnit_of_self_mul_dvd_separable {p q : R[X]} (hp : p.Separable) (hq : q * q ∣ p) :
IsUnit q := by
obtain ⟨p, rfl⟩ := hq
apply isCoprime_self.mp
have : IsCoprime (q * (q * p))
(q * (derivative q * p + derivative q * p + q * derivative p)) := by
simp only [← mul_assoc, mul_add]
dsimp only [Separable] at hp
convert hp using 1
rw [derivative_mul, derivative_mul]
ring
exact IsCoprime.of_mul_right_left (IsCoprime.of_mul_left_left this)
theorem emultiplicity_le_one_of_separable {p q : R[X]} (hq : ¬IsUnit q) (hsep : Separable p) :
emultiplicity q p ≤ 1 := by
contrapose! hq
apply isUnit_of_self_mul_dvd_separable hsep
rw [← sq]
apply pow_dvd_of_le_emultiplicity
exact Order.add_one_le_of_lt hq
/-- A separable polynomial is square-free.
See `PerfectField.separable_iff_squarefree` for the converse when the coefficients are a perfect
field. -/
theorem Separable.squarefree {p : R[X]} (hsep : Separable p) : Squarefree p := by
classical
rw [squarefree_iff_emultiplicity_le_one p]
exact fun f => or_iff_not_imp_right.mpr fun hunit => emultiplicity_le_one_of_separable hunit hsep
end CommSemiring
section CommRing
variable {R : Type u} [CommRing R]
theorem separable_X_sub_C {x : R} : Separable (X - C x) := by
simpa only [sub_eq_add_neg, C_neg] using separable_X_add_C (-x)
theorem Separable.mul {f g : R[X]} (hf : f.Separable) (hg : g.Separable) (h : IsCoprime f g) :
(f * g).Separable := by
rw [separable_def, derivative_mul]
exact
((hf.mul_right h).add_mul_left_right _).mul_left ((h.symm.mul_right hg).mul_add_right_right _)
theorem separable_prod' {ι : Sort _} {f : ι → R[X]} {s : Finset ι} :
(∀ x ∈ s, ∀ y ∈ s, x ≠ y → IsCoprime (f x) (f y)) →
(∀ x ∈ s, (f x).Separable) → (∏ x ∈ s, f x).Separable := by
classical
exact Finset.induction_on s (fun _ _ => separable_one) fun a s has ih h1 h2 => by
simp_rw [Finset.forall_mem_insert, forall_and] at h1 h2; rw [prod_insert has]
exact
h2.1.mul (ih h1.2.2 h2.2)
(IsCoprime.prod_right fun i his => h1.1.2 i his <| Ne.symm <| ne_of_mem_of_not_mem his has)
open scoped Function in -- required for scoped `on` notation
theorem separable_prod {ι : Sort _} [Fintype ι] {f : ι → R[X]} (h1 : Pairwise (IsCoprime on f))
(h2 : ∀ x, (f x).Separable) : (∏ x, f x).Separable :=
separable_prod' (fun _x _hx _y _hy hxy => h1 hxy) fun x _hx => h2 x
theorem Separable.inj_of_prod_X_sub_C [Nontrivial R] {ι : Sort _} {f : ι → R} {s : Finset ι}
(hfs : (∏ i ∈ s, (X - C (f i))).Separable) {x y : ι} (hx : x ∈ s) (hy : y ∈ s)
(hfxy : f x = f y) : x = y := by
classical
by_contra hxy
rw [← insert_erase hx, prod_insert (not_mem_erase _ _), ←
insert_erase (mem_erase_of_ne_of_mem (Ne.symm hxy) hy), prod_insert (not_mem_erase _ _), ←
mul_assoc, hfxy, ← sq] at hfs
cases (hfs.of_mul_left.of_pow (not_isUnit_X_sub_C _) two_ne_zero).2
theorem Separable.injective_of_prod_X_sub_C [Nontrivial R] {ι : Sort _} [Fintype ι] {f : ι → R}
(hfs : (∏ i, (X - C (f i))).Separable) : Function.Injective f := fun _x _y hfxy =>
hfs.inj_of_prod_X_sub_C (mem_univ _) (mem_univ _) hfxy
theorem nodup_of_separable_prod [Nontrivial R] {s : Multiset R}
(hs : Separable (Multiset.map (fun a => X - C a) s).prod) : s.Nodup := by
rw [Multiset.nodup_iff_ne_cons_cons]
rintro a t rfl
refine not_isUnit_X_sub_C a (isUnit_of_self_mul_dvd_separable hs ?_)
simpa only [Multiset.map_cons, Multiset.prod_cons] using mul_dvd_mul_left _ (dvd_mul_right _ _)
/-- If `IsUnit n` in a `CommRing R`, then `X ^ n - u` is separable for any unit `u`. -/
theorem separable_X_pow_sub_C_unit {n : ℕ} (u : Rˣ) (hn : IsUnit (n : R)) :
Separable (X ^ n - C (u : R)) := by
nontriviality R
rcases n.eq_zero_or_pos with (rfl | hpos)
· simp at hn
apply (separable_def' (X ^ n - C (u : R))).2
obtain ⟨n', hn'⟩ := hn.exists_left_inv
refine ⟨-C ↑u⁻¹, C (↑u⁻¹ : R) * C n' * X, ?_⟩
rw [derivative_sub, derivative_C, sub_zero, derivative_pow X n, derivative_X, mul_one]
calc
-C ↑u⁻¹ * (X ^ n - C ↑u) + C ↑u⁻¹ * C n' * X * (↑n * X ^ (n - 1)) =
C (↑u⁻¹ * ↑u) - C ↑u⁻¹ * X ^ n + C ↑u⁻¹ * C (n' * ↑n) * (X * X ^ (n - 1)) := by
simp only [C.map_mul, C_eq_natCast]
ring
_ = 1 := by
simp only [Units.inv_mul, hn', C.map_one, mul_one, ← pow_succ',
Nat.sub_add_cancel (show 1 ≤ n from hpos), sub_add_cancel]
/-- If `n = 0` in `R` and `b` is a unit, then `a * X ^ n + b * X + c` is separable. -/
theorem separable_C_mul_X_pow_add_C_mul_X_add_C
{n : ℕ} (a b c : R) (hn : (n : R) = 0) (hb : IsUnit b) :
(C a * X ^ n + C b * X + C c).Separable := by
set f := C a * X ^ n + C b * X + C c
obtain ⟨e, hb⟩ := hb.exists_left_inv
refine ⟨-derivative f, f + C e, ?_⟩
have hderiv : derivative f = C b := by
simp [hn, f, map_add derivative, derivative_C, derivative_X_pow]
rw [hderiv, right_distrib, ← add_assoc, neg_mul, mul_comm, neg_add_cancel, zero_add,
← map_mul, hb, map_one]
/-- If `R` is of characteristic `p`, `p ∣ n` and `b` is a unit,
then `a * X ^ n + b * X + c` is separable. -/
theorem separable_C_mul_X_pow_add_C_mul_X_add_C'
(p n : ℕ) (a b c : R) [CharP R p] (hn : p ∣ n) (hb : IsUnit b) :
(C a * X ^ n + C b * X + C c).Separable :=
separable_C_mul_X_pow_add_C_mul_X_add_C a b c ((CharP.cast_eq_zero_iff R p n).2 hn) hb
theorem rootMultiplicity_le_one_of_separable [Nontrivial R] {p : R[X]} (hsep : Separable p)
(x : R) : rootMultiplicity x p ≤ 1 := by
classical
by_cases hp : p = 0
· simp [hp]
rw [rootMultiplicity_eq_multiplicity, if_neg hp, ← Nat.cast_le (α := ℕ∞),
Nat.cast_one, ← (finiteMultiplicity_X_sub_C x hp).emultiplicity_eq_multiplicity]
apply emultiplicity_le_one_of_separable (not_isUnit_X_sub_C _) hsep
end CommRing
section IsDomain
variable {R : Type u} [CommRing R] [IsDomain R]
theorem count_roots_le_one [DecidableEq R] {p : R[X]} (hsep : Separable p) (x : R) :
p.roots.count x ≤ 1 := by
rw [count_roots p]
exact rootMultiplicity_le_one_of_separable hsep x
theorem nodup_roots {p : R[X]} (hsep : Separable p) : p.roots.Nodup := by
classical
exact Multiset.nodup_iff_count_le_one.mpr (count_roots_le_one hsep)
|
end IsDomain
| Mathlib/FieldTheory/Separable.lean | 303 | 305 |
/-
Copyright (c) 2018 Robert Y. Lewis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Robert Y. Lewis
-/
import Mathlib.RingTheory.Valuation.Basic
import Mathlib.NumberTheory.Padics.PadicNorm
import Mathlib.Analysis.Normed.Field.Lemmas
import Mathlib.Tactic.Peel
import Mathlib.Topology.MetricSpace.Ultra.Basic
/-!
# p-adic numbers
This file defines the `p`-adic numbers (rationals) `ℚ_[p]` as
the completion of `ℚ` with respect to the `p`-adic norm.
We show that the `p`-adic norm on `ℚ` extends to `ℚ_[p]`, that `ℚ` is embedded in `ℚ_[p]`,
and that `ℚ_[p]` is Cauchy complete.
## Important definitions
* `Padic` : the type of `p`-adic numbers
* `padicNormE` : the rational valued `p`-adic norm on `ℚ_[p]`
* `Padic.addValuation` : the additive `p`-adic valuation on `ℚ_[p]`, with values in `WithTop ℤ`
## Notation
We introduce the notation `ℚ_[p]` for the `p`-adic numbers.
## Implementation notes
Much, but not all, of this file assumes that `p` is prime. This assumption is inferred automatically
by taking `[Fact p.Prime]` as a type class argument.
We use the same concrete Cauchy sequence construction that is used to construct `ℝ`.
`ℚ_[p]` inherits a field structure from this construction.
The extension of the norm on `ℚ` to `ℚ_[p]` is *not* analogous to extending the absolute value to
`ℝ` and hence the proof that `ℚ_[p]` is complete is different from the proof that ℝ is complete.
`padicNormE` is the rational-valued `p`-adic norm on `ℚ_[p]`.
To instantiate `ℚ_[p]` as a normed field, we must cast this into an `ℝ`-valued norm.
The `ℝ`-valued norm, using notation `‖ ‖` from normed spaces,
is the canonical representation of this norm.
`simp` prefers `padicNorm` to `padicNormE` when possible.
Since `padicNormE` and `‖ ‖` have different types, `simp` does not rewrite one to the other.
Coercions from `ℚ` to `ℚ_[p]` are set up to work with the `norm_cast` tactic.
## References
* [F. Q. Gouvêa, *p-adic numbers*][gouvea1997]
* [R. Y. Lewis, *A formal proof of Hensel's lemma over the p-adic integers*][lewis2019]
* <https://en.wikipedia.org/wiki/P-adic_number>
## Tags
p-adic, p adic, padic, norm, valuation, cauchy, completion, p-adic completion
-/
noncomputable section
open Nat padicNorm CauSeq CauSeq.Completion Metric
/-- The type of Cauchy sequences of rationals with respect to the `p`-adic norm. -/
abbrev PadicSeq (p : ℕ) :=
CauSeq _ (padicNorm p)
namespace PadicSeq
section
variable {p : ℕ} [Fact p.Prime]
/-- The `p`-adic norm of the entries of a nonzero Cauchy sequence of rationals is eventually
constant. -/
theorem stationary {f : CauSeq ℚ (padicNorm p)} (hf : ¬f ≈ 0) :
∃ N, ∀ m n, N ≤ m → N ≤ n → padicNorm p (f n) = padicNorm p (f m) :=
have : ∃ ε > 0, ∃ N1, ∀ j ≥ N1, ε ≤ padicNorm p (f j) :=
CauSeq.abv_pos_of_not_limZero <| not_limZero_of_not_congr_zero hf
let ⟨ε, hε, N1, hN1⟩ := this
let ⟨N2, hN2⟩ := CauSeq.cauchy₂ f hε
⟨max N1 N2, fun n m hn hm ↦ by
have : padicNorm p (f n - f m) < ε := hN2 _ (max_le_iff.1 hn).2 _ (max_le_iff.1 hm).2
have : padicNorm p (f n - f m) < padicNorm p (f n) :=
lt_of_lt_of_le this <| hN1 _ (max_le_iff.1 hn).1
have : padicNorm p (f n - f m) < max (padicNorm p (f n)) (padicNorm p (f m)) :=
lt_max_iff.2 (Or.inl this)
by_contra hne
rw [← padicNorm.neg (f m)] at hne
have hnam := add_eq_max_of_ne hne
rw [padicNorm.neg, max_comm] at hnam
rw [← hnam, sub_eq_add_neg, add_comm] at this
apply _root_.lt_irrefl _ this⟩
/-- For all `n ≥ stationaryPoint f hf`, the `p`-adic norm of `f n` is the same. -/
def stationaryPoint {f : PadicSeq p} (hf : ¬f ≈ 0) : ℕ :=
Classical.choose <| stationary hf
theorem stationaryPoint_spec {f : PadicSeq p} (hf : ¬f ≈ 0) :
∀ {m n},
stationaryPoint hf ≤ m → stationaryPoint hf ≤ n → padicNorm p (f n) = padicNorm p (f m) :=
@(Classical.choose_spec <| stationary hf)
open Classical in
/-- Since the norm of the entries of a Cauchy sequence is eventually stationary,
we can lift the norm to sequences. -/
def norm (f : PadicSeq p) : ℚ :=
if hf : f ≈ 0 then 0 else padicNorm p (f (stationaryPoint hf))
theorem norm_zero_iff (f : PadicSeq p) : f.norm = 0 ↔ f ≈ 0 := by
constructor
· intro h
by_contra hf
unfold norm at h
split_ifs at h
apply hf
intro ε hε
exists stationaryPoint hf
intro j hj
have heq := stationaryPoint_spec hf le_rfl hj
simpa [h, heq]
· intro h
simp [norm, h]
end
section Embedding
open CauSeq
variable {p : ℕ} [Fact p.Prime]
theorem equiv_zero_of_val_eq_of_equiv_zero {f g : PadicSeq p}
(h : ∀ k, padicNorm p (f k) = padicNorm p (g k)) (hf : f ≈ 0) : g ≈ 0 := fun ε hε ↦
let ⟨i, hi⟩ := hf _ hε
⟨i, fun j hj ↦ by simpa [h] using hi _ hj⟩
theorem norm_nonzero_of_not_equiv_zero {f : PadicSeq p} (hf : ¬f ≈ 0) : f.norm ≠ 0 :=
hf ∘ f.norm_zero_iff.1
theorem norm_eq_norm_app_of_nonzero {f : PadicSeq p} (hf : ¬f ≈ 0) :
∃ k, f.norm = padicNorm p k ∧ k ≠ 0 :=
have heq : f.norm = padicNorm p (f <| stationaryPoint hf) := by simp [norm, hf]
⟨f <| stationaryPoint hf, heq, fun h ↦
norm_nonzero_of_not_equiv_zero hf (by simpa [h] using heq)⟩
theorem not_limZero_const_of_nonzero {q : ℚ} (hq : q ≠ 0) : ¬LimZero (const (padicNorm p) q) :=
fun h' ↦ hq <| const_limZero.1 h'
theorem not_equiv_zero_const_of_nonzero {q : ℚ} (hq : q ≠ 0) : ¬const (padicNorm p) q ≈ 0 :=
fun h : LimZero (const (padicNorm p) q - 0) ↦
not_limZero_const_of_nonzero (p := p) hq <| by simpa using h
theorem norm_nonneg (f : PadicSeq p) : 0 ≤ f.norm := by
classical exact if hf : f ≈ 0 then by simp [hf, norm] else by simp [norm, hf, padicNorm.nonneg]
/-- An auxiliary lemma for manipulating sequence indices. -/
theorem lift_index_left_left {f : PadicSeq p} (hf : ¬f ≈ 0) (v2 v3 : ℕ) :
padicNorm p (f (stationaryPoint hf)) =
padicNorm p (f (max (stationaryPoint hf) (max v2 v3))) := by
apply stationaryPoint_spec hf
· apply le_max_left
· exact le_rfl
/-- An auxiliary lemma for manipulating sequence indices. -/
theorem lift_index_left {f : PadicSeq p} (hf : ¬f ≈ 0) (v1 v3 : ℕ) :
padicNorm p (f (stationaryPoint hf)) =
padicNorm p (f (max v1 (max (stationaryPoint hf) v3))) := by
apply stationaryPoint_spec hf
· apply le_trans
· apply le_max_left _ v3
· apply le_max_right
· exact le_rfl
/-- An auxiliary lemma for manipulating sequence indices. -/
theorem lift_index_right {f : PadicSeq p} (hf : ¬f ≈ 0) (v1 v2 : ℕ) :
padicNorm p (f (stationaryPoint hf)) =
padicNorm p (f (max v1 (max v2 (stationaryPoint hf)))) := by
apply stationaryPoint_spec hf
· apply le_trans
· apply le_max_right v2
· apply le_max_right
· exact le_rfl
end Embedding
section Valuation
open CauSeq
variable {p : ℕ} [Fact p.Prime]
/-! ### Valuation on `PadicSeq` -/
open Classical in
/-- The `p`-adic valuation on `ℚ` lifts to `PadicSeq p`.
`Valuation f` is defined to be the valuation of the (`ℚ`-valued) stationary point of `f`. -/
def valuation (f : PadicSeq p) : ℤ :=
if hf : f ≈ 0 then 0 else padicValRat p (f (stationaryPoint hf))
theorem norm_eq_zpow_neg_valuation {f : PadicSeq p} (hf : ¬f ≈ 0) :
f.norm = (p : ℚ) ^ (-f.valuation : ℤ) := by
rw [norm, valuation, dif_neg hf, dif_neg hf, padicNorm, if_neg]
intro H
apply CauSeq.not_limZero_of_not_congr_zero hf
intro ε hε
use stationaryPoint hf
intro n hn
rw [stationaryPoint_spec hf le_rfl hn]
simpa [H] using hε
@[deprecated (since := "2024-12-10")] alias norm_eq_pow_val := norm_eq_zpow_neg_valuation
theorem val_eq_iff_norm_eq {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) :
f.valuation = g.valuation ↔ f.norm = g.norm := by
rw [norm_eq_zpow_neg_valuation hf, norm_eq_zpow_neg_valuation hg, ← neg_inj, zpow_right_inj₀]
· exact mod_cast (Fact.out : p.Prime).pos
· exact mod_cast (Fact.out : p.Prime).ne_one
end Valuation
end PadicSeq
section
open PadicSeq
-- Porting note: Commented out `padic_index_simp` tactic
/-
private unsafe def index_simp_core (hh hf hg : expr)
(at_ : Interactive.Loc := Interactive.Loc.ns [none]) : tactic Unit := do
let [v1, v2, v3] ← [hh, hf, hg].mapM fun n => tactic.mk_app `` stationary_point [n] <|> return n
let e1 ← tactic.mk_app `` lift_index_left_left [hh, v2, v3] <|> return q(True)
let e2 ← tactic.mk_app `` lift_index_left [hf, v1, v3] <|> return q(True)
let e3 ← tactic.mk_app `` lift_index_right [hg, v1, v2] <|> return q(True)
let sl ← [e1, e2, e3].foldlM (fun s e => simp_lemmas.add s e) simp_lemmas.mk
when at_ (tactic.simp_target sl >> tactic.skip)
let hs ← at_.get_locals
hs (tactic.simp_hyp sl [])
/-- This is a special-purpose tactic that lifts `padicNorm (f (stationary_point f))` to
`padicNorm (f (max _ _ _))`. -/
unsafe def tactic.interactive.padic_index_simp (l : interactive.parse interactive.types.pexpr_list)
(at_ : interactive.parse interactive.types.location) : tactic Unit := do
let [h, f, g] ← l.mapM tactic.i_to_expr
index_simp_core h f g at_
-/
end
namespace PadicSeq
section Embedding
open CauSeq
variable {p : ℕ} [hp : Fact p.Prime]
theorem norm_mul (f g : PadicSeq p) : (f * g).norm = f.norm * g.norm := by
classical
exact if hf : f ≈ 0 then by
have hg : f * g ≈ 0 := mul_equiv_zero' _ hf
simp only [hf, hg, norm, dif_pos, zero_mul]
else
if hg : g ≈ 0 then by
have hf : f * g ≈ 0 := mul_equiv_zero _ hg
simp only [hf, hg, norm, dif_pos, mul_zero]
else by
unfold norm
have hfg := mul_not_equiv_zero hf hg
simp only [hfg, hf, hg, dite_false]
-- Porting note: originally `padic_index_simp [hfg, hf, hg]`
rw [lift_index_left_left hfg, lift_index_left hf, lift_index_right hg]
apply padicNorm.mul
theorem eq_zero_iff_equiv_zero (f : PadicSeq p) : mk f = 0 ↔ f ≈ 0 :=
mk_eq
theorem ne_zero_iff_nequiv_zero (f : PadicSeq p) : mk f ≠ 0 ↔ ¬f ≈ 0 :=
eq_zero_iff_equiv_zero _ |>.not
theorem norm_const (q : ℚ) : norm (const (padicNorm p) q) = padicNorm p q := by
obtain rfl | hq := eq_or_ne q 0
· simp [norm]
· simp [norm, not_equiv_zero_const_of_nonzero hq]
theorem norm_values_discrete (a : PadicSeq p) (ha : ¬a ≈ 0) : ∃ z : ℤ, a.norm = (p : ℚ) ^ (-z) := by
let ⟨k, hk, hk'⟩ := norm_eq_norm_app_of_nonzero ha
simpa [hk] using padicNorm.values_discrete hk'
theorem norm_one : norm (1 : PadicSeq p) = 1 := by
have h1 : ¬(1 : PadicSeq p) ≈ 0 := one_not_equiv_zero _
simp [h1, norm, hp.1.one_lt]
private theorem norm_eq_of_equiv_aux {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) (hfg : f ≈ g)
(h : padicNorm p (f (stationaryPoint hf)) ≠ padicNorm p (g (stationaryPoint hg)))
(hlt : padicNorm p (g (stationaryPoint hg)) < padicNorm p (f (stationaryPoint hf))) :
False := by
have hpn : 0 < padicNorm p (f (stationaryPoint hf)) - padicNorm p (g (stationaryPoint hg)) :=
sub_pos_of_lt hlt
obtain ⟨N, hN⟩ := hfg _ hpn
let i := max N (max (stationaryPoint hf) (stationaryPoint hg))
have hi : N ≤ i := le_max_left _ _
have hN' := hN _ hi
-- Porting note: originally `padic_index_simp [N, hf, hg] at hN' h hlt`
rw [lift_index_left hf N (stationaryPoint hg), lift_index_right hg N (stationaryPoint hf)]
at hN' h hlt
have hpne : padicNorm p (f i) ≠ padicNorm p (-g i) := by rwa [← padicNorm.neg (g i)] at h
rw [CauSeq.sub_apply, sub_eq_add_neg, add_eq_max_of_ne hpne, padicNorm.neg, max_eq_left_of_lt hlt]
at hN'
have : padicNorm p (f i) < padicNorm p (f i) := by
apply lt_of_lt_of_le hN'
apply sub_le_self
apply padicNorm.nonneg
exact lt_irrefl _ this
private theorem norm_eq_of_equiv {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) (hfg : f ≈ g) :
padicNorm p (f (stationaryPoint hf)) = padicNorm p (g (stationaryPoint hg)) := by
by_contra h
cases lt_or_le (padicNorm p (g (stationaryPoint hg))) (padicNorm p (f (stationaryPoint hf))) with
| inl hlt =>
exact norm_eq_of_equiv_aux hf hg hfg h hlt
| inr hle =>
apply norm_eq_of_equiv_aux hg hf (Setoid.symm hfg) (Ne.symm h)
exact lt_of_le_of_ne hle h
theorem norm_equiv {f g : PadicSeq p} (hfg : f ≈ g) : f.norm = g.norm := by
classical
exact if hf : f ≈ 0 then by
have hg : g ≈ 0 := Setoid.trans (Setoid.symm hfg) hf
simp [norm, hf, hg]
else by
have hg : ¬g ≈ 0 := hf ∘ Setoid.trans hfg
unfold norm; split_ifs; exact norm_eq_of_equiv hf hg hfg
private theorem norm_nonarchimedean_aux {f g : PadicSeq p} (hfg : ¬f + g ≈ 0) (hf : ¬f ≈ 0)
(hg : ¬g ≈ 0) : (f + g).norm ≤ max f.norm g.norm := by
unfold norm; split_ifs
-- Porting note: originally `padic_index_simp [hfg, hf, hg]`
rw [lift_index_left_left hfg, lift_index_left hf, lift_index_right hg]
apply padicNorm.nonarchimedean
theorem norm_nonarchimedean (f g : PadicSeq p) : (f + g).norm ≤ max f.norm g.norm := by
classical
exact if hfg : f + g ≈ 0 then by
have : 0 ≤ max f.norm g.norm := le_max_of_le_left (norm_nonneg _)
simpa only [hfg, norm]
else
if hf : f ≈ 0 then by
have hfg' : f + g ≈ g := by
change LimZero (f - 0) at hf
show LimZero (f + g - g); · simpa only [sub_zero, add_sub_cancel_right] using hf
have hcfg : (f + g).norm = g.norm := norm_equiv hfg'
have hcl : f.norm = 0 := (norm_zero_iff f).2 hf
have : max f.norm g.norm = g.norm := by rw [hcl]; exact max_eq_right (norm_nonneg _)
rw [this, hcfg]
else
if hg : g ≈ 0 then by
have hfg' : f + g ≈ f := by
change LimZero (g - 0) at hg
show LimZero (f + g - f); · simpa only [add_sub_cancel_left, sub_zero] using hg
have hcfg : (f + g).norm = f.norm := norm_equiv hfg'
have hcl : g.norm = 0 := (norm_zero_iff g).2 hg
have : max f.norm g.norm = f.norm := by rw [hcl]; exact max_eq_left (norm_nonneg _)
rw [this, hcfg]
else norm_nonarchimedean_aux hfg hf hg
theorem norm_eq {f g : PadicSeq p} (h : ∀ k, padicNorm p (f k) = padicNorm p (g k)) :
f.norm = g.norm := by
classical
exact if hf : f ≈ 0 then by
have hg : g ≈ 0 := equiv_zero_of_val_eq_of_equiv_zero h hf
simp only [hf, hg, norm, dif_pos]
else by
have hg : ¬g ≈ 0 := fun hg ↦
hf <| equiv_zero_of_val_eq_of_equiv_zero (by simp only [h, forall_const, eq_self_iff_true]) hg
simp only [hg, hf, norm, dif_neg, not_false_iff]
let i := max (stationaryPoint hf) (stationaryPoint hg)
have hpf : padicNorm p (f (stationaryPoint hf)) = padicNorm p (f i) := by
apply stationaryPoint_spec
· apply le_max_left
· exact le_rfl
have hpg : padicNorm p (g (stationaryPoint hg)) = padicNorm p (g i) := by
apply stationaryPoint_spec
· apply le_max_right
· exact le_rfl
rw [hpf, hpg, h]
theorem norm_neg (a : PadicSeq p) : (-a).norm = a.norm :=
norm_eq <| by simp
theorem norm_eq_of_add_equiv_zero {f g : PadicSeq p} (h : f + g ≈ 0) : f.norm = g.norm := by
have : LimZero (f + g - 0) := h
have : f ≈ -g := show LimZero (f - -g) by simpa only [sub_zero, sub_neg_eq_add]
have : f.norm = (-g).norm := norm_equiv this
simpa only [norm_neg] using this
theorem add_eq_max_of_ne {f g : PadicSeq p} (hfgne : f.norm ≠ g.norm) :
(f + g).norm = max f.norm g.norm := by
classical
have hfg : ¬f + g ≈ 0 := mt norm_eq_of_add_equiv_zero hfgne
exact if hf : f ≈ 0 then by
have : LimZero (f - 0) := hf
have : f + g ≈ g := show LimZero (f + g - g) by simpa only [sub_zero, add_sub_cancel_right]
have h1 : (f + g).norm = g.norm := norm_equiv this
have h2 : f.norm = 0 := (norm_zero_iff _).2 hf
rw [h1, h2, max_eq_right (norm_nonneg _)]
else
if hg : g ≈ 0 then by
have : LimZero (g - 0) := hg
have : f + g ≈ f := show LimZero (f + g - f) by simpa only [add_sub_cancel_left, sub_zero]
have h1 : (f + g).norm = f.norm := norm_equiv this
have h2 : g.norm = 0 := (norm_zero_iff _).2 hg
rw [h1, h2, max_eq_left (norm_nonneg _)]
else by
unfold norm at hfgne ⊢; split_ifs at hfgne ⊢
-- Porting note: originally `padic_index_simp [hfg, hf, hg] at hfgne ⊢`
rw [lift_index_left hf, lift_index_right hg] at hfgne
· rw [lift_index_left_left hfg, lift_index_left hf, lift_index_right hg]
exact padicNorm.add_eq_max_of_ne hfgne
end Embedding
end PadicSeq
/-- The `p`-adic numbers `ℚ_[p]` are the Cauchy completion of `ℚ` with respect to the `p`-adic norm.
-/
def Padic (p : ℕ) [Fact p.Prime] :=
CauSeq.Completion.Cauchy (padicNorm p)
/-- notation for p-padic rationals -/
notation "ℚ_[" p "]" => Padic p
namespace Padic
section Completion
variable {p : ℕ} [Fact p.Prime]
instance field : Field ℚ_[p] :=
Cauchy.field
instance : Inhabited ℚ_[p] :=
⟨0⟩
-- short circuits
instance : CommRing ℚ_[p] :=
Cauchy.commRing
instance : Ring ℚ_[p] :=
Cauchy.ring
instance : Zero ℚ_[p] := by infer_instance
instance : One ℚ_[p] := by infer_instance
instance : Add ℚ_[p] := by infer_instance
instance : Mul ℚ_[p] := by infer_instance
instance : Sub ℚ_[p] := by infer_instance
instance : Neg ℚ_[p] := by infer_instance
instance : Div ℚ_[p] := by infer_instance
instance : AddCommGroup ℚ_[p] := by infer_instance
/-- Builds the equivalence class of a Cauchy sequence of rationals. -/
def mk : PadicSeq p → ℚ_[p] :=
Quotient.mk'
variable (p)
theorem zero_def : (0 : ℚ_[p]) = ⟦0⟧ := rfl
theorem mk_eq {f g : PadicSeq p} : mk f = mk g ↔ f ≈ g :=
Quotient.eq'
theorem const_equiv {q r : ℚ} : const (padicNorm p) q ≈ const (padicNorm p) r ↔ q = r :=
⟨fun heq ↦ eq_of_sub_eq_zero <| const_limZero.1 heq, fun heq ↦ by
rw [heq]⟩
@[norm_cast]
theorem coe_inj {q r : ℚ} : (↑q : ℚ_[p]) = ↑r ↔ q = r :=
⟨(const_equiv p).1 ∘ Quotient.eq'.1, fun h ↦ by rw [h]⟩
instance : CharZero ℚ_[p] :=
⟨fun m n ↦ by
rw [← Rat.cast_natCast]
norm_cast
exact id⟩
@[norm_cast]
theorem coe_add : ∀ {x y : ℚ}, (↑(x + y) : ℚ_[p]) = ↑x + ↑y :=
Rat.cast_add _ _
@[norm_cast]
theorem coe_neg : ∀ {x : ℚ}, (↑(-x) : ℚ_[p]) = -↑x :=
Rat.cast_neg _
@[norm_cast]
theorem coe_mul : ∀ {x y : ℚ}, (↑(x * y) : ℚ_[p]) = ↑x * ↑y :=
Rat.cast_mul _ _
@[norm_cast]
theorem coe_sub : ∀ {x y : ℚ}, (↑(x - y) : ℚ_[p]) = ↑x - ↑y :=
Rat.cast_sub _ _
@[norm_cast]
theorem coe_div : ∀ {x y : ℚ}, (↑(x / y) : ℚ_[p]) = ↑x / ↑y :=
Rat.cast_div _ _
@[norm_cast]
theorem coe_one : (↑(1 : ℚ) : ℚ_[p]) = 1 := rfl
@[norm_cast]
theorem coe_zero : (↑(0 : ℚ) : ℚ_[p]) = 0 := rfl
end Completion
end Padic
/-- The rational-valued `p`-adic norm on `ℚ_[p]` is lifted from the norm on Cauchy sequences. The
canonical form of this function is the normed space instance, with notation `‖ ‖`. -/
def padicNormE {p : ℕ} [hp : Fact p.Prime] : AbsoluteValue ℚ_[p] ℚ where
toFun := Quotient.lift PadicSeq.norm <| @PadicSeq.norm_equiv _ _
map_mul' q r := Quotient.inductionOn₂ q r <| PadicSeq.norm_mul
nonneg' q := Quotient.inductionOn q <| PadicSeq.norm_nonneg
eq_zero' q := Quotient.inductionOn q fun r ↦ by
rw [Padic.zero_def, Quotient.eq]
exact PadicSeq.norm_zero_iff r
add_le' q r := by
trans
max ((Quotient.lift PadicSeq.norm <| @PadicSeq.norm_equiv _ _) q)
((Quotient.lift PadicSeq.norm <| @PadicSeq.norm_equiv _ _) r)
· exact Quotient.inductionOn₂ q r <| PadicSeq.norm_nonarchimedean
refine max_le_add_of_nonneg (Quotient.inductionOn q <| PadicSeq.norm_nonneg) ?_
exact Quotient.inductionOn r <| PadicSeq.norm_nonneg
namespace padicNormE
section Embedding
open PadicSeq
variable {p : ℕ} [Fact p.Prime]
theorem defn (f : PadicSeq p) {ε : ℚ} (hε : 0 < ε) :
∃ N, ∀ i ≥ N, padicNormE (Padic.mk f - f i : ℚ_[p]) < ε := by
dsimp [padicNormE]
-- `change ∃ N, ∀ i ≥ N, (f - const _ (f i)).norm < ε` also works, but is very slow
suffices hyp : ∃ N, ∀ i ≥ N, (f - const _ (f i)).norm < ε by peel hyp with N; use N
by_contra! h
obtain ⟨N, hN⟩ := cauchy₂ f hε
rcases h N with ⟨i, hi, hge⟩
have hne : ¬f - const (padicNorm p) (f i) ≈ 0 := fun h ↦ by
rw [PadicSeq.norm, dif_pos h] at hge
exact not_lt_of_ge hge hε
unfold PadicSeq.norm at hge; split_ifs at hge
apply not_le_of_gt _ hge
cases _root_.le_total N (stationaryPoint hne) with
| inl hgen =>
exact hN _ hgen _ hi
| inr hngen =>
have := stationaryPoint_spec hne le_rfl hngen
rw [← this]
exact hN _ le_rfl _ hi
/-- Theorems about `padicNormE` are named with a `'` so the names do not conflict with the
equivalent theorems about `norm` (`‖ ‖`). -/
theorem nonarchimedean' (q r : ℚ_[p]) :
padicNormE (q + r : ℚ_[p]) ≤ max (padicNormE q) (padicNormE r) :=
Quotient.inductionOn₂ q r <| norm_nonarchimedean
/-- Theorems about `padicNormE` are named with a `'` so the names do not conflict with the
equivalent theorems about `norm` (`‖ ‖`). -/
theorem add_eq_max_of_ne' {q r : ℚ_[p]} :
padicNormE q ≠ padicNormE r → padicNormE (q + r : ℚ_[p]) = max (padicNormE q) (padicNormE r) :=
Quotient.inductionOn₂ q r fun _ _ ↦ PadicSeq.add_eq_max_of_ne
@[simp]
theorem eq_padic_norm' (q : ℚ) : padicNormE (q : ℚ_[p]) = padicNorm p q :=
norm_const _
protected theorem image' {q : ℚ_[p]} : q ≠ 0 → ∃ n : ℤ, padicNormE q = (p : ℚ) ^ (-n) :=
Quotient.inductionOn q fun f hf ↦
have : ¬f ≈ 0 := (ne_zero_iff_nequiv_zero f).1 hf
norm_values_discrete f this
end Embedding
end padicNormE
namespace Padic
section Complete
open PadicSeq Padic
variable {p : ℕ} [Fact p.Prime] (f : CauSeq _ (@padicNormE p _))
theorem rat_dense' (q : ℚ_[p]) {ε : ℚ} (hε : 0 < ε) : ∃ r : ℚ, padicNormE (q - r : ℚ_[p]) < ε :=
Quotient.inductionOn q fun q' ↦
have : ∃ N, ∀ m ≥ N, ∀ n ≥ N, padicNorm p (q' m - q' n) < ε := cauchy₂ _ hε
let ⟨N, hN⟩ := this
⟨q' N, by
classical
dsimp [padicNormE]
-- Porting note: this used to be `change`, but that times out.
convert_to PadicSeq.norm (q' - const _ (q' N)) < ε
rcases Decidable.em (q' - const (padicNorm p) (q' N) ≈ 0) with heq | hne'
· simpa only [heq, PadicSeq.norm, dif_pos]
· simp only [PadicSeq.norm, dif_neg hne']
change padicNorm p (q' _ - q' _) < ε
rcases Decidable.em (stationaryPoint hne' ≤ N) with hle | hle
· have := (stationaryPoint_spec hne' le_rfl hle).symm
simp only [const_apply, sub_apply, padicNorm.zero, sub_self] at this
simpa only [this]
· exact hN _ (lt_of_not_ge hle).le _ le_rfl⟩
private theorem div_nat_pos (n : ℕ) : 0 < 1 / (n + 1 : ℚ) :=
div_pos zero_lt_one (mod_cast succ_pos _)
/-- `limSeq f`, for `f` a Cauchy sequence of `p`-adic numbers, is a sequence of rationals with the
same limit point as `f`. -/
def limSeq : ℕ → ℚ :=
fun n ↦ Classical.choose (rat_dense' (f n) (div_nat_pos n))
theorem exi_rat_seq_conv {ε : ℚ} (hε : 0 < ε) :
∃ N, ∀ i ≥ N, padicNormE (f i - (limSeq f i : ℚ_[p]) : ℚ_[p]) < ε := by
refine (exists_nat_gt (1 / ε)).imp fun N hN i hi ↦ ?_
have h := Classical.choose_spec (rat_dense' (f i) (div_nat_pos i))
refine lt_of_lt_of_le h ((div_le_iff₀' <| mod_cast succ_pos _).mpr ?_)
rw [right_distrib]
apply le_add_of_le_of_nonneg
· exact (div_le_iff₀ hε).mp (le_trans (le_of_lt hN) (mod_cast hi))
· apply le_of_lt
simpa
theorem exi_rat_seq_conv_cauchy : IsCauSeq (padicNorm p) (limSeq f) := fun ε hε ↦ by
have hε3 : 0 < ε / 3 := div_pos hε (by norm_num)
let ⟨N, hN⟩ := exi_rat_seq_conv f hε3
let ⟨N2, hN2⟩ := f.cauchy₂ hε3
exists max N N2
intro j hj
suffices
padicNormE (limSeq f j - f (max N N2) + (f (max N N2) - limSeq f (max N N2)) : ℚ_[p]) < ε by
ring_nf at this ⊢
rw [← padicNormE.eq_padic_norm']
exact mod_cast this
apply lt_of_le_of_lt
· apply padicNormE.add_le
· rw [← add_thirds ε]
apply _root_.add_lt_add
· suffices padicNormE (limSeq f j - f j + (f j - f (max N N2)) : ℚ_[p]) < ε / 3 + ε / 3 by
simpa only [sub_add_sub_cancel]
apply lt_of_le_of_lt
· apply padicNormE.add_le
· apply _root_.add_lt_add
· rw [padicNormE.map_sub]
apply mod_cast hN j
exact le_of_max_le_left hj
· exact hN2 _ (le_of_max_le_right hj) _ (le_max_right _ _)
· apply mod_cast hN (max N N2)
apply le_max_left
private def lim' : PadicSeq p :=
⟨_, exi_rat_seq_conv_cauchy f⟩
private def lim : ℚ_[p] :=
⟦lim' f⟧
theorem complete' : ∃ q : ℚ_[p], ∀ ε > 0, ∃ N, ∀ i ≥ N, padicNormE (q - f i : ℚ_[p]) < ε :=
⟨lim f, fun ε hε ↦ by
obtain ⟨N, hN⟩ := exi_rat_seq_conv f (half_pos hε)
obtain ⟨N2, hN2⟩ := padicNormE.defn (lim' f) (half_pos hε)
refine ⟨max N N2, fun i hi ↦ ?_⟩
rw [← sub_add_sub_cancel _ (lim' f i : ℚ_[p]) _]
refine (padicNormE.add_le _ _).trans_lt ?_
rw [← add_halves ε]
apply _root_.add_lt_add
· apply hN2 _ (le_of_max_le_right hi)
· rw [padicNormE.map_sub]
exact hN _ (le_of_max_le_left hi)⟩
theorem complete'' : ∃ q : ℚ_[p], ∀ ε > 0, ∃ N, ∀ i ≥ N, padicNormE (f i - q : ℚ_[p]) < ε := by
obtain ⟨x, hx⟩ := complete' f
refine ⟨x, fun ε hε => ?_⟩
obtain ⟨N, hN⟩ := hx ε hε
refine ⟨N, fun i hi => ?_⟩
rw [padicNormE.map_sub]
exact hN i hi
end Complete
section NormedSpace
variable (p : ℕ) [Fact p.Prime]
instance : Dist ℚ_[p] :=
⟨fun x y ↦ padicNormE (x - y : ℚ_[p])⟩
instance : IsUltrametricDist ℚ_[p] :=
⟨fun x y z ↦ by simpa [dist] using padicNormE.nonarchimedean' (x - y) (y - z)⟩
instance metricSpace : MetricSpace ℚ_[p] where
dist_self := by simp [dist]
dist := dist
dist_comm x y := by simp [dist, ← padicNormE.map_neg (x - y : ℚ_[p])]
dist_triangle x y z := by
dsimp [dist]
exact mod_cast padicNormE.sub_le x y z
eq_of_dist_eq_zero := by
dsimp [dist]; intro _ _ h
apply eq_of_sub_eq_zero
apply padicNormE.eq_zero.1
exact mod_cast h
instance : Norm ℚ_[p] :=
⟨fun x ↦ padicNormE x⟩
instance normedField : NormedField ℚ_[p] :=
{ Padic.field,
Padic.metricSpace p with
dist_eq := fun _ _ ↦ rfl
norm_mul := by simp [Norm.norm, map_mul]
norm := norm }
instance isAbsoluteValue : IsAbsoluteValue fun a : ℚ_[p] ↦ ‖a‖ where
abv_nonneg' := norm_nonneg
abv_eq_zero' := norm_eq_zero
abv_add' := norm_add_le
abv_mul' := by simp [Norm.norm, map_mul]
theorem rat_dense (q : ℚ_[p]) {ε : ℝ} (hε : 0 < ε) : ∃ r : ℚ, ‖q - r‖ < ε :=
let ⟨ε', hε'l, hε'r⟩ := exists_rat_btwn hε
let ⟨r, hr⟩ := rat_dense' q (ε := ε') (by simpa using hε'l)
⟨r, lt_trans (by simpa [Norm.norm] using hr) hε'r⟩
end NormedSpace
end Padic
namespace padicNormE
section NormedSpace
variable {p : ℕ} [hp : Fact p.Prime]
-- Porting note: Linter thinks this is a duplicate simp lemma, so `priority` is assigned
@[simp (high)]
protected theorem mul (q r : ℚ_[p]) : ‖q * r‖ = ‖q‖ * ‖r‖ := by simp [Norm.norm, map_mul]
protected theorem is_norm (q : ℚ_[p]) : ↑(padicNormE q) = ‖q‖ := rfl
theorem nonarchimedean (q r : ℚ_[p]) : ‖q + r‖ ≤ max ‖q‖ ‖r‖ := by
dsimp [norm]
exact mod_cast nonarchimedean' _ _
theorem add_eq_max_of_ne {q r : ℚ_[p]} (h : ‖q‖ ≠ ‖r‖) : ‖q + r‖ = max ‖q‖ ‖r‖ := by
dsimp [norm] at h ⊢
have : padicNormE q ≠ padicNormE r := mod_cast h
exact mod_cast add_eq_max_of_ne' this
@[simp]
theorem eq_padicNorm (q : ℚ) : ‖(q : ℚ_[p])‖ = padicNorm p q := by
dsimp [norm]
rw [← padicNormE.eq_padic_norm']
@[simp]
theorem norm_p : ‖(p : ℚ_[p])‖ = (p : ℝ)⁻¹ := by
rw [← @Rat.cast_natCast ℝ _ p]
rw [← @Rat.cast_natCast ℚ_[p] _ p]
simp [hp.1.ne_zero, hp.1.ne_one, norm, padicNorm, padicValRat, padicValInt, zpow_neg,
-Rat.cast_natCast]
theorem norm_p_lt_one : ‖(p : ℚ_[p])‖ < 1 := by
rw [norm_p]
exact inv_lt_one_of_one_lt₀ <| mod_cast hp.1.one_lt
-- Porting note: Linter thinks this is a duplicate simp lemma, so `priority` is assigned
@[simp (high)]
theorem norm_p_zpow (n : ℤ) : ‖(p : ℚ_[p]) ^ n‖ = (p : ℝ) ^ (-n) := by
rw [norm_zpow, norm_p, zpow_neg, inv_zpow]
-- Porting note: Linter thinks this is a duplicate simp lemma, so `priority` is assigned
@[simp (high)]
theorem norm_p_pow (n : ℕ) : ‖(p : ℚ_[p]) ^ n‖ = (p : ℝ) ^ (-n : ℤ) := by
rw [← norm_p_zpow, zpow_natCast]
instance : NontriviallyNormedField ℚ_[p] :=
{ Padic.normedField p with
non_trivial :=
⟨p⁻¹, by
rw [norm_inv, norm_p, inv_inv]
exact mod_cast hp.1.one_lt⟩ }
protected theorem image {q : ℚ_[p]} : q ≠ 0 → ∃ n : ℤ, ‖q‖ = ↑((p : ℚ) ^ (-n)) :=
Quotient.inductionOn q fun f hf ↦
have : ¬f ≈ 0 := (PadicSeq.ne_zero_iff_nequiv_zero f).1 hf
let ⟨n, hn⟩ := PadicSeq.norm_values_discrete f this
⟨n, by rw [← hn]; rfl⟩
protected theorem is_rat (q : ℚ_[p]) : ∃ q' : ℚ, ‖q‖ = q' := by
classical
exact if h : q = 0 then ⟨0, by simp [h]⟩
else
let ⟨n, hn⟩ := padicNormE.image h
⟨_, hn⟩
/-- `ratNorm q`, for a `p`-adic number `q` is the `p`-adic norm of `q`, as rational number.
The lemma `padicNormE.eq_ratNorm` asserts `‖q‖ = ratNorm q`. -/
def ratNorm (q : ℚ_[p]) : ℚ :=
Classical.choose (padicNormE.is_rat q)
theorem eq_ratNorm (q : ℚ_[p]) : ‖q‖ = ratNorm q :=
Classical.choose_spec (padicNormE.is_rat q)
theorem norm_rat_le_one : ∀ {q : ℚ} (_ : ¬p ∣ q.den), ‖(q : ℚ_[p])‖ ≤ 1
| ⟨n, d, hn, hd⟩ => fun hq : ¬p ∣ d ↦
if hnz : n = 0 then by
have : (⟨n, d, hn, hd⟩ : ℚ) = 0 := Rat.zero_iff_num_zero.mpr hnz
norm_num [this]
else by
have hnz' : (⟨n, d, hn, hd⟩ : ℚ) ≠ 0 := mt Rat.zero_iff_num_zero.1 hnz
rw [padicNormE.eq_padicNorm]
norm_cast
-- Porting note: `Nat.cast_zero` instead of another `norm_cast` call
rw [padicNorm.eq_zpow_of_nonzero hnz', padicValRat, neg_sub,
padicValNat.eq_zero_of_not_dvd hq, Nat.cast_zero, zero_sub, zpow_neg, zpow_natCast]
apply inv_le_one_of_one_le₀
norm_cast
apply one_le_pow
exact hp.1.pos
theorem norm_int_le_one (z : ℤ) : ‖(z : ℚ_[p])‖ ≤ 1 :=
suffices ‖((z : ℚ) : ℚ_[p])‖ ≤ 1 by simpa
norm_rat_le_one <| by simp [hp.1.ne_one]
theorem norm_int_lt_one_iff_dvd (k : ℤ) : ‖(k : ℚ_[p])‖ < 1 ↔ ↑p ∣ k := by
constructor
· intro h
contrapose! h
apply le_of_eq
rw [eq_comm]
calc
‖(k : ℚ_[p])‖ = ‖((k : ℚ) : ℚ_[p])‖ := by norm_cast
_ = padicNorm p k := padicNormE.eq_padicNorm _
_ = 1 := mod_cast (int_eq_one_iff k).mpr h
· rintro ⟨x, rfl⟩
push_cast
rw [padicNormE.mul]
calc
_ ≤ ‖(p : ℚ_[p])‖ * 1 :=
mul_le_mul le_rfl (by simpa using norm_int_le_one _) (norm_nonneg _) (norm_nonneg _)
_ < 1 := by
rw [mul_one, padicNormE.norm_p]
exact inv_lt_one_of_one_lt₀ <| mod_cast hp.1.one_lt
theorem norm_int_le_pow_iff_dvd (k : ℤ) (n : ℕ) :
‖(k : ℚ_[p])‖ ≤ (p : ℝ) ^ (-n : ℤ) ↔ (p ^ n : ℤ) ∣ k := by
have : (p : ℝ) ^ (-n : ℤ) = (p : ℚ) ^ (-n : ℤ) := by simp
rw [show (k : ℚ_[p]) = ((k : ℚ) : ℚ_[p]) by norm_cast, eq_padicNorm, this]
norm_cast
rw [← padicNorm.dvd_iff_norm_le]
theorem eq_of_norm_add_lt_right {z1 z2 : ℚ_[p]} (h : ‖z1 + z2‖ < ‖z2‖) : ‖z1‖ = ‖z2‖ :=
_root_.by_contradiction fun hne ↦
not_lt_of_ge (by rw [padicNormE.add_eq_max_of_ne hne]; apply le_max_right) h
theorem eq_of_norm_add_lt_left {z1 z2 : ℚ_[p]} (h : ‖z1 + z2‖ < ‖z1‖) : ‖z1‖ = ‖z2‖ :=
_root_.by_contradiction fun hne ↦
not_lt_of_ge (by rw [padicNormE.add_eq_max_of_ne hne]; apply le_max_left) h
end NormedSpace
end padicNormE
namespace Padic
variable {p : ℕ} [hp : Fact p.Prime]
instance complete : CauSeq.IsComplete ℚ_[p] norm where
isComplete f := by
have cau_seq_norm_e : IsCauSeq padicNormE f := fun ε hε => by
have h := isCauSeq f ε (mod_cast hε)
dsimp [norm] at h
exact mod_cast h
-- Porting note: Padic.complete' works with `f i - q`, but the goal needs `q - f i`,
-- using `rewrite [padicNormE.map_sub]` causes time out, so a separate lemma is created
obtain ⟨q, hq⟩ := Padic.complete'' ⟨f, cau_seq_norm_e⟩
exists q
intro ε hε
obtain ⟨ε', hε'⟩ := exists_rat_btwn hε
norm_cast at hε'
obtain ⟨N, hN⟩ := hq ε' hε'.1
exists N
intro i hi
have h := hN i hi
change norm (f i - q) < ε
refine lt_trans ?_ hε'.2
dsimp [norm]
exact mod_cast h
theorem padicNormE_lim_le {f : CauSeq ℚ_[p] norm} {a : ℝ} (ha : 0 < a) (hf : ∀ i, ‖f i‖ ≤ a) :
‖f.lim‖ ≤ a := by
obtain ⟨N, hN⟩ := Setoid.symm (CauSeq.equiv_lim f) _ ha
calc
‖f.lim‖ = ‖f.lim - f N + f N‖ := by simp
_ ≤ max ‖f.lim - f N‖ ‖f N‖ := padicNormE.nonarchimedean _ _
_ ≤ a := max_le (le_of_lt (hN _ le_rfl)) (hf _)
open Filter Set
instance : CompleteSpace ℚ_[p] := by
apply complete_of_cauchySeq_tendsto
intro u hu
let c : CauSeq ℚ_[p] norm := ⟨u, Metric.cauchySeq_iff'.mp hu⟩
refine ⟨c.lim, fun s h ↦ ?_⟩
rcases Metric.mem_nhds_iff.1 h with ⟨ε, ε0, hε⟩
have := c.equiv_lim ε ε0
simp only [mem_map, mem_atTop_sets, mem_setOf_eq]
exact this.imp fun N hN n hn ↦ hε (hN n hn)
/-! ### Valuation on `ℚ_[p]` -/
/-- `Padic.valuation` lifts the `p`-adic valuation on rationals to `ℚ_[p]`. -/
def valuation : ℚ_[p] → ℤ :=
Quotient.lift (@PadicSeq.valuation p _) fun f g h ↦ by
by_cases hf : f ≈ 0
· have hg : g ≈ 0 := Setoid.trans (Setoid.symm h) hf
simp [hf, hg, PadicSeq.valuation]
· have hg : ¬g ≈ 0 := fun hg ↦ hf (Setoid.trans h hg)
rw [PadicSeq.val_eq_iff_norm_eq hf hg]
exact PadicSeq.norm_equiv h
@[simp]
theorem valuation_zero : valuation (0 : ℚ_[p]) = 0 :=
dif_pos ((const_equiv p).2 rfl)
theorem norm_eq_zpow_neg_valuation {x : ℚ_[p]} : x ≠ 0 → ‖x‖ = (p : ℝ) ^ (-x.valuation) := by
refine Quotient.inductionOn' x fun f hf => ?_
change (PadicSeq.norm _ : ℝ) = (p : ℝ) ^ (-PadicSeq.valuation _)
rw [PadicSeq.norm_eq_zpow_neg_valuation]
· rw [Rat.cast_zpow, Rat.cast_natCast]
· apply CauSeq.not_limZero_of_not_congr_zero
-- Porting note: was `contrapose! hf`
intro hf'
apply hf
apply Quotient.sound
simpa using hf'
@[simp]
lemma valuation_ratCast (q : ℚ) : valuation (q : ℚ_[p]) = padicValRat p q := by
rcases eq_or_ne q 0 with rfl | hq
· simp only [Rat.cast_zero, valuation_zero, padicValRat.zero]
refine neg_injective ((zpow_right_strictMono₀ (mod_cast hp.out.one_lt)).injective
<| (norm_eq_zpow_neg_valuation (mod_cast hq)).symm.trans ?_)
rw [padicNormE.eq_padicNorm, ← Rat.cast_natCast, ← Rat.cast_zpow, Rat.cast_inj]
exact padicNorm.eq_zpow_of_nonzero hq
@[simp]
lemma valuation_intCast (n : ℤ) : valuation (n : ℚ_[p]) = padicValInt p n := by
rw [← Rat.cast_intCast, valuation_ratCast, padicValRat.of_int]
@[simp]
lemma valuation_natCast (n : ℕ) : valuation (n : ℚ_[p]) = padicValNat p n := by
rw [← Rat.cast_natCast, valuation_ratCast, padicValRat.of_nat]
@[simp]
lemma valuation_ofNat (n : ℕ) [n.AtLeastTwo] :
valuation (ofNat(n) : ℚ_[p]) = padicValNat p n :=
valuation_natCast n
@[simp]
lemma valuation_one : valuation (1 : ℚ_[p]) = 0 := by
rw [← Nat.cast_one, valuation_natCast, padicValNat.one, cast_zero]
-- not @[simp], since simp can prove it
lemma valuation_p : valuation (p : ℚ_[p]) = 1 := by
rw [valuation_natCast, padicValNat_self, cast_one]
theorem le_valuation_add {x y : ℚ_[p]} (hxy : x + y ≠ 0) :
min x.valuation y.valuation ≤ (x + y).valuation := by
by_cases hx : x = 0
· simpa only [hx, zero_add] using min_le_right _ _
by_cases hy : y = 0
· simpa only [hy, add_zero] using min_le_left _ _
have : ‖x + y‖ ≤ max ‖x‖ ‖y‖ := padicNormE.nonarchimedean x y
simpa only [norm_eq_zpow_neg_valuation hxy, norm_eq_zpow_neg_valuation hx,
norm_eq_zpow_neg_valuation hy, le_max_iff,
zpow_le_zpow_iff_right₀ (mod_cast hp.out.one_lt : 1 < (p : ℝ)), neg_le_neg_iff, ← min_le_iff]
@[simp]
lemma valuation_mul {x y : ℚ_[p]} (hx : x ≠ 0) (hy : y ≠ 0) :
(x * y).valuation = x.valuation + y.valuation := by
have h_norm : ‖x * y‖ = ‖x‖ * ‖y‖ := norm_mul x y
have hp_ne_one : (p : ℝ) ≠ 1 := mod_cast (Fact.out : p.Prime).ne_one
have hp_pos : (0 : ℝ) < p := mod_cast NeZero.pos _
rwa [norm_eq_zpow_neg_valuation hx, norm_eq_zpow_neg_valuation hy,
norm_eq_zpow_neg_valuation (mul_ne_zero hx hy), ← zpow_add₀ hp_pos.ne',
zpow_right_inj₀ hp_pos hp_ne_one, ← neg_add, neg_inj] at h_norm
@[simp]
lemma valuation_inv (x : ℚ_[p]) : x⁻¹.valuation = -x.valuation := by
obtain rfl | hx := eq_or_ne x 0
· simp
have h_norm : ‖x⁻¹‖ = ‖x‖⁻¹ := norm_inv x
have hp_ne_one : (p : ℝ) ≠ 1 := mod_cast (Fact.out : p.Prime).ne_one
have hp_pos : (0 : ℝ) < p := mod_cast NeZero.pos _
rwa [norm_eq_zpow_neg_valuation hx, norm_eq_zpow_neg_valuation <| inv_ne_zero hx,
← zpow_neg, zpow_right_inj₀ hp_pos hp_ne_one, neg_inj] at h_norm
@[simp]
lemma valuation_pow (x : ℚ_[p]) : ∀ n : ℕ, (x ^ n).valuation = n * x.valuation
| 0 => by simp
| n + 1 => by
obtain rfl | hx := eq_or_ne x 0
· simp
· simp [pow_succ, hx, valuation_mul, valuation_pow, _root_.add_one_mul]
@[simp]
lemma valuation_zpow (x : ℚ_[p]) : ∀ n : ℤ, (x ^ n).valuation = n * x.valuation
| (n : ℕ) => by simp
| .negSucc n => by simp [← neg_mul]; simp [Int.negSucc_eq]
@[deprecated (since := "2024-12-10")] alias valuation_map_add := le_valuation_add
@[deprecated (since := "2024-12-10")] alias valuation_map_mul := valuation_mul
open Classical in
/-- The additive `p`-adic valuation on `ℚ_[p]`, with values in `WithTop ℤ`. -/
def addValuationDef : ℚ_[p] → WithTop ℤ :=
fun x ↦ if x = 0 then ⊤ else x.valuation
@[simp]
theorem AddValuation.map_zero : addValuationDef (0 : ℚ_[p]) = ⊤ := by
| rw [addValuationDef, if_pos rfl]
@[simp]
theorem AddValuation.map_one : addValuationDef (1 : ℚ_[p]) = 0 := by
rw [addValuationDef, if_neg one_ne_zero, valuation_one, WithTop.coe_zero]
theorem AddValuation.map_mul (x y : ℚ_[p]) :
addValuationDef (x * y : ℚ_[p]) = addValuationDef x + addValuationDef y := by
| Mathlib/NumberTheory/Padics/PadicNumbers.lean | 1,039 | 1,046 |
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.CategoryTheory.Localization.Opposite
/-!
# Calculus of fractions
Following the definitions by [Gabriel and Zisman][gabriel-zisman-1967],
given a morphism property `W : MorphismProperty C` on a category `C`,
we introduce the class `W.HasLeftCalculusOfFractions`. The main
result `Localization.exists_leftFraction` is that if `L : C ⥤ D`
is a localization functor for `W`, then for any morphism `L.obj X ⟶ L.obj Y` in `D`,
there exists an auxiliary object `Y' : C` and morphisms `g : X ⟶ Y'` and `s : Y ⟶ Y'`,
with `W s`, such that the given morphism is a sort of fraction `g / s`,
or more precisely of the form `L.map g ≫ (Localization.isoOfHom L W s hs).inv`.
We also show that the functor `L.mapArrow : Arrow C ⥤ Arrow D` is essentially surjective.
Similar results are obtained when `W` has a right calculus of fractions.
## References
* [P. Gabriel, M. Zisman, *Calculus of fractions and homotopy theory*][gabriel-zisman-1967]
-/
namespace CategoryTheory
variable {C D : Type*} [Category C] [Category D]
open Category
namespace MorphismProperty
/-- A left fraction from `X : C` to `Y : C` for `W : MorphismProperty C` consists of the
datum of an object `Y' : C` and maps `f : X ⟶ Y'` and `s : Y ⟶ Y'` such that `W s`. -/
structure LeftFraction (W : MorphismProperty C) (X Y : C) where
/-- the auxiliary object of a left fraction -/
{Y' : C}
/-- the numerator of a left fraction -/
f : X ⟶ Y'
/-- the denominator of a left fraction -/
s : Y ⟶ Y'
/-- the condition that the denominator belongs to the given morphism property -/
hs : W s
namespace LeftFraction
variable (W : MorphismProperty C) {X Y : C}
/-- The left fraction from `X` to `Y` given by a morphism `f : X ⟶ Y`. -/
@[simps]
def ofHom (f : X ⟶ Y) [W.ContainsIdentities] :
W.LeftFraction X Y := mk f (𝟙 Y) (W.id_mem Y)
variable {W}
/-- The left fraction from `X` to `Y` given by a morphism `s : Y ⟶ X` such that `W s`. -/
@[simps]
def ofInv (s : Y ⟶ X) (hs : W s) :
W.LeftFraction X Y := mk (𝟙 X) s hs
/-- If `φ : W.LeftFraction X Y` and `L` is a functor which inverts `W`, this is the
induced morphism `L.obj X ⟶ L.obj Y` -/
noncomputable def map (φ : W.LeftFraction X Y) (L : C ⥤ D) (hL : W.IsInvertedBy L) :
L.obj X ⟶ L.obj Y :=
have := hL _ φ.hs
L.map φ.f ≫ inv (L.map φ.s)
@[reassoc (attr := simp)]
lemma map_comp_map_s (φ : W.LeftFraction X Y) (L : C ⥤ D) (hL : W.IsInvertedBy L) :
φ.map L hL ≫ L.map φ.s = L.map φ.f := by
letI := hL _ φ.hs
simp [map]
variable (W)
lemma map_ofHom (f : X ⟶ Y) (L : C ⥤ D) (hL : W.IsInvertedBy L) [W.ContainsIdentities] :
(ofHom W f).map L hL = L.map f := by
simp [map]
@[reassoc (attr := simp)]
lemma map_ofInv_hom_id (s : Y ⟶ X) (hs : W s) (L : C ⥤ D) (hL : W.IsInvertedBy L) :
(ofInv s hs).map L hL ≫ L.map s = 𝟙 _ := by
letI := hL _ hs
simp [map]
@[reassoc (attr := simp)]
lemma map_hom_ofInv_id (s : Y ⟶ X) (hs : W s) (L : C ⥤ D) (hL : W.IsInvertedBy L) :
L.map s ≫ (ofInv s hs).map L hL = 𝟙 _ := by
letI := hL _ hs
simp [map]
variable {W}
lemma cases (α : W.LeftFraction X Y) :
∃ (Y' : C) (f : X ⟶ Y') (s : Y ⟶ Y') (hs : W s), α = LeftFraction.mk f s hs :=
⟨_, _, _, _, rfl⟩
end LeftFraction
/-- A right fraction from `X : C` to `Y : C` for `W : MorphismProperty C` consists of the
datum of an object `X' : C` and maps `s : X' ⟶ X` and `f : X' ⟶ Y` such that `W s`. -/
structure RightFraction (W : MorphismProperty C) (X Y : C) where
/-- the auxiliary object of a right fraction -/
{X' : C}
/-- the denominator of a right fraction -/
s : X' ⟶ X
/-- the condition that the denominator belongs to the given morphism property -/
hs : W s
/-- the numerator of a right fraction -/
f : X' ⟶ Y
namespace RightFraction
variable (W : MorphismProperty C)
variable {X Y : C}
/-- The right fraction from `X` to `Y` given by a morphism `f : X ⟶ Y`. -/
@[simps]
def ofHom (f : X ⟶ Y) [W.ContainsIdentities] :
W.RightFraction X Y := mk (𝟙 X) (W.id_mem X) f
variable {W}
/-- The right fraction from `X` to `Y` given by a morphism `s : Y ⟶ X` such that `W s`. -/
@[simps]
def ofInv (s : Y ⟶ X) (hs : W s) :
W.RightFraction X Y := mk s hs (𝟙 Y)
/-- If `φ : W.RightFraction X Y` and `L` is a functor which inverts `W`, this is the
induced morphism `L.obj X ⟶ L.obj Y` -/
noncomputable def map (φ : W.RightFraction X Y) (L : C ⥤ D) (hL : W.IsInvertedBy L) :
L.obj X ⟶ L.obj Y :=
have := hL _ φ.hs
inv (L.map φ.s) ≫ L.map φ.f
@[reassoc (attr := simp)]
lemma map_s_comp_map (φ : W.RightFraction X Y) (L : C ⥤ D) (hL : W.IsInvertedBy L) :
L.map φ.s ≫ φ.map L hL = L.map φ.f := by
letI := hL _ φ.hs
simp [map]
variable (W)
@[simp]
lemma map_ofHom (f : X ⟶ Y) (L : C ⥤ D) (hL : W.IsInvertedBy L) [W.ContainsIdentities] :
(ofHom W f).map L hL = L.map f := by
simp [map]
@[reassoc (attr := simp)]
lemma map_ofInv_hom_id (s : Y ⟶ X) (hs : W s) (L : C ⥤ D) (hL : W.IsInvertedBy L) :
(ofInv s hs).map L hL ≫ L.map s = 𝟙 _ := by
letI := hL _ hs
simp [map]
@[reassoc (attr := simp)]
lemma map_hom_ofInv_id (s : Y ⟶ X) (hs : W s) (L : C ⥤ D) (hL : W.IsInvertedBy L) :
L.map s ≫ (ofInv s hs).map L hL = 𝟙 _ := by
letI := hL _ hs
simp [map]
variable {W}
lemma cases (α : W.RightFraction X Y) :
∃ (X' : C) (s : X' ⟶ X) (hs : W s) (f : X' ⟶ Y) , α = RightFraction.mk s hs f :=
⟨_, _, _, _, rfl⟩
end RightFraction
variable (W : MorphismProperty C)
/-- A multiplicative morphism property `W` has left calculus of fractions if
any right fraction can be turned into a left fraction and that two morphisms
that can be equalized by precomposition with a morphism in `W` can also
be equalized by postcomposition with a morphism in `W`. -/
class HasLeftCalculusOfFractions : Prop extends W.IsMultiplicative where
exists_leftFraction ⦃X Y : C⦄ (φ : W.RightFraction X Y) :
∃ (ψ : W.LeftFraction X Y), φ.f ≫ ψ.s = φ.s ≫ ψ.f
ext : ∀ ⦃X' X Y : C⦄ (f₁ f₂ : X ⟶ Y) (s : X' ⟶ X) (_ : W s)
(_ : s ≫ f₁ = s ≫ f₂), ∃ (Y' : C) (t : Y ⟶ Y') (_ : W t), f₁ ≫ t = f₂ ≫ t
/-- A multiplicative morphism property `W` has right calculus of fractions if
any left fraction can be turned into a right fraction and that two morphisms
that can be equalized by postcomposition with a morphism in `W` can also
be equalized by precomposition with a morphism in `W`. -/
class HasRightCalculusOfFractions : Prop extends W.IsMultiplicative where
exists_rightFraction ⦃X Y : C⦄ (φ : W.LeftFraction X Y) :
∃ (ψ : W.RightFraction X Y), ψ.s ≫ φ.f = ψ.f ≫ φ.s
ext : ∀ ⦃X Y Y' : C⦄ (f₁ f₂ : X ⟶ Y) (s : Y ⟶ Y') (_ : W s)
(_ : f₁ ≫ s = f₂ ≫ s), ∃ (X' : C) (t : X' ⟶ X) (_ : W t), t ≫ f₁ = t ≫ f₂
variable {W}
lemma RightFraction.exists_leftFraction [W.HasLeftCalculusOfFractions] {X Y : C}
(φ : W.RightFraction X Y) : ∃ (ψ : W.LeftFraction X Y), φ.f ≫ ψ.s = φ.s ≫ ψ.f :=
HasLeftCalculusOfFractions.exists_leftFraction φ
/-- A choice of a left fraction deduced from a right fraction for a morphism property `W`
when `W` has left calculus of fractions. -/
noncomputable def RightFraction.leftFraction [W.HasLeftCalculusOfFractions] {X Y : C}
(φ : W.RightFraction X Y) : W.LeftFraction X Y :=
φ.exists_leftFraction.choose
@[reassoc]
lemma RightFraction.leftFraction_fac [W.HasLeftCalculusOfFractions] {X Y : C}
(φ : W.RightFraction X Y) : φ.f ≫ φ.leftFraction.s = φ.s ≫ φ.leftFraction.f :=
φ.exists_leftFraction.choose_spec
lemma LeftFraction.exists_rightFraction [W.HasRightCalculusOfFractions] {X Y : C}
(φ : W.LeftFraction X Y) : ∃ (ψ : W.RightFraction X Y), ψ.s ≫ φ.f = ψ.f ≫ φ.s :=
HasRightCalculusOfFractions.exists_rightFraction φ
/-- A choice of a right fraction deduced from a left fraction for a morphism property `W`
when `W` has right calculus of fractions. -/
noncomputable def LeftFraction.rightFraction [W.HasRightCalculusOfFractions] {X Y : C}
(φ : W.LeftFraction X Y) : W.RightFraction X Y :=
φ.exists_rightFraction.choose
@[reassoc]
lemma LeftFraction.rightFraction_fac [W.HasRightCalculusOfFractions] {X Y : C}
(φ : W.LeftFraction X Y) : φ.rightFraction.s ≫ φ.f = φ.rightFraction.f ≫ φ.s :=
φ.exists_rightFraction.choose_spec
/-- The equivalence relation on left fractions for a morphism property `W`. -/
def LeftFractionRel {X Y : C} (z₁ z₂ : W.LeftFraction X Y) : Prop :=
∃ (Z : C) (t₁ : z₁.Y' ⟶ Z) (t₂ : z₂.Y' ⟶ Z) (_ : z₁.s ≫ t₁ = z₂.s ≫ t₂)
(_ : z₁.f ≫ t₁ = z₂.f ≫ t₂), W (z₁.s ≫ t₁)
namespace LeftFractionRel
lemma refl {X Y : C} (z : W.LeftFraction X Y) : LeftFractionRel z z :=
⟨z.Y', 𝟙 _, 𝟙 _, rfl, rfl, by simpa only [Category.comp_id] using z.hs⟩
lemma symm {X Y : C} {z₁ z₂ : W.LeftFraction X Y} (h : LeftFractionRel z₁ z₂) :
LeftFractionRel z₂ z₁ := by
obtain ⟨Z, t₁, t₂, hst, hft, ht⟩ := h
exact ⟨Z, t₂, t₁, hst.symm, hft.symm, by simpa only [← hst] using ht⟩
lemma trans {X Y : C} {z₁ z₂ z₃ : W.LeftFraction X Y}
[HasLeftCalculusOfFractions W]
(h₁₂ : LeftFractionRel z₁ z₂) (h₂₃ : LeftFractionRel z₂ z₃) :
LeftFractionRel z₁ z₃ := by
obtain ⟨Z₄, t₁, t₂, hst, hft, ht⟩ := h₁₂
obtain ⟨Z₅, u₂, u₃, hsu, hfu, hu⟩ := h₂₃
obtain ⟨⟨v₄, v₅, hv₅⟩, fac⟩ := HasLeftCalculusOfFractions.exists_leftFraction
(RightFraction.mk (z₁.s ≫ t₁) ht (z₃.s ≫ u₃))
simp only [Category.assoc] at fac
have eq : z₂.s ≫ u₂ ≫ v₅ = z₂.s ≫ t₂ ≫ v₄ := by
simpa only [← reassoc_of% hsu, reassoc_of% hst] using fac
obtain ⟨Z₇, w, hw, fac'⟩ := HasLeftCalculusOfFractions.ext _ _ _ z₂.hs eq
simp only [Category.assoc] at fac'
refine ⟨Z₇, t₁ ≫ v₄ ≫ w, u₃ ≫ v₅ ≫ w, ?_, ?_, ?_⟩
· rw [reassoc_of% fac]
· rw [reassoc_of% hft, ← fac', reassoc_of% hfu]
· rw [← reassoc_of% fac, ← reassoc_of% hsu, ← Category.assoc]
exact W.comp_mem _ _ hu (W.comp_mem _ _ hv₅ hw)
end LeftFractionRel
section
variable (W)
lemma equivalenceLeftFractionRel [W.HasLeftCalculusOfFractions] (X Y : C) :
@_root_.Equivalence (W.LeftFraction X Y) LeftFractionRel where
refl := LeftFractionRel.refl
symm := LeftFractionRel.symm
trans := LeftFractionRel.trans
variable {W}
namespace LeftFraction
open HasLeftCalculusOfFractions
/-- Auxiliary definition for the composition of left fractions. -/
@[simp]
def comp₀ [W.HasLeftCalculusOfFractions] {X Y Z : C}
(z₁ : W.LeftFraction X Y) (z₂ : W.LeftFraction Y Z) (z₃ : W.LeftFraction z₁.Y' z₂.Y') :
W.LeftFraction X Z :=
mk (z₁.f ≫ z₃.f) (z₂.s ≫ z₃.s) (W.comp_mem _ _ z₂.hs z₃.hs)
/-- The equivalence class of `z₁.comp₀ z₂ z₃` does not depend on the choice of `z₃` provided
they satisfy the compatibility `z₂.f ≫ z₃.s = z₁.s ≫ z₃.f`. -/
lemma comp₀_rel [W.HasLeftCalculusOfFractions]
{X Y Z : C} (z₁ : W.LeftFraction X Y) (z₂ : W.LeftFraction Y Z)
(z₃ z₃' : W.LeftFraction z₁.Y' z₂.Y') (h₃ : z₂.f ≫ z₃.s = z₁.s ≫ z₃.f)
(h₃' : z₂.f ≫ z₃'.s = z₁.s ≫ z₃'.f) :
LeftFractionRel (z₁.comp₀ z₂ z₃) (z₁.comp₀ z₂ z₃') := by
obtain ⟨z₄, fac⟩ := exists_leftFraction (RightFraction.mk z₃.s z₃.hs z₃'.s)
dsimp at fac
have eq : z₁.s ≫ z₃.f ≫ z₄.f = z₁.s ≫ z₃'.f ≫ z₄.s := by
rw [← reassoc_of% h₃, ← reassoc_of% h₃', fac]
obtain ⟨Y, t, ht, fac'⟩ := HasLeftCalculusOfFractions.ext _ _ _ z₁.hs eq
simp only [assoc] at fac'
refine ⟨Y, z₄.f ≫ t, z₄.s ≫ t, ?_, ?_, ?_⟩
· simp only [comp₀, assoc, reassoc_of% fac]
· simp only [comp₀, assoc, fac']
· simp only [comp₀, assoc, ← reassoc_of% fac]
exact W.comp_mem _ _ z₂.hs (W.comp_mem _ _ z₃'.hs (W.comp_mem _ _ z₄.hs ht))
variable (W) in
/-- The morphisms in the constructed localized category for a morphism property `W`
that has left calculus of fractions are equivalence classes of left fractions. -/
def Localization.Hom (X Y : C) :=
Quot (LeftFractionRel : W.LeftFraction X Y → W.LeftFraction X Y → Prop)
/-- The morphism in the constructed localized category that is induced by a left fraction. -/
def Localization.Hom.mk {X Y : C} (z : W.LeftFraction X Y) : Localization.Hom W X Y :=
Quot.mk _ z
lemma Localization.Hom.mk_surjective {X Y : C} (f : Localization.Hom W X Y) :
∃ (z : W.LeftFraction X Y), f = mk z := by
obtain ⟨z⟩ := f
exact ⟨z, rfl⟩
variable [W.HasLeftCalculusOfFractions]
/-- Auxiliary definition towards the definition of the composition of morphisms
in the constructed localized category for a morphism property that has
left calculus of fractions. -/
noncomputable def comp
{X Y Z : C} (z₁ : W.LeftFraction X Y) (z₂ : W.LeftFraction Y Z) :
Localization.Hom W X Z :=
Localization.Hom.mk (z₁.comp₀ z₂ (RightFraction.mk z₁.s z₁.hs z₂.f).leftFraction)
lemma comp_eq {X Y Z : C} (z₁ : W.LeftFraction X Y) (z₂ : W.LeftFraction Y Z)
(z₃ : W.LeftFraction z₁.Y' z₂.Y') (h₃ : z₂.f ≫ z₃.s = z₁.s ≫ z₃.f) :
z₁.comp z₂ = Localization.Hom.mk (z₁.comp₀ z₂ z₃) :=
Quot.sound (LeftFraction.comp₀_rel _ _ _ _
(RightFraction.leftFraction_fac (RightFraction.mk z₁.s z₁.hs z₂.f)) h₃)
namespace Localization
/-- Composition of morphisms in the constructed localized category
for a morphism property that has left calculus of fractions. -/
noncomputable def Hom.comp {X Y Z : C} (z₁ : Hom W X Y) (z₂ : Hom W Y Z) : Hom W X Z := by
refine Quot.lift₂ (fun a b => a.comp b) ?_ ?_ z₁ z₂
· rintro a b₁ b₂ ⟨U, t₁, t₂, hst, hft, ht⟩
obtain ⟨z₁, fac₁⟩ := exists_leftFraction (RightFraction.mk a.s a.hs b₁.f)
obtain ⟨z₂, fac₂⟩ := exists_leftFraction (RightFraction.mk a.s a.hs b₂.f)
obtain ⟨w₁, fac₁'⟩ := exists_leftFraction (RightFraction.mk z₁.s z₁.hs t₁)
obtain ⟨w₂, fac₂'⟩ := exists_leftFraction (RightFraction.mk z₂.s z₂.hs t₂)
obtain ⟨u, fac₃⟩ := exists_leftFraction (RightFraction.mk w₁.s w₁.hs w₂.s)
dsimp at fac₁ fac₂ fac₁' fac₂' fac₃ ⊢
have eq : a.s ≫ z₁.f ≫ w₁.f ≫ u.f = a.s ≫ z₂.f ≫ w₂.f ≫ u.s := by
rw [← reassoc_of% fac₁, ← reassoc_of% fac₂, ← reassoc_of% fac₁', ← reassoc_of% fac₂',
reassoc_of% hft, fac₃]
obtain ⟨Z, p, hp, fac₄⟩ := HasLeftCalculusOfFractions.ext _ _ _ a.hs eq
simp only [assoc] at fac₄
rw [comp_eq _ _ z₁ fac₁, comp_eq _ _ z₂ fac₂]
apply Quot.sound
refine ⟨Z, w₁.f ≫ u.f ≫ p, w₂.f ≫ u.s ≫ p, ?_, ?_, ?_⟩
· dsimp
simp only [assoc, ← reassoc_of% fac₁', ← reassoc_of% fac₂',
reassoc_of% hst, reassoc_of% fac₃]
· dsimp
simp only [assoc, fac₄]
· dsimp
simp only [assoc]
rw [← reassoc_of% fac₁', ← reassoc_of% fac₃, ← assoc]
exact W.comp_mem _ _ ht (W.comp_mem _ _ w₂.hs (W.comp_mem _ _ u.hs hp))
· rintro a₁ a₂ b ⟨U, t₁, t₂, hst, hft, ht⟩
obtain ⟨z₁, fac₁⟩ := exists_leftFraction (RightFraction.mk a₁.s a₁.hs b.f)
obtain ⟨z₂, fac₂⟩ := exists_leftFraction (RightFraction.mk a₂.s a₂.hs b.f)
obtain ⟨w₁, fac₁'⟩ := exists_leftFraction (RightFraction.mk (a₁.s ≫ t₁) ht (b.f ≫ z₁.s))
obtain ⟨w₂, fac₂'⟩ := exists_leftFraction (RightFraction.mk (a₂.s ≫ t₂)
(show W _ by rw [← hst]; exact ht) (b.f ≫ z₂.s))
let p₁ : W.LeftFraction X Z := LeftFraction.mk (a₁.f ≫ t₁ ≫ w₁.f) (b.s ≫ z₁.s ≫ w₁.s)
(W.comp_mem _ _ b.hs (W.comp_mem _ _ z₁.hs w₁.hs))
let p₂ : W.LeftFraction X Z := LeftFraction.mk (a₂.f ≫ t₂ ≫ w₂.f) (b.s ≫ z₂.s ≫ w₂.s)
(W.comp_mem _ _ b.hs (W.comp_mem _ _ z₂.hs w₂.hs))
dsimp at fac₁ fac₂ fac₁' fac₂' ⊢
simp only [assoc] at fac₁' fac₂'
rw [comp_eq _ _ z₁ fac₁, comp_eq _ _ z₂ fac₂]
apply Quot.sound
refine LeftFractionRel.trans ?_ ((?_ : LeftFractionRel p₁ p₂).trans ?_)
· have eq : a₁.s ≫ z₁.f ≫ w₁.s = a₁.s ≫ t₁ ≫ w₁.f := by rw [← fac₁', reassoc_of% fac₁]
obtain ⟨Z, u, hu, fac₃⟩ := HasLeftCalculusOfFractions.ext _ _ _ a₁.hs eq
simp only [assoc] at fac₃
refine ⟨Z, w₁.s ≫ u, u, ?_, ?_, ?_⟩
· dsimp [p₁]
simp only [assoc]
· dsimp [p₁]
simp only [assoc, fac₃]
· dsimp
simp only [assoc]
exact W.comp_mem _ _ b.hs (W.comp_mem _ _ z₁.hs (W.comp_mem _ _ w₁.hs hu))
· obtain ⟨q, fac₃⟩ := exists_leftFraction (RightFraction.mk (z₁.s ≫ w₁.s)
(W.comp_mem _ _ z₁.hs w₁.hs) (z₂.s ≫ w₂.s))
dsimp at fac₃
simp only [assoc] at fac₃
have eq : a₁.s ≫ t₁ ≫ w₁.f ≫ q.f = a₁.s ≫ t₁ ≫ w₂.f ≫ q.s := by
rw [← reassoc_of% fac₁', ← fac₃, reassoc_of% hst, reassoc_of% fac₂']
obtain ⟨Z, u, hu, fac₄⟩ := HasLeftCalculusOfFractions.ext _ _ _ a₁.hs eq
simp only [assoc] at fac₄
refine ⟨Z, q.f ≫ u, q.s ≫ u, ?_, ?_, ?_⟩
· simp only [p₁, p₂, assoc, reassoc_of% fac₃]
· rw [assoc, assoc, assoc, assoc, fac₄, reassoc_of% hft]
· simp only [p₁, p₂, assoc, ← reassoc_of% fac₃]
exact W.comp_mem _ _ b.hs (W.comp_mem _ _ z₂.hs
(W.comp_mem _ _ w₂.hs (W.comp_mem _ _ q.hs hu)))
· have eq : a₂.s ≫ z₂.f ≫ w₂.s = a₂.s ≫ t₂ ≫ w₂.f := by
rw [← fac₂', reassoc_of% fac₂]
obtain ⟨Z, u, hu, fac₄⟩ := HasLeftCalculusOfFractions.ext _ _ _ a₂.hs eq
simp only [assoc] at fac₄
refine ⟨Z, u, w₂.s ≫ u, ?_, ?_, ?_⟩
· dsimp [p₁, p₂]
simp only [assoc]
· dsimp [p₁, p₂]
simp only [assoc, fac₄]
· dsimp [p₁, p₂]
simp only [assoc]
exact W.comp_mem _ _ b.hs (W.comp_mem _ _ z₂.hs (W.comp_mem _ _ w₂.hs hu))
lemma Hom.comp_eq {X Y Z : C} (z₁ : W.LeftFraction X Y) (z₂ : W.LeftFraction Y Z) :
Hom.comp (mk z₁) (mk z₂) = z₁.comp z₂ := rfl
end Localization
/-- The constructed localized category for a morphism property
that has left calculus of fractions. -/
@[nolint unusedArguments]
def Localization (_ : MorphismProperty C) := C
namespace Localization
noncomputable instance : Category (Localization W) where
Hom X Y := Localization.Hom W X Y
id _ := Localization.Hom.mk (ofHom W (𝟙 _))
comp f g := f.comp g
comp_id := by
rintro (X Y : C) f
obtain ⟨z, rfl⟩ := Hom.mk_surjective f
change (Hom.mk z).comp (Hom.mk (ofHom W (𝟙 Y))) = Hom.mk z
rw [Hom.comp_eq, comp_eq z (ofHom W (𝟙 Y)) (ofInv z.s z.hs) (by simp)]
dsimp [comp₀]
simp only [comp_id, id_comp]
id_comp := by
rintro (X Y : C) f
obtain ⟨z, rfl⟩ := Hom.mk_surjective f
change (Hom.mk (ofHom W (𝟙 X))).comp (Hom.mk z) = Hom.mk z
rw [Hom.comp_eq, comp_eq (ofHom W (𝟙 X)) z (ofHom W z.f) (by simp)]
dsimp
simp only [comp₀, id_comp, comp_id]
assoc := by
rintro (X₁ X₂ X₃ X₄ : C) f₁ f₂ f₃
obtain ⟨z₁, rfl⟩ := Hom.mk_surjective f₁
obtain ⟨z₂, rfl⟩ := Hom.mk_surjective f₂
obtain ⟨z₃, rfl⟩ := Hom.mk_surjective f₃
change ((Hom.mk z₁).comp (Hom.mk z₂)).comp (Hom.mk z₃) =
(Hom.mk z₁).comp ((Hom.mk z₂).comp (Hom.mk z₃))
rw [Hom.comp_eq z₁ z₂, Hom.comp_eq z₂ z₃]
obtain ⟨z₁₂, fac₁₂⟩ := exists_leftFraction (RightFraction.mk z₁.s z₁.hs z₂.f)
obtain ⟨z₂₃, fac₂₃⟩ := exists_leftFraction (RightFraction.mk z₂.s z₂.hs z₃.f)
obtain ⟨z', fac⟩ := exists_leftFraction (RightFraction.mk z₁₂.s z₁₂.hs z₂₃.f)
dsimp at fac₁₂ fac₂₃ fac
rw [comp_eq z₁ z₂ z₁₂ fac₁₂, comp_eq z₂ z₃ z₂₃ fac₂₃, comp₀, comp₀,
Hom.comp_eq, Hom.comp_eq,
comp_eq _ z₃ (mk z'.f (z₂₃.s ≫ z'.s) (W.comp_mem _ _ z₂₃.hs z'.hs))
(by dsimp; rw [assoc, reassoc_of% fac₂₃, fac]),
comp_eq z₁ _ (mk (z₁₂.f ≫ z'.f) z'.s z'.hs)
(by dsimp; rw [assoc, ← reassoc_of% fac₁₂, fac])]
simp
variable (W) in
/-- The localization functor to the constructed localized category for a morphism property
that has left calculus of fractions. -/
@[simps obj]
def Q : C ⥤ Localization W where
obj X := X
map f := Hom.mk (ofHom W f)
map_id _ := rfl
map_comp {X Y Z} f g := by
change _ = Hom.comp _ _
rw [Hom.comp_eq, comp_eq (ofHom W f) (ofHom W g) (ofHom W g) (by simp)]
simp only [ofHom, comp₀, comp_id]
/-- The morphism on `Localization W` that is induced by a left fraction. -/
abbrev homMk {X Y : C} (f : W.LeftFraction X Y) : (Q W).obj X ⟶ (Q W).obj Y := Hom.mk f
lemma homMk_eq_hom_mk {X Y : C} (f : W.LeftFraction X Y) : homMk f = Hom.mk f := rfl
variable (W)
lemma Q_map {X Y : C} (f : X ⟶ Y) : (Q W).map f = homMk (ofHom W f) := rfl
variable {W}
lemma homMk_comp_homMk {X Y Z : C} (z₁ : W.LeftFraction X Y) (z₂ : W.LeftFraction Y Z)
(z₃ : W.LeftFraction z₁.Y' z₂.Y') (h₃ : z₂.f ≫ z₃.s = z₁.s ≫ z₃.f) :
homMk z₁ ≫ homMk z₂ = homMk (z₁.comp₀ z₂ z₃) := by
change Hom.comp _ _ = _
rw [Hom.comp_eq, comp_eq z₁ z₂ z₃ h₃]
lemma homMk_eq_of_leftFractionRel {X Y : C} (z₁ z₂ : W.LeftFraction X Y)
(h : LeftFractionRel z₁ z₂) :
homMk z₁ = homMk z₂ :=
Quot.sound h
lemma homMk_eq_iff_leftFractionRel {X Y : C} (z₁ z₂ : W.LeftFraction X Y) :
homMk z₁ = homMk z₂ ↔ LeftFractionRel z₁ z₂ :=
@Equivalence.quot_mk_eq_iff _ _ (equivalenceLeftFractionRel W X Y) _ _
/-- The morphism in `Localization W` that is the formal inverse of a morphism
which belongs to `W`. -/
def Qinv {X Y : C} (s : X ⟶ Y) (hs : W s) : (Q W).obj Y ⟶ (Q W).obj X := homMk (ofInv s hs)
lemma Q_map_comp_Qinv {X Y Y' : C} (f : X ⟶ Y') (s : Y ⟶ Y') (hs : W s) :
(Q W).map f ≫ Qinv s hs = homMk (mk f s hs) := by
dsimp only [Q_map, Qinv]
rw [homMk_comp_homMk (ofHom W f) (ofInv s hs) (ofHom W (𝟙 _)) (by simp)]
simp
/-- The isomorphism in `Localization W` that is induced by a morphism in `W`. -/
@[simps]
def Qiso {X Y : C} (s : X ⟶ Y) (hs : W s) : (Q W).obj X ≅ (Q W).obj Y where
hom := (Q W).map s
inv := Qinv s hs
hom_inv_id := by
rw [Q_map_comp_Qinv]
apply homMk_eq_of_leftFractionRel
exact ⟨_, 𝟙 Y, s, by simp, by simp, by simpa using hs⟩
inv_hom_id := by
dsimp only [Qinv, Q_map]
rw [homMk_comp_homMk (ofInv s hs) (ofHom W s) (ofHom W (𝟙 Y)) (by simp)]
apply homMk_eq_of_leftFractionRel
exact ⟨_, 𝟙 Y, 𝟙 Y, by simp, by simp, by simpa using W.id_mem Y⟩
@[reassoc (attr := simp)]
lemma Qiso_hom_inv_id {X Y : C} (s : X ⟶ Y) (hs : W s) :
(Q W).map s ≫ Qinv s hs = 𝟙 _ := (Qiso s hs).hom_inv_id
@[reassoc (attr := simp)]
lemma Qiso_inv_hom_id {X Y : C} (s : X ⟶ Y) (hs : W s) :
Qinv s hs ≫ (Q W).map s = 𝟙 _ := (Qiso s hs).inv_hom_id
instance {X Y : C} (s : X ⟶ Y) (hs : W s) : IsIso (Qinv s hs) :=
(inferInstance : IsIso (Qiso s hs).inv)
section
variable {E : Type*} [Category E]
/-- The image by a functor which inverts `W` of an equivalence class of left fractions. -/
noncomputable def Hom.map {X Y : C} (f : Hom W X Y) (F : C ⥤ E) (hF : W.IsInvertedBy F) :
F.obj X ⟶ F.obj Y :=
Quot.lift (fun f => f.map F hF) (by
intro a₁ a₂ ⟨Z, t₁, t₂, hst, hft, h⟩
dsimp
have := hF _ h
rw [← cancel_mono (F.map (a₁.s ≫ t₁)), F.map_comp, map_comp_map_s_assoc,
← F.map_comp, ← F.map_comp, hst, hft, F.map_comp,
F.map_comp, map_comp_map_s_assoc]) f
@[simp]
lemma Hom.map_mk {W} {X Y : C} (f : LeftFraction W X Y)
(F : C ⥤ E) (hF : W.IsInvertedBy F) :
Hom.map (Hom.mk f) F hF = f.map F hF := rfl
namespace StrictUniversalPropertyFixedTarget
variable (W)
lemma inverts : W.IsInvertedBy (Q W) := fun _ _ s hs =>
(inferInstance : IsIso (Qiso s hs).hom)
variable {W}
/-- The functor `Localization W ⥤ E` that is induced by a functor `C ⥤ E` which inverts `W`,
when `W` has a left calculus of fractions. -/
noncomputable def lift (F : C ⥤ E) (hF : W.IsInvertedBy F) :
Localization W ⥤ E where
obj X := F.obj X
map {_ _ : C} f := f.map F hF
map_id := by
intro (X : C)
change (Hom.mk (ofHom W (𝟙 X))).map F hF = _
rw [Hom.map_mk, map_ofHom, F.map_id]
map_comp := by
rintro (X Y Z : C) f g
obtain ⟨f, rfl⟩ := Hom.mk_surjective f
obtain ⟨g, rfl⟩ := Hom.mk_surjective g
dsimp
obtain ⟨z, fac⟩ := HasLeftCalculusOfFractions.exists_leftFraction
(RightFraction.mk f.s f.hs g.f)
rw [homMk_comp_homMk f g z fac, Hom.map_mk]
dsimp at fac ⊢
have := hF _ g.hs
have := hF _ z.hs
rw [← cancel_mono (F.map g.s), assoc, map_comp_map_s,
← cancel_mono (F.map z.s), assoc, assoc, ← F.map_comp,
← F.map_comp, map_comp_map_s, fac]
dsimp
rw [F.map_comp, F.map_comp, map_comp_map_s_assoc]
lemma fac (F : C ⥤ E) (hF : W.IsInvertedBy F) : Q W ⋙ lift F hF = F :=
Functor.ext (fun _ => rfl) (fun X Y f => by
dsimp [lift]
rw [Q_map, Hom.map_mk, id_comp, comp_id, map_ofHom])
lemma uniq (F₁ F₂ : Localization W ⥤ E) (h : Q W ⋙ F₁ = Q W ⋙ F₂) : F₁ = F₂ :=
Functor.ext (fun X => Functor.congr_obj h X) (by
rintro (X Y : C) f
obtain ⟨f, rfl⟩ := Hom.mk_surjective f
rw [show Hom.mk f = homMk (mk f.f f.s f.hs) by rfl,
← Q_map_comp_Qinv f.f f.s f.hs, F₁.map_comp, F₂.map_comp, assoc]
erw [Functor.congr_hom h f.f]
rw [assoc, assoc]
congr 2
have := inverts W _ f.hs
rw [← cancel_epi (F₂.map ((Q W).map f.s)), ← F₂.map_comp_assoc,
Qiso_hom_inv_id, Functor.map_id, id_comp]
erw [Functor.congr_hom h.symm f.s]
dsimp
rw [assoc, assoc, eqToHom_trans_assoc, eqToHom_refl, id_comp, ← F₁.map_comp,
Qiso_hom_inv_id]
dsimp
rw [F₁.map_id, comp_id])
end StrictUniversalPropertyFixedTarget
variable (W)
open StrictUniversalPropertyFixedTarget in
/-- The universal property of the localization for the constructed localized category
when there is a left calculus of fractions. -/
noncomputable def strictUniversalPropertyFixedTarget (E : Type*) [Category E] :
Localization.StrictUniversalPropertyFixedTarget (Q W) W E where
inverts := inverts W
lift := lift
fac := fac
uniq := uniq
instance : (Q W).IsLocalization W :=
Functor.IsLocalization.mk' _ _
(strictUniversalPropertyFixedTarget W _)
(strictUniversalPropertyFixedTarget W _)
end
lemma homMk_eq {X Y : C} (f : LeftFraction W X Y) :
homMk f = f.map (Q W) (Localization.inverts _ W) := by
have := Localization.inverts (Q W) W f.s f.hs
rw [← Q_map_comp_Qinv f.f f.s f.hs, ← cancel_mono ((Q W).map f.s),
assoc, Qiso_inv_hom_id, comp_id, map_comp_map_s]
lemma map_eq_iff {X Y : C} (f g : LeftFraction W X Y) :
f.map (LeftFraction.Localization.Q W) (Localization.inverts _ _) =
g.map (LeftFraction.Localization.Q W) (Localization.inverts _ _) ↔
LeftFractionRel f g := by
simp only [← Hom.map_mk _ (Q W)]
constructor
· intro h
rw [← homMk_eq_iff_leftFractionRel, homMk_eq, homMk_eq]
exact h
· intro h
congr 1
exact Quot.sound h
end Localization
section
lemma map_eq {W} {X Y : C} (φ : W.LeftFraction X Y) (L : C ⥤ D) [L.IsLocalization W] :
φ.map L (Localization.inverts L W) =
L.map φ.f ≫ (Localization.isoOfHom L W φ.s φ.hs).inv := rfl
lemma map_compatibility {W} {X Y : C}
(φ : W.LeftFraction X Y) {E : Type*} [Category E]
(L₁ : C ⥤ D) (L₂ : C ⥤ E) [L₁.IsLocalization W] [L₂.IsLocalization W] :
| (Localization.uniq L₁ L₂ W).functor.map (φ.map L₁ (Localization.inverts L₁ W)) =
(Localization.compUniqFunctor L₁ L₂ W).hom.app X ≫
φ.map L₂ (Localization.inverts L₂ W) ≫
(Localization.compUniqFunctor L₁ L₂ W).inv.app Y := by
let e := Localization.compUniqFunctor L₁ L₂ W
have := Localization.inverts L₂ W φ.s φ.hs
rw [← cancel_mono (e.hom.app Y), assoc, assoc, e.inv_hom_id_app, comp_id,
← cancel_mono (L₂.map φ.s), assoc, assoc, map_comp_map_s, ← e.hom.naturality]
simpa [← Functor.map_comp_assoc, map_comp_map_s] using e.hom.naturality φ.f
lemma map_eq_of_map_eq {W} {X Y : C}
(φ₁ φ₂ : W.LeftFraction X Y) {E : Type*} [Category E]
| Mathlib/CategoryTheory/Localization/CalculusOfFractions.lean | 675 | 686 |
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Polynomial.Expand
import Mathlib.Algebra.Polynomial.Splits
import Mathlib.Algebra.Squarefree.Basic
import Mathlib.FieldTheory.IntermediateField.Basic
import Mathlib.FieldTheory.Minpoly.Field
import Mathlib.RingTheory.Polynomial.Content
import Mathlib.RingTheory.PowerBasis
import Mathlib.Data.ENat.Lattice
/-!
# Separable polynomials
We define a polynomial to be separable if it is coprime with its derivative. We prove basic
properties about separable polynomials here.
## Main definitions
* `Polynomial.Separable f`: a polynomial `f` is separable iff it is coprime with its derivative.
* `IsSeparable K x`: an element `x` is separable over `K` iff the minimal polynomial of `x`
over `K` is separable.
* `Algebra.IsSeparable K L`: `L` is separable over `K` iff every element in `L` is separable
over `K`.
-/
universe u v w
open Polynomial Finset
namespace Polynomial
section CommSemiring
variable {R : Type u} [CommSemiring R] {S : Type v} [CommSemiring S]
/-- A polynomial is separable iff it is coprime with its derivative. -/
@[stacks 09H1 "first part"]
def Separable (f : R[X]) : Prop :=
IsCoprime f (derivative f)
theorem separable_def (f : R[X]) : f.Separable ↔ IsCoprime f (derivative f) :=
Iff.rfl
theorem separable_def' (f : R[X]) : f.Separable ↔ ∃ a b : R[X], a * f + b * (derivative f) = 1 :=
Iff.rfl
theorem not_separable_zero [Nontrivial R] : ¬Separable (0 : R[X]) := by
rintro ⟨x, y, h⟩
simp only [derivative_zero, mul_zero, add_zero, zero_ne_one] at h
theorem Separable.ne_zero [Nontrivial R] {f : R[X]} (h : f.Separable) : f ≠ 0 :=
(not_separable_zero <| · ▸ h)
@[simp]
theorem separable_one : (1 : R[X]).Separable :=
isCoprime_one_left
@[nontriviality]
theorem separable_of_subsingleton [Subsingleton R] (f : R[X]) : f.Separable := by
simp [Separable, IsCoprime, eq_iff_true_of_subsingleton]
theorem separable_X_add_C (a : R) : (X + C a).Separable := by
rw [separable_def, derivative_add, derivative_X, derivative_C, add_zero]
exact isCoprime_one_right
theorem separable_X : (X : R[X]).Separable := by
rw [separable_def, derivative_X]
exact isCoprime_one_right
theorem separable_C (r : R) : (C r).Separable ↔ IsUnit r := by
rw [separable_def, derivative_C, isCoprime_zero_right, isUnit_C]
theorem Separable.of_mul_left {f g : R[X]} (h : (f * g).Separable) : f.Separable := by
have := h.of_mul_left_left; rw [derivative_mul] at this
exact IsCoprime.of_mul_right_left (IsCoprime.of_add_mul_left_right this)
theorem Separable.of_mul_right {f g : R[X]} (h : (f * g).Separable) : g.Separable := by
rw [mul_comm] at h
exact h.of_mul_left
theorem Separable.of_dvd {f g : R[X]} (hf : f.Separable) (hfg : g ∣ f) : g.Separable := by
rcases hfg with ⟨f', rfl⟩
exact Separable.of_mul_left hf
theorem separable_gcd_left {F : Type*} [Field F] [DecidableEq F[X]]
{f : F[X]} (hf : f.Separable) (g : F[X]) :
(EuclideanDomain.gcd f g).Separable :=
Separable.of_dvd hf (EuclideanDomain.gcd_dvd_left f g)
theorem separable_gcd_right {F : Type*} [Field F] [DecidableEq F[X]]
{g : F[X]} (f : F[X]) (hg : g.Separable) :
(EuclideanDomain.gcd f g).Separable :=
Separable.of_dvd hg (EuclideanDomain.gcd_dvd_right f g)
theorem Separable.isCoprime {f g : R[X]} (h : (f * g).Separable) : IsCoprime f g := by
have := h.of_mul_left_left; rw [derivative_mul] at this
exact IsCoprime.of_mul_right_right (IsCoprime.of_add_mul_left_right this)
theorem Separable.of_pow' {f : R[X]} :
∀ {n : ℕ} (_h : (f ^ n).Separable), IsUnit f ∨ f.Separable ∧ n = 1 ∨ n = 0
| 0 => fun _h => Or.inr <| Or.inr rfl
| 1 => fun h => Or.inr <| Or.inl ⟨pow_one f ▸ h, rfl⟩
| n + 2 => fun h => by
rw [pow_succ, pow_succ] at h
exact Or.inl (isCoprime_self.1 h.isCoprime.of_mul_left_right)
theorem Separable.of_pow {f : R[X]} (hf : ¬IsUnit f) {n : ℕ} (hn : n ≠ 0)
(hfs : (f ^ n).Separable) : f.Separable ∧ n = 1 :=
(hfs.of_pow'.resolve_left hf).resolve_right hn
theorem Separable.map {p : R[X]} (h : p.Separable) {f : R →+* S} : (p.map f).Separable :=
let ⟨a, b, H⟩ := h
⟨a.map f, b.map f, by
rw [derivative_map, ← Polynomial.map_mul, ← Polynomial.map_mul, ← Polynomial.map_add, H,
Polynomial.map_one]⟩
theorem _root_.Associated.separable {f g : R[X]}
(ha : Associated f g) (h : f.Separable) : g.Separable := by
obtain ⟨⟨u, v, h1, h2⟩, ha⟩ := ha
obtain ⟨a, b, h⟩ := h
refine ⟨a * v + b * derivative v, b * v, ?_⟩
replace h := congr($h * $(h1))
have h3 := congr(derivative $(h1))
simp only [← ha, derivative_mul, derivative_one] at h3 ⊢
calc
_ = (a * f + b * derivative f) * (u * v)
+ (b * f) * (derivative u * v + u * derivative v) := by ring1
_ = 1 := by rw [h, h3]; ring1
theorem _root_.Associated.separable_iff {f g : R[X]}
(ha : Associated f g) : f.Separable ↔ g.Separable := ⟨ha.separable, ha.symm.separable⟩
theorem Separable.mul_unit {f g : R[X]} (hf : f.Separable) (hg : IsUnit g) : (f * g).Separable :=
(associated_mul_unit_right f g hg).separable hf
theorem Separable.unit_mul {f g : R[X]} (hf : IsUnit f) (hg : g.Separable) : (f * g).Separable :=
(associated_unit_mul_right g f hf).separable hg
theorem Separable.eval₂_derivative_ne_zero [Nontrivial S] (f : R →+* S) {p : R[X]}
(h : p.Separable) {x : S} (hx : p.eval₂ f x = 0) :
(derivative p).eval₂ f x ≠ 0 := by
intro hx'
obtain ⟨a, b, e⟩ := h
apply_fun Polynomial.eval₂ f x at e
simp only [eval₂_add, eval₂_mul, hx, mul_zero, hx', add_zero, eval₂_one, zero_ne_one] at e
theorem Separable.aeval_derivative_ne_zero [Nontrivial S] [Algebra R S] {p : R[X]}
(h : p.Separable) {x : S} (hx : aeval x p = 0) :
aeval x (derivative p) ≠ 0 :=
h.eval₂_derivative_ne_zero (algebraMap R S) hx
variable (p q : ℕ)
theorem isUnit_of_self_mul_dvd_separable {p q : R[X]} (hp : p.Separable) (hq : q * q ∣ p) :
IsUnit q := by
obtain ⟨p, rfl⟩ := hq
apply isCoprime_self.mp
have : IsCoprime (q * (q * p))
(q * (derivative q * p + derivative q * p + q * derivative p)) := by
simp only [← mul_assoc, mul_add]
dsimp only [Separable] at hp
convert hp using 1
rw [derivative_mul, derivative_mul]
ring
exact IsCoprime.of_mul_right_left (IsCoprime.of_mul_left_left this)
theorem emultiplicity_le_one_of_separable {p q : R[X]} (hq : ¬IsUnit q) (hsep : Separable p) :
emultiplicity q p ≤ 1 := by
contrapose! hq
apply isUnit_of_self_mul_dvd_separable hsep
rw [← sq]
apply pow_dvd_of_le_emultiplicity
exact Order.add_one_le_of_lt hq
/-- A separable polynomial is square-free.
See `PerfectField.separable_iff_squarefree` for the converse when the coefficients are a perfect
field. -/
theorem Separable.squarefree {p : R[X]} (hsep : Separable p) : Squarefree p := by
classical
rw [squarefree_iff_emultiplicity_le_one p]
exact fun f => or_iff_not_imp_right.mpr fun hunit => emultiplicity_le_one_of_separable hunit hsep
end CommSemiring
section CommRing
variable {R : Type u} [CommRing R]
theorem separable_X_sub_C {x : R} : Separable (X - C x) := by
simpa only [sub_eq_add_neg, C_neg] using separable_X_add_C (-x)
theorem Separable.mul {f g : R[X]} (hf : f.Separable) (hg : g.Separable) (h : IsCoprime f g) :
(f * g).Separable := by
rw [separable_def, derivative_mul]
exact
((hf.mul_right h).add_mul_left_right _).mul_left ((h.symm.mul_right hg).mul_add_right_right _)
theorem separable_prod' {ι : Sort _} {f : ι → R[X]} {s : Finset ι} :
(∀ x ∈ s, ∀ y ∈ s, x ≠ y → IsCoprime (f x) (f y)) →
(∀ x ∈ s, (f x).Separable) → (∏ x ∈ s, f x).Separable := by
classical
exact Finset.induction_on s (fun _ _ => separable_one) fun a s has ih h1 h2 => by
simp_rw [Finset.forall_mem_insert, forall_and] at h1 h2; rw [prod_insert has]
exact
h2.1.mul (ih h1.2.2 h2.2)
(IsCoprime.prod_right fun i his => h1.1.2 i his <| Ne.symm <| ne_of_mem_of_not_mem his has)
open scoped Function in -- required for scoped `on` notation
theorem separable_prod {ι : Sort _} [Fintype ι] {f : ι → R[X]} (h1 : Pairwise (IsCoprime on f))
(h2 : ∀ x, (f x).Separable) : (∏ x, f x).Separable :=
separable_prod' (fun _x _hx _y _hy hxy => h1 hxy) fun x _hx => h2 x
theorem Separable.inj_of_prod_X_sub_C [Nontrivial R] {ι : Sort _} {f : ι → R} {s : Finset ι}
(hfs : (∏ i ∈ s, (X - C (f i))).Separable) {x y : ι} (hx : x ∈ s) (hy : y ∈ s)
(hfxy : f x = f y) : x = y := by
classical
by_contra hxy
rw [← insert_erase hx, prod_insert (not_mem_erase _ _), ←
insert_erase (mem_erase_of_ne_of_mem (Ne.symm hxy) hy), prod_insert (not_mem_erase _ _), ←
mul_assoc, hfxy, ← sq] at hfs
cases (hfs.of_mul_left.of_pow (not_isUnit_X_sub_C _) two_ne_zero).2
theorem Separable.injective_of_prod_X_sub_C [Nontrivial R] {ι : Sort _} [Fintype ι] {f : ι → R}
(hfs : (∏ i, (X - C (f i))).Separable) : Function.Injective f := fun _x _y hfxy =>
hfs.inj_of_prod_X_sub_C (mem_univ _) (mem_univ _) hfxy
theorem nodup_of_separable_prod [Nontrivial R] {s : Multiset R}
(hs : Separable (Multiset.map (fun a => X - C a) s).prod) : s.Nodup := by
rw [Multiset.nodup_iff_ne_cons_cons]
rintro a t rfl
refine not_isUnit_X_sub_C a (isUnit_of_self_mul_dvd_separable hs ?_)
simpa only [Multiset.map_cons, Multiset.prod_cons] using mul_dvd_mul_left _ (dvd_mul_right _ _)
/-- If `IsUnit n` in a `CommRing R`, then `X ^ n - u` is separable for any unit `u`. -/
theorem separable_X_pow_sub_C_unit {n : ℕ} (u : Rˣ) (hn : IsUnit (n : R)) :
Separable (X ^ n - C (u : R)) := by
nontriviality R
rcases n.eq_zero_or_pos with (rfl | hpos)
· simp at hn
apply (separable_def' (X ^ n - C (u : R))).2
obtain ⟨n', hn'⟩ := hn.exists_left_inv
refine ⟨-C ↑u⁻¹, C (↑u⁻¹ : R) * C n' * X, ?_⟩
rw [derivative_sub, derivative_C, sub_zero, derivative_pow X n, derivative_X, mul_one]
calc
-C ↑u⁻¹ * (X ^ n - C ↑u) + C ↑u⁻¹ * C n' * X * (↑n * X ^ (n - 1)) =
C (↑u⁻¹ * ↑u) - C ↑u⁻¹ * X ^ n + C ↑u⁻¹ * C (n' * ↑n) * (X * X ^ (n - 1)) := by
simp only [C.map_mul, C_eq_natCast]
ring
_ = 1 := by
simp only [Units.inv_mul, hn', C.map_one, mul_one, ← pow_succ',
Nat.sub_add_cancel (show 1 ≤ n from hpos), sub_add_cancel]
/-- If `n = 0` in `R` and `b` is a unit, then `a * X ^ n + b * X + c` is separable. -/
theorem separable_C_mul_X_pow_add_C_mul_X_add_C
{n : ℕ} (a b c : R) (hn : (n : R) = 0) (hb : IsUnit b) :
(C a * X ^ n + C b * X + C c).Separable := by
set f := C a * X ^ n + C b * X + C c
obtain ⟨e, hb⟩ := hb.exists_left_inv
refine ⟨-derivative f, f + C e, ?_⟩
have hderiv : derivative f = C b := by
simp [hn, f, map_add derivative, derivative_C, derivative_X_pow]
rw [hderiv, right_distrib, ← add_assoc, neg_mul, mul_comm, neg_add_cancel, zero_add,
← map_mul, hb, map_one]
/-- If `R` is of characteristic `p`, `p ∣ n` and `b` is a unit,
then `a * X ^ n + b * X + c` is separable. -/
theorem separable_C_mul_X_pow_add_C_mul_X_add_C'
(p n : ℕ) (a b c : R) [CharP R p] (hn : p ∣ n) (hb : IsUnit b) :
(C a * X ^ n + C b * X + C c).Separable :=
separable_C_mul_X_pow_add_C_mul_X_add_C a b c ((CharP.cast_eq_zero_iff R p n).2 hn) hb
theorem rootMultiplicity_le_one_of_separable [Nontrivial R] {p : R[X]} (hsep : Separable p)
(x : R) : rootMultiplicity x p ≤ 1 := by
classical
by_cases hp : p = 0
· simp [hp]
rw [rootMultiplicity_eq_multiplicity, if_neg hp, ← Nat.cast_le (α := ℕ∞),
Nat.cast_one, ← (finiteMultiplicity_X_sub_C x hp).emultiplicity_eq_multiplicity]
apply emultiplicity_le_one_of_separable (not_isUnit_X_sub_C _) hsep
end CommRing
section IsDomain
variable {R : Type u} [CommRing R] [IsDomain R]
theorem count_roots_le_one [DecidableEq R] {p : R[X]} (hsep : Separable p) (x : R) :
p.roots.count x ≤ 1 := by
rw [count_roots p]
exact rootMultiplicity_le_one_of_separable hsep x
theorem nodup_roots {p : R[X]} (hsep : Separable p) : p.roots.Nodup := by
classical
exact Multiset.nodup_iff_count_le_one.mpr (count_roots_le_one hsep)
end IsDomain
section Field
variable {F : Type u} [Field F] {K : Type v} [Field K]
theorem separable_iff_derivative_ne_zero {f : F[X]} (hf : Irreducible f) :
f.Separable ↔ derivative f ≠ 0 :=
⟨fun h1 h2 => hf.not_isUnit <| isCoprime_zero_right.1 <| h2 ▸ h1, fun h =>
EuclideanDomain.isCoprime_of_dvd (mt And.right h) fun g hg1 _hg2 ⟨p, hg3⟩ hg4 =>
let ⟨u, hu⟩ := (hf.isUnit_or_isUnit hg3).resolve_left hg1
have : f ∣ derivative f := by
conv_lhs => rw [hg3, ← hu]
rwa [Units.mul_right_dvd]
not_lt_of_le (natDegree_le_of_dvd this h) <|
natDegree_derivative_lt <| mt derivative_of_natDegree_zero h⟩
attribute [local instance] Ideal.Quotient.field in
theorem separable_map {S} [CommRing S] [Nontrivial S] (f : F →+* S) {p : F[X]} :
(p.map f).Separable ↔ p.Separable := by
refine ⟨fun H ↦ ?_, fun H ↦ H.map⟩
obtain ⟨m, hm⟩ := Ideal.exists_maximal S
have := Separable.map H (f := Ideal.Quotient.mk m)
rwa [map_map, separable_def, derivative_map, isCoprime_map] at this
theorem separable_prod_X_sub_C_iff' {ι : Sort _} {f : ι → F} {s : Finset ι} :
(∏ i ∈ s, (X - C (f i))).Separable ↔ ∀ x ∈ s, ∀ y ∈ s, f x = f y → x = y :=
⟨fun hfs _ hx _ hy hfxy => hfs.inj_of_prod_X_sub_C hx hy hfxy, fun H => by
rw [← prod_attach]
exact
separable_prod'
(fun x _hx y _hy hxy =>
@pairwise_coprime_X_sub_C _ _ { x // x ∈ s } (fun x => f x)
(fun x y hxy => Subtype.eq <| H x.1 x.2 y.1 y.2 hxy) _ _ hxy)
fun _ _ => separable_X_sub_C⟩
theorem separable_prod_X_sub_C_iff {ι : Sort _} [Fintype ι] {f : ι → F} :
(∏ i, (X - C (f i))).Separable ↔ Function.Injective f :=
separable_prod_X_sub_C_iff'.trans <| by simp_rw [mem_univ, true_imp_iff, Function.Injective]
section CharP
variable (p : ℕ) [HF : CharP F p]
theorem separable_or {f : F[X]} (hf : Irreducible f) :
f.Separable ∨ ¬f.Separable ∧ ∃ g : F[X], Irreducible g ∧ expand F p g = f := by
classical
exact if H : derivative f = 0 then by
rcases p.eq_zero_or_pos with (rfl | hp)
· haveI := CharP.charP_to_charZero F
have := natDegree_eq_zero_of_derivative_eq_zero H
have := (natDegree_pos_iff_degree_pos.mpr <| degree_pos_of_irreducible hf).ne'
contradiction
haveI := isLocalHom_expand F hp
exact
Or.inr
⟨by rw [separable_iff_derivative_ne_zero hf, Classical.not_not, H], contract p f,
Irreducible.of_map (by rwa [← expand_contract p H hp.ne'] at hf),
expand_contract p H hp.ne'⟩
else Or.inl <| (separable_iff_derivative_ne_zero hf).2 H
theorem exists_separable_of_irreducible {f : F[X]} (hf : Irreducible f) (hp : p ≠ 0) :
∃ (n : ℕ) (g : F[X]), g.Separable ∧ expand F (p ^ n) g = f := by
replace hp : p.Prime := (CharP.char_is_prime_or_zero F p).resolve_right hp
induction' hn : f.natDegree using Nat.strong_induction_on with N ih generalizing f
rcases separable_or p hf with (h | ⟨h1, g, hg, hgf⟩)
· refine ⟨0, f, h, ?_⟩
rw [pow_zero, expand_one]
· rcases N with - | N
· rw [natDegree_eq_zero_iff_degree_le_zero, degree_le_zero_iff] at hn
rw [hn, separable_C, isUnit_iff_ne_zero, Classical.not_not] at h1
have hf0 : f ≠ 0 := hf.ne_zero
rw [h1, C_0] at hn
exact absurd hn hf0
have hg1 : g.natDegree * p = N.succ := by rwa [← natDegree_expand, hgf]
have hg2 : g.natDegree ≠ 0 := by
intro this
rw [this, zero_mul] at hg1
cases hg1
have hg3 : g.natDegree < N.succ := by
rw [← mul_one g.natDegree, ← hg1]
exact Nat.mul_lt_mul_of_pos_left hp.one_lt hg2.bot_lt
rcases ih _ hg3 hg rfl with ⟨n, g, hg4, rfl⟩
refine ⟨n + 1, g, hg4, ?_⟩
rw [← hgf, expand_expand, pow_succ']
theorem isUnit_or_eq_zero_of_separable_expand {f : F[X]} (n : ℕ) (hp : 0 < p)
(hf : (expand F (p ^ n) f).Separable) : IsUnit f ∨ n = 0 := by
rw [or_iff_not_imp_right]
rintro hn : n ≠ 0
have hf2 : derivative (expand F (p ^ n) f) = 0 := by
rw [derivative_expand, Nat.cast_pow, CharP.cast_eq_zero, zero_pow hn, zero_mul, mul_zero]
rw [separable_def, hf2, isCoprime_zero_right, isUnit_iff] at hf
rcases hf with ⟨r, hr, hrf⟩
rw [eq_comm, expand_eq_C (pow_pos hp _)] at hrf
rwa [hrf, isUnit_C]
theorem unique_separable_of_irreducible {f : F[X]} (hf : Irreducible f) (hp : 0 < p) (n₁ : ℕ)
(g₁ : F[X]) (hg₁ : g₁.Separable) (hgf₁ : expand F (p ^ n₁) g₁ = f) (n₂ : ℕ) (g₂ : F[X])
(hg₂ : g₂.Separable) (hgf₂ : expand F (p ^ n₂) g₂ = f) : n₁ = n₂ ∧ g₁ = g₂ := by
revert g₁ g₂
wlog hn : n₁ ≤ n₂
· intro g₁ hg₁ Hg₁ g₂ hg₂ Hg₂
simpa only [eq_comm] using this p hf hp n₂ n₁ (le_of_not_le hn) g₂ hg₂ Hg₂ g₁ hg₁ Hg₁
have hf0 : f ≠ 0 := hf.ne_zero
intros g₁ hg₁ hgf₁ g₂ hg₂ hgf₂
rw [le_iff_exists_add] at hn
rcases hn with ⟨k, rfl⟩
rw [← hgf₁, pow_add, expand_mul, expand_inj (pow_pos hp n₁)] at hgf₂
subst hgf₂
subst hgf₁
rcases isUnit_or_eq_zero_of_separable_expand p k hp hg₁ with (h | rfl)
· rw [isUnit_iff] at h
rcases h with ⟨r, hr, rfl⟩
simp_rw [expand_C] at hf
exact absurd (isUnit_C.2 hr) hf.1
· rw [add_zero, pow_zero, expand_one]
constructor <;> rfl
end CharP
/-- If `n ≠ 0` in `F`, then `X ^ n - a` is separable for any `a ≠ 0`. -/
theorem separable_X_pow_sub_C {n : ℕ} (a : F) (hn : (n : F) ≠ 0) (ha : a ≠ 0) :
Separable (X ^ n - C a) :=
separable_X_pow_sub_C_unit (Units.mk0 a ha) (IsUnit.mk0 (n : F) hn)
/-- If `F` is of characteristic `p` and `p ∤ n`, then `X ^ n - a` is separable for any `a ≠ 0`. -/
theorem separable_X_pow_sub_C' (p n : ℕ) (a : F) [CharP F p] (hn : ¬p ∣ n) (ha : a ≠ 0) :
Separable (X ^ n - C a) :=
separable_X_pow_sub_C a (by rwa [← CharP.cast_eq_zero_iff F p n] at hn) ha
-- this can possibly be strengthened to making `separable_X_pow_sub_C_unit` a
-- bi-implication, but it is nontrivial!
/-- In a field `F`, `X ^ n - 1` is separable iff `↑n ≠ 0`. -/
theorem X_pow_sub_one_separable_iff {n : ℕ} : (X ^ n - 1 : F[X]).Separable ↔ (n : F) ≠ 0 := by
refine ⟨?_, fun h => separable_X_pow_sub_C_unit 1 (IsUnit.mk0 _ h)⟩
rw [separable_def', derivative_sub, derivative_X_pow, derivative_one, sub_zero]
-- Suppose `(n : F) = 0`, then the derivative is `0`, so `X ^ n - 1` is a unit, contradiction.
rintro (h : IsCoprime _ _) hn'
rw [hn', C_0, zero_mul, isCoprime_zero_right] at h
exact not_isUnit_X_pow_sub_one F n h
section Splits
theorem card_rootSet_eq_natDegree [Algebra F K] {p : F[X]} (hsep : p.Separable)
(hsplit : Splits (algebraMap F K) p) : Fintype.card (p.rootSet K) = p.natDegree := by
classical
simp_rw [rootSet_def, Finset.coe_sort_coe, Fintype.card_coe]
rw [Multiset.toFinset_card_of_nodup (nodup_roots hsep.map), ← natDegree_eq_card_roots hsplit]
/-- If a non-zero polynomial splits, then it has no repeated roots on that field
if and only if it is separable. -/
theorem nodup_roots_iff_of_splits {f : F[X]} (hf : f ≠ 0) (h : f.Splits (RingHom.id F)) :
f.roots.Nodup ↔ f.Separable := by
classical
refine ⟨(fun hnsep ↦ ?_).mtr, nodup_roots⟩
rw [Separable, ← gcd_isUnit_iff, isUnit_iff_degree_eq_zero] at hnsep
obtain ⟨x, hx⟩ := exists_root_of_splits _
(splits_of_splits_of_dvd _ hf h (gcd_dvd_left f _)) hnsep
simp_rw [Multiset.nodup_iff_count_le_one, not_forall, not_le]
exact ⟨x, ((one_lt_rootMultiplicity_iff_isRoot_gcd hf).2 hx).trans_eq f.count_roots.symm⟩
/-- If a non-zero polynomial over `F` splits in `K`, then it has no repeated roots on `K`
if and only if it is separable. -/
@[stacks 09H3 "Here we only require `f` splits instead of `K` is algebraically closed."]
theorem nodup_aroots_iff_of_splits [Algebra F K] {f : F[X]} (hf : f ≠ 0)
(h : f.Splits (algebraMap F K)) : (f.aroots K).Nodup ↔ f.Separable := by
rw [← (algebraMap F K).id_comp, ← splits_map_iff] at h
rw [nodup_roots_iff_of_splits (map_ne_zero hf) h, separable_map]
theorem card_rootSet_eq_natDegree_iff_of_splits [Algebra F K] {f : F[X]} (hf : f ≠ 0)
(h : f.Splits (algebraMap F K)) : Fintype.card (f.rootSet K) = f.natDegree ↔ f.Separable := by
classical
simp_rw [rootSet_def, Finset.coe_sort_coe, Fintype.card_coe, natDegree_eq_card_roots h,
Multiset.toFinset_card_eq_card_iff_nodup, nodup_aroots_iff_of_splits hf h]
variable {i : F →+* K}
theorem eq_X_sub_C_of_separable_of_root_eq {x : F} {h : F[X]} (h_sep : h.Separable)
(h_root : h.eval x = 0) (h_splits : Splits i h) (h_roots : ∀ y ∈ (h.map i).roots, y = i x) :
h = C (leadingCoeff h) * (X - C x) := by
have h_ne_zero : h ≠ 0 := by
rintro rfl
exact not_separable_zero h_sep
apply Polynomial.eq_X_sub_C_of_splits_of_single_root i h_splits
apply Finset.mk.inj
· change _ = {i x}
rw [Finset.eq_singleton_iff_unique_mem]
constructor
· apply Finset.mem_mk.mpr
· rw [mem_roots (show h.map i ≠ 0 from map_ne_zero h_ne_zero)]
rw [IsRoot.def, ← eval₂_eq_eval_map, eval₂_hom, h_root]
exact RingHom.map_zero i
· exact nodup_roots (Separable.map h_sep)
| · exact h_roots
theorem exists_finset_of_splits (i : F →+* K) {f : F[X]} (sep : Separable f) (sp : Splits i f) :
∃ s : Finset K, f.map i = C (i f.leadingCoeff) * s.prod fun a : K => X - C a := by
classical
obtain ⟨s, h⟩ := (splits_iff_exists_multiset _).1 sp
use s.toFinset
rw [h, Finset.prod_eq_multiset_prod, ← Multiset.toFinset_eq]
apply nodup_of_separable_prod
apply Separable.of_mul_right
rw [← h]
exact sep.map
end Splits
theorem _root_.Irreducible.separable [CharZero F] {f : F[X]} (hf : Irreducible f) :
f.Separable := by
| Mathlib/FieldTheory/Separable.lean | 498 | 514 |
/-
Copyright (c) 2022 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.CategoryTheory.Functor.ReflectsIso.Basic
import Mathlib.CategoryTheory.MorphismProperty.Basic
/-!
# Morphism properties that are inverted by a functor
In this file, we introduce the predicate `P.IsInvertedBy F` which expresses
that the morphisms satisfying `P : MorphismProperty C` are mapped to
isomorphisms by a functor `F : C ⥤ D`.
This is used in the localization of categories API (folder `CategoryTheory.Localization`).
-/
universe w v v' u u'
namespace CategoryTheory
namespace MorphismProperty
variable {C : Type u} [Category.{v} C] {D : Type u'} [Category.{v'} D]
/-- If `P : MorphismProperty C` and `F : C ⥤ D`, then
`P.IsInvertedBy F` means that all morphisms in `P` are mapped by `F`
to isomorphisms in `D`. -/
def IsInvertedBy (P : MorphismProperty C) (F : C ⥤ D) : Prop :=
∀ ⦃X Y : C⦄ (f : X ⟶ Y) (_ : P f), IsIso (F.map f)
namespace IsInvertedBy
lemma of_le (P Q : MorphismProperty C) (F : C ⥤ D) (hQ : Q.IsInvertedBy F) (h : P ≤ Q) :
P.IsInvertedBy F :=
fun _ _ _ hf => hQ _ (h _ hf)
theorem of_comp {C₁ C₂ C₃ : Type*} [Category C₁] [Category C₂] [Category C₃]
(W : MorphismProperty C₁) (F : C₁ ⥤ C₂) (hF : W.IsInvertedBy F) (G : C₂ ⥤ C₃) :
W.IsInvertedBy (F ⋙ G) := fun X Y f hf => by
haveI := hF f hf
dsimp
infer_instance
theorem op {W : MorphismProperty C} {L : C ⥤ D} (h : W.IsInvertedBy L) : W.op.IsInvertedBy L.op :=
fun X Y f hf => by
haveI := h f.unop hf
dsimp
infer_instance
theorem rightOp {W : MorphismProperty C} {L : Cᵒᵖ ⥤ D} (h : W.op.IsInvertedBy L) :
W.IsInvertedBy L.rightOp := fun X Y f hf => by
haveI := h f.op hf
dsimp
infer_instance
theorem leftOp {W : MorphismProperty C} {L : C ⥤ Dᵒᵖ} (h : W.IsInvertedBy L) :
W.op.IsInvertedBy L.leftOp := fun X Y f hf => by
haveI := h f.unop hf
dsimp
infer_instance
theorem unop {W : MorphismProperty C} {L : Cᵒᵖ ⥤ Dᵒᵖ} (h : W.op.IsInvertedBy L) :
W.IsInvertedBy L.unop := fun X Y f hf => by
haveI := h f.op hf
dsimp
infer_instance
|
lemma prod {C₁ C₂ : Type*} [Category C₁] [Category C₂]
{W₁ : MorphismProperty C₁} {W₂ : MorphismProperty C₂}
{E₁ E₂ : Type*} [Category E₁] [Category E₂] {F₁ : C₁ ⥤ E₁} {F₂ : C₂ ⥤ E₂}
(h₁ : W₁.IsInvertedBy F₁) (h₂ : W₂.IsInvertedBy F₂) :
| Mathlib/CategoryTheory/MorphismProperty/IsInvertedBy.lean | 70 | 74 |
/-
Copyright (c) 2021 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn, Yury Kudryashov
-/
import Mathlib.MeasureTheory.Constructions.BorelSpace.Order
import Mathlib.MeasureTheory.Group.MeasurableEquiv
import Mathlib.Topology.MetricSpace.HausdorffDistance
/-!
# Regular measures
A measure is `OuterRegular` if the measure of any measurable set `A` is the infimum of `μ U` over
all open sets `U` containing `A`.
A measure is `WeaklyRegular` if it satisfies the following properties:
* it is outer regular;
* it is inner regular for open sets with respect to closed sets: the measure of any open set `U`
is the supremum of `μ F` over all closed sets `F` contained in `U`.
A measure is `Regular` if it satisfies the following properties:
* it is finite on compact sets;
* it is outer regular;
* it is inner regular for open sets with respect to compacts closed sets: the measure of any open
set `U` is the supremum of `μ K` over all compact sets `K` contained in `U`.
A measure is `InnerRegular` if it is inner regular for measurable sets with respect to compact
sets: the measure of any measurable set `s` is the supremum of `μ K` over all compact
sets contained in `s`.
A measure is `InnerRegularCompactLTTop` if it is inner regular for measurable sets of finite
measure with respect to compact sets: the measure of any measurable set `s` is the supremum
of `μ K` over all compact sets contained in `s`.
There is a reason for this zoo of regularity classes:
* A finite measure on a metric space is always weakly regular. Therefore, in probability theory,
weakly regular measures play a prominent role.
* In locally compact topological spaces, there are two competing notions of Radon measures: the
ones that are regular, and the ones that are inner regular. For any of these two notions, there is
a Riesz representation theorem, and an existence and uniqueness statement for the Haar measure in
locally compact topological groups. The two notions coincide in sigma-compact spaces, but they
differ in general, so it is worth having the two of them.
* Both notions of Haar measure satisfy the weaker notion `InnerRegularCompactLTTop`, so it is worth
trying to express theorems using this weaker notion whenever possible, to make sure that it
applies to both Haar measures simultaneously.
While traditional textbooks on measure theory on locally compact spaces emphasize regular measures,
more recent textbooks emphasize that inner regular Haar measures are better behaved than regular
Haar measures, so we will develop both notions.
The five conditions above are registered as typeclasses for a measure `μ`, and implications between
them are recorded as instances. For example, in a Hausdorff topological space, regularity implies
weak regularity. Also, regularity or inner regularity both imply `InnerRegularCompactLTTop`.
In a regular locally compact finite measure space, then regularity, inner regularity
and `InnerRegularCompactLTTop` are all equivalent.
In order to avoid code duplication, we also define a measure `μ` to be `InnerRegularWRT` for sets
satisfying a predicate `q` with respect to sets satisfying a predicate `p` if for any set
`U ∈ {U | q U}` and a number `r < μ U` there exists `F ⊆ U` such that `p F` and `r < μ F`.
There are two main nontrivial results in the development below:
* `InnerRegularWRT.measurableSet_of_isOpen` shows that, for an outer regular measure, inner
regularity for open sets with respect to compact sets or closed sets implies inner regularity for
all measurable sets of finite measure (with respect to compact sets or closed sets respectively).
* `InnerRegularWRT.weaklyRegular_of_finite` shows that a finite measure which is inner regular for
open sets with respect to closed sets (for instance a finite measure on a metric space) is weakly
regular.
All other results are deduced from these ones.
Here is an example showing how regularity and inner regularity may differ even on locally compact
spaces. Consider the group `ℝ × ℝ` where the first factor has the discrete topology and the second
one the usual topology. It is a locally compact Hausdorff topological group, with Haar measure equal
to Lebesgue measure on each vertical fiber. Let us consider the regular version of Haar measure.
Then the set `ℝ × {0}` has infinite measure (by outer regularity), but any compact set it contains
has zero measure (as it is finite). In fact, this set only contains subset with measure zero or
infinity. The inner regular version of Haar measure, on the other hand, gives zero mass to the
set `ℝ × {0}`.
Another interesting example is the sum of the Dirac masses at rational points in the real line.
It is a σ-finite measure on a locally compact metric space, but it is not outer regular: for
outer regularity, one needs additional locally finite assumptions. On the other hand, it is
inner regular.
Several authors require both regularity and inner regularity for their measures. We have opted
for the more fine grained definitions above as they apply more generally.
## Main definitions
* `MeasureTheory.Measure.OuterRegular μ`: a typeclass registering that a measure `μ` on a
topological space is outer regular.
* `MeasureTheory.Measure.Regular μ`: a typeclass registering that a measure `μ` on a topological
space is regular.
* `MeasureTheory.Measure.WeaklyRegular μ`: a typeclass registering that a measure `μ` on a
topological space is weakly regular.
* `MeasureTheory.Measure.InnerRegularWRT μ p q`: a non-typeclass predicate saying that a measure `μ`
is inner regular for sets satisfying `q` with respect to sets satisfying `p`.
* `MeasureTheory.Measure.InnerRegular μ`: a typeclass registering that a measure `μ` on a
topological space is inner regular for measurable sets with respect to compact sets.
* `MeasureTheory.Measure.InnerRegularCompactLTTop μ`: a typeclass registering that a measure `μ`
on a topological space is inner regular for measurable sets of finite measure with respect to
compact sets.
## Main results
### Outer regular measures
* `Set.measure_eq_iInf_isOpen` asserts that, when `μ` is outer regular, the measure of a
set is the infimum of the measure of open sets containing it.
* `Set.exists_isOpen_lt_of_lt` asserts that, when `μ` is outer regular, for every set `s`
and `r > μ s` there exists an open superset `U ⊇ s` of measure less than `r`.
* push forward of an outer regular measure is outer regular, and scalar multiplication of a regular
measure by a finite number is outer regular.
### Weakly regular measures
* `IsOpen.measure_eq_iSup_isClosed` asserts that the measure of an open set is the supremum of
the measure of closed sets it contains.
* `IsOpen.exists_lt_isClosed`: for an open set `U` and `r < μ U`, there exists a closed `F ⊆ U`
of measure greater than `r`;
* `MeasurableSet.measure_eq_iSup_isClosed_of_ne_top` asserts that the measure of a measurable set
of finite measure is the supremum of the measure of closed sets it contains.
* `MeasurableSet.exists_lt_isClosed_of_ne_top` and `MeasurableSet.exists_isClosed_lt_add`:
a measurable set of finite measure can be approximated by a closed subset (stated as
`r < μ F` and `μ s < μ F + ε`, respectively).
* `MeasureTheory.Measure.WeaklyRegular.of_pseudoMetrizableSpace_of_isFiniteMeasure` is an
instance registering that a finite measure on a metric space is weakly regular (in fact, a pseudo
metrizable space is enough);
* `MeasureTheory.Measure.WeaklyRegular.of_pseudoMetrizableSpace_secondCountable_of_locallyFinite`
is an instance registering that a locally finite measure on a second countable metric space (or
even a pseudo metrizable space) is weakly regular.
### Regular measures
* `IsOpen.measure_eq_iSup_isCompact` asserts that the measure of an open set is the supremum of
the measure of compact sets it contains.
* `IsOpen.exists_lt_isCompact`: for an open set `U` and `r < μ U`, there exists a compact `K ⊆ U`
of measure greater than `r`;
* `MeasureTheory.Measure.Regular.of_sigmaCompactSpace_of_isLocallyFiniteMeasure` is an
instance registering that a locally finite measure on a `σ`-compact metric space is regular (in
fact, an emetric space is enough).
### Inner regular measures
* `MeasurableSet.measure_eq_iSup_isCompact` asserts that the measure of a measurable set is the
supremum of the measure of compact sets it contains.
* `MeasurableSet.exists_lt_isCompact`: for a measurable set `s` and `r < μ s`, there exists a
compact `K ⊆ s` of measure greater than `r`;
### Inner regular measures for finite measure sets with respect to compact sets
* `MeasurableSet.measure_eq_iSup_isCompact_of_ne_top` asserts that the measure of a measurable set
of finite measure is the supremum of the measure of compact sets it contains.
* `MeasurableSet.exists_lt_isCompact_of_ne_top` and `MeasurableSet.exists_isCompact_lt_add`:
a measurable set of finite measure can be approximated by a compact subset (stated as
`r < μ K` and `μ s < μ K + ε`, respectively).
## Implementation notes
The main nontrivial statement is `MeasureTheory.Measure.InnerRegular.weaklyRegular_of_finite`,
expressing that in a finite measure space, if every open set can be approximated from inside by
closed sets, then the measure is in fact weakly regular. To prove that we show that any measurable
set can be approximated from inside by closed sets and from outside by open sets. This statement is
proved by measurable induction, starting from open sets and checking that it is stable by taking
complements (this is the point of this condition, being symmetrical between inside and outside) and
countable disjoint unions.
Once this statement is proved, one deduces results for `σ`-finite measures from this statement, by
restricting them to finite measure sets (and proving that this restriction is weakly regular, using
again the same statement).
For non-Hausdorff spaces, one may argue whether the right condition for inner regularity is with
respect to compact sets, or to compact closed sets. For instance,
[Fremlin, *Measure Theory* (volume 4, 411J)][fremlin_vol4] considers measures which are inner
regular with respect to compact closed sets (and calls them *tight*). However, since most of the
literature uses mere compact sets, we have chosen to follow this convention. It doesn't make a
difference in Hausdorff spaces, of course. In locally compact topological groups, the two
conditions coincide, since if a compact set `k` is contained in a measurable set `u`, then the
closure of `k` is a compact closed set still contained in `u`, see
`IsCompact.closure_subset_of_measurableSet_of_group`.
## References
[Halmos, Measure Theory, §52][halmos1950measure]. Note that Halmos uses an unusual definition of
Borel sets (for him, they are elements of the `σ`-algebra generated by compact sets!), so his
proofs or statements do not apply directly.
[Billingsley, Convergence of Probability Measures][billingsley1999]
[Bogachev, Measure Theory, volume 2, Theorem 7.11.1][bogachev2007]
-/
open Set Filter ENNReal NNReal TopologicalSpace
open scoped symmDiff Topology
namespace MeasureTheory
namespace Measure
/-- We say that a measure `μ` is *inner regular* with respect to predicates `p q : Set α → Prop`,
if for every `U` such that `q U` and `r < μ U`, there exists a subset `K ⊆ U` satisfying `p K`
of measure greater than `r`.
This definition is used to prove some facts about regular and weakly regular measures without
repeating the proofs. -/
def InnerRegularWRT {α} {_ : MeasurableSpace α} (μ : Measure α) (p q : Set α → Prop) :=
∀ ⦃U⦄, q U → ∀ r < μ U, ∃ K, K ⊆ U ∧ p K ∧ r < μ K
namespace InnerRegularWRT
variable {α : Type*} {m : MeasurableSpace α} {μ : Measure α} {p q : Set α → Prop} {U : Set α}
{ε : ℝ≥0∞}
theorem measure_eq_iSup (H : InnerRegularWRT μ p q) (hU : q U) :
μ U = ⨆ (K) (_ : K ⊆ U) (_ : p K), μ K := by
refine
le_antisymm (le_of_forall_lt fun r hr => ?_) (iSup₂_le fun K hK => iSup_le fun _ => μ.mono hK)
simpa only [lt_iSup_iff, exists_prop] using H hU r hr
theorem exists_subset_lt_add (H : InnerRegularWRT μ p q) (h0 : p ∅) (hU : q U) (hμU : μ U ≠ ∞)
(hε : ε ≠ 0) : ∃ K, K ⊆ U ∧ p K ∧ μ U < μ K + ε := by
rcases eq_or_ne (μ U) 0 with h₀ | h₀
· refine ⟨∅, empty_subset _, h0, ?_⟩
rwa [measure_empty, h₀, zero_add, pos_iff_ne_zero]
· rcases H hU _ (ENNReal.sub_lt_self hμU h₀ hε) with ⟨K, hKU, hKc, hrK⟩
exact ⟨K, hKU, hKc, ENNReal.lt_add_of_sub_lt_right (Or.inl hμU) hrK⟩
protected theorem map {α β} [MeasurableSpace α] [MeasurableSpace β]
{μ : Measure α} {pa qa : Set α → Prop}
(H : InnerRegularWRT μ pa qa) {f : α → β} (hf : AEMeasurable f μ) {pb qb : Set β → Prop}
(hAB : ∀ U, qb U → qa (f ⁻¹' U)) (hAB' : ∀ K, pa K → pb (f '' K))
(hB₂ : ∀ U, qb U → MeasurableSet U) :
InnerRegularWRT (map f μ) pb qb := by
intro U hU r hr
rw [map_apply_of_aemeasurable hf (hB₂ _ hU)] at hr
rcases H (hAB U hU) r hr with ⟨K, hKU, hKc, hK⟩
refine ⟨f '' K, image_subset_iff.2 hKU, hAB' _ hKc, ?_⟩
exact hK.trans_le (le_map_apply_image hf _)
theorem map' {α β} [MeasurableSpace α] [MeasurableSpace β] {μ : Measure α} {pa qa : Set α → Prop}
(H : InnerRegularWRT μ pa qa) (f : α ≃ᵐ β) {pb qb : Set β → Prop}
(hAB : ∀ U, qb U → qa (f ⁻¹' U)) (hAB' : ∀ K, pa K → pb (f '' K)) :
InnerRegularWRT (map f μ) pb qb := by
intro U hU r hr
rw [f.map_apply U] at hr
rcases H (hAB U hU) r hr with ⟨K, hKU, hKc, hK⟩
refine ⟨f '' K, image_subset_iff.2 hKU, hAB' _ hKc, ?_⟩
rwa [f.map_apply, f.preimage_image]
theorem smul (H : InnerRegularWRT μ p q) (c : ℝ≥0∞) : InnerRegularWRT (c • μ) p q := by
intro U hU r hr
rw [smul_apply, H.measure_eq_iSup hU, smul_eq_mul] at hr
simpa only [ENNReal.mul_iSup, lt_iSup_iff, exists_prop] using hr
theorem trans {q' : Set α → Prop} (H : InnerRegularWRT μ p q) (H' : InnerRegularWRT μ q q') :
InnerRegularWRT μ p q' := by
intro U hU r hr
rcases H' hU r hr with ⟨F, hFU, hqF, hF⟩; rcases H hqF _ hF with ⟨K, hKF, hpK, hrK⟩
exact ⟨K, hKF.trans hFU, hpK, hrK⟩
theorem rfl {p : Set α → Prop} : InnerRegularWRT μ p p :=
fun U hU _r hr ↦ ⟨U, Subset.rfl, hU, hr⟩
theorem of_imp (h : ∀ s, q s → p s) : InnerRegularWRT μ p q :=
fun U hU _ hr ↦ ⟨U, Subset.rfl, h U hU, hr⟩
theorem mono {p' q' : Set α → Prop} (H : InnerRegularWRT μ p q)
(h : ∀ s, q' s → q s) (h' : ∀ s, p s → p' s) : InnerRegularWRT μ p' q' :=
of_imp h' |>.trans H |>.trans (of_imp h)
end InnerRegularWRT
variable {α β : Type*} [MeasurableSpace α] {μ : Measure α}
section Classes
variable [TopologicalSpace α]
/-- A measure `μ` is outer regular if `μ(A) = inf {μ(U) | A ⊆ U open}` for a measurable set `A`.
This definition implies the same equality for any (not necessarily measurable) set, see
`Set.measure_eq_iInf_isOpen`. -/
class OuterRegular (μ : Measure α) : Prop where
protected outerRegular :
∀ ⦃A : Set α⦄, MeasurableSet A → ∀ r > μ A, ∃ U, U ⊇ A ∧ IsOpen U ∧ μ U < r
/-- A measure `μ` is regular if
- it is finite on all compact sets;
- it is outer regular: `μ(A) = inf {μ(U) | A ⊆ U open}` for `A` measurable;
- it is inner regular for open sets, using compact sets:
`μ(U) = sup {μ(K) | K ⊆ U compact}` for `U` open. -/
class Regular (μ : Measure α) : Prop extends IsFiniteMeasureOnCompacts μ, OuterRegular μ where
innerRegular : InnerRegularWRT μ IsCompact IsOpen
/-- A measure `μ` is weakly regular if
- it is outer regular: `μ(A) = inf {μ(U) | A ⊆ U open}` for `A` measurable;
- it is inner regular for open sets, using closed sets:
`μ(U) = sup {μ(F) | F ⊆ U closed}` for `U` open. -/
class WeaklyRegular (μ : Measure α) : Prop extends OuterRegular μ where
protected innerRegular : InnerRegularWRT μ IsClosed IsOpen
/-- A measure `μ` is inner regular if, for any measurable set `s`, then
`μ(s) = sup {μ(K) | K ⊆ s compact}`. -/
class InnerRegular (μ : Measure α) : Prop where
protected innerRegular : InnerRegularWRT μ IsCompact MeasurableSet
/-- A measure `μ` is inner regular for finite measure sets with respect to compact sets:
for any measurable set `s` with finite measure, then `μ(s) = sup {μ(K) | K ⊆ s compact}`.
The main interest of this class is that it is satisfied for both natural Haar measures (the
regular one and the inner regular one). -/
class InnerRegularCompactLTTop (μ : Measure α) : Prop where
protected innerRegular : InnerRegularWRT μ IsCompact (fun s ↦ MeasurableSet s ∧ μ s ≠ ∞)
-- see Note [lower instance priority]
/-- A regular measure is weakly regular in an R₁ space. -/
instance (priority := 100) Regular.weaklyRegular [R1Space α] [Regular μ] :
WeaklyRegular μ where
innerRegular := fun _U hU r hr ↦
let ⟨K, KU, K_comp, hK⟩ := Regular.innerRegular hU r hr
⟨closure K, K_comp.closure_subset_of_isOpen hU KU, isClosed_closure,
hK.trans_le (measure_mono subset_closure)⟩
end Classes
namespace OuterRegular
variable [TopologicalSpace α]
instance zero : OuterRegular (0 : Measure α) :=
⟨fun A _ _r hr => ⟨univ, subset_univ A, isOpen_univ, hr⟩⟩
/-- Given `r` larger than the measure of a set `A`, there exists an open superset of `A` with
measure less than `r`. -/
theorem _root_.Set.exists_isOpen_lt_of_lt [OuterRegular μ] (A : Set α) (r : ℝ≥0∞) (hr : μ A < r) :
∃ U, U ⊇ A ∧ IsOpen U ∧ μ U < r := by
rcases OuterRegular.outerRegular (measurableSet_toMeasurable μ A) r
(by rwa [measure_toMeasurable]) with
⟨U, hAU, hUo, hU⟩
exact ⟨U, (subset_toMeasurable _ _).trans hAU, hUo, hU⟩
/-- For an outer regular measure, the measure of a set is the infimum of the measures of open sets
containing it. -/
theorem _root_.Set.measure_eq_iInf_isOpen (A : Set α) (μ : Measure α) [OuterRegular μ] :
μ A = ⨅ (U : Set α) (_ : A ⊆ U) (_ : IsOpen U), μ U := by
refine le_antisymm (le_iInf₂ fun s hs => le_iInf fun _ => μ.mono hs) ?_
refine le_of_forall_lt' fun r hr => ?_
simpa only [iInf_lt_iff, exists_prop] using A.exists_isOpen_lt_of_lt r hr
theorem _root_.Set.exists_isOpen_lt_add [OuterRegular μ] (A : Set α) (hA : μ A ≠ ∞) {ε : ℝ≥0∞}
(hε : ε ≠ 0) : ∃ U, U ⊇ A ∧ IsOpen U ∧ μ U < μ A + ε :=
A.exists_isOpen_lt_of_lt _ (ENNReal.lt_add_right hA hε)
theorem _root_.Set.exists_isOpen_le_add (A : Set α) (μ : Measure α) [OuterRegular μ] {ε : ℝ≥0∞}
(hε : ε ≠ 0) : ∃ U, U ⊇ A ∧ IsOpen U ∧ μ U ≤ μ A + ε := by
rcases eq_or_ne (μ A) ∞ with (H | H)
· exact ⟨univ, subset_univ _, isOpen_univ, by simp only [H, _root_.top_add, le_top]⟩
· rcases A.exists_isOpen_lt_add H hε with ⟨U, AU, U_open, hU⟩
exact ⟨U, AU, U_open, hU.le⟩
theorem _root_.MeasurableSet.exists_isOpen_diff_lt [OuterRegular μ] {A : Set α}
(hA : MeasurableSet A) (hA' : μ A ≠ ∞) {ε : ℝ≥0∞} (hε : ε ≠ 0) :
∃ U, U ⊇ A ∧ IsOpen U ∧ μ U < ∞ ∧ μ (U \ A) < ε := by
rcases A.exists_isOpen_lt_add hA' hε with ⟨U, hAU, hUo, hU⟩
use U, hAU, hUo, hU.trans_le le_top
exact measure_diff_lt_of_lt_add hA.nullMeasurableSet hAU hA' hU
protected theorem map [OpensMeasurableSpace α] [MeasurableSpace β] [TopologicalSpace β]
[BorelSpace β] (f : α ≃ₜ β) (μ : Measure α) [OuterRegular μ] :
(Measure.map f μ).OuterRegular := by
refine ⟨fun A hA r hr => ?_⟩
rw [map_apply f.measurable hA, ← f.image_symm] at hr
rcases Set.exists_isOpen_lt_of_lt _ r hr with ⟨U, hAU, hUo, hU⟩
have : IsOpen (f.symm ⁻¹' U) := hUo.preimage f.symm.continuous
refine ⟨f.symm ⁻¹' U, image_subset_iff.1 hAU, this, ?_⟩
rwa [map_apply f.measurable this.measurableSet, f.preimage_symm, f.preimage_image]
protected theorem smul (μ : Measure α) [OuterRegular μ] {x : ℝ≥0∞} (hx : x ≠ ∞) :
(x • μ).OuterRegular := by
rcases eq_or_ne x 0 with (rfl | h0)
· rw [zero_smul]
exact OuterRegular.zero
· refine ⟨fun A _ r hr => ?_⟩
rw [smul_apply, A.measure_eq_iInf_isOpen, smul_eq_mul] at hr
simpa only [ENNReal.mul_iInf_of_ne h0 hx, gt_iff_lt, iInf_lt_iff, exists_prop] using hr
instance smul_nnreal (μ : Measure α) [OuterRegular μ] (c : ℝ≥0) :
OuterRegular (c • μ) :=
OuterRegular.smul μ coe_ne_top
open scoped Function in -- required for scoped `on` notation
/-- If the restrictions of a measure to countably many open sets covering the space are
outer regular, then the measure itself is outer regular. -/
lemma of_restrict [OpensMeasurableSpace α] {μ : Measure α} {s : ℕ → Set α}
(h : ∀ n, OuterRegular (μ.restrict (s n))) (h' : ∀ n, IsOpen (s n)) (h'' : univ ⊆ ⋃ n, s n) :
OuterRegular μ := by
refine ⟨fun A hA r hr => ?_⟩
have HA : μ A < ∞ := lt_of_lt_of_le hr le_top
have hm : ∀ n, MeasurableSet (s n) := fun n => (h' n).measurableSet
-- Note that `A = ⋃ n, A ∩ disjointed s n`. We replace `A` with this sequence.
obtain ⟨A, hAm, hAs, hAd, rfl⟩ :
∃ A' : ℕ → Set α,
(∀ n, MeasurableSet (A' n)) ∧
(∀ n, A' n ⊆ s n) ∧ Pairwise (Disjoint on A') ∧ A = ⋃ n, A' n := by
refine
⟨fun n => A ∩ disjointed s n, fun n => hA.inter (MeasurableSet.disjointed hm _), fun n =>
inter_subset_right.trans (disjointed_subset _ _),
(disjoint_disjointed s).mono fun k l hkl => hkl.mono inf_le_right inf_le_right, ?_⟩
rw [← inter_iUnion, iUnion_disjointed, univ_subset_iff.mp h'', inter_univ]
rcases ENNReal.exists_pos_sum_of_countable' (tsub_pos_iff_lt.2 hr).ne' ℕ with ⟨δ, δ0, hδε⟩
rw [lt_tsub_iff_right, add_comm] at hδε
have : ∀ n, ∃ U ⊇ A n, IsOpen U ∧ μ U < μ (A n) + δ n := by
intro n
have H₁ : ∀ t, μ.restrict (s n) t = μ (t ∩ s n) := fun t => restrict_apply' (hm n)
have Ht : μ.restrict (s n) (A n) ≠ ∞ := by
rw [H₁]
exact ((measure_mono (inter_subset_left.trans (subset_iUnion A n))).trans_lt HA).ne
rcases (A n).exists_isOpen_lt_add Ht (δ0 n).ne' with ⟨U, hAU, hUo, hU⟩
rw [H₁, H₁, inter_eq_self_of_subset_left (hAs _)] at hU
exact ⟨U ∩ s n, subset_inter hAU (hAs _), hUo.inter (h' n), hU⟩
choose U hAU hUo hU using this
refine ⟨⋃ n, U n, iUnion_mono hAU, isOpen_iUnion hUo, ?_⟩
calc
μ (⋃ n, U n) ≤ ∑' n, μ (U n) := measure_iUnion_le _
_ ≤ ∑' n, (μ (A n) + δ n) := ENNReal.tsum_le_tsum fun n => (hU n).le
_ = ∑' n, μ (A n) + ∑' n, δ n := ENNReal.tsum_add
_ = μ (⋃ n, A n) + ∑' n, δ n := (congr_arg₂ (· + ·) (measure_iUnion hAd hAm).symm rfl)
_ < r := hδε
/-- See also `IsCompact.measure_closure` for a version
that assumes the `σ`-algebra to be the Borel `σ`-algebra but makes no assumptions on `μ`. -/
lemma measure_closure_eq_of_isCompact [R1Space α] [OuterRegular μ]
{k : Set α} (hk : IsCompact k) : μ (closure k) = μ k := by
apply le_antisymm ?_ (measure_mono subset_closure)
simp only [measure_eq_iInf_isOpen k, le_iInf_iff]
intro u ku u_open
exact measure_mono (hk.closure_subset_of_isOpen u_open ku)
end OuterRegular
/-- If a measure `μ` admits finite spanning open sets such that the restriction of `μ` to each set
is outer regular, then the original measure is outer regular as well. -/
protected theorem FiniteSpanningSetsIn.outerRegular
[TopologicalSpace α] [OpensMeasurableSpace α] {μ : Measure α}
(s : μ.FiniteSpanningSetsIn { U | IsOpen U ∧ OuterRegular (μ.restrict U) }) :
OuterRegular μ :=
OuterRegular.of_restrict (s := fun n ↦ s.set n) (fun n ↦ (s.set_mem n).2)
(fun n ↦ (s.set_mem n).1) s.spanning.symm.subset
namespace InnerRegularWRT
variable {p : Set α → Prop}
/-- If the restrictions of a measure to a monotone sequence of sets covering the space are
inner regular for some property `p` and all measurable sets, then the measure itself is
inner regular. -/
lemma of_restrict {μ : Measure α} {s : ℕ → Set α}
(h : ∀ n, InnerRegularWRT (μ.restrict (s n)) p MeasurableSet)
(hs : univ ⊆ ⋃ n, s n) (hmono : Monotone s) : InnerRegularWRT μ p MeasurableSet := by
intro F hF r hr
have hBU : ⋃ n, F ∩ s n = F := by rw [← inter_iUnion, univ_subset_iff.mp hs, inter_univ]
have : μ F = ⨆ n, μ (F ∩ s n) := by
rw [← (monotone_const.inter hmono).measure_iUnion, hBU]
rw [this] at hr
rcases lt_iSup_iff.1 hr with ⟨n, hn⟩
rw [← restrict_apply hF] at hn
rcases h n hF _ hn with ⟨K, KF, hKp, hK⟩
exact ⟨K, KF, hKp, hK.trans_le (restrict_apply_le _ _)⟩
/-- If `μ` is inner regular for measurable finite measure sets with respect to some class of sets,
then its restriction to any set is also inner regular for measurable finite measure sets, with
respect to the same class of sets. -/
lemma restrict (h : InnerRegularWRT μ p (fun s ↦ MeasurableSet s ∧ μ s ≠ ∞)) (A : Set α) :
InnerRegularWRT (μ.restrict A) p (fun s ↦ MeasurableSet s ∧ μ.restrict A s ≠ ∞) := by
rintro s ⟨s_meas, hs⟩ r hr
rw [restrict_apply s_meas] at hs
obtain ⟨K, K_subs, pK, rK⟩ : ∃ K, K ⊆ (toMeasurable μ (s ∩ A)) ∩ s ∧ p K ∧ r < μ K := by
have : r < μ ((toMeasurable μ (s ∩ A)) ∩ s) := by
apply hr.trans_le
rw [restrict_apply s_meas]
exact measure_mono <| subset_inter (subset_toMeasurable μ (s ∩ A)) inter_subset_left
refine h ⟨(measurableSet_toMeasurable _ _).inter s_meas, ?_⟩ _ this
apply (lt_of_le_of_lt _ hs.lt_top).ne
rw [← measure_toMeasurable (s ∩ A)]
exact measure_mono inter_subset_left
refine ⟨K, K_subs.trans inter_subset_right, pK, ?_⟩
calc
r < μ K := rK
_ = μ.restrict (toMeasurable μ (s ∩ A)) K := by
rw [restrict_apply' (measurableSet_toMeasurable μ (s ∩ A))]
congr
apply (inter_eq_left.2 ?_).symm
exact K_subs.trans inter_subset_left
_ = μ.restrict (s ∩ A) K := by rwa [restrict_toMeasurable]
_ ≤ μ.restrict A K := Measure.le_iff'.1 (restrict_mono inter_subset_right le_rfl) K
/-- If `μ` is inner regular for measurable finite measure sets with respect to some class of sets,
then its restriction to any finite measure set is also inner regular for measurable sets with
respect to the same class of sets. -/
lemma restrict_of_measure_ne_top (h : InnerRegularWRT μ p (fun s ↦ MeasurableSet s ∧ μ s ≠ ∞))
{A : Set α} (hA : μ A ≠ ∞) :
InnerRegularWRT (μ.restrict A) p (fun s ↦ MeasurableSet s) := by
have : Fact (μ A < ∞) := ⟨hA.lt_top⟩
exact (restrict h A).trans (of_imp (fun s hs ↦ ⟨hs, measure_ne_top _ _⟩))
/-- Given a σ-finite measure, any measurable set can be approximated from inside by a measurable
set of finite measure. -/
lemma of_sigmaFinite [SigmaFinite μ] :
InnerRegularWRT μ (fun s ↦ MeasurableSet s ∧ μ s ≠ ∞) (fun s ↦ MeasurableSet s) := by
intro s hs r hr
set B : ℕ → Set α := spanningSets μ
have hBU : ⋃ n, s ∩ B n = s := by rw [← inter_iUnion, iUnion_spanningSets, inter_univ]
have : μ s = ⨆ n, μ (s ∩ B n) := by
rw [← (monotone_const.inter (monotone_spanningSets μ)).measure_iUnion, hBU]
rw [this] at hr
rcases lt_iSup_iff.1 hr with ⟨n, hn⟩
refine ⟨s ∩ B n, inter_subset_left, ⟨hs.inter (measurableSet_spanningSets μ n), ?_⟩, hn⟩
exact ((measure_mono inter_subset_right).trans_lt (measure_spanningSets_lt_top μ n)).ne
variable [TopologicalSpace α]
/-- If a measure is inner regular (using closed or compact sets) for open sets, then every
measurable set of finite measure can be approximated by a (closed or compact) subset. -/
theorem measurableSet_of_isOpen [OuterRegular μ] (H : InnerRegularWRT μ p IsOpen)
(hd : ∀ ⦃s U⦄, p s → IsOpen U → p (s \ U)) :
InnerRegularWRT μ p fun s => MeasurableSet s ∧ μ s ≠ ∞ := by
rintro s ⟨hs, hμs⟩ r hr
have h0 : p ∅ := by
have : 0 < μ univ := (bot_le.trans_lt hr).trans_le (measure_mono (subset_univ _))
obtain ⟨K, -, hK, -⟩ : ∃ K, K ⊆ univ ∧ p K ∧ 0 < μ K := H isOpen_univ _ this
simpa using hd hK isOpen_univ
obtain ⟨ε, hε, hεs, rfl⟩ : ∃ ε ≠ 0, ε + ε ≤ μ s ∧ r = μ s - (ε + ε) := by
use (μ s - r) / 2
simp [*, hr.le, ENNReal.add_halves, ENNReal.sub_sub_cancel, le_add_right, tsub_eq_zero_iff_le]
rcases hs.exists_isOpen_diff_lt hμs hε with ⟨U, hsU, hUo, hUt, hμU⟩
rcases (U \ s).exists_isOpen_lt_of_lt _ hμU with ⟨U', hsU', hU'o, hμU'⟩
replace hsU' := diff_subset_comm.1 hsU'
rcases H.exists_subset_lt_add h0 hUo hUt.ne hε with ⟨K, hKU, hKc, hKr⟩
refine ⟨K \ U', fun x hx => hsU' ⟨hKU hx.1, hx.2⟩, hd hKc hU'o, ENNReal.sub_lt_of_lt_add hεs ?_⟩
calc
μ s ≤ μ U := μ.mono hsU
_ < μ K + ε := hKr
_ ≤ μ (K \ U') + μ U' + ε := add_le_add_right (tsub_le_iff_right.1 le_measure_diff) _
_ ≤ μ (K \ U') + ε + ε := by gcongr
_ = μ (K \ U') + (ε + ε) := add_assoc _ _ _
open Finset in
/-- In a finite measure space, assume that any open set can be approximated from inside by closed
sets. Then the measure is weakly regular. -/
theorem weaklyRegular_of_finite [BorelSpace α] (μ : Measure α) [IsFiniteMeasure μ]
(H : InnerRegularWRT μ IsClosed IsOpen) : WeaklyRegular μ := by
have hfin : ∀ {s}, μ s ≠ ∞ := @(measure_ne_top μ)
suffices ∀ s, MeasurableSet s → ∀ ε, ε ≠ 0 → ∃ F, F ⊆ s ∧ ∃ U, U ⊇ s ∧
IsClosed F ∧ IsOpen U ∧ μ s ≤ μ F + ε ∧ μ U ≤ μ s + ε by
refine
{ outerRegular := fun s hs r hr => ?_
innerRegular := H }
rcases exists_between hr with ⟨r', hsr', hr'r⟩
rcases this s hs _ (tsub_pos_iff_lt.2 hsr').ne' with ⟨-, -, U, hsU, -, hUo, -, H⟩
refine ⟨U, hsU, hUo, ?_⟩
rw [add_tsub_cancel_of_le hsr'.le] at H
exact H.trans_lt hr'r
apply MeasurableSet.induction_on_open
/- The proof is by measurable induction: we should check that the property is true for the empty
set, for open sets, and is stable by taking the complement and by taking countable disjoint
unions. The point of the property we are proving is that it is stable by taking complements
(exchanging the roles of closed and open sets and thanks to the finiteness of the measure). -/
-- check for open set
· intro U hU ε hε
rcases H.exists_subset_lt_add isClosed_empty hU hfin hε with ⟨F, hsF, hFc, hF⟩
exact ⟨F, hsF, U, Subset.rfl, hFc, hU, hF.le, le_self_add⟩
-- check for complements
· rintro s hs H ε hε
rcases H ε hε with ⟨F, hFs, U, hsU, hFc, hUo, hF, hU⟩
refine
⟨Uᶜ, compl_subset_compl.2 hsU, Fᶜ, compl_subset_compl.2 hFs, hUo.isClosed_compl,
hFc.isOpen_compl, ?_⟩
simp only [measure_compl_le_add_iff, *, hUo.measurableSet, hFc.measurableSet, true_and]
-- check for disjoint unions
· intro s hsd hsm H ε ε0
have ε0' : ε / 2 ≠ 0 := (ENNReal.half_pos ε0).ne'
rcases ENNReal.exists_pos_sum_of_countable' ε0' ℕ with ⟨δ, δ0, hδε⟩
choose F hFs U hsU hFc hUo hF hU using fun n => H n (δ n) (δ0 n).ne'
-- the approximating closed set is constructed by considering finitely many sets `s i`, which
-- cover all the measure up to `ε/2`, approximating each of these by a closed set `F i`, and
-- taking the union of these (finitely many) `F i`.
have : Tendsto (fun t => (∑ k ∈ t, μ (s k)) + ε / 2) atTop (𝓝 <| μ (⋃ n, s n) + ε / 2) := by
rw [measure_iUnion hsd hsm]
exact Tendsto.add ENNReal.summable.hasSum tendsto_const_nhds
rcases (this.eventually <| lt_mem_nhds <| ENNReal.lt_add_right hfin ε0').exists with ⟨t, ht⟩
-- the approximating open set is constructed by taking for each `s n` an approximating open set
-- `U n` with measure at most `μ (s n) + δ n` for a summable `δ`, and taking the union of these.
refine
⟨⋃ k ∈ t, F k, iUnion_mono fun k => iUnion_subset fun _ => hFs _, ⋃ n, U n, iUnion_mono hsU,
isClosed_biUnion_finset fun k _ => hFc k, isOpen_iUnion hUo, ht.le.trans ?_, ?_⟩
· calc
(∑ k ∈ t, μ (s k)) + ε / 2 ≤ ((∑ k ∈ t, μ (F k)) + ∑ k ∈ t, δ k) + ε / 2 := by
rw [← sum_add_distrib]
gcongr
apply hF
_ ≤ (∑ k ∈ t, μ (F k)) + ε / 2 + ε / 2 := by
gcongr
exact (ENNReal.sum_le_tsum _).trans hδε.le
_ = μ (⋃ k ∈ t, F k) + ε := by
rw [measure_biUnion_finset, add_assoc, ENNReal.add_halves]
exacts [fun k _ n _ hkn => (hsd hkn).mono (hFs k) (hFs n),
fun k _ => (hFc k).measurableSet]
· calc
μ (⋃ n, U n) ≤ ∑' n, μ (U n) := measure_iUnion_le _
_ ≤ ∑' n, (μ (s n) + δ n) := ENNReal.tsum_le_tsum hU
_ = μ (⋃ n, s n) + ∑' n, δ n := by rw [measure_iUnion hsd hsm, ENNReal.tsum_add]
_ ≤ μ (⋃ n, s n) + ε := add_le_add_left (hδε.le.trans ENNReal.half_le_self) _
/-- In a metrizable space (or even a pseudo metrizable space), an open set can be approximated from
inside by closed sets. -/
theorem of_pseudoMetrizableSpace {X : Type*} [TopologicalSpace X] [PseudoMetrizableSpace X]
[MeasurableSpace X] (μ : Measure X) : InnerRegularWRT μ IsClosed IsOpen := by
let A : PseudoMetricSpace X := TopologicalSpace.pseudoMetrizableSpacePseudoMetric X
intro U hU r hr
rcases hU.exists_iUnion_isClosed with ⟨F, F_closed, -, rfl, F_mono⟩
rw [F_mono.measure_iUnion] at hr
rcases lt_iSup_iff.1 hr with ⟨n, hn⟩
exact ⟨F n, subset_iUnion _ _, F_closed n, hn⟩
/-- In a `σ`-compact space, any closed set can be approximated by a compact subset. -/
theorem isCompact_isClosed {X : Type*} [TopologicalSpace X] [SigmaCompactSpace X]
[MeasurableSpace X] (μ : Measure X) : InnerRegularWRT μ IsCompact IsClosed := by
intro F hF r hr
set B : ℕ → Set X := compactCovering X
| have hBc : ∀ n, IsCompact (F ∩ B n) := fun n => (isCompact_compactCovering X n).inter_left hF
have hBU : ⋃ n, F ∩ B n = F := by rw [← inter_iUnion, iUnion_compactCovering, Set.inter_univ]
have : μ F = ⨆ n, μ (F ∩ B n) := by
rw [← Monotone.measure_iUnion, hBU]
exact monotone_const.inter monotone_accumulate
rw [this] at hr
rcases lt_iSup_iff.1 hr with ⟨n, hn⟩
exact ⟨_, inter_subset_left, hBc n, hn⟩
| Mathlib/MeasureTheory/Measure/Regular.lean | 629 | 636 |
/-
Copyright (c) 2015, 2017 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Robert Y. Lewis, Johannes Hölzl, Mario Carneiro, Sébastien Gouëzel
-/
import Mathlib.Algebra.Order.BigOperators.Group.Finset
import Mathlib.Order.Interval.Finset.Nat
import Mathlib.Topology.EMetricSpace.Defs
import Mathlib.Topology.UniformSpace.Compact
import Mathlib.Topology.UniformSpace.LocallyUniformConvergence
import Mathlib.Topology.UniformSpace.UniformEmbedding
/-!
# Extended metric spaces
Further results about extended metric spaces.
-/
open Set Filter
universe u v w
variable {α : Type u} {β : Type v} {X : Type*}
open scoped Uniformity Topology NNReal ENNReal Pointwise
variable [PseudoEMetricSpace α]
/-- The triangle (polygon) inequality for sequences of points; `Finset.Ico` version. -/
theorem edist_le_Ico_sum_edist (f : ℕ → α) {m n} (h : m ≤ n) :
edist (f m) (f n) ≤ ∑ i ∈ Finset.Ico m n, edist (f i) (f (i + 1)) := by
induction n, h using Nat.le_induction with
| base => rw [Finset.Ico_self, Finset.sum_empty, edist_self]
| succ n hle ihn =>
calc
edist (f m) (f (n + 1)) ≤ edist (f m) (f n) + edist (f n) (f (n + 1)) := edist_triangle _ _ _
_ ≤ (∑ i ∈ Finset.Ico m n, _) + _ := add_le_add ihn le_rfl
_ = ∑ i ∈ Finset.Ico m (n + 1), _ := by
{ rw [Nat.Ico_succ_right_eq_insert_Ico hle, Finset.sum_insert, add_comm]; simp }
/-- The triangle (polygon) inequality for sequences of points; `Finset.range` version. -/
theorem edist_le_range_sum_edist (f : ℕ → α) (n : ℕ) :
edist (f 0) (f n) ≤ ∑ i ∈ Finset.range n, edist (f i) (f (i + 1)) :=
Nat.Ico_zero_eq_range ▸ edist_le_Ico_sum_edist f (Nat.zero_le n)
/-- A version of `edist_le_Ico_sum_edist` with each intermediate distance replaced
with an upper estimate. -/
theorem edist_le_Ico_sum_of_edist_le {f : ℕ → α} {m n} (hmn : m ≤ n) {d : ℕ → ℝ≥0∞}
(hd : ∀ {k}, m ≤ k → k < n → edist (f k) (f (k + 1)) ≤ d k) :
edist (f m) (f n) ≤ ∑ i ∈ Finset.Ico m n, d i :=
le_trans (edist_le_Ico_sum_edist f hmn) <|
Finset.sum_le_sum fun _k hk => hd (Finset.mem_Ico.1 hk).1 (Finset.mem_Ico.1 hk).2
/-- A version of `edist_le_range_sum_edist` with each intermediate distance replaced
with an upper estimate. -/
theorem edist_le_range_sum_of_edist_le {f : ℕ → α} (n : ℕ) {d : ℕ → ℝ≥0∞}
(hd : ∀ {k}, k < n → edist (f k) (f (k + 1)) ≤ d k) :
edist (f 0) (f n) ≤ ∑ i ∈ Finset.range n, d i :=
Nat.Ico_zero_eq_range ▸ edist_le_Ico_sum_of_edist_le (zero_le n) fun _ => hd
namespace EMetric
theorem isUniformInducing_iff [PseudoEMetricSpace β] {f : α → β} :
IsUniformInducing f ↔ UniformContinuous f ∧
∀ δ > 0, ∃ ε > 0, ∀ {a b : α}, edist (f a) (f b) < ε → edist a b < δ :=
isUniformInducing_iff'.trans <| Iff.rfl.and <|
((uniformity_basis_edist.comap _).le_basis_iff uniformity_basis_edist).trans <| by
simp only [subset_def, Prod.forall]; rfl
/-- ε-δ characterization of uniform embeddings on pseudoemetric spaces -/
nonrec theorem isUniformEmbedding_iff [PseudoEMetricSpace β] {f : α → β} :
IsUniformEmbedding f ↔ Function.Injective f ∧ UniformContinuous f ∧
∀ δ > 0, ∃ ε > 0, ∀ {a b : α}, edist (f a) (f b) < ε → edist a b < δ :=
(isUniformEmbedding_iff _).trans <| and_comm.trans <| Iff.rfl.and isUniformInducing_iff
/-- If a map between pseudoemetric spaces is a uniform embedding then the edistance between `f x`
and `f y` is controlled in terms of the distance between `x` and `y`.
In fact, this lemma holds for a `IsUniformInducing` map.
TODO: generalize? -/
theorem controlled_of_isUniformEmbedding [PseudoEMetricSpace β] {f : α → β}
(h : IsUniformEmbedding f) :
(∀ ε > 0, ∃ δ > 0, ∀ {a b : α}, edist a b < δ → edist (f a) (f b) < ε) ∧
∀ δ > 0, ∃ ε > 0, ∀ {a b : α}, edist (f a) (f b) < ε → edist a b < δ :=
⟨uniformContinuous_iff.1 h.uniformContinuous, (isUniformEmbedding_iff.1 h).2.2⟩
/-- ε-δ characterization of Cauchy sequences on pseudoemetric spaces -/
protected theorem cauchy_iff {f : Filter α} :
Cauchy f ↔ f ≠ ⊥ ∧ ∀ ε > 0, ∃ t ∈ f, ∀ x, x ∈ t → ∀ y, y ∈ t → edist x y < ε := by
rw [← neBot_iff]; exact uniformity_basis_edist.cauchy_iff
/-- A very useful criterion to show that a space is complete is to show that all sequences
which satisfy a bound of the form `edist (u n) (u m) < B N` for all `n m ≥ N` are
converging. This is often applied for `B N = 2^{-N}`, i.e., with a very fast convergence to
`0`, which makes it possible to use arguments of converging series, while this is impossible
to do in general for arbitrary Cauchy sequences. -/
theorem complete_of_convergent_controlled_sequences (B : ℕ → ℝ≥0∞) (hB : ∀ n, 0 < B n)
(H : ∀ u : ℕ → α, (∀ N n m : ℕ, N ≤ n → N ≤ m → edist (u n) (u m) < B N) →
∃ x, Tendsto u atTop (𝓝 x)) :
CompleteSpace α :=
UniformSpace.complete_of_convergent_controlled_sequences
(fun n => { p : α × α | edist p.1 p.2 < B n }) (fun n => edist_mem_uniformity <| hB n) H
/-- A sequentially complete pseudoemetric space is complete. -/
theorem complete_of_cauchySeq_tendsto :
(∀ u : ℕ → α, CauchySeq u → ∃ a, Tendsto u atTop (𝓝 a)) → CompleteSpace α :=
UniformSpace.complete_of_cauchySeq_tendsto
/-- Expressing locally uniform convergence on a set using `edist`. -/
theorem tendstoLocallyUniformlyOn_iff {ι : Type*} [TopologicalSpace β] {F : ι → β → α} {f : β → α}
{p : Filter ι} {s : Set β} :
TendstoLocallyUniformlyOn F f p s ↔
∀ ε > 0, ∀ x ∈ s, ∃ t ∈ 𝓝[s] x, ∀ᶠ n in p, ∀ y ∈ t, edist (f y) (F n y) < ε := by
refine ⟨fun H ε hε => H _ (edist_mem_uniformity hε), fun H u hu x hx => ?_⟩
rcases mem_uniformity_edist.1 hu with ⟨ε, εpos, hε⟩
rcases H ε εpos x hx with ⟨t, ht, Ht⟩
exact ⟨t, ht, Ht.mono fun n hs x hx => hε (hs x hx)⟩
/-- Expressing uniform convergence on a set using `edist`. -/
theorem tendstoUniformlyOn_iff {ι : Type*} {F : ι → β → α} {f : β → α} {p : Filter ι} {s : Set β} :
TendstoUniformlyOn F f p s ↔ ∀ ε > 0, ∀ᶠ n in p, ∀ x ∈ s, edist (f x) (F n x) < ε := by
refine ⟨fun H ε hε => H _ (edist_mem_uniformity hε), fun H u hu => ?_⟩
rcases mem_uniformity_edist.1 hu with ⟨ε, εpos, hε⟩
exact (H ε εpos).mono fun n hs x hx => hε (hs x hx)
/-- Expressing locally uniform convergence using `edist`. -/
theorem tendstoLocallyUniformly_iff {ι : Type*} [TopologicalSpace β] {F : ι → β → α} {f : β → α}
{p : Filter ι} :
TendstoLocallyUniformly F f p ↔
∀ ε > 0, ∀ x : β, ∃ t ∈ 𝓝 x, ∀ᶠ n in p, ∀ y ∈ t, edist (f y) (F n y) < ε := by
simp only [← tendstoLocallyUniformlyOn_univ, tendstoLocallyUniformlyOn_iff, mem_univ,
forall_const, exists_prop, nhdsWithin_univ]
/-- Expressing uniform convergence using `edist`. -/
theorem tendstoUniformly_iff {ι : Type*} {F : ι → β → α} {f : β → α} {p : Filter ι} :
TendstoUniformly F f p ↔ ∀ ε > 0, ∀ᶠ n in p, ∀ x, edist (f x) (F n x) < ε := by
simp only [← tendstoUniformlyOn_univ, tendstoUniformlyOn_iff, mem_univ, forall_const]
end EMetric
open EMetric
namespace EMetric
variable {x y z : α} {ε ε₁ ε₂ : ℝ≥0∞} {s t : Set α}
theorem inseparable_iff : Inseparable x y ↔ edist x y = 0 := by
simp [inseparable_iff_mem_closure, mem_closure_iff, edist_comm, forall_lt_iff_le']
alias ⟨_root_.Inseparable.edist_eq_zero, _⟩ := EMetric.inseparable_iff
-- see Note [nolint_ge]
/-- In a pseudoemetric space, Cauchy sequences are characterized by the fact that, eventually,
the pseudoedistance between its elements is arbitrarily small -/
theorem cauchySeq_iff [Nonempty β] [SemilatticeSup β] {u : β → α} :
CauchySeq u ↔ ∀ ε > 0, ∃ N, ∀ m, N ≤ m → ∀ n, N ≤ n → edist (u m) (u n) < ε :=
uniformity_basis_edist.cauchySeq_iff
/-- A variation around the emetric characterization of Cauchy sequences -/
theorem cauchySeq_iff' [Nonempty β] [SemilatticeSup β] {u : β → α} :
CauchySeq u ↔ ∀ ε > (0 : ℝ≥0∞), ∃ N, ∀ n ≥ N, edist (u n) (u N) < ε :=
uniformity_basis_edist.cauchySeq_iff'
/-- A variation of the emetric characterization of Cauchy sequences that deals with
`ℝ≥0` upper bounds. -/
theorem cauchySeq_iff_NNReal [Nonempty β] [SemilatticeSup β] {u : β → α} :
CauchySeq u ↔ ∀ ε : ℝ≥0, 0 < ε → ∃ N, ∀ n, N ≤ n → edist (u n) (u N) < ε :=
uniformity_basis_edist_nnreal.cauchySeq_iff'
theorem totallyBounded_iff {s : Set α} :
TotallyBounded s ↔ ∀ ε > 0, ∃ t : Set α, t.Finite ∧ s ⊆ ⋃ y ∈ t, ball y ε :=
⟨fun H _ε ε0 => H _ (edist_mem_uniformity ε0), fun H _r ru =>
let ⟨ε, ε0, hε⟩ := mem_uniformity_edist.1 ru
let ⟨t, ft, h⟩ := H ε ε0
⟨t, ft, h.trans <| iUnion₂_mono fun _ _ _ => hε⟩⟩
theorem totallyBounded_iff' {s : Set α} :
TotallyBounded s ↔ ∀ ε > 0, ∃ t, t ⊆ s ∧ Set.Finite t ∧ s ⊆ ⋃ y ∈ t, ball y ε :=
⟨fun H _ε ε0 => (totallyBounded_iff_subset.1 H) _ (edist_mem_uniformity ε0), fun H _r ru =>
let ⟨ε, ε0, hε⟩ := mem_uniformity_edist.1 ru
let ⟨t, _, ft, h⟩ := H ε ε0
⟨t, ft, h.trans <| iUnion₂_mono fun _ _ _ => hε⟩⟩
section Compact
-- TODO: generalize to metrizable spaces
/-- A compact set in a pseudo emetric space is separable, i.e., it is a subset of the closure of a
countable set. -/
theorem subset_countable_closure_of_compact {s : Set α} (hs : IsCompact s) :
∃ t, t ⊆ s ∧ t.Countable ∧ s ⊆ closure t := by
refine subset_countable_closure_of_almost_dense_set s fun ε hε => ?_
rcases totallyBounded_iff'.1 hs.totallyBounded ε hε with ⟨t, -, htf, hst⟩
exact ⟨t, htf.countable, hst.trans <| iUnion₂_mono fun _ _ => ball_subset_closedBall⟩
end Compact
section SecondCountable
open TopologicalSpace
variable (α) in
/-- A sigma compact pseudo emetric space has second countable topology. -/
instance (priority := 90) secondCountable_of_sigmaCompact [SigmaCompactSpace α] :
SecondCountableTopology α := by
suffices SeparableSpace α by exact UniformSpace.secondCountable_of_separable α
choose T _ hTc hsubT using fun n =>
subset_countable_closure_of_compact (isCompact_compactCovering α n)
refine ⟨⟨⋃ n, T n, countable_iUnion hTc, fun x => ?_⟩⟩
rcases iUnion_eq_univ_iff.1 (iUnion_compactCovering α) x with ⟨n, hn⟩
exact closure_mono (subset_iUnion _ n) (hsubT _ hn)
theorem secondCountable_of_almost_dense_set
(hs : ∀ ε > 0, ∃ t : Set α, t.Countable ∧ ⋃ x ∈ t, closedBall x ε = univ) :
SecondCountableTopology α := by
suffices SeparableSpace α from UniformSpace.secondCountable_of_separable α
have : ∀ ε > 0, ∃ t : Set α, Set.Countable t ∧ univ ⊆ ⋃ x ∈ t, closedBall x ε := by
simpa only [univ_subset_iff] using hs
rcases subset_countable_closure_of_almost_dense_set (univ : Set α) this with ⟨t, -, htc, ht⟩
exact ⟨⟨t, htc, fun x => ht (mem_univ x)⟩⟩
end SecondCountable
end EMetric
variable {γ : Type w} [EMetricSpace γ]
-- see Note [lower instance priority]
/-- An emetric space is separated -/
instance (priority := 100) EMetricSpace.instT0Space : T0Space γ where
t0 _ _ h := eq_of_edist_eq_zero <| inseparable_iff.1 h
/-- A map between emetric spaces is a uniform embedding if and only if the edistance between `f x`
and `f y` is controlled in terms of the distance between `x` and `y` and conversely. -/
theorem EMetric.isUniformEmbedding_iff' [PseudoEMetricSpace β] {f : γ → β} :
IsUniformEmbedding f ↔
(∀ ε > 0, ∃ δ > 0, ∀ {a b : γ}, edist a b < δ → edist (f a) (f b) < ε) ∧
∀ δ > 0, ∃ ε > 0, ∀ {a b : γ}, edist (f a) (f b) < ε → edist a b < δ := by
rw [isUniformEmbedding_iff_isUniformInducing, isUniformInducing_iff, uniformContinuous_iff]
/-- If a `PseudoEMetricSpace` is a T₀ space, then it is an `EMetricSpace`. -/
-- TODO: make it an instance?
abbrev EMetricSpace.ofT0PseudoEMetricSpace (α : Type*) [PseudoEMetricSpace α] [T0Space α] :
EMetricSpace α :=
{ ‹PseudoEMetricSpace α› with
eq_of_edist_eq_zero := fun h => (EMetric.inseparable_iff.2 h).eq }
/-- The product of two emetric spaces, with the max distance, is an extended
metric spaces. We make sure that the uniform structure thus constructed is the one
corresponding to the product of uniform spaces, to avoid diamond problems. -/
instance Prod.emetricSpaceMax [EMetricSpace β] : EMetricSpace (γ × β) :=
.ofT0PseudoEMetricSpace _
namespace EMetric
/-- A compact set in an emetric space is separable, i.e., it is the closure of a countable set. -/
theorem countable_closure_of_compact {s : Set γ} (hs : IsCompact s) :
∃ t, t ⊆ s ∧ t.Countable ∧ s = closure t := by
rcases subset_countable_closure_of_compact hs with ⟨t, hts, htc, hsub⟩
exact ⟨t, hts, htc, hsub.antisymm (closure_minimal hts hs.isClosed)⟩
end EMetric
/-!
### Separation quotient
-/
instance [PseudoEMetricSpace X] : EDist (SeparationQuotient X) where
edist := SeparationQuotient.lift₂ edist fun _ _ _ _ hx hy =>
edist_congr (EMetric.inseparable_iff.1 hx) (EMetric.inseparable_iff.1 hy)
@[simp] theorem SeparationQuotient.edist_mk [PseudoEMetricSpace X] (x y : X) :
edist (mk x) (mk y) = edist x y :=
rfl
open SeparationQuotient in
instance [PseudoEMetricSpace X] : EMetricSpace (SeparationQuotient X) :=
@EMetricSpace.ofT0PseudoEMetricSpace (SeparationQuotient X)
{ edist_self := surjective_mk.forall.2 edist_self,
edist_comm := surjective_mk.forall₂.2 edist_comm,
edist_triangle := surjective_mk.forall₃.2 edist_triangle,
toUniformSpace := inferInstance,
uniformity_edist := comap_injective (surjective_mk.prodMap surjective_mk) <| by
simp [comap_mk_uniformity, PseudoEMetricSpace.uniformity_edist] } _
namespace TopologicalSpace
section Compact
open Topology
/-- If a set `s` is separable in a (pseudo extended) metric space, then it admits a countable dense
subset. This is not obvious, as the countable set whose closure covers `s` given by the definition
of separability does not need in general to be contained in `s`. -/
theorem IsSeparable.exists_countable_dense_subset
{s : Set α} (hs : IsSeparable s) : ∃ t, t ⊆ s ∧ t.Countable ∧ s ⊆ closure t := by
have : ∀ ε > 0, ∃ t : Set α, t.Countable ∧ s ⊆ ⋃ x ∈ t, closedBall x ε := fun ε ε0 => by
rcases hs with ⟨t, htc, hst⟩
refine ⟨t, htc, hst.trans fun x hx => ?_⟩
rcases mem_closure_iff.1 hx ε ε0 with ⟨y, hyt, hxy⟩
exact mem_iUnion₂.2 ⟨y, hyt, mem_closedBall.2 hxy.le⟩
exact subset_countable_closure_of_almost_dense_set _ this
/-- If a set `s` is separable, then the corresponding subtype is separable in a (pseudo extended)
metric space. This is not obvious, as the countable set whose closure covers `s` does not need in
general to be contained in `s`. -/
theorem IsSeparable.separableSpace {s : Set α} (hs : IsSeparable s) :
SeparableSpace s := by
rcases hs.exists_countable_dense_subset with ⟨t, hts, htc, hst⟩
lift t to Set s using hts
refine ⟨⟨t, countable_of_injective_of_countable_image Subtype.coe_injective.injOn htc, ?_⟩⟩
rwa [IsInducing.subtypeVal.dense_iff, Subtype.forall]
end Compact
end TopologicalSpace
section LebesgueNumberLemma
variable {s : Set α}
theorem lebesgue_number_lemma_of_emetric {ι : Sort*} {c : ι → Set α} (hs : IsCompact s)
(hc₁ : ∀ i, IsOpen (c i)) (hc₂ : s ⊆ ⋃ i, c i) : ∃ δ > 0, ∀ x ∈ s, ∃ i, ball x δ ⊆ c i := by
simpa only [ball, UniformSpace.ball, preimage_setOf_eq, edist_comm]
using uniformity_basis_edist.lebesgue_number_lemma hs hc₁ hc₂
theorem lebesgue_number_lemma_of_emetric_nhds' {c : (x : α) → x ∈ s → Set α} (hs : IsCompact s)
(hc : ∀ x hx, c x hx ∈ 𝓝 x) : ∃ δ > 0, ∀ x ∈ s, ∃ y : s, ball x δ ⊆ c y y.2 := by
simpa only [ball, UniformSpace.ball, preimage_setOf_eq, edist_comm]
using uniformity_basis_edist.lebesgue_number_lemma_nhds' hs hc
theorem lebesgue_number_lemma_of_emetric_nhds {c : α → Set α} (hs : IsCompact s)
(hc : ∀ x ∈ s, c x ∈ 𝓝 x) : ∃ δ > 0, ∀ x ∈ s, ∃ y, ball x δ ⊆ c y := by
simpa only [ball, UniformSpace.ball, preimage_setOf_eq, edist_comm]
using uniformity_basis_edist.lebesgue_number_lemma_nhds hs hc
theorem lebesgue_number_lemma_of_emetric_nhdsWithin' {c : (x : α) → x ∈ s → Set α}
(hs : IsCompact s) (hc : ∀ x hx, c x hx ∈ 𝓝[s] x) :
∃ δ > 0, ∀ x ∈ s, ∃ y : s, ball x δ ∩ s ⊆ c y y.2 := by
simpa only [ball, UniformSpace.ball, preimage_setOf_eq, edist_comm]
using uniformity_basis_edist.lebesgue_number_lemma_nhdsWithin' hs hc
theorem lebesgue_number_lemma_of_emetric_nhdsWithin {c : α → Set α} (hs : IsCompact s)
(hc : ∀ x ∈ s, c x ∈ 𝓝[s] x) : ∃ δ > 0, ∀ x ∈ s, ∃ y, ball x δ ∩ s ⊆ c y := by
simpa only [ball, UniformSpace.ball, preimage_setOf_eq, edist_comm]
using uniformity_basis_edist.lebesgue_number_lemma_nhdsWithin hs hc
theorem lebesgue_number_lemma_of_emetric_sUnion {c : Set (Set α)} (hs : IsCompact s)
(hc₁ : ∀ t ∈ c, IsOpen t) (hc₂ : s ⊆ ⋃₀ c) : ∃ δ > 0, ∀ x ∈ s, ∃ t ∈ c, ball x δ ⊆ t := by
rw [sUnion_eq_iUnion] at hc₂; simpa using lebesgue_number_lemma_of_emetric hs (by simpa) hc₂
end LebesgueNumberLemma
| Mathlib/Topology/EMetricSpace/Basic.lean | 680 | 685 | |
/-
Copyright (c) 2020 Jujian Zhang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jujian Zhang, Johan Commelin
-/
import Mathlib.RingTheory.GradedAlgebra.Homogeneous.Ideal
import Mathlib.Topology.Category.TopCat.Basic
import Mathlib.Topology.Sets.Opens
import Mathlib.Data.Set.Subsingleton
/-!
# Projective spectrum of a graded ring
The projective spectrum of a graded commutative ring is the subtype of all homogeneous ideals that
are prime and do not contain the irrelevant ideal.
It is naturally endowed with a topology: the Zariski topology.
## Notation
- `R` is a commutative semiring;
- `A` is a commutative ring and an `R`-algebra;
- `𝒜 : ℕ → Submodule R A` is the grading of `A`;
## Main definitions
* `ProjectiveSpectrum 𝒜`: The projective spectrum of a graded ring `A`, or equivalently, the set of
all homogeneous ideals of `A` that is both prime and relevant i.e. not containing irrelevant
ideal. Henceforth, we call elements of projective spectrum *relevant homogeneous prime ideals*.
* `ProjectiveSpectrum.zeroLocus 𝒜 s`: The zero locus of a subset `s` of `A`
is the subset of `ProjectiveSpectrum 𝒜` consisting of all relevant homogeneous prime ideals that
contain `s`.
* `ProjectiveSpectrum.vanishingIdeal t`: The vanishing ideal of a subset `t` of
`ProjectiveSpectrum 𝒜` is the intersection of points in `t` (viewed as relevant homogeneous prime
ideals).
* `ProjectiveSpectrum.Top`: the topological space of `ProjectiveSpectrum 𝒜` endowed with the
Zariski topology.
-/
noncomputable section
open DirectSum Pointwise SetLike TopCat TopologicalSpace CategoryTheory Opposite
variable {R A : Type*}
variable [CommSemiring R] [CommRing A] [Algebra R A]
variable (𝒜 : ℕ → Submodule R A) [GradedAlgebra 𝒜]
/-- The projective spectrum of a graded commutative ring is the subtype of all homogeneous ideals
that are prime and do not contain the irrelevant ideal. -/
@[ext]
structure ProjectiveSpectrum where
asHomogeneousIdeal : HomogeneousIdeal 𝒜
isPrime : asHomogeneousIdeal.toIdeal.IsPrime
not_irrelevant_le : ¬HomogeneousIdeal.irrelevant 𝒜 ≤ asHomogeneousIdeal
attribute [instance] ProjectiveSpectrum.isPrime
namespace ProjectiveSpectrum
instance (x : ProjectiveSpectrum 𝒜) : Ideal.IsPrime x.asHomogeneousIdeal.toIdeal := x.isPrime
/-- The zero locus of a set `s` of elements of a commutative ring `A` is the set of all relevant
homogeneous prime ideals of the ring that contain the set `s`.
An element `f` of `A` can be thought of as a dependent function on the projective spectrum of `𝒜`.
At a point `x` (a homogeneous prime ideal) the function (i.e., element) `f` takes values in the
quotient ring `A` modulo the prime ideal `x`. In this manner, `zeroLocus s` is exactly the subset
of `ProjectiveSpectrum 𝒜` where all "functions" in `s` vanish simultaneously. -/
def zeroLocus (s : Set A) : Set (ProjectiveSpectrum 𝒜) :=
{ x | s ⊆ x.asHomogeneousIdeal }
@[simp]
theorem mem_zeroLocus (x : ProjectiveSpectrum 𝒜) (s : Set A) :
x ∈ zeroLocus 𝒜 s ↔ s ⊆ x.asHomogeneousIdeal :=
Iff.rfl
@[simp]
theorem zeroLocus_span (s : Set A) : zeroLocus 𝒜 (Ideal.span s) = zeroLocus 𝒜 s := by
ext x
exact (Submodule.gi _ _).gc s x.asHomogeneousIdeal.toIdeal
variable {𝒜}
/-- The vanishing ideal of a set `t` of points of the projective spectrum of a commutative ring `R`
is the intersection of all the relevant homogeneous prime ideals in the set `t`.
An element `f` of `A` can be thought of as a dependent function on the projective spectrum of `𝒜`.
At a point `x` (a homogeneous prime ideal) the function (i.e., element) `f` takes values in the
quotient ring `A` modulo the prime ideal `x`. In this manner, `vanishingIdeal t` is exactly the
ideal of `A` consisting of all "functions" that vanish on all of `t`. -/
def vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) : HomogeneousIdeal 𝒜 :=
⨅ (x : ProjectiveSpectrum 𝒜) (_ : x ∈ t), x.asHomogeneousIdeal
theorem coe_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) :
(vanishingIdeal t : Set A) =
{ f | ∀ x : ProjectiveSpectrum 𝒜, x ∈ t → f ∈ x.asHomogeneousIdeal } := by
ext f
rw [vanishingIdeal, SetLike.mem_coe, ← HomogeneousIdeal.mem_iff, HomogeneousIdeal.toIdeal_iInf,
Submodule.mem_iInf]
refine forall_congr' fun x => ?_
rw [HomogeneousIdeal.toIdeal_iInf, Submodule.mem_iInf, HomogeneousIdeal.mem_iff]
theorem mem_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) (f : A) :
f ∈ vanishingIdeal t ↔ ∀ x : ProjectiveSpectrum 𝒜, x ∈ t → f ∈ x.asHomogeneousIdeal := by
rw [← SetLike.mem_coe, coe_vanishingIdeal, Set.mem_setOf_eq]
@[simp]
theorem vanishingIdeal_singleton (x : ProjectiveSpectrum 𝒜) :
vanishingIdeal ({x} : Set (ProjectiveSpectrum 𝒜)) = x.asHomogeneousIdeal := by
simp [vanishingIdeal]
theorem subset_zeroLocus_iff_le_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) (I : Ideal A) :
t ⊆ zeroLocus 𝒜 I ↔ I ≤ (vanishingIdeal t).toIdeal :=
⟨fun h _ k => (mem_vanishingIdeal _ _).mpr fun _ j => (mem_zeroLocus _ _ _).mpr (h j) k, fun h =>
fun x j =>
(mem_zeroLocus _ _ _).mpr (le_trans h fun _ h => ((mem_vanishingIdeal _ _).mp h) x j)⟩
variable (𝒜)
/-- `zeroLocus` and `vanishingIdeal` form a galois connection. -/
theorem gc_ideal :
@GaloisConnection (Ideal A) (Set (ProjectiveSpectrum 𝒜))ᵒᵈ _ _
(fun I => zeroLocus 𝒜 I) fun t => (vanishingIdeal t).toIdeal :=
fun I t => subset_zeroLocus_iff_le_vanishingIdeal t I
/-- `zeroLocus` and `vanishingIdeal` form a galois connection. -/
theorem gc_set :
@GaloisConnection (Set A) (Set (ProjectiveSpectrum 𝒜))ᵒᵈ _ _
(fun s => zeroLocus 𝒜 s) fun t => vanishingIdeal t := by
have ideal_gc : GaloisConnection Ideal.span _ := (Submodule.gi A _).gc
simpa [zeroLocus_span, Function.comp_def] using GaloisConnection.compose ideal_gc (gc_ideal 𝒜)
theorem gc_homogeneousIdeal :
@GaloisConnection (HomogeneousIdeal 𝒜) (Set (ProjectiveSpectrum 𝒜))ᵒᵈ _ _
(fun I => zeroLocus 𝒜 I) fun t => vanishingIdeal t :=
fun I t => by
simpa [show I.toIdeal ≤ (vanishingIdeal t).toIdeal ↔ I ≤ vanishingIdeal t from Iff.rfl] using
subset_zeroLocus_iff_le_vanishingIdeal t I.toIdeal
theorem subset_zeroLocus_iff_subset_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) (s : Set A) :
t ⊆ zeroLocus 𝒜 s ↔ s ⊆ vanishingIdeal t :=
(gc_set _) s t
theorem subset_vanishingIdeal_zeroLocus (s : Set A) : s ⊆ vanishingIdeal (zeroLocus 𝒜 s) :=
(gc_set _).le_u_l s
theorem ideal_le_vanishingIdeal_zeroLocus (I : Ideal A) :
I ≤ (vanishingIdeal (zeroLocus 𝒜 I)).toIdeal :=
(gc_ideal _).le_u_l I
theorem homogeneousIdeal_le_vanishingIdeal_zeroLocus (I : HomogeneousIdeal 𝒜) :
I ≤ vanishingIdeal (zeroLocus 𝒜 I) :=
(gc_homogeneousIdeal _).le_u_l I
theorem subset_zeroLocus_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) :
t ⊆ zeroLocus 𝒜 (vanishingIdeal t) :=
(gc_ideal _).l_u_le t
theorem zeroLocus_anti_mono {s t : Set A} (h : s ⊆ t) : zeroLocus 𝒜 t ⊆ zeroLocus 𝒜 s :=
(gc_set _).monotone_l h
theorem zeroLocus_anti_mono_ideal {s t : Ideal A} (h : s ≤ t) :
zeroLocus 𝒜 (t : Set A) ⊆ zeroLocus 𝒜 (s : Set A) :=
(gc_ideal _).monotone_l h
theorem zeroLocus_anti_mono_homogeneousIdeal {s t : HomogeneousIdeal 𝒜} (h : s ≤ t) :
zeroLocus 𝒜 (t : Set A) ⊆ zeroLocus 𝒜 (s : Set A) :=
(gc_homogeneousIdeal _).monotone_l h
theorem vanishingIdeal_anti_mono {s t : Set (ProjectiveSpectrum 𝒜)} (h : s ⊆ t) :
vanishingIdeal t ≤ vanishingIdeal s :=
(gc_ideal _).monotone_u h
theorem zeroLocus_bot : zeroLocus 𝒜 ((⊥ : Ideal A) : Set A) = Set.univ :=
(gc_ideal 𝒜).l_bot
@[simp]
theorem zeroLocus_singleton_zero : zeroLocus 𝒜 ({0} : Set A) = Set.univ :=
zeroLocus_bot _
@[simp]
theorem zeroLocus_empty : zeroLocus 𝒜 (∅ : Set A) = Set.univ :=
(gc_set 𝒜).l_bot
@[simp]
theorem vanishingIdeal_univ : vanishingIdeal (∅ : Set (ProjectiveSpectrum 𝒜)) = ⊤ := by
simpa using (gc_ideal _).u_top
theorem zeroLocus_empty_of_one_mem {s : Set A} (h : (1 : A) ∈ s) : zeroLocus 𝒜 s = ∅ :=
Set.eq_empty_iff_forall_not_mem.mpr fun x hx =>
(inferInstance : x.asHomogeneousIdeal.toIdeal.IsPrime).ne_top <|
x.asHomogeneousIdeal.toIdeal.eq_top_iff_one.mpr <| hx h
@[simp]
theorem zeroLocus_singleton_one : zeroLocus 𝒜 ({1} : Set A) = ∅ :=
zeroLocus_empty_of_one_mem 𝒜 (Set.mem_singleton (1 : A))
@[simp]
theorem zeroLocus_univ : zeroLocus 𝒜 (Set.univ : Set A) = ∅ :=
zeroLocus_empty_of_one_mem _ (Set.mem_univ 1)
theorem zeroLocus_sup_ideal (I J : Ideal A) :
zeroLocus 𝒜 ((I ⊔ J : Ideal A) : Set A) = zeroLocus _ I ∩ zeroLocus _ J :=
(gc_ideal 𝒜).l_sup
theorem zeroLocus_sup_homogeneousIdeal (I J : HomogeneousIdeal 𝒜) :
zeroLocus 𝒜 ((I ⊔ J : HomogeneousIdeal 𝒜) : Set A) = zeroLocus _ I ∩ zeroLocus _ J :=
(gc_homogeneousIdeal 𝒜).l_sup
theorem zeroLocus_union (s s' : Set A) : zeroLocus 𝒜 (s ∪ s') = zeroLocus _ s ∩ zeroLocus _ s' :=
(gc_set 𝒜).l_sup
theorem vanishingIdeal_union (t t' : Set (ProjectiveSpectrum 𝒜)) :
vanishingIdeal (t ∪ t') = vanishingIdeal t ⊓ vanishingIdeal t' := by
ext1; exact (gc_ideal 𝒜).u_inf
theorem zeroLocus_iSup_ideal {γ : Sort*} (I : γ → Ideal A) :
zeroLocus _ ((⨆ i, I i : Ideal A) : Set A) = ⋂ i, zeroLocus 𝒜 (I i) :=
(gc_ideal 𝒜).l_iSup
theorem zeroLocus_iSup_homogeneousIdeal {γ : Sort*} (I : γ → HomogeneousIdeal 𝒜) :
zeroLocus _ ((⨆ i, I i : HomogeneousIdeal 𝒜) : Set A) = ⋂ i, zeroLocus 𝒜 (I i) :=
(gc_homogeneousIdeal 𝒜).l_iSup
theorem zeroLocus_iUnion {γ : Sort*} (s : γ → Set A) :
zeroLocus 𝒜 (⋃ i, s i) = ⋂ i, zeroLocus 𝒜 (s i) :=
(gc_set 𝒜).l_iSup
theorem zeroLocus_bUnion (s : Set (Set A)) :
zeroLocus 𝒜 (⋃ s' ∈ s, s' : Set A) = ⋂ s' ∈ s, zeroLocus 𝒜 s' := by
simp only [zeroLocus_iUnion]
theorem vanishingIdeal_iUnion {γ : Sort*} (t : γ → Set (ProjectiveSpectrum 𝒜)) :
vanishingIdeal (⋃ i, t i) = ⨅ i, vanishingIdeal (t i) :=
HomogeneousIdeal.toIdeal_injective <| by
convert (gc_ideal 𝒜).u_iInf; exact HomogeneousIdeal.toIdeal_iInf _
theorem zeroLocus_inf (I J : Ideal A) :
zeroLocus 𝒜 ((I ⊓ J : Ideal A) : Set A) = zeroLocus 𝒜 I ∪ zeroLocus 𝒜 J :=
Set.ext fun x => x.isPrime.inf_le
theorem union_zeroLocus (s s' : Set A) :
zeroLocus 𝒜 s ∪ zeroLocus 𝒜 s' = zeroLocus 𝒜 (Ideal.span s ⊓ Ideal.span s' : Ideal A) := by
rw [zeroLocus_inf]
simp
theorem zeroLocus_mul_ideal (I J : Ideal A) :
zeroLocus 𝒜 ((I * J : Ideal A) : Set A) = zeroLocus 𝒜 I ∪ zeroLocus 𝒜 J :=
Set.ext fun x => x.isPrime.mul_le
theorem zeroLocus_mul_homogeneousIdeal (I J : HomogeneousIdeal 𝒜) :
zeroLocus 𝒜 ((I * J : HomogeneousIdeal 𝒜) : Set A) = zeroLocus 𝒜 I ∪ zeroLocus 𝒜 J :=
Set.ext fun x => x.isPrime.mul_le
theorem zeroLocus_singleton_mul (f g : A) :
zeroLocus 𝒜 ({f * g} : Set A) = zeroLocus 𝒜 {f} ∪ zeroLocus 𝒜 {g} :=
Set.ext fun x => by simpa using x.isPrime.mul_mem_iff_mem_or_mem
@[simp]
theorem zeroLocus_singleton_pow (f : A) (n : ℕ) (hn : 0 < n) :
zeroLocus 𝒜 ({f ^ n} : Set A) = zeroLocus 𝒜 {f} :=
Set.ext fun x => by simpa using x.isPrime.pow_mem_iff_mem n hn
theorem sup_vanishingIdeal_le (t t' : Set (ProjectiveSpectrum 𝒜)) :
vanishingIdeal t ⊔ vanishingIdeal t' ≤ vanishingIdeal (t ∩ t') := by
intro r
rw [← HomogeneousIdeal.mem_iff, HomogeneousIdeal.toIdeal_sup, mem_vanishingIdeal,
Submodule.mem_sup]
rintro ⟨f, hf, g, hg, rfl⟩ x ⟨hxt, hxt'⟩
rw [HomogeneousIdeal.mem_iff, mem_vanishingIdeal] at hf hg
apply Submodule.add_mem <;> solve_by_elim
theorem mem_compl_zeroLocus_iff_not_mem {f : A} {I : ProjectiveSpectrum 𝒜} :
I ∈ (zeroLocus 𝒜 {f} : Set (ProjectiveSpectrum 𝒜))ᶜ ↔ f ∉ I.asHomogeneousIdeal := by
rw [Set.mem_compl_iff, mem_zeroLocus, Set.singleton_subset_iff]; rfl
/-- The Zariski topology on the prime spectrum of a commutative ring is defined via the closed sets
of the topology: they are exactly those sets that are the zero locus of a subset of the ring. -/
instance zariskiTopology : TopologicalSpace (ProjectiveSpectrum 𝒜) :=
TopologicalSpace.ofClosed (Set.range (ProjectiveSpectrum.zeroLocus 𝒜)) ⟨Set.univ, by simp⟩
(by
intro Zs h
rw [Set.sInter_eq_iInter]
let f : Zs → Set _ := fun i => Classical.choose (h i.2)
have H : (Set.iInter fun i ↦ zeroLocus 𝒜 (f i)) ∈ Set.range (zeroLocus 𝒜) :=
⟨_, zeroLocus_iUnion 𝒜 _⟩
convert H using 2
funext i
exact (Classical.choose_spec (h i.2)).symm)
(by
rintro _ ⟨s, rfl⟩ _ ⟨t, rfl⟩
exact ⟨_, (union_zeroLocus 𝒜 s t).symm⟩)
/-- The underlying topology of `Proj` is the projective spectrum of graded ring `A`. -/
def top : TopCat :=
TopCat.of (ProjectiveSpectrum 𝒜)
theorem isOpen_iff (U : Set (ProjectiveSpectrum 𝒜)) : IsOpen U ↔ ∃ s, Uᶜ = zeroLocus 𝒜 s := by
simp only [@eq_comm _ Uᶜ]; rfl
theorem isClosed_iff_zeroLocus (Z : Set (ProjectiveSpectrum 𝒜)) :
IsClosed Z ↔ ∃ s, Z = zeroLocus 𝒜 s := by rw [← isOpen_compl_iff, isOpen_iff, compl_compl]
theorem isClosed_zeroLocus (s : Set A) : IsClosed (zeroLocus 𝒜 s) := by
rw [isClosed_iff_zeroLocus]
exact ⟨s, rfl⟩
theorem zeroLocus_vanishingIdeal_eq_closure (t : Set (ProjectiveSpectrum 𝒜)) :
zeroLocus 𝒜 (vanishingIdeal t : Set A) = closure t := by
apply Set.Subset.antisymm
· rintro x hx t' ⟨ht', ht⟩
obtain ⟨fs, rfl⟩ : ∃ s, t' = zeroLocus 𝒜 s := by rwa [isClosed_iff_zeroLocus] at ht'
rw [subset_zeroLocus_iff_subset_vanishingIdeal] at ht
exact Set.Subset.trans ht hx
· rw [(isClosed_zeroLocus _ _).closure_subset_iff]
exact subset_zeroLocus_vanishingIdeal 𝒜 t
theorem vanishingIdeal_closure (t : Set (ProjectiveSpectrum 𝒜)) :
vanishingIdeal (closure t) = vanishingIdeal t := by
have : (vanishingIdeal (zeroLocus 𝒜 (vanishingIdeal t))).toIdeal = _ := (gc_ideal 𝒜).u_l_u_eq_u t
ext1
rw [zeroLocus_vanishingIdeal_eq_closure 𝒜 t] at this
exact this
section BasicOpen
/-- `basicOpen r` is the open subset containing all prime ideals not containing `r`. -/
def basicOpen (r : A) : TopologicalSpace.Opens (ProjectiveSpectrum 𝒜) where
carrier := { x | r ∉ x.asHomogeneousIdeal }
is_open' := ⟨{r}, Set.ext fun _ => Set.singleton_subset_iff.trans <| Classical.not_not.symm⟩
@[simp]
theorem mem_basicOpen (f : A) (x : ProjectiveSpectrum 𝒜) :
x ∈ basicOpen 𝒜 f ↔ f ∉ x.asHomogeneousIdeal :=
Iff.rfl
theorem mem_coe_basicOpen (f : A) (x : ProjectiveSpectrum 𝒜) :
x ∈ (↑(basicOpen 𝒜 f) : Set (ProjectiveSpectrum 𝒜)) ↔ f ∉ x.asHomogeneousIdeal :=
Iff.rfl
theorem isOpen_basicOpen {a : A} : IsOpen (basicOpen 𝒜 a : Set (ProjectiveSpectrum 𝒜)) :=
(basicOpen 𝒜 a).isOpen
@[simp]
theorem basicOpen_eq_zeroLocus_compl (r : A) :
(basicOpen 𝒜 r : Set (ProjectiveSpectrum 𝒜)) = (zeroLocus 𝒜 {r})ᶜ :=
| Set.ext fun x => by simp only [Set.mem_compl_iff, mem_zeroLocus, Set.singleton_subset_iff]; rfl
| Mathlib/AlgebraicGeometry/ProjectiveSpectrum/Topology.lean | 346 | 347 |
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Johan Commelin
-/
import Mathlib.Analysis.Analytic.Basic
import Mathlib.Combinatorics.Enumerative.Composition
/-!
# Composition of analytic functions
In this file we prove that the composition of analytic functions is analytic.
The argument is the following. Assume `g z = ∑' qₙ (z, ..., z)` and `f y = ∑' pₖ (y, ..., y)`. Then
`g (f y) = ∑' qₙ (∑' pₖ (y, ..., y), ..., ∑' pₖ (y, ..., y))
= ∑' qₙ (p_{i₁} (y, ..., y), ..., p_{iₙ} (y, ..., y))`.
For each `n` and `i₁, ..., iₙ`, define a `i₁ + ... + iₙ` multilinear function mapping
`(y₀, ..., y_{i₁ + ... + iₙ - 1})` to
`qₙ (p_{i₁} (y₀, ..., y_{i₁-1}), p_{i₂} (y_{i₁}, ..., y_{i₁ + i₂ - 1}), ..., p_{iₙ} (....)))`.
Then `g ∘ f` is obtained by summing all these multilinear functions.
To formalize this, we use compositions of an integer `N`, i.e., its decompositions into
a sum `i₁ + ... + iₙ` of positive integers. Given such a composition `c` and two formal
multilinear series `q` and `p`, let `q.compAlongComposition p c` be the above multilinear
function. Then the `N`-th coefficient in the power series expansion of `g ∘ f` is the sum of these
terms over all `c : Composition N`.
To complete the proof, we need to show that this power series has a positive radius of convergence.
This follows from the fact that `Composition N` has cardinality `2^(N-1)` and estimates on
the norm of `qₙ` and `pₖ`, which give summability. We also need to show that it indeed converges to
`g ∘ f`. For this, we note that the composition of partial sums converges to `g ∘ f`, and that it
corresponds to a part of the whole sum, on a subset that increases to the whole space. By
summability of the norms, this implies the overall convergence.
## Main results
* `q.comp p` is the formal composition of the formal multilinear series `q` and `p`.
* `HasFPowerSeriesAt.comp` states that if two functions `g` and `f` admit power series expansions
`q` and `p`, then `g ∘ f` admits a power series expansion given by `q.comp p`.
* `AnalyticAt.comp` states that the composition of analytic functions is analytic.
* `FormalMultilinearSeries.comp_assoc` states that composition is associative on formal
multilinear series.
## Implementation details
The main technical difficulty is to write down things. In particular, we need to define precisely
`q.compAlongComposition p c` and to show that it is indeed a continuous multilinear
function. This requires a whole interface built on the class `Composition`. Once this is set,
the main difficulty is to reorder the sums, writing the composition of the partial sums as a sum
over some subset of `Σ n, Composition n`. We need to check that the reordering is a bijection,
running over difficulties due to the dependent nature of the types under consideration, that are
controlled thanks to the interface for `Composition`.
The associativity of composition on formal multilinear series is a nontrivial result: it does not
follow from the associativity of composition of analytic functions, as there is no uniqueness for
the formal multilinear series representing a function (and also, it holds even when the radius of
convergence of the series is `0`). Instead, we give a direct proof, which amounts to reordering
double sums in a careful way. The change of variables is a canonical (combinatorial) bijection
`Composition.sigmaEquivSigmaPi` between `(Σ (a : Composition n), Composition a.length)` and
`(Σ (c : Composition n), Π (i : Fin c.length), Composition (c.blocksFun i))`, and is described
in more details below in the paragraph on associativity.
-/
noncomputable section
variable {𝕜 : Type*} {E F G H : Type*}
open Filter List
open scoped Topology NNReal ENNReal
section Topological
variable [CommRing 𝕜] [AddCommGroup E] [AddCommGroup F] [AddCommGroup G]
variable [Module 𝕜 E] [Module 𝕜 F] [Module 𝕜 G]
variable [TopologicalSpace E] [TopologicalSpace F] [TopologicalSpace G]
/-! ### Composing formal multilinear series -/
namespace FormalMultilinearSeries
variable [IsTopologicalAddGroup E] [ContinuousConstSMul 𝕜 E]
variable [IsTopologicalAddGroup F] [ContinuousConstSMul 𝕜 F]
variable [IsTopologicalAddGroup G] [ContinuousConstSMul 𝕜 G]
/-!
In this paragraph, we define the composition of formal multilinear series, by summing over all
possible compositions of `n`.
-/
/-- Given a formal multilinear series `p`, a composition `c` of `n` and the index `i` of a
block of `c`, we may define a function on `Fin n → E` by picking the variables in the `i`-th block
of `n`, and applying the corresponding coefficient of `p` to these variables. This function is
called `p.applyComposition c v i` for `v : Fin n → E` and `i : Fin c.length`. -/
def applyComposition (p : FormalMultilinearSeries 𝕜 E F) {n : ℕ} (c : Composition n) :
(Fin n → E) → Fin c.length → F := fun v i => p (c.blocksFun i) (v ∘ c.embedding i)
theorem applyComposition_ones (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
p.applyComposition (Composition.ones n) = fun v i =>
p 1 fun _ => v (Fin.castLE (Composition.length_le _) i) := by
funext v i
apply p.congr (Composition.ones_blocksFun _ _)
intro j hjn hj1
obtain rfl : j = 0 := by omega
refine congr_arg v ?_
rw [Fin.ext_iff, Fin.coe_castLE, Composition.ones_embedding, Fin.val_mk]
theorem applyComposition_single (p : FormalMultilinearSeries 𝕜 E F) {n : ℕ} (hn : 0 < n)
(v : Fin n → E) : p.applyComposition (Composition.single n hn) v = fun _j => p n v := by
ext j
refine p.congr (by simp) fun i hi1 hi2 => ?_
dsimp
congr 1
convert Composition.single_embedding hn ⟨i, hi2⟩ using 1
obtain ⟨j_val, j_property⟩ := j
have : j_val = 0 := le_bot_iff.1 (Nat.lt_succ_iff.1 j_property)
congr!
simp
@[simp]
theorem removeZero_applyComposition (p : FormalMultilinearSeries 𝕜 E F) {n : ℕ}
(c : Composition n) : p.removeZero.applyComposition c = p.applyComposition c := by
ext v i
simp [applyComposition, zero_lt_one.trans_le (c.one_le_blocksFun i), removeZero_of_pos]
/-- Technical lemma stating how `p.applyComposition` commutes with updating variables. This
will be the key point to show that functions constructed from `applyComposition` retain
multilinearity. -/
theorem applyComposition_update (p : FormalMultilinearSeries 𝕜 E F) {n : ℕ} (c : Composition n)
(j : Fin n) (v : Fin n → E) (z : E) :
p.applyComposition c (Function.update v j z) =
Function.update (p.applyComposition c v) (c.index j)
(p (c.blocksFun (c.index j))
(Function.update (v ∘ c.embedding (c.index j)) (c.invEmbedding j) z)) := by
ext k
by_cases h : k = c.index j
· rw [h]
let r : Fin (c.blocksFun (c.index j)) → Fin n := c.embedding (c.index j)
simp only [Function.update_self]
change p (c.blocksFun (c.index j)) (Function.update v j z ∘ r) = _
let j' := c.invEmbedding j
suffices B : Function.update v j z ∘ r = Function.update (v ∘ r) j' z by rw [B]
suffices C : Function.update v (r j') z ∘ r = Function.update (v ∘ r) j' z by
convert C; exact (c.embedding_comp_inv j).symm
exact Function.update_comp_eq_of_injective _ (c.embedding _).injective _ _
· simp only [h, Function.update_eq_self, Function.update_of_ne, Ne, not_false_iff]
let r : Fin (c.blocksFun k) → Fin n := c.embedding k
change p (c.blocksFun k) (Function.update v j z ∘ r) = p (c.blocksFun k) (v ∘ r)
suffices B : Function.update v j z ∘ r = v ∘ r by rw [B]
apply Function.update_comp_eq_of_not_mem_range
rwa [c.mem_range_embedding_iff']
@[simp]
theorem compContinuousLinearMap_applyComposition {n : ℕ} (p : FormalMultilinearSeries 𝕜 F G)
(f : E →L[𝕜] F) (c : Composition n) (v : Fin n → E) :
(p.compContinuousLinearMap f).applyComposition c v = p.applyComposition c (f ∘ v) := by
simp (config := {unfoldPartialApp := true}) [applyComposition]; rfl
end FormalMultilinearSeries
namespace ContinuousMultilinearMap
open FormalMultilinearSeries
variable [IsTopologicalAddGroup E] [ContinuousConstSMul 𝕜 E]
variable [IsTopologicalAddGroup F] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p`, a composition `c` of `n` and a continuous multilinear
map `f` in `c.length` variables, one may form a continuous multilinear map in `n` variables by
applying the right coefficient of `p` to each block of the composition, and then applying `f` to
the resulting vector. It is called `f.compAlongComposition p c`. -/
def compAlongComposition {n : ℕ} (p : FormalMultilinearSeries 𝕜 E F) (c : Composition n)
(f : F [×c.length]→L[𝕜] G) : E [×n]→L[𝕜] G where
toMultilinearMap :=
MultilinearMap.mk' (fun v ↦ f (p.applyComposition c v))
(fun v i x y ↦ by simp only [applyComposition_update, map_update_add])
(fun v i c x ↦ by simp only [applyComposition_update, map_update_smul])
cont :=
f.cont.comp <|
continuous_pi fun _ => (coe_continuous _).comp <| continuous_pi fun _ => continuous_apply _
@[simp]
theorem compAlongComposition_apply {n : ℕ} (p : FormalMultilinearSeries 𝕜 E F) (c : Composition n)
(f : F [×c.length]→L[𝕜] G) (v : Fin n → E) :
(f.compAlongComposition p c) v = f (p.applyComposition c v) :=
rfl
end ContinuousMultilinearMap
namespace FormalMultilinearSeries
variable [IsTopologicalAddGroup E] [ContinuousConstSMul 𝕜 E]
variable [IsTopologicalAddGroup F] [ContinuousConstSMul 𝕜 F]
variable [IsTopologicalAddGroup G] [ContinuousConstSMul 𝕜 G]
/-- Given two formal multilinear series `q` and `p` and a composition `c` of `n`, one may
form a continuous multilinear map in `n` variables by applying the right coefficient of `p` to each
block of the composition, and then applying `q c.length` to the resulting vector. It is
called `q.compAlongComposition p c`. -/
def compAlongComposition {n : ℕ} (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) (c : Composition n) : (E [×n]→L[𝕜] G) :=
(q c.length).compAlongComposition p c
@[simp]
theorem compAlongComposition_apply {n : ℕ} (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) (c : Composition n) (v : Fin n → E) :
(q.compAlongComposition p c) v = q c.length (p.applyComposition c v) :=
rfl
/-- Formal composition of two formal multilinear series. The `n`-th coefficient in the composition
is defined to be the sum of `q.compAlongComposition p c` over all compositions of
`n`. In other words, this term (as a multilinear function applied to `v_0, ..., v_{n-1}`) is
`∑'_{k} ∑'_{i₁ + ... + iₖ = n} qₖ (p_{i_1} (...), ..., p_{i_k} (...))`, where one puts all variables
`v_0, ..., v_{n-1}` in increasing order in the dots.
In general, the composition `q ∘ p` only makes sense when the constant coefficient of `p` vanishes.
We give a general formula but which ignores the value of `p 0` instead.
-/
protected def comp (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F) :
FormalMultilinearSeries 𝕜 E G := fun n => ∑ c : Composition n, q.compAlongComposition p c
/-- The `0`-th coefficient of `q.comp p` is `q 0`. Since these maps are multilinear maps in zero
variables, but on different spaces, we can not state this directly, so we state it when applied to
arbitrary vectors (which have to be the zero vector). -/
theorem comp_coeff_zero (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F)
(v : Fin 0 → E) (v' : Fin 0 → F) : (q.comp p) 0 v = q 0 v' := by
let c : Composition 0 := Composition.ones 0
dsimp [FormalMultilinearSeries.comp]
have : {c} = (Finset.univ : Finset (Composition 0)) := by
apply Finset.eq_of_subset_of_card_le <;> simp [Finset.card_univ, composition_card 0]
rw [← this, Finset.sum_singleton, compAlongComposition_apply]
symm; congr! -- Porting note: needed the stronger `congr!`!
@[simp]
theorem comp_coeff_zero' (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F)
(v : Fin 0 → E) : (q.comp p) 0 v = q 0 fun _i => 0 :=
q.comp_coeff_zero p v _
/-- The `0`-th coefficient of `q.comp p` is `q 0`. When `p` goes from `E` to `E`, this can be
expressed as a direct equality -/
theorem comp_coeff_zero'' (q : FormalMultilinearSeries 𝕜 E F) (p : FormalMultilinearSeries 𝕜 E E) :
(q.comp p) 0 = q 0 := by ext v; exact q.comp_coeff_zero p _ _
/-- The first coefficient of a composition of formal multilinear series is the composition of the
first coefficients seen as continuous linear maps. -/
theorem comp_coeff_one (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F)
(v : Fin 1 → E) : (q.comp p) 1 v = q 1 fun _i => p 1 v := by
have : {Composition.ones 1} = (Finset.univ : Finset (Composition 1)) :=
Finset.eq_univ_of_card _ (by simp [composition_card])
simp only [FormalMultilinearSeries.comp, compAlongComposition_apply, ← this,
Finset.sum_singleton]
refine q.congr (by simp) fun i hi1 hi2 => ?_
simp only [applyComposition_ones]
exact p.congr rfl fun j _hj1 hj2 => by congr! -- Porting note: needed the stronger `congr!`
/-- Only `0`-th coefficient of `q.comp p` depends on `q 0`. -/
theorem removeZero_comp_of_pos (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) {n : ℕ} (hn : 0 < n) :
q.removeZero.comp p n = q.comp p n := by
ext v
simp only [FormalMultilinearSeries.comp, compAlongComposition,
ContinuousMultilinearMap.compAlongComposition_apply, ContinuousMultilinearMap.sum_apply]
refine Finset.sum_congr rfl fun c _hc => ?_
rw [removeZero_of_pos _ (c.length_pos_of_pos hn)]
@[simp]
theorem comp_removeZero (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F) :
q.comp p.removeZero = q.comp p := by ext n; simp [FormalMultilinearSeries.comp]
end FormalMultilinearSeries
end Topological
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G] [NormedAddCommGroup H]
[NormedSpace 𝕜 H]
namespace FormalMultilinearSeries
/-- The norm of `f.compAlongComposition p c` is controlled by the product of
the norms of the relevant bits of `f` and `p`. -/
theorem compAlongComposition_bound {n : ℕ} (p : FormalMultilinearSeries 𝕜 E F) (c : Composition n)
(f : F [×c.length]→L[𝕜] G) (v : Fin n → E) :
‖f.compAlongComposition p c v‖ ≤ (‖f‖ * ∏ i, ‖p (c.blocksFun i)‖) * ∏ i : Fin n, ‖v i‖ :=
calc
‖f.compAlongComposition p c v‖ = ‖f (p.applyComposition c v)‖ := rfl
_ ≤ ‖f‖ * ∏ i, ‖p.applyComposition c v i‖ := ContinuousMultilinearMap.le_opNorm _ _
_ ≤ ‖f‖ * ∏ i, ‖p (c.blocksFun i)‖ * ∏ j : Fin (c.blocksFun i), ‖(v ∘ c.embedding i) j‖ := by
apply mul_le_mul_of_nonneg_left _ (norm_nonneg _)
refine Finset.prod_le_prod (fun i _hi => norm_nonneg _) fun i _hi => ?_
apply ContinuousMultilinearMap.le_opNorm
_ = (‖f‖ * ∏ i, ‖p (c.blocksFun i)‖) *
∏ i, ∏ j : Fin (c.blocksFun i), ‖(v ∘ c.embedding i) j‖ := by
rw [Finset.prod_mul_distrib, mul_assoc]
_ = (‖f‖ * ∏ i, ‖p (c.blocksFun i)‖) * ∏ i : Fin n, ‖v i‖ := by
rw [← c.blocksFinEquiv.prod_comp, ← Finset.univ_sigma_univ, Finset.prod_sigma]
congr
/-- The norm of `q.compAlongComposition p c` is controlled by the product of
the norms of the relevant bits of `q` and `p`. -/
theorem compAlongComposition_norm {n : ℕ} (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) (c : Composition n) :
‖q.compAlongComposition p c‖ ≤ ‖q c.length‖ * ∏ i, ‖p (c.blocksFun i)‖ :=
ContinuousMultilinearMap.opNorm_le_bound (by positivity) (compAlongComposition_bound _ _ _)
theorem compAlongComposition_nnnorm {n : ℕ} (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) (c : Composition n) :
‖q.compAlongComposition p c‖₊ ≤ ‖q c.length‖₊ * ∏ i, ‖p (c.blocksFun i)‖₊ := by
rw [← NNReal.coe_le_coe]; push_cast; exact q.compAlongComposition_norm p c
/-!
### The identity formal power series
We will now define the identity power series, and show that it is a neutral element for left and
right composition.
-/
section
variable (𝕜 E)
/-- The identity formal multilinear series, with all coefficients equal to `0` except for `n = 1`
where it is (the continuous multilinear version of) the identity. We allow an arbitrary
constant coefficient `x`. -/
def id (x : E) : FormalMultilinearSeries 𝕜 E E
| 0 => ContinuousMultilinearMap.uncurry0 𝕜 _ x
| 1 => (continuousMultilinearCurryFin1 𝕜 E E).symm (ContinuousLinearMap.id 𝕜 E)
| _ => 0
@[simp] theorem id_apply_zero (x : E) (v : Fin 0 → E) :
(FormalMultilinearSeries.id 𝕜 E x) 0 v = x := rfl
/-- The first coefficient of `id 𝕜 E` is the identity. -/
@[simp]
theorem id_apply_one (x : E) (v : Fin 1 → E) : (FormalMultilinearSeries.id 𝕜 E x) 1 v = v 0 :=
rfl
/-- The `n`th coefficient of `id 𝕜 E` is the identity when `n = 1`. We state this in a dependent
way, as it will often appear in this form. -/
theorem id_apply_one' (x : E) {n : ℕ} (h : n = 1) (v : Fin n → E) :
(id 𝕜 E x) n v = v ⟨0, h.symm ▸ zero_lt_one⟩ := by
subst n
apply id_apply_one
/-- For `n ≠ 1`, the `n`-th coefficient of `id 𝕜 E` is zero, by definition. -/
@[simp]
theorem id_apply_of_one_lt (x : E) {n : ℕ} (h : 1 < n) :
(FormalMultilinearSeries.id 𝕜 E x) n = 0 := by
match n with
| 0 => contradiction
| 1 => contradiction
| n + 2 => rfl
end
@[simp]
theorem comp_id (p : FormalMultilinearSeries 𝕜 E F) (x : E) : p.comp (id 𝕜 E x) = p := by
ext1 n
dsimp [FormalMultilinearSeries.comp]
rw [Finset.sum_eq_single (Composition.ones n)]
· show compAlongComposition p (id 𝕜 E x) (Composition.ones n) = p n
ext v
rw [compAlongComposition_apply]
apply p.congr (Composition.ones_length n)
intros
rw [applyComposition_ones]
refine congr_arg v ?_
rw [Fin.ext_iff, Fin.coe_castLE, Fin.val_mk]
· show
∀ b : Composition n,
b ∈ Finset.univ → b ≠ Composition.ones n → compAlongComposition p (id 𝕜 E x) b = 0
intro b _ hb
obtain ⟨k, hk, lt_k⟩ : ∃ (k : ℕ), k ∈ Composition.blocks b ∧ 1 < k :=
Composition.ne_ones_iff.1 hb
obtain ⟨i, hi⟩ : ∃ (i : Fin b.blocks.length), b.blocks[i] = k :=
List.get_of_mem hk
let j : Fin b.length := ⟨i.val, b.blocks_length ▸ i.prop⟩
have A : 1 < b.blocksFun j := by convert lt_k
ext v
rw [compAlongComposition_apply, ContinuousMultilinearMap.zero_apply]
apply ContinuousMultilinearMap.map_coord_zero _ j
dsimp [applyComposition]
rw [id_apply_of_one_lt _ _ _ A, ContinuousMultilinearMap.zero_apply]
· simp
@[simp]
theorem id_comp (p : FormalMultilinearSeries 𝕜 E F) (v0 : Fin 0 → E) :
(id 𝕜 F (p 0 v0)).comp p = p := by
ext1 n
obtain rfl | n_pos := n.eq_zero_or_pos
· ext v
simp only [comp_coeff_zero', id_apply_zero]
congr with i
exact i.elim0
· dsimp [FormalMultilinearSeries.comp]
rw [Finset.sum_eq_single (Composition.single n n_pos)]
· show compAlongComposition (id 𝕜 F (p 0 v0)) p (Composition.single n n_pos) = p n
ext v
rw [compAlongComposition_apply, id_apply_one' _ _ _ (Composition.single_length n_pos)]
dsimp [applyComposition]
refine p.congr rfl fun i him hin => congr_arg v <| ?_
ext; simp
· show
∀ b : Composition n, b ∈ Finset.univ → b ≠ Composition.single n n_pos →
compAlongComposition (id 𝕜 F (p 0 v0)) p b = 0
intro b _ hb
have A : 1 < b.length := by
have : b.length ≠ 1 := by simpa [Composition.eq_single_iff_length] using hb
have : 0 < b.length := Composition.length_pos_of_pos b n_pos
omega
ext v
rw [compAlongComposition_apply, id_apply_of_one_lt _ _ _ A,
ContinuousMultilinearMap.zero_apply, ContinuousMultilinearMap.zero_apply]
· simp
/-- Variant of `id_comp` in which the zero coefficient is given by an equality hypothesis instead
of a definitional equality. Useful for rewriting or simplifying out in some situations. -/
theorem id_comp' (p : FormalMultilinearSeries 𝕜 E F) (x : F) (v0 : Fin 0 → E) (h : x = p 0 v0) :
(id 𝕜 F x).comp p = p := by
simp [h]
/-! ### Summability properties of the composition of formal power series -/
section
/-- If two formal multilinear series have positive radius of convergence, then the terms appearing
in the definition of their composition are also summable (when multiplied by a suitable positive
geometric term). -/
theorem comp_summable_nnreal (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F)
(hq : 0 < q.radius) (hp : 0 < p.radius) :
∃ r > (0 : ℝ≥0),
Summable fun i : Σ n, Composition n => ‖q.compAlongComposition p i.2‖₊ * r ^ i.1 := by
/- This follows from the fact that the growth rate of `‖qₙ‖` and `‖pₙ‖` is at most geometric,
giving a geometric bound on each `‖q.compAlongComposition p op‖`, together with the
fact that there are `2^(n-1)` compositions of `n`, giving at most a geometric loss. -/
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 (lt_min zero_lt_one hq) with ⟨rq, rq_pos, hrq⟩
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 (lt_min zero_lt_one hp) with ⟨rp, rp_pos, hrp⟩
simp only [lt_min_iff, ENNReal.coe_lt_one_iff, ENNReal.coe_pos] at hrp hrq rp_pos rq_pos
obtain ⟨Cq, _hCq0, hCq⟩ : ∃ Cq > 0, ∀ n, ‖q n‖₊ * rq ^ n ≤ Cq :=
q.nnnorm_mul_pow_le_of_lt_radius hrq.2
obtain ⟨Cp, hCp1, hCp⟩ : ∃ Cp ≥ 1, ∀ n, ‖p n‖₊ * rp ^ n ≤ Cp := by
rcases p.nnnorm_mul_pow_le_of_lt_radius hrp.2 with ⟨Cp, -, hCp⟩
exact ⟨max Cp 1, le_max_right _ _, fun n => (hCp n).trans (le_max_left _ _)⟩
let r0 : ℝ≥0 := (4 * Cp)⁻¹
have r0_pos : 0 < r0 := inv_pos.2 (mul_pos zero_lt_four (zero_lt_one.trans_le hCp1))
set r : ℝ≥0 := rp * rq * r0
have r_pos : 0 < r := mul_pos (mul_pos rp_pos rq_pos) r0_pos
have I :
∀ i : Σ n : ℕ, Composition n, ‖q.compAlongComposition p i.2‖₊ * r ^ i.1 ≤ Cq / 4 ^ i.1 := by
rintro ⟨n, c⟩
have A := calc
‖q c.length‖₊ * rq ^ n ≤ ‖q c.length‖₊ * rq ^ c.length :=
mul_le_mul' le_rfl (pow_le_pow_of_le_one rq.2 hrq.1.le c.length_le)
_ ≤ Cq := hCq _
have B := calc
(∏ i, ‖p (c.blocksFun i)‖₊) * rp ^ n = ∏ i, ‖p (c.blocksFun i)‖₊ * rp ^ c.blocksFun i := by
simp only [Finset.prod_mul_distrib, Finset.prod_pow_eq_pow_sum, c.sum_blocksFun]
_ ≤ ∏ _i : Fin c.length, Cp := Finset.prod_le_prod' fun i _ => hCp _
_ = Cp ^ c.length := by simp
_ ≤ Cp ^ n := pow_right_mono₀ hCp1 c.length_le
calc
‖q.compAlongComposition p c‖₊ * r ^ n ≤
(‖q c.length‖₊ * ∏ i, ‖p (c.blocksFun i)‖₊) * r ^ n :=
mul_le_mul' (q.compAlongComposition_nnnorm p c) le_rfl
_ = ‖q c.length‖₊ * rq ^ n * ((∏ i, ‖p (c.blocksFun i)‖₊) * rp ^ n) * r0 ^ n := by
ring
_ ≤ Cq * Cp ^ n * r0 ^ n := mul_le_mul' (mul_le_mul' A B) le_rfl
_ = Cq / 4 ^ n := by
simp only [r0]
field_simp [mul_pow, (zero_lt_one.trans_le hCp1).ne']
ring
refine ⟨r, r_pos, NNReal.summable_of_le I ?_⟩
simp_rw [div_eq_mul_inv]
refine Summable.mul_left _ ?_
have : ∀ n : ℕ, HasSum (fun c : Composition n => (4 ^ n : ℝ≥0)⁻¹) (2 ^ (n - 1) / 4 ^ n) := by
intro n
convert hasSum_fintype fun c : Composition n => (4 ^ n : ℝ≥0)⁻¹
simp [Finset.card_univ, composition_card, div_eq_mul_inv]
refine NNReal.summable_sigma.2 ⟨fun n => (this n).summable, (NNReal.summable_nat_add_iff 1).1 ?_⟩
convert (NNReal.summable_geometric (NNReal.div_lt_one_of_lt one_lt_two)).mul_left (1 / 4) using 1
ext1 n
rw [(this _).tsum_eq, add_tsub_cancel_right]
field_simp [← mul_assoc, pow_succ, mul_pow, show (4 : ℝ≥0) = 2 * 2 by norm_num,
mul_right_comm]
end
/-- Bounding below the radius of the composition of two formal multilinear series assuming
summability over all compositions. -/
theorem le_comp_radius_of_summable (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) (r : ℝ≥0)
(hr : Summable fun i : Σ n, Composition n => ‖q.compAlongComposition p i.2‖₊ * r ^ i.1) :
(r : ℝ≥0∞) ≤ (q.comp p).radius := by
refine
le_radius_of_bound_nnreal _
(∑' i : Σ n, Composition n, ‖compAlongComposition q p i.snd‖₊ * r ^ i.fst) fun n => ?_
calc
‖FormalMultilinearSeries.comp q p n‖₊ * r ^ n ≤
∑' c : Composition n, ‖compAlongComposition q p c‖₊ * r ^ n := by
rw [tsum_fintype, ← Finset.sum_mul]
exact mul_le_mul' (nnnorm_sum_le _ _) le_rfl
_ ≤ ∑' i : Σ n : ℕ, Composition n, ‖compAlongComposition q p i.snd‖₊ * r ^ i.fst :=
NNReal.tsum_comp_le_tsum_of_inj hr sigma_mk_injective
/-!
### Composing analytic functions
Now, we will prove that the composition of the partial sums of `q` and `p` up to order `N` is
given by a sum over some large subset of `Σ n, Composition n` of `q.compAlongComposition p`, to
deduce that the series for `q.comp p` indeed converges to `g ∘ f` when `q` is a power series for
`g` and `p` is a power series for `f`.
This proof is a big reindexing argument of a sum. Since it is a bit involved, we define first
the source of the change of variables (`compPartialSumSource`), its target
(`compPartialSumTarget`) and the change of variables itself (`compChangeOfVariables`) before
giving the main statement in `comp_partialSum`. -/
/-- Source set in the change of variables to compute the composition of partial sums of formal
power series.
See also `comp_partialSum`. -/
def compPartialSumSource (m M N : ℕ) : Finset (Σ n, Fin n → ℕ) :=
Finset.sigma (Finset.Ico m M) (fun n : ℕ => Fintype.piFinset fun _i : Fin n => Finset.Ico 1 N :)
@[simp]
theorem mem_compPartialSumSource_iff (m M N : ℕ) (i : Σ n, Fin n → ℕ) :
i ∈ compPartialSumSource m M N ↔
(m ≤ i.1 ∧ i.1 < M) ∧ ∀ a : Fin i.1, 1 ≤ i.2 a ∧ i.2 a < N := by
simp only [compPartialSumSource, Finset.mem_Ico, Fintype.mem_piFinset, Finset.mem_sigma]
/-- Change of variables appearing to compute the composition of partial sums of formal
power series -/
def compChangeOfVariables (m M N : ℕ) (i : Σ n, Fin n → ℕ) (hi : i ∈ compPartialSumSource m M N) :
Σ n, Composition n := by
rcases i with ⟨n, f⟩
rw [mem_compPartialSumSource_iff] at hi
refine ⟨∑ j, f j, ofFn fun a => f a, fun {i} hi' => ?_, by simp [sum_ofFn]⟩
obtain ⟨j, rfl⟩ : ∃ j : Fin n, f j = i := by rwa [mem_ofFn', Set.mem_range] at hi'
exact (hi.2 j).1
@[simp]
theorem compChangeOfVariables_length (m M N : ℕ) {i : Σ n, Fin n → ℕ}
(hi : i ∈ compPartialSumSource m M N) :
Composition.length (compChangeOfVariables m M N i hi).2 = i.1 := by
rcases i with ⟨k, blocks_fun⟩
dsimp [compChangeOfVariables]
simp only [Composition.length, map_ofFn, length_ofFn]
theorem compChangeOfVariables_blocksFun (m M N : ℕ) {i : Σ n, Fin n → ℕ}
(hi : i ∈ compPartialSumSource m M N) (j : Fin i.1) :
(compChangeOfVariables m M N i hi).2.blocksFun
⟨j, (compChangeOfVariables_length m M N hi).symm ▸ j.2⟩ =
i.2 j := by
rcases i with ⟨n, f⟩
dsimp [Composition.blocksFun, Composition.blocks, compChangeOfVariables]
simp only [map_ofFn, List.getElem_ofFn, Function.comp_apply]
/-- Target set in the change of variables to compute the composition of partial sums of formal
power series, here given a a set. -/
def compPartialSumTargetSet (m M N : ℕ) : Set (Σ n, Composition n) :=
{i | m ≤ i.2.length ∧ i.2.length < M ∧ ∀ j : Fin i.2.length, i.2.blocksFun j < N}
theorem compPartialSumTargetSet_image_compPartialSumSource (m M N : ℕ)
(i : Σ n, Composition n) (hi : i ∈ compPartialSumTargetSet m M N) :
∃ (j : _) (hj : j ∈ compPartialSumSource m M N), compChangeOfVariables m M N j hj = i := by
rcases i with ⟨n, c⟩
refine ⟨⟨c.length, c.blocksFun⟩, ?_, ?_⟩
· simp only [compPartialSumTargetSet, Set.mem_setOf_eq] at hi
simp only [mem_compPartialSumSource_iff, hi.left, hi.right, true_and, and_true]
exact fun a => c.one_le_blocks' _
· dsimp [compChangeOfVariables]
rw [Composition.sigma_eq_iff_blocks_eq]
simp only [Composition.blocksFun, Composition.blocks, Subtype.coe_eta]
conv_rhs => rw [← List.ofFn_get c.blocks]
/-- Target set in the change of variables to compute the composition of partial sums of formal
power series, here given a a finset.
See also `comp_partialSum`. -/
def compPartialSumTarget (m M N : ℕ) : Finset (Σ n, Composition n) :=
Set.Finite.toFinset <|
((Finset.finite_toSet _).dependent_image _).subset <|
compPartialSumTargetSet_image_compPartialSumSource m M N
@[simp]
theorem mem_compPartialSumTarget_iff {m M N : ℕ} {a : Σ n, Composition n} :
a ∈ compPartialSumTarget m M N ↔
m ≤ a.2.length ∧ a.2.length < M ∧ ∀ j : Fin a.2.length, a.2.blocksFun j < N := by
simp [compPartialSumTarget, compPartialSumTargetSet]
/-- `compChangeOfVariables m M N` is a bijection between `compPartialSumSource m M N`
and `compPartialSumTarget m M N`, yielding equal sums for functions that correspond to each
other under the bijection. As `compChangeOfVariables m M N` is a dependent function, stating
that it is a bijection is not directly possible, but the consequence on sums can be stated
more easily. -/
theorem compChangeOfVariables_sum {α : Type*} [AddCommMonoid α] (m M N : ℕ)
(f : (Σ n : ℕ, Fin n → ℕ) → α) (g : (Σ n, Composition n) → α)
(h : ∀ (e) (he : e ∈ compPartialSumSource m M N), f e = g (compChangeOfVariables m M N e he)) :
∑ e ∈ compPartialSumSource m M N, f e = ∑ e ∈ compPartialSumTarget m M N, g e := by
apply Finset.sum_bij (compChangeOfVariables m M N)
-- We should show that the correspondence we have set up is indeed a bijection
-- between the index sets of the two sums.
-- 1 - show that the image belongs to `compPartialSumTarget m N N`
· rintro ⟨k, blocks_fun⟩ H
rw [mem_compPartialSumSource_iff] at H
simp only [mem_compPartialSumTarget_iff, Composition.length, Composition.blocks, H.left,
map_ofFn, length_ofFn, true_and, compChangeOfVariables]
intro j
simp only [Composition.blocksFun, (H.right _).right, List.get_ofFn]
-- 2 - show that the map is injective
· rintro ⟨k, blocks_fun⟩ H ⟨k', blocks_fun'⟩ H' heq
obtain rfl : k = k' := by
have := (compChangeOfVariables_length m M N H).symm
rwa [heq, compChangeOfVariables_length] at this
congr
funext i
calc
blocks_fun i = (compChangeOfVariables m M N _ H).2.blocksFun _ :=
(compChangeOfVariables_blocksFun m M N H i).symm
_ = (compChangeOfVariables m M N _ H').2.blocksFun _ := by
apply Composition.blocksFun_congr <;>
first | rw [heq] | rfl
_ = blocks_fun' i := compChangeOfVariables_blocksFun m M N H' i
-- 3 - show that the map is surjective
· intro i hi
apply compPartialSumTargetSet_image_compPartialSumSource m M N i
simpa [compPartialSumTarget] using hi
-- 4 - show that the composition gives the `compAlongComposition` application
· rintro ⟨k, blocks_fun⟩ H
rw [h]
/-- The auxiliary set corresponding to the composition of partial sums asymptotically contains
all possible compositions. -/
theorem compPartialSumTarget_tendsto_prod_atTop :
Tendsto (fun (p : ℕ × ℕ) => compPartialSumTarget 0 p.1 p.2) atTop atTop := by
apply Monotone.tendsto_atTop_finset
· intro m n hmn a ha
have : ∀ i, i < m.1 → i < n.1 := fun i hi => lt_of_lt_of_le hi hmn.1
have : ∀ i, i < m.2 → i < n.2 := fun i hi => lt_of_lt_of_le hi hmn.2
aesop
· rintro ⟨n, c⟩
simp only [mem_compPartialSumTarget_iff]
obtain ⟨n, hn⟩ : BddAbove ((Finset.univ.image fun i : Fin c.length => c.blocksFun i) : Set ℕ) :=
Finset.bddAbove _
refine
⟨max n c.length + 1, bot_le, lt_of_le_of_lt (le_max_right n c.length) (lt_add_one _), fun j =>
lt_of_le_of_lt (le_trans ?_ (le_max_left _ _)) (lt_add_one _)⟩
apply hn
simp only [Finset.mem_image_of_mem, Finset.mem_coe, Finset.mem_univ]
/-- The auxiliary set corresponding to the composition of partial sums asymptotically contains
all possible compositions. -/
theorem compPartialSumTarget_tendsto_atTop :
Tendsto (fun N => compPartialSumTarget 0 N N) atTop atTop := by
apply Tendsto.comp compPartialSumTarget_tendsto_prod_atTop tendsto_atTop_diagonal
/-- Composing the partial sums of two multilinear series coincides with the sum over all
compositions in `compPartialSumTarget 0 N N`. This is precisely the motivation for the
definition of `compPartialSumTarget`. -/
theorem comp_partialSum (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F)
(M N : ℕ) (z : E) :
q.partialSum M (∑ i ∈ Finset.Ico 1 N, p i fun _j => z) =
∑ i ∈ compPartialSumTarget 0 M N, q.compAlongComposition p i.2 fun _j => z := by
-- we expand the composition, using the multilinearity of `q` to expand along each coordinate.
suffices H :
(∑ n ∈ Finset.range M,
∑ r ∈ Fintype.piFinset fun i : Fin n => Finset.Ico 1 N,
q n fun i : Fin n => p (r i) fun _j => z) =
∑ i ∈ compPartialSumTarget 0 M N, q.compAlongComposition p i.2 fun _j => z by
simpa only [FormalMultilinearSeries.partialSum, ContinuousMultilinearMap.map_sum_finset] using H
-- rewrite the first sum as a big sum over a sigma type, in the finset
-- `compPartialSumTarget 0 N N`
rw [Finset.range_eq_Ico, Finset.sum_sigma']
-- use `compChangeOfVariables_sum`, saying that this change of variables respects sums
apply compChangeOfVariables_sum 0 M N
rintro ⟨k, blocks_fun⟩ H
apply congr _ (compChangeOfVariables_length 0 M N H).symm
intros
rw [← compChangeOfVariables_blocksFun 0 M N H, applyComposition, Function.comp_def]
end FormalMultilinearSeries
open FormalMultilinearSeries
/-- If two functions `g` and `f` have power series `q` and `p` respectively at `f x` and `x`, within
two sets `s` and `t` such that `f` maps `s` to `t`, then `g ∘ f` admits the power
series `q.comp p` at `x` within `s`. -/
theorem HasFPowerSeriesWithinAt.comp {g : F → G} {f : E → F} {q : FormalMultilinearSeries 𝕜 F G}
{p : FormalMultilinearSeries 𝕜 E F} {x : E} {t : Set F} {s : Set E}
(hg : HasFPowerSeriesWithinAt g q t (f x)) (hf : HasFPowerSeriesWithinAt f p s x)
(hs : Set.MapsTo f s t) : HasFPowerSeriesWithinAt (g ∘ f) (q.comp p) s x := by
/- Consider `rf` and `rg` such that `f` and `g` have power series expansion on the disks
of radius `rf` and `rg`. -/
rcases hg with ⟨rg, Hg⟩
rcases hf with ⟨rf, Hf⟩
-- The terms defining `q.comp p` are geometrically summable in a disk of some radius `r`.
rcases q.comp_summable_nnreal p Hg.radius_pos Hf.radius_pos with ⟨r, r_pos : 0 < r, hr⟩
/- We will consider `y` which is smaller than `r` and `rf`, and also small enough that
`f (x + y)` is close enough to `f x` to be in the disk where `g` is well behaved. Let
`min (r, rf, δ)` be this new radius. -/
obtain ⟨δ, δpos, hδ⟩ :
∃ δ : ℝ≥0∞, 0 < δ ∧ ∀ {z : E}, z ∈ insert x s ∩ EMetric.ball x δ
→ f z ∈ insert (f x) t ∩ EMetric.ball (f x) rg := by
have : insert (f x) t ∩ EMetric.ball (f x) rg ∈ 𝓝[insert (f x) t] (f x) := by
apply inter_mem_nhdsWithin
exact EMetric.ball_mem_nhds _ Hg.r_pos
have := Hf.analyticWithinAt.continuousWithinAt_insert.tendsto_nhdsWithin (hs.insert x) this
rcases EMetric.mem_nhdsWithin_iff.1 this with ⟨δ, δpos, Hδ⟩
exact ⟨δ, δpos, fun {z} hz => Hδ (by rwa [Set.inter_comm])⟩
let rf' := min rf δ
have min_pos : 0 < min rf' r := by
simp only [rf', r_pos, Hf.r_pos, δpos, lt_min_iff, ENNReal.coe_pos, and_self_iff]
/- We will show that `g ∘ f` admits the power series `q.comp p` in the disk of
radius `min (r, rf', δ)`. -/
refine ⟨min rf' r, ?_⟩
refine
⟨le_trans (min_le_right rf' r) (FormalMultilinearSeries.le_comp_radius_of_summable q p r hr),
min_pos, fun {y} h'y hy ↦ ?_⟩
/- Let `y` satisfy `‖y‖ < min (r, rf', δ)`. We want to show that `g (f (x + y))` is the sum of
`q.comp p` applied to `y`. -/
| -- First, check that `y` is small enough so that estimates for `f` and `g` apply.
have y_mem : y ∈ EMetric.ball (0 : E) rf :=
(EMetric.ball_subset_ball (le_trans (min_le_left _ _) (min_le_left _ _))) hy
have fy_mem : f (x + y) ∈ insert (f x) t ∩ EMetric.ball (f x) rg := by
apply hδ
have : y ∈ EMetric.ball (0 : E) δ :=
(EMetric.ball_subset_ball (le_trans (min_le_left _ _) (min_le_right _ _))) hy
simpa [-Set.mem_insert_iff, edist_eq_enorm_sub, h'y]
/- Now the proof starts. To show that the sum of `q.comp p` at `y` is `g (f (x + y))`,
we will write `q.comp p` applied to `y` as a big sum over all compositions.
Since the sum is summable, to get its convergence it suffices to get
the convergence along some increasing sequence of sets.
We will use the sequence of sets `compPartialSumTarget 0 n n`,
along which the sum is exactly the composition of the partial sums of `q` and `p`, by design.
To show that it converges to `g (f (x + y))`, pointwise convergence would not be enough,
but we have uniform convergence to save the day. -/
-- First step: the partial sum of `p` converges to `f (x + y)`.
have A : Tendsto (fun n ↦ (n, ∑ a ∈ Finset.Ico 1 n, p a fun _ ↦ y))
atTop (atTop ×ˢ 𝓝 (f (x + y) - f x)) := by
apply Tendsto.prodMk tendsto_id
have L : ∀ᶠ n in atTop, (∑ a ∈ Finset.range n, p a fun _b ↦ y) - f x
= ∑ a ∈ Finset.Ico 1 n, p a fun _b ↦ y := by
rw [eventually_atTop]
refine ⟨1, fun n hn => ?_⟩
symm
rw [eq_sub_iff_add_eq', Finset.range_eq_Ico, ← Hf.coeff_zero fun _i => y,
Finset.sum_eq_sum_Ico_succ_bot hn]
have :
Tendsto (fun n => (∑ a ∈ Finset.range n, p a fun _b => y) - f x) atTop
(𝓝 (f (x + y) - f x)) :=
(Hf.hasSum h'y y_mem).tendsto_sum_nat.sub tendsto_const_nhds
exact Tendsto.congr' L this
-- Second step: the composition of the partial sums of `q` and `p` converges to `g (f (x + y))`.
have B : Tendsto (fun n => q.partialSum n (∑ a ∈ Finset.Ico 1 n, p a fun _b ↦ y)) atTop
(𝓝 (g (f (x + y)))) := by
-- we use the fact that the partial sums of `q` converge to `g (f (x + y))`, uniformly on a
-- neighborhood of `f (x + y)`.
have : Tendsto (fun (z : ℕ × F) ↦ q.partialSum z.1 z.2)
(atTop ×ˢ 𝓝 (f (x + y) - f x)) (𝓝 (g (f x + (f (x + y) - f x)))) := by
apply Hg.tendsto_partialSum_prod (y := f (x + y) - f x)
· simpa [edist_eq_enorm_sub] using fy_mem.2
· simpa using fy_mem.1
simpa using this.comp A
-- Third step: the sum over all compositions in `compPartialSumTarget 0 n n` converges to
-- `g (f (x + y))`. As this sum is exactly the composition of the partial sum, this is a direct
-- consequence of the second step
have C :
Tendsto
(fun n => ∑ i ∈ compPartialSumTarget 0 n n, q.compAlongComposition p i.2 fun _j => y)
atTop (𝓝 (g (f (x + y)))) := by
simpa [comp_partialSum] using B
-- Fourth step: the sum over all compositions is `g (f (x + y))`. This follows from the
-- convergence along a subsequence proved in the third step, and the fact that the sum is Cauchy
-- thanks to the summability properties.
have D :
HasSum (fun i : Σ n, Composition n => q.compAlongComposition p i.2 fun _j => y)
(g (f (x + y))) :=
haveI cau :
CauchySeq fun s : Finset (Σ n, Composition n) =>
∑ i ∈ s, q.compAlongComposition p i.2 fun _j => y := by
apply cauchySeq_finset_of_norm_bounded _ (NNReal.summable_coe.2 hr) _
simp only [coe_nnnorm, NNReal.coe_mul, NNReal.coe_pow]
rintro ⟨n, c⟩
calc
‖(compAlongComposition q p c) fun _j : Fin n => y‖ ≤
‖compAlongComposition q p c‖ * ∏ _j : Fin n, ‖y‖ := by
apply ContinuousMultilinearMap.le_opNorm
_ ≤ ‖compAlongComposition q p c‖ * (r : ℝ) ^ n := by
rw [Finset.prod_const, Finset.card_fin]
gcongr
rw [EMetric.mem_ball, edist_zero_eq_enorm] at hy
have := le_trans (le_of_lt hy) (min_le_right _ _)
rwa [enorm_le_coe, ← NNReal.coe_le_coe, coe_nnnorm] at this
tendsto_nhds_of_cauchySeq_of_subseq cau compPartialSumTarget_tendsto_atTop C
-- Fifth step: the sum over `n` of `q.comp p n` can be expressed as a particular resummation of
-- the sum over all compositions, by grouping together the compositions of the same
-- integer `n`. The convergence of the whole sum therefore implies the converence of the sum
-- of `q.comp p n`
have E : HasSum (fun n => (q.comp p) n fun _j => y) (g (f (x + y))) := by
apply D.sigma
intro n
simp only [compAlongComposition_apply, FormalMultilinearSeries.comp,
ContinuousMultilinearMap.sum_apply]
exact hasSum_fintype _
rw [Function.comp_apply]
exact E
/-- If two functions `g` and `f` have power series `q` and `p` respectively at `f x` and `x`,
then `g ∘ f` admits the power series `q.comp p` at `x` within `s`. -/
theorem HasFPowerSeriesAt.comp {g : F → G} {f : E → F} {q : FormalMultilinearSeries 𝕜 F G}
{p : FormalMultilinearSeries 𝕜 E F} {x : E}
(hg : HasFPowerSeriesAt g q (f x)) (hf : HasFPowerSeriesAt f p x) :
HasFPowerSeriesAt (g ∘ f) (q.comp p) x := by
rw [← hasFPowerSeriesWithinAt_univ] at hf hg ⊢
apply hg.comp hf (by simp)
/-- If two functions `g` and `f` are analytic respectively at `f x` and `x`, within
two sets `s` and `t` such that `f` maps `s` to `t`, then `g ∘ f` is analytic at `x` within `s`. -/
theorem AnalyticWithinAt.comp {g : F → G} {f : E → F} {x : E} {t : Set F} {s : Set E}
(hg : AnalyticWithinAt 𝕜 g t (f x)) (hf : AnalyticWithinAt 𝕜 f s x) (h : Set.MapsTo f s t) :
AnalyticWithinAt 𝕜 (g ∘ f) s x := by
let ⟨_q, hq⟩ := hg
let ⟨_p, hp⟩ := hf
exact (hq.comp hp h).analyticWithinAt
/-- Version of `AnalyticWithinAt.comp` where point equality is a separate hypothesis. -/
theorem AnalyticWithinAt.comp_of_eq {g : F → G} {f : E → F} {y : F} {x : E} {t : Set F} {s : Set E}
(hg : AnalyticWithinAt 𝕜 g t y) (hf : AnalyticWithinAt 𝕜 f s x) (h : Set.MapsTo f s t)
(hy : f x = y) :
AnalyticWithinAt 𝕜 (g ∘ f) s x := by
rw [← hy] at hg
exact hg.comp hf h
lemma AnalyticOn.comp {f : F → G} {g : E → F} {s : Set F}
{t : Set E} (hf : AnalyticOn 𝕜 f s) (hg : AnalyticOn 𝕜 g t) (h : Set.MapsTo g t s) :
AnalyticOn 𝕜 (f ∘ g) t :=
fun x m ↦ (hf _ (h m)).comp (hg x m) h
/-- If two functions `g` and `f` are analytic respectively at `f x` and `x`, then `g ∘ f` is
analytic at `x`. -/
| Mathlib/Analysis/Analytic/Composition.lean | 727 | 846 |
/-
Copyright (c) 2019 Johannes Hölzl, Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Zhouhang Zhou
-/
import Mathlib.Dynamics.Ergodic.MeasurePreserving
import Mathlib.MeasureTheory.Function.StronglyMeasurable.AEStronglyMeasurable
import Mathlib.MeasureTheory.Integral.Lebesgue.Add
import Mathlib.Order.Filter.Germ.Basic
import Mathlib.Topology.ContinuousMap.Algebra
/-!
# Almost everywhere equal functions
We build a space of equivalence classes of functions, where two functions are treated as identical
if they are almost everywhere equal. We form the set of equivalence classes under the relation of
being almost everywhere equal, which is sometimes known as the `L⁰` space.
To use this space as a basis for the `L^p` spaces and for the Bochner integral, we consider
equivalence classes of strongly measurable functions (or, equivalently, of almost everywhere
strongly measurable functions.)
See `L1Space.lean` for `L¹` space.
## Notation
* `α →ₘ[μ] β` is the type of `L⁰` space, where `α` is a measurable space, `β` is a topological
space, and `μ` is a measure on `α`. `f : α →ₘ β` is a "function" in `L⁰`.
In comments, `[f]` is also used to denote an `L⁰` function.
`ₘ` can be typed as `\_m`. Sometimes it is shown as a box if font is missing.
## Main statements
* The linear structure of `L⁰` :
Addition and scalar multiplication are defined on `L⁰` in the natural way, i.e.,
`[f] + [g] := [f + g]`, `c • [f] := [c • f]`. So defined, `α →ₘ β` inherits the linear structure
of `β`. For example, if `β` is a module, then `α →ₘ β` is a module over the same ring.
See `mk_add_mk`, `neg_mk`, `mk_sub_mk`, `smul_mk`,
`add_toFun`, `neg_toFun`, `sub_toFun`, `smul_toFun`
* The order structure of `L⁰` :
`≤` can be defined in a similar way: `[f] ≤ [g]` if `f a ≤ g a` for almost all `a` in domain.
And `α →ₘ β` inherits the preorder and partial order of `β`.
TODO: Define `sup` and `inf` on `L⁰` so that it forms a lattice. It seems that `β` must be a
linear order, since otherwise `f ⊔ g` may not be a measurable function.
## Implementation notes
* `f.toFun` : To find a representative of `f : α →ₘ β`, use the coercion `(f : α → β)`, which
is implemented as `f.toFun`.
For each operation `op` in `L⁰`, there is a lemma called `coe_fn_op`,
characterizing, say, `(f op g : α → β)`.
* `ae_eq_fun.mk` : To constructs an `L⁰` function `α →ₘ β` from an almost everywhere strongly
measurable function `f : α → β`, use `ae_eq_fun.mk`
* `comp` : Use `comp g f` to get `[g ∘ f]` from `g : β → γ` and `[f] : α →ₘ γ` when `g` is
continuous. Use `comp_measurable` if `g` is only measurable (this requires the
target space to be second countable).
* `comp₂` : Use `comp₂ g f₁ f₂` to get `[fun a ↦ g (f₁ a) (f₂ a)]`.
For example, `[f + g]` is `comp₂ (+)`
## Tags
function space, almost everywhere equal, `L⁰`, ae_eq_fun
-/
-- Guard against import creep
assert_not_exists InnerProductSpace
noncomputable section
open Topology Set Filter TopologicalSpace ENNReal EMetric MeasureTheory Function
variable {α β γ δ : Type*} [MeasurableSpace α] {μ ν : Measure α}
namespace MeasureTheory
section MeasurableSpace
variable [TopologicalSpace β]
variable (β)
/-- The equivalence relation of being almost everywhere equal for almost everywhere strongly
measurable functions. -/
def Measure.aeEqSetoid (μ : Measure α) : Setoid { f : α → β // AEStronglyMeasurable f μ } :=
⟨fun f g => (f : α → β) =ᵐ[μ] g, fun {f} => ae_eq_refl f.val, fun {_ _} => ae_eq_symm,
fun {_ _ _} => ae_eq_trans⟩
variable (α)
/-- The space of equivalence classes of almost everywhere strongly measurable functions, where two
strongly measurable functions are equivalent if they agree almost everywhere, i.e.,
they differ on a set of measure `0`. -/
def AEEqFun (μ : Measure α) : Type _ :=
Quotient (μ.aeEqSetoid β)
variable {α β}
@[inherit_doc MeasureTheory.AEEqFun]
notation:25 α " →ₘ[" μ "] " β => AEEqFun α β μ
end MeasurableSpace
variable [TopologicalSpace δ]
namespace AEEqFun
section
variable [TopologicalSpace β]
/-- Construct the equivalence class `[f]` of an almost everywhere measurable function `f`, based
on the equivalence relation of being almost everywhere equal. -/
def mk {β : Type*} [TopologicalSpace β] (f : α → β) (hf : AEStronglyMeasurable f μ) : α →ₘ[μ] β :=
Quotient.mk'' ⟨f, hf⟩
open scoped Classical in
/-- Coercion from a space of equivalence classes of almost everywhere strongly measurable
functions to functions. We ensure that if `f` has a constant representative,
then we choose that one. -/
@[coe]
def cast (f : α →ₘ[μ] β) : α → β :=
if h : ∃ (b : β), f = mk (const α b) aestronglyMeasurable_const then
const α <| Classical.choose h else
AEStronglyMeasurable.mk _ (Quotient.out f : { f : α → β // AEStronglyMeasurable f μ }).2
/-- A measurable representative of an `AEEqFun` [f] -/
instance instCoeFun : CoeFun (α →ₘ[μ] β) fun _ => α → β := ⟨cast⟩
protected theorem stronglyMeasurable (f : α →ₘ[μ] β) : StronglyMeasurable f := by
simp only [cast]
split_ifs with h
· exact stronglyMeasurable_const
· apply AEStronglyMeasurable.stronglyMeasurable_mk
protected theorem aestronglyMeasurable (f : α →ₘ[μ] β) : AEStronglyMeasurable f μ :=
f.stronglyMeasurable.aestronglyMeasurable
protected theorem measurable [PseudoMetrizableSpace β] [MeasurableSpace β] [BorelSpace β]
(f : α →ₘ[μ] β) : Measurable f :=
f.stronglyMeasurable.measurable
protected theorem aemeasurable [PseudoMetrizableSpace β] [MeasurableSpace β] [BorelSpace β]
(f : α →ₘ[μ] β) : AEMeasurable f μ :=
f.measurable.aemeasurable
@[simp]
theorem quot_mk_eq_mk (f : α → β) (hf) :
(Quot.mk (@Setoid.r _ <| μ.aeEqSetoid β) ⟨f, hf⟩ : α →ₘ[μ] β) = mk f hf :=
rfl
@[simp]
theorem mk_eq_mk {f g : α → β} {hf hg} : (mk f hf : α →ₘ[μ] β) = mk g hg ↔ f =ᵐ[μ] g :=
Quotient.eq''
@[simp]
theorem mk_coeFn (f : α →ₘ[μ] β) : mk f f.aestronglyMeasurable = f := by
conv_lhs => simp only [cast]
split_ifs with h
· exact Classical.choose_spec h |>.symm
conv_rhs => rw [← Quotient.out_eq' f]
rw [← mk, mk_eq_mk]
exact (AEStronglyMeasurable.ae_eq_mk _).symm
@[ext]
theorem ext {f g : α →ₘ[μ] β} (h : f =ᵐ[μ] g) : f = g := by
rwa [← f.mk_coeFn, ← g.mk_coeFn, mk_eq_mk]
theorem coeFn_mk (f : α → β) (hf) : (mk f hf : α →ₘ[μ] β) =ᵐ[μ] f := by
rw [← mk_eq_mk, mk_coeFn]
@[elab_as_elim]
theorem induction_on (f : α →ₘ[μ] β) {p : (α →ₘ[μ] β) → Prop} (H : ∀ f hf, p (mk f hf)) : p f :=
Quotient.inductionOn' f <| Subtype.forall.2 H
@[elab_as_elim]
theorem induction_on₂ {α' β' : Type*} [MeasurableSpace α'] [TopologicalSpace β'] {μ' : Measure α'}
(f : α →ₘ[μ] β) (f' : α' →ₘ[μ'] β') {p : (α →ₘ[μ] β) → (α' →ₘ[μ'] β') → Prop}
(H : ∀ f hf f' hf', p (mk f hf) (mk f' hf')) : p f f' :=
induction_on f fun f hf => induction_on f' <| H f hf
@[elab_as_elim]
theorem induction_on₃ {α' β' : Type*} [MeasurableSpace α'] [TopologicalSpace β'] {μ' : Measure α'}
{α'' β'' : Type*} [MeasurableSpace α''] [TopologicalSpace β''] {μ'' : Measure α''}
(f : α →ₘ[μ] β) (f' : α' →ₘ[μ'] β') (f'' : α'' →ₘ[μ''] β'')
{p : (α →ₘ[μ] β) → (α' →ₘ[μ'] β') → (α'' →ₘ[μ''] β'') → Prop}
(H : ∀ f hf f' hf' f'' hf'', p (mk f hf) (mk f' hf') (mk f'' hf'')) : p f f' f'' :=
induction_on f fun f hf => induction_on₂ f' f'' <| H f hf
end
/-!
### Composition of an a.e. equal function with a (quasi) measure preserving function
-/
section compQuasiMeasurePreserving
variable [TopologicalSpace γ] [MeasurableSpace β] {ν : MeasureTheory.Measure β} {f : α → β}
open MeasureTheory.Measure (QuasiMeasurePreserving)
/-- Composition of an almost everywhere equal function and a quasi measure preserving function.
See also `AEEqFun.compMeasurePreserving`. -/
def compQuasiMeasurePreserving (g : β →ₘ[ν] γ) (f : α → β) (hf : QuasiMeasurePreserving f μ ν) :
α →ₘ[μ] γ :=
Quotient.liftOn' g (fun g ↦ mk (g ∘ f) <| g.2.comp_quasiMeasurePreserving hf) fun _ _ h ↦
mk_eq_mk.2 <| h.comp_tendsto hf.tendsto_ae
@[simp]
theorem compQuasiMeasurePreserving_mk {g : β → γ} (hg : AEStronglyMeasurable g ν)
(hf : QuasiMeasurePreserving f μ ν) :
(mk g hg).compQuasiMeasurePreserving f hf = mk (g ∘ f) (hg.comp_quasiMeasurePreserving hf) :=
rfl
theorem compQuasiMeasurePreserving_eq_mk (g : β →ₘ[ν] γ) (hf : QuasiMeasurePreserving f μ ν) :
g.compQuasiMeasurePreserving f hf =
mk (g ∘ f) (g.aestronglyMeasurable.comp_quasiMeasurePreserving hf) := by
rw [← compQuasiMeasurePreserving_mk g.aestronglyMeasurable hf, mk_coeFn]
theorem coeFn_compQuasiMeasurePreserving (g : β →ₘ[ν] γ) (hf : QuasiMeasurePreserving f μ ν) :
g.compQuasiMeasurePreserving f hf =ᵐ[μ] g ∘ f := by
rw [compQuasiMeasurePreserving_eq_mk]
apply coeFn_mk
end compQuasiMeasurePreserving
section compMeasurePreserving
variable [TopologicalSpace γ] [MeasurableSpace β] {ν : MeasureTheory.Measure β}
{f : α → β} {g : β → γ}
/-- Composition of an almost everywhere equal function and a quasi measure preserving function.
This is an important special case of `AEEqFun.compQuasiMeasurePreserving`. We use a separate
definition so that lemmas that need `f` to be measure preserving can be `@[simp]` lemmas. -/
def compMeasurePreserving (g : β →ₘ[ν] γ) (f : α → β) (hf : MeasurePreserving f μ ν) : α →ₘ[μ] γ :=
g.compQuasiMeasurePreserving f hf.quasiMeasurePreserving
@[simp]
theorem compMeasurePreserving_mk (hg : AEStronglyMeasurable g ν) (hf : MeasurePreserving f μ ν) :
(mk g hg).compMeasurePreserving f hf =
mk (g ∘ f) (hg.comp_quasiMeasurePreserving hf.quasiMeasurePreserving) :=
rfl
theorem compMeasurePreserving_eq_mk (g : β →ₘ[ν] γ) (hf : MeasurePreserving f μ ν) :
g.compMeasurePreserving f hf =
mk (g ∘ f) (g.aestronglyMeasurable.comp_quasiMeasurePreserving hf.quasiMeasurePreserving) :=
g.compQuasiMeasurePreserving_eq_mk _
theorem coeFn_compMeasurePreserving (g : β →ₘ[ν] γ) (hf : MeasurePreserving f μ ν) :
g.compMeasurePreserving f hf =ᵐ[μ] g ∘ f :=
g.coeFn_compQuasiMeasurePreserving _
end compMeasurePreserving
variable [TopologicalSpace β] [TopologicalSpace γ]
/-- Given a continuous function `g : β → γ`, and an almost everywhere equal function `[f] : α →ₘ β`,
return the equivalence class of `g ∘ f`, i.e., the almost everywhere equal function
`[g ∘ f] : α →ₘ γ`. -/
def comp (g : β → γ) (hg : Continuous g) (f : α →ₘ[μ] β) : α →ₘ[μ] γ :=
Quotient.liftOn' f (fun f => mk (g ∘ (f : α → β)) (hg.comp_aestronglyMeasurable f.2))
fun _ _ H => mk_eq_mk.2 <| H.fun_comp g
@[simp]
theorem comp_mk (g : β → γ) (hg : Continuous g) (f : α → β) (hf) :
comp g hg (mk f hf : α →ₘ[μ] β) = mk (g ∘ f) (hg.comp_aestronglyMeasurable hf) :=
rfl
theorem comp_eq_mk (g : β → γ) (hg : Continuous g) (f : α →ₘ[μ] β) :
comp g hg f = mk (g ∘ f) (hg.comp_aestronglyMeasurable f.aestronglyMeasurable) := by
rw [← comp_mk g hg f f.aestronglyMeasurable, mk_coeFn]
theorem coeFn_comp (g : β → γ) (hg : Continuous g) (f : α →ₘ[μ] β) : comp g hg f =ᵐ[μ] g ∘ f := by
rw [comp_eq_mk]
apply coeFn_mk
theorem comp_compQuasiMeasurePreserving
{β : Type*} [MeasurableSpace β] {ν} (g : γ → δ) (hg : Continuous g)
(f : β →ₘ[ν] γ) {φ : α → β} (hφ : Measure.QuasiMeasurePreserving φ μ ν) :
(comp g hg f).compQuasiMeasurePreserving φ hφ =
comp g hg (f.compQuasiMeasurePreserving φ hφ) := by
rcases f; rfl
section CompMeasurable
variable [MeasurableSpace β] [PseudoMetrizableSpace β] [BorelSpace β] [MeasurableSpace γ]
[PseudoMetrizableSpace γ] [OpensMeasurableSpace γ] [SecondCountableTopology γ]
/-- Given a measurable function `g : β → γ`, and an almost everywhere equal function `[f] : α →ₘ β`,
return the equivalence class of `g ∘ f`, i.e., the almost everywhere equal function
`[g ∘ f] : α →ₘ γ`. This requires that `γ` has a second countable topology. -/
def compMeasurable (g : β → γ) (hg : Measurable g) (f : α →ₘ[μ] β) : α →ₘ[μ] γ :=
Quotient.liftOn' f
(fun f' => mk (g ∘ (f' : α → β)) (hg.comp_aemeasurable f'.2.aemeasurable).aestronglyMeasurable)
fun _ _ H => mk_eq_mk.2 <| H.fun_comp g
@[simp]
theorem compMeasurable_mk (g : β → γ) (hg : Measurable g) (f : α → β)
(hf : AEStronglyMeasurable f μ) :
compMeasurable g hg (mk f hf : α →ₘ[μ] β) =
mk (g ∘ f) (hg.comp_aemeasurable hf.aemeasurable).aestronglyMeasurable :=
rfl
theorem compMeasurable_eq_mk (g : β → γ) (hg : Measurable g) (f : α →ₘ[μ] β) :
compMeasurable g hg f =
mk (g ∘ f) (hg.comp_aemeasurable f.aemeasurable).aestronglyMeasurable := by
rw [← compMeasurable_mk g hg f f.aestronglyMeasurable, mk_coeFn]
theorem coeFn_compMeasurable (g : β → γ) (hg : Measurable g) (f : α →ₘ[μ] β) :
compMeasurable g hg f =ᵐ[μ] g ∘ f := by
rw [compMeasurable_eq_mk]
apply coeFn_mk
end CompMeasurable
/-- The class of `x ↦ (f x, g x)`. -/
def pair (f : α →ₘ[μ] β) (g : α →ₘ[μ] γ) : α →ₘ[μ] β × γ :=
Quotient.liftOn₂' f g (fun f g => mk (fun x => (f.1 x, g.1 x)) (f.2.prodMk g.2))
fun _f _g _f' _g' Hf Hg => mk_eq_mk.2 <| Hf.prodMk Hg
@[simp]
theorem pair_mk_mk (f : α → β) (hf) (g : α → γ) (hg) :
(mk f hf : α →ₘ[μ] β).pair (mk g hg) = mk (fun x => (f x, g x)) (hf.prodMk hg) :=
rfl
theorem pair_eq_mk (f : α →ₘ[μ] β) (g : α →ₘ[μ] γ) :
f.pair g =
mk (fun x => (f x, g x)) (f.aestronglyMeasurable.prodMk g.aestronglyMeasurable) := by
simp only [← pair_mk_mk, mk_coeFn, f.aestronglyMeasurable, g.aestronglyMeasurable]
theorem coeFn_pair (f : α →ₘ[μ] β) (g : α →ₘ[μ] γ) : f.pair g =ᵐ[μ] fun x => (f x, g x) := by
rw [pair_eq_mk]
apply coeFn_mk
/-- Given a continuous function `g : β → γ → δ`, and almost everywhere equal functions
`[f₁] : α →ₘ β` and `[f₂] : α →ₘ γ`, return the equivalence class of the function
`fun a => g (f₁ a) (f₂ a)`, i.e., the almost everywhere equal function
`[fun a => g (f₁ a) (f₂ a)] : α →ₘ γ` -/
def comp₂ (g : β → γ → δ) (hg : Continuous (uncurry g)) (f₁ : α →ₘ[μ] β) (f₂ : α →ₘ[μ] γ) :
α →ₘ[μ] δ :=
comp _ hg (f₁.pair f₂)
@[simp]
theorem comp₂_mk_mk (g : β → γ → δ) (hg : Continuous (uncurry g)) (f₁ : α → β) (f₂ : α → γ)
(hf₁ hf₂) :
comp₂ g hg (mk f₁ hf₁ : α →ₘ[μ] β) (mk f₂ hf₂) =
mk (fun a => g (f₁ a) (f₂ a)) (hg.comp_aestronglyMeasurable (hf₁.prodMk hf₂)) :=
rfl
theorem comp₂_eq_pair (g : β → γ → δ) (hg : Continuous (uncurry g)) (f₁ : α →ₘ[μ] β)
(f₂ : α →ₘ[μ] γ) : comp₂ g hg f₁ f₂ = comp _ hg (f₁.pair f₂) :=
rfl
theorem comp₂_eq_mk (g : β → γ → δ) (hg : Continuous (uncurry g)) (f₁ : α →ₘ[μ] β)
(f₂ : α →ₘ[μ] γ) : comp₂ g hg f₁ f₂ = mk (fun a => g (f₁ a) (f₂ a))
(hg.comp_aestronglyMeasurable (f₁.aestronglyMeasurable.prodMk f₂.aestronglyMeasurable)) := by
rw [comp₂_eq_pair, pair_eq_mk, comp_mk]; rfl
theorem coeFn_comp₂ (g : β → γ → δ) (hg : Continuous (uncurry g)) (f₁ : α →ₘ[μ] β)
(f₂ : α →ₘ[μ] γ) : comp₂ g hg f₁ f₂ =ᵐ[μ] fun a => g (f₁ a) (f₂ a) := by
rw [comp₂_eq_mk]
apply coeFn_mk
section
variable [MeasurableSpace β] [PseudoMetrizableSpace β] [BorelSpace β]
[MeasurableSpace γ] [PseudoMetrizableSpace γ] [BorelSpace γ] [SecondCountableTopologyEither β γ]
[MeasurableSpace δ] [PseudoMetrizableSpace δ] [OpensMeasurableSpace δ] [SecondCountableTopology δ]
/-- Given a measurable function `g : β → γ → δ`, and almost everywhere equal functions
`[f₁] : α →ₘ β` and `[f₂] : α →ₘ γ`, return the equivalence class of the function
`fun a => g (f₁ a) (f₂ a)`, i.e., the almost everywhere equal function
`[fun a => g (f₁ a) (f₂ a)] : α →ₘ γ`. This requires `δ` to have second-countable topology. -/
def comp₂Measurable (g : β → γ → δ) (hg : Measurable (uncurry g)) (f₁ : α →ₘ[μ] β)
(f₂ : α →ₘ[μ] γ) : α →ₘ[μ] δ :=
compMeasurable _ hg (f₁.pair f₂)
@[simp]
theorem comp₂Measurable_mk_mk (g : β → γ → δ) (hg : Measurable (uncurry g)) (f₁ : α → β)
(f₂ : α → γ) (hf₁ hf₂) :
comp₂Measurable g hg (mk f₁ hf₁ : α →ₘ[μ] β) (mk f₂ hf₂) =
mk (fun a => g (f₁ a) (f₂ a))
(hg.comp_aemeasurable (hf₁.aemeasurable.prodMk hf₂.aemeasurable)).aestronglyMeasurable :=
rfl
theorem comp₂Measurable_eq_pair (g : β → γ → δ) (hg : Measurable (uncurry g)) (f₁ : α →ₘ[μ] β)
(f₂ : α →ₘ[μ] γ) : comp₂Measurable g hg f₁ f₂ = compMeasurable _ hg (f₁.pair f₂) :=
rfl
theorem comp₂Measurable_eq_mk (g : β → γ → δ) (hg : Measurable (uncurry g)) (f₁ : α →ₘ[μ] β)
(f₂ : α →ₘ[μ] γ) :
comp₂Measurable g hg f₁ f₂ =
mk (fun a => g (f₁ a) (f₂ a))
(hg.comp_aemeasurable (f₁.aemeasurable.prodMk f₂.aemeasurable)).aestronglyMeasurable := by
rw [comp₂Measurable_eq_pair, pair_eq_mk, compMeasurable_mk]; rfl
theorem coeFn_comp₂Measurable (g : β → γ → δ) (hg : Measurable (uncurry g)) (f₁ : α →ₘ[μ] β)
(f₂ : α →ₘ[μ] γ) : comp₂Measurable g hg f₁ f₂ =ᵐ[μ] fun a => g (f₁ a) (f₂ a) := by
rw [comp₂Measurable_eq_mk]
apply coeFn_mk
end
/-- Interpret `f : α →ₘ[μ] β` as a germ at `ae μ` forgetting that `f` is almost everywhere
strongly measurable. -/
def toGerm (f : α →ₘ[μ] β) : Germ (ae μ) β :=
Quotient.liftOn' f (fun f => ((f : α → β) : Germ (ae μ) β)) fun _ _ H => Germ.coe_eq.2 H
@[simp]
theorem mk_toGerm (f : α → β) (hf) : (mk f hf : α →ₘ[μ] β).toGerm = f :=
rfl
theorem toGerm_eq (f : α →ₘ[μ] β) : f.toGerm = (f : α → β) := by rw [← mk_toGerm, mk_coeFn]
theorem toGerm_injective : Injective (toGerm : (α →ₘ[μ] β) → Germ (ae μ) β) := fun f g H =>
ext <| Germ.coe_eq.1 <| by rwa [← toGerm_eq, ← toGerm_eq]
@[simp]
theorem compQuasiMeasurePreserving_toGerm {β : Type*} [MeasurableSpace β] {f : α → β} {ν}
(g : β →ₘ[ν] γ) (hf : Measure.QuasiMeasurePreserving f μ ν) :
(g.compQuasiMeasurePreserving f hf).toGerm = g.toGerm.compTendsto f hf.tendsto_ae := by
rcases g; rfl
@[simp]
theorem compMeasurePreserving_toGerm {β : Type*} [MeasurableSpace β] {f : α → β} {ν}
(g : β →ₘ[ν] γ) (hf : MeasurePreserving f μ ν) :
(g.compMeasurePreserving f hf).toGerm =
g.toGerm.compTendsto f hf.quasiMeasurePreserving.tendsto_ae :=
compQuasiMeasurePreserving_toGerm _ _
theorem comp_toGerm (g : β → γ) (hg : Continuous g) (f : α →ₘ[μ] β) :
(comp g hg f).toGerm = f.toGerm.map g :=
induction_on f fun f _ => by simp
theorem compMeasurable_toGerm [MeasurableSpace β] [BorelSpace β] [PseudoMetrizableSpace β]
[PseudoMetrizableSpace γ] [SecondCountableTopology γ] [MeasurableSpace γ]
[OpensMeasurableSpace γ] (g : β → γ) (hg : Measurable g) (f : α →ₘ[μ] β) :
(compMeasurable g hg f).toGerm = f.toGerm.map g :=
induction_on f fun f _ => by simp
theorem comp₂_toGerm (g : β → γ → δ) (hg : Continuous (uncurry g)) (f₁ : α →ₘ[μ] β)
| (f₂ : α →ₘ[μ] γ) : (comp₂ g hg f₁ f₂).toGerm = f₁.toGerm.map₂ g f₂.toGerm :=
| Mathlib/MeasureTheory/Function/AEEqFun.lean | 447 | 447 |
/-
Copyright (c) 2020 Markus Himmel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel, Adam Topaz, Johan Commelin, Jakob von Raumer
-/
import Mathlib.Algebra.Homology.ImageToKernel
import Mathlib.Algebra.Homology.ShortComplex.Exact
import Mathlib.CategoryTheory.Abelian.Opposite
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Zero
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Kernels
import Mathlib.CategoryTheory.Adjunction.Limits
import Mathlib.Tactic.TFAE
/-!
# Exact sequences in abelian categories
In an abelian category, we get several interesting results related to exactness which are not
true in more general settings.
## Main results
* A short complex `S` is exact iff `imageSubobject S.f = kernelSubobject S.g`.
* If `(f, g)` is exact, then `image.ι f` has the universal property of the kernel of `g`.
* `f` is a monomorphism iff `kernel.ι f = 0` iff `Exact 0 f`, and `f` is an epimorphism iff
`cokernel.π = 0` iff `Exact f 0`.
* A faithful functor between abelian categories that preserves zero morphisms reflects exact
sequences.
* `X ⟶ Y ⟶ Z ⟶ 0` is exact if and only if the second map is a cokernel of the first, and
`0 ⟶ X ⟶ Y ⟶ Z` is exact if and only if the first map is a kernel of the second.
* A functor `F` such that for all `S`, we have `S.Exact → (S.map F).Exact` preserves both
finite limits and colimits.
-/
universe v₁ v₂ u₁ u₂
noncomputable section
open CategoryTheory Limits Preadditive
variable {C : Type u₁} [Category.{v₁} C] [Abelian C]
namespace CategoryTheory
namespace ShortComplex
variable (S : ShortComplex C)
attribute [local instance] hasEqualizers_of_hasKernels
theorem exact_iff_epi_imageToKernel' : S.Exact ↔ Epi (imageToKernel' S.f S.g S.zero) := by
rw [S.exact_iff_epi_kernel_lift]
have : factorThruImage S.f ≫ imageToKernel' S.f S.g S.zero = kernel.lift S.g S.f S.zero := by
simp only [← cancel_mono (kernel.ι _), kernel.lift_ι, imageToKernel',
Category.assoc, image.fac]
constructor
· intro
exact epi_of_epi_fac this
· intro
rw [← this]
apply epi_comp
theorem exact_iff_epi_imageToKernel : S.Exact ↔ Epi (imageToKernel S.f S.g S.zero) := by
rw [S.exact_iff_epi_imageToKernel']
apply (MorphismProperty.epimorphisms C).arrow_mk_iso_iff
exact Arrow.isoMk (imageSubobjectIso S.f).symm (kernelSubobjectIso S.g).symm
theorem exact_iff_isIso_imageToKernel : S.Exact ↔ IsIso (imageToKernel S.f S.g S.zero) := by
rw [S.exact_iff_epi_imageToKernel]
constructor
· intro
apply isIso_of_mono_of_epi
· intro
infer_instance
/-- In an abelian category, a short complex `S` is exact
iff `imageSubobject S.f = kernelSubobject S.g`.
-/
theorem exact_iff_image_eq_kernel : S.Exact ↔ imageSubobject S.f = kernelSubobject S.g := by
rw [exact_iff_isIso_imageToKernel]
constructor
· intro
exact Subobject.eq_of_comm (asIso (imageToKernel _ _ S.zero)) (by simp)
· intro h
exact ⟨Subobject.ofLE _ _ h.ge, by ext; simp, by ext; simp⟩
theorem exact_iff_of_forks {cg : KernelFork S.g} (hg : IsLimit cg) {cf : CokernelCofork S.f}
(hf : IsColimit cf) : S.Exact ↔ cg.ι ≫ cf.π = 0 := by
rw [exact_iff_kernel_ι_comp_cokernel_π_zero]
let e₁ := IsLimit.conePointUniqueUpToIso (kernelIsKernel S.g) hg
let e₂ := IsColimit.coconePointUniqueUpToIso (cokernelIsCokernel S.f) hf
have : cg.ι ≫ cf.π = e₁.inv ≫ kernel.ι S.g ≫ cokernel.π S.f ≫ e₂.hom := by
have eq₁ := IsLimit.conePointUniqueUpToIso_inv_comp (kernelIsKernel S.g) hg (.zero)
have eq₂ := IsColimit.comp_coconePointUniqueUpToIso_hom (cokernelIsCokernel S.f) hf (.one)
dsimp at eq₁ eq₂
rw [← eq₁, ← eq₂, Category.assoc]
rw [this, IsIso.comp_left_eq_zero e₁.inv, ← Category.assoc,
IsIso.comp_right_eq_zero _ e₂.hom]
variable {S}
/-- If `(f, g)` is exact, then `Abelian.image.ι S.f` is a kernel of `S.g`. -/
def Exact.isLimitImage (h : S.Exact) :
IsLimit (KernelFork.ofι (Abelian.image.ι S.f)
(Abelian.image_ι_comp_eq_zero S.zero) : KernelFork S.g) := by
rw [exact_iff_kernel_ι_comp_cokernel_π_zero] at h
exact KernelFork.IsLimit.ofι _ _
(fun u hu ↦ kernel.lift (cokernel.π S.f) u
(by rw [← kernel.lift_ι S.g u hu, Category.assoc, h, comp_zero])) (by simp)
(fun _ _ _ hm => by rw [← cancel_mono (Abelian.image.ι S.f), hm, kernel.lift_ι])
/-- If `(f, g)` is exact, then `image.ι f` is a kernel of `g`. -/
def Exact.isLimitImage' (h : S.Exact) :
IsLimit (KernelFork.ofι (Limits.image.ι S.f)
(image_ι_comp_eq_zero S.zero) : KernelFork S.g) :=
IsKernel.isoKernel _ _ h.isLimitImage (Abelian.imageIsoImage S.f).symm <| IsImage.lift_fac _ _
/-- If `(f, g)` is exact, then `Abelian.coimage.π g` is a cokernel of `f`. -/
def Exact.isColimitCoimage (h : S.Exact) :
IsColimit
(CokernelCofork.ofπ (Abelian.coimage.π S.g) (Abelian.comp_coimage_π_eq_zero S.zero) :
CokernelCofork S.f) := by
rw [exact_iff_kernel_ι_comp_cokernel_π_zero] at h
refine CokernelCofork.IsColimit.ofπ _ _
(fun u hu => cokernel.desc (kernel.ι S.g) u
(by rw [← cokernel.π_desc S.f u hu, ← Category.assoc, h, zero_comp]))
(by simp) ?_
intros _ _ _ _ hm
ext
rw [hm, cokernel.π_desc]
/-- If `(f, g)` is exact, then `factorThruImage g` is a cokernel of `f`. -/
def Exact.isColimitImage (h : S.Exact) :
IsColimit (CokernelCofork.ofπ (Limits.factorThruImage S.g)
(comp_factorThruImage_eq_zero S.zero)) :=
IsCokernel.cokernelIso _ _ h.isColimitCoimage (Abelian.coimageIsoImage' S.g) <|
(cancel_mono (Limits.image.ι S.g)).1 <| by simp
theorem exact_kernel {X Y : C} (f : X ⟶ Y) :
(ShortComplex.mk (kernel.ι f) f (by simp)).Exact :=
exact_of_f_is_kernel _ (kernelIsKernel f)
theorem exact_cokernel {X Y : C} (f : X ⟶ Y) :
(ShortComplex.mk f (cokernel.π f) (by simp)).Exact :=
exact_of_g_is_cokernel _ (cokernelIsCokernel f)
variable (S)
theorem exact_iff_exact_image_ι :
S.Exact ↔ (ShortComplex.mk (Abelian.image.ι S.f) S.g
(Abelian.image_ι_comp_eq_zero S.zero)).Exact :=
ShortComplex.exact_iff_of_epi_of_isIso_of_mono
{ τ₁ := Abelian.factorThruImage S.f
τ₂ := 𝟙 _
τ₃ := 𝟙 _ }
theorem exact_iff_exact_coimage_π :
S.Exact ↔ (ShortComplex.mk S.f (Abelian.coimage.π S.g)
(Abelian.comp_coimage_π_eq_zero S.zero)).Exact := by
symm
exact ShortComplex.exact_iff_of_epi_of_isIso_of_mono
{ τ₁ := 𝟙 _
| τ₂ := 𝟙 _
τ₃ := Abelian.factorThruCoimage S.g }
| Mathlib/CategoryTheory/Abelian/Exact.lean | 162 | 164 |
/-
Copyright (c) 2021 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.MeasureTheory.Constructions.BorelSpace.Basic
import Mathlib.Dynamics.Ergodic.MeasurePreserving
import Mathlib.Combinatorics.Pigeonhole
/-!
# Conservative systems
In this file we define `f : α → α` to be a *conservative* system w.r.t a measure `μ` if `f` is
non-singular (`MeasureTheory.QuasiMeasurePreserving`) and for every measurable set `s` of
positive measure at least one point `x ∈ s` returns back to `s` after some number of iterations of
`f`. There are several properties that look like they are stronger than this one but actually follow
from it:
* `MeasureTheory.Conservative.frequently_measure_inter_ne_zero`,
`MeasureTheory.Conservative.exists_gt_measure_inter_ne_zero`: if `μ s ≠ 0`, then for infinitely
many `n`, the measure of `s ∩ f^[n] ⁻¹' s` is positive.
* `MeasureTheory.Conservative.measure_mem_forall_ge_image_not_mem_eq_zero`,
`MeasureTheory.Conservative.ae_mem_imp_frequently_image_mem`: a.e. every point of `s` visits `s`
infinitely many times (Poincaré recurrence theorem).
We also prove the topological Poincaré recurrence theorem
`MeasureTheory.Conservative.ae_frequently_mem_of_mem_nhds`. Let `f : α → α` be a conservative
dynamical system on a topological space with second countable topology and measurable open
sets. Then almost every point `x : α` is recurrent: it visits every neighborhood `s ∈ 𝓝 x`
infinitely many times.
## Tags
conservative dynamical system, Poincare recurrence theorem
-/
noncomputable section
open Set Filter MeasureTheory Finset Function TopologicalSpace Topology
variable {α : Type*} [MeasurableSpace α] {f : α → α} {s : Set α} {μ : Measure α}
namespace MeasureTheory
open Measure
/-- We say that a non-singular (`MeasureTheory.QuasiMeasurePreserving`) self-map is
*conservative* if for any measurable set `s` of positive measure there exists `x ∈ s` such that `x`
returns back to `s` under some iteration of `f`. -/
structure Conservative (f : α → α) (μ : Measure α) : Prop extends QuasiMeasurePreserving f μ μ where
/-- If `f` is a conservative self-map and `s` is a measurable set of nonzero measure,
then there exists a point `x ∈ s` that returns to `s` under a non-zero iteration of `f`. -/
exists_mem_iterate_mem' : ∀ ⦃s⦄, MeasurableSet s → μ s ≠ 0 → ∃ x ∈ s, ∃ m ≠ 0, f^[m] x ∈ s
/-- A self-map preserving a finite measure is conservative. -/
protected theorem MeasurePreserving.conservative [IsFiniteMeasure μ] (h : MeasurePreserving f μ μ) :
Conservative f μ :=
⟨h.quasiMeasurePreserving, fun _ hsm h0 => h.exists_mem_iterate_mem hsm.nullMeasurableSet h0⟩
namespace Conservative
/-- The identity map is conservative w.r.t. any measure. -/
protected theorem id (μ : Measure α) : Conservative id μ :=
{ toQuasiMeasurePreserving := QuasiMeasurePreserving.id μ
exists_mem_iterate_mem' := fun _ _ h0 => by
simpa [exists_ne] using nonempty_of_measure_ne_zero h0 }
theorem of_absolutelyContinuous {ν : Measure α} (h : Conservative f μ) (hν : ν ≪ μ)
(h' : QuasiMeasurePreserving f ν ν) : Conservative f ν :=
⟨h', fun _ hsm h0 ↦ h.exists_mem_iterate_mem' hsm (mt (@hν _) h0)⟩
/-- Restriction of a conservative system to an invariant set is a conservative system,
formulated in terms of the restriction of the measure. -/
theorem measureRestrict (h : Conservative f μ) (hs : MapsTo f s s) :
Conservative f (μ.restrict s) :=
.of_absolutelyContinuous h (absolutelyContinuous_of_le restrict_le_self) <|
h.toQuasiMeasurePreserving.restrict hs
theorem congr_ae {ν : Measure α} (hf : Conservative f μ) (h : ae μ = ae ν) :
Conservative f ν :=
.of_absolutelyContinuous hf h.ge.absolutelyContinuous_of_ae <|
hf.toQuasiMeasurePreserving.mono h.ge.absolutelyContinuous_of_ae h.le.absolutelyContinuous_of_ae
theorem _root_.MeasureTheory.conservative_congr {ν : Measure α} (h : ae μ = ae ν) :
Conservative f μ ↔ Conservative f ν :=
⟨(congr_ae · h), (congr_ae · h.symm)⟩
/-- If `f` is a conservative self-map and `s` is a null measurable set of nonzero measure,
then there exists a point `x ∈ s` that returns to `s` under a non-zero iteration of `f`. -/
theorem exists_mem_iterate_mem (hf : Conservative f μ)
(hsm : NullMeasurableSet s μ) (hs₀ : μ s ≠ 0) :
∃ x ∈ s, ∃ m ≠ 0, f^[m] x ∈ s := by
rcases hsm.exists_measurable_subset_ae_eq with ⟨t, hsub, htm, hts⟩
rcases hf.exists_mem_iterate_mem' htm (by rwa [measure_congr hts]) with ⟨x, hxt, m, hm₀, hmt⟩
exact ⟨x, hsub hxt, m, hm₀, hsub hmt⟩
/-- If `f` is a conservative map and `s` is a measurable set of nonzero measure, then
for infinitely many values of `m` a positive measure of points `x ∈ s` returns back to `s`
after `m` iterations of `f`. -/
theorem frequently_measure_inter_ne_zero (hf : Conservative f μ) (hs : NullMeasurableSet s μ)
(h0 : μ s ≠ 0) : ∃ᶠ m in atTop, μ (s ∩ f^[m] ⁻¹' s) ≠ 0 := by
set t : ℕ → Set α := fun n ↦ s ∩ f^[n] ⁻¹' s
-- Assume that `μ (t n) ≠ 0`, where `t n = s ∩ f^[n] ⁻¹' s`, only for finitely many `n`.
by_contra H
-- Let `N` be the maximal `n` such that `μ (t n) ≠ 0`.
obtain ⟨N, hN, hmax⟩ : ∃ N, μ (t N) ≠ 0 ∧ ∀ n > N, μ (t n) = 0 := by
rw [Nat.frequently_atTop_iff_infinite, not_infinite] at H
convert exists_max_image _ (·) H ⟨0, by simpa⟩ using 4
rw [gt_iff_lt, ← not_le, not_imp_comm, mem_setOf]
have htm {n : ℕ} : NullMeasurableSet (t n) μ :=
hs.inter <| hs.preimage <| hf.toQuasiMeasurePreserving.iterate n
-- Then all `t n`, `n > N`, are null sets, hence `T = t N \ ⋃ n > N, t n` has positive measure.
set T := t N \ ⋃ n > N, t n with hT
have hμT : μ T ≠ 0 := by
rwa [hT, measure_diff_null]
exact (measure_biUnion_null_iff {n | N < n}.to_countable).2 hmax
have hTm : NullMeasurableSet T μ := htm.diff <| .biUnion {n | N < n}.to_countable fun _ _ ↦ htm
-- Take `x ∈ T` and `m ≠ 0` such that `f^[m] x ∈ T`.
rcases hf.exists_mem_iterate_mem hTm hμT with ⟨x, hxt, m, hm₀, hmt⟩
-- Then `N + m > N`, `x ∈ s`, and `f^[N + m] x = f^[N] (f^[m] x) ∈ s`.
-- This contradicts `x ∈ T ⊆ (⋃ n > N, t n)ᶜ`.
refine hxt.2 <| mem_iUnion₂.2 ⟨N + m, ?_, hxt.1.1, ?_⟩
· simpa [pos_iff_ne_zero]
· simpa only [iterate_add] using hmt.1.2
/-- If `f` is a conservative map and `s` is a measurable set of nonzero measure, then
for an arbitrarily large `m` a positive measure of points `x ∈ s` returns back to `s`
after `m` iterations of `f`. -/
theorem exists_gt_measure_inter_ne_zero (hf : Conservative f μ) (hs : NullMeasurableSet s μ)
(h0 : μ s ≠ 0) (N : ℕ) : ∃ m > N, μ (s ∩ f^[m] ⁻¹' s) ≠ 0 :=
let ⟨m, hm, hmN⟩ :=
((hf.frequently_measure_inter_ne_zero hs h0).and_eventually (eventually_gt_atTop N)).exists
| ⟨m, hmN, hm⟩
/-- Poincaré recurrence theorem: given a conservative map `f` and a measurable set `s`, the set
of points `x ∈ s` such that `x` does not return to `s` after `≥ n` iterations has measure zero. -/
theorem measure_mem_forall_ge_image_not_mem_eq_zero (hf : Conservative f μ)
(hs : NullMeasurableSet s μ) (n : ℕ) :
| Mathlib/Dynamics/Ergodic/Conservative.lean | 135 | 140 |
/-
Copyright (c) 2022 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.Analysis.Calculus.ContDiff.Basic
import Mathlib.Analysis.Calculus.ParametricIntegral
import Mathlib.MeasureTheory.Integral.Prod
import Mathlib.MeasureTheory.Function.LocallyIntegrable
import Mathlib.MeasureTheory.Group.Integral
import Mathlib.MeasureTheory.Group.Prod
import Mathlib.MeasureTheory.Integral.IntervalIntegral.Basic
/-!
# Convolution of functions
This file defines the convolution on two functions, i.e. `x ↦ ∫ f(t)g(x - t) ∂t`.
In the general case, these functions can be vector-valued, and have an arbitrary (additive)
group as domain. We use a continuous bilinear operation `L` on these function values as
"multiplication". The domain must be equipped with a Haar measure `μ`
(though many individual results have weaker conditions on `μ`).
For many applications we can take `L = ContinuousLinearMap.lsmul ℝ ℝ` or
`L = ContinuousLinearMap.mul ℝ ℝ`.
We also define `ConvolutionExists` and `ConvolutionExistsAt` to state that the convolution is
well-defined (everywhere or at a single point). These conditions are needed for pointwise
computations (e.g. `ConvolutionExistsAt.distrib_add`), but are generally not strong enough for any
local (or global) properties of the convolution. For this we need stronger assumptions on `f`
and/or `g`, and generally if we impose stronger conditions on one of the functions, we can impose
weaker conditions on the other.
We have proven many of the properties of the convolution assuming one of these functions
has compact support (in which case the other function only needs to be locally integrable).
We still need to prove the properties for other pairs of conditions (e.g. both functions are
rapidly decreasing)
# Design Decisions
We use a bilinear map `L` to "multiply" the two functions in the integrand.
This generality has several advantages
* This allows us to compute the total derivative of the convolution, in case the functions are
multivariate. The total derivative is again a convolution, but where the codomains of the
functions can be higher-dimensional. See `HasCompactSupport.hasFDerivAt_convolution_right`.
* This allows us to use `@[to_additive]` everywhere (which would not be possible if we would use
`mul`/`smul` in the integral, since `@[to_additive]` will incorrectly also try to additivize
those definitions).
* We need to support the case where at least one of the functions is vector-valued, but if we use
`smul` to multiply the functions, that would be an asymmetric definition.
# Main Definitions
* `MeasureTheory.convolution f g L μ x = (f ⋆[L, μ] g) x = ∫ t, L (f t) (g (x - t)) ∂μ`
is the convolution of `f` and `g` w.r.t. the continuous bilinear map `L` and measure `μ`.
* `MeasureTheory.ConvolutionExistsAt f g x L μ` states that the convolution `(f ⋆[L, μ] g) x`
is well-defined (i.e. the integral exists).
* `MeasureTheory.ConvolutionExists f g L μ` states that the convolution `f ⋆[L, μ] g`
is well-defined at each point.
# Main Results
* `HasCompactSupport.hasFDerivAt_convolution_right` and
`HasCompactSupport.hasFDerivAt_convolution_left`: we can compute the total derivative
of the convolution as a convolution with the total derivative of the right (left) function.
* `HasCompactSupport.contDiff_convolution_right` and
`HasCompactSupport.contDiff_convolution_left`: the convolution is `𝒞ⁿ` if one of the functions
is `𝒞ⁿ` with compact support and the other function in locally integrable.
Versions of these statements for functions depending on a parameter are also given.
* `MeasureTheory.convolution_tendsto_right`: Given a sequence of nonnegative normalized functions
whose support tends to a small neighborhood around `0`, the convolution tends to the right
argument. This is specialized to bump functions in `ContDiffBump.convolution_tendsto_right`.
# Notation
The following notations are localized in the locale `Convolution`:
* `f ⋆[L, μ] g` for the convolution. Note: you have to use parentheses to apply the convolution
to an argument: `(f ⋆[L, μ] g) x`.
* `f ⋆[L] g := f ⋆[L, volume] g`
* `f ⋆ g := f ⋆[lsmul ℝ ℝ] g`
# To do
* Existence and (uniform) continuity of the convolution if
one of the maps is in `ℒ^p` and the other in `ℒ^q` with `1 / p + 1 / q = 1`.
This might require a generalization of `MeasureTheory.MemLp.smul` where `smul` is generalized
to a continuous bilinear map.
(see e.g. [Fremlin, *Measure Theory* (volume 2)][fremlin_vol2], 255K)
* The convolution is an `AEStronglyMeasurable` function
(see e.g. [Fremlin, *Measure Theory* (volume 2)][fremlin_vol2], 255I).
* Prove properties about the convolution if both functions are rapidly decreasing.
* Use `@[to_additive]` everywhere (this likely requires changes in `to_additive`)
-/
open Set Function Filter MeasureTheory MeasureTheory.Measure TopologicalSpace
open Bornology ContinuousLinearMap Metric Topology
open scoped Pointwise NNReal Filter
universe u𝕜 uG uE uE' uE'' uF uF' uF'' uP
variable {𝕜 : Type u𝕜} {G : Type uG} {E : Type uE} {E' : Type uE'} {E'' : Type uE''} {F : Type uF}
{F' : Type uF'} {F'' : Type uF''} {P : Type uP}
variable [NormedAddCommGroup E] [NormedAddCommGroup E'] [NormedAddCommGroup E'']
[NormedAddCommGroup F] {f f' : G → E} {g g' : G → E'} {x x' : G} {y y' : E}
namespace MeasureTheory
section NontriviallyNormedField
variable [NontriviallyNormedField 𝕜]
variable [NormedSpace 𝕜 E] [NormedSpace 𝕜 E'] [NormedSpace 𝕜 E''] [NormedSpace 𝕜 F]
variable (L : E →L[𝕜] E' →L[𝕜] F)
section NoMeasurability
variable [AddGroup G] [TopologicalSpace G]
theorem convolution_integrand_bound_right_of_le_of_subset {C : ℝ} (hC : ∀ i, ‖g i‖ ≤ C) {x t : G}
{s u : Set G} (hx : x ∈ s) (hu : -tsupport g + s ⊆ u) :
‖L (f t) (g (x - t))‖ ≤ u.indicator (fun t => ‖L‖ * ‖f t‖ * C) t := by
-- Porting note: had to add `f := _`
refine le_indicator (f := fun t ↦ ‖L (f t) (g (x - t))‖) (fun t _ => ?_) (fun t ht => ?_) t
· apply_rules [L.le_of_opNorm₂_le_of_le, le_rfl]
· have : x - t ∉ support g := by
refine mt (fun hxt => hu ?_) ht
refine ⟨_, Set.neg_mem_neg.mpr (subset_closure hxt), _, hx, ?_⟩
simp only [neg_sub, sub_add_cancel]
simp only [nmem_support.mp this, (L _).map_zero, norm_zero, le_rfl]
theorem _root_.HasCompactSupport.convolution_integrand_bound_right_of_subset
(hcg : HasCompactSupport g) (hg : Continuous g)
{x t : G} {s u : Set G} (hx : x ∈ s) (hu : -tsupport g + s ⊆ u) :
‖L (f t) (g (x - t))‖ ≤ u.indicator (fun t => ‖L‖ * ‖f t‖ * ⨆ i, ‖g i‖) t := by
refine convolution_integrand_bound_right_of_le_of_subset _ (fun i => ?_) hx hu
exact le_ciSup (hg.norm.bddAbove_range_of_hasCompactSupport hcg.norm) _
theorem _root_.HasCompactSupport.convolution_integrand_bound_right (hcg : HasCompactSupport g)
(hg : Continuous g) {x t : G} {s : Set G} (hx : x ∈ s) :
‖L (f t) (g (x - t))‖ ≤ (-tsupport g + s).indicator (fun t => ‖L‖ * ‖f t‖ * ⨆ i, ‖g i‖) t :=
hcg.convolution_integrand_bound_right_of_subset L hg hx Subset.rfl
theorem _root_.Continuous.convolution_integrand_fst [ContinuousSub G] (hg : Continuous g) (t : G) :
Continuous fun x => L (f t) (g (x - t)) :=
L.continuous₂.comp₂ continuous_const <| hg.comp <| continuous_id.sub continuous_const
theorem _root_.HasCompactSupport.convolution_integrand_bound_left (hcf : HasCompactSupport f)
(hf : Continuous f) {x t : G} {s : Set G} (hx : x ∈ s) :
‖L (f (x - t)) (g t)‖ ≤
(-tsupport f + s).indicator (fun t => (‖L‖ * ⨆ i, ‖f i‖) * ‖g t‖) t := by
convert hcf.convolution_integrand_bound_right L.flip hf hx using 1
simp_rw [L.opNorm_flip, mul_right_comm]
end NoMeasurability
section Measurability
variable [MeasurableSpace G] {μ ν : Measure G}
/-- The convolution of `f` and `g` exists at `x` when the function `t ↦ L (f t) (g (x - t))` is
integrable. There are various conditions on `f` and `g` to prove this. -/
def ConvolutionExistsAt [Sub G] (f : G → E) (g : G → E') (x : G) (L : E →L[𝕜] E' →L[𝕜] F)
(μ : Measure G := by volume_tac) : Prop :=
Integrable (fun t => L (f t) (g (x - t))) μ
/-- The convolution of `f` and `g` exists when the function `t ↦ L (f t) (g (x - t))` is integrable
for all `x : G`. There are various conditions on `f` and `g` to prove this. -/
def ConvolutionExists [Sub G] (f : G → E) (g : G → E') (L : E →L[𝕜] E' →L[𝕜] F)
(μ : Measure G := by volume_tac) : Prop :=
∀ x : G, ConvolutionExistsAt f g x L μ
section ConvolutionExists
variable {L} in
theorem ConvolutionExistsAt.integrable [Sub G] {x : G} (h : ConvolutionExistsAt f g x L μ) :
Integrable (fun t => L (f t) (g (x - t))) μ :=
h
section Group
variable [AddGroup G]
theorem AEStronglyMeasurable.convolution_integrand' [MeasurableAdd₂ G]
[MeasurableNeg G] (hf : AEStronglyMeasurable f ν)
(hg : AEStronglyMeasurable g <| map (fun p : G × G => p.1 - p.2) (μ.prod ν)) :
AEStronglyMeasurable (fun p : G × G => L (f p.2) (g (p.1 - p.2))) (μ.prod ν) :=
L.aestronglyMeasurable_comp₂ hf.snd <| hg.comp_measurable measurable_sub
section
variable [MeasurableAdd G] [MeasurableNeg G]
theorem AEStronglyMeasurable.convolution_integrand_snd'
(hf : AEStronglyMeasurable f μ) {x : G}
(hg : AEStronglyMeasurable g <| map (fun t => x - t) μ) :
AEStronglyMeasurable (fun t => L (f t) (g (x - t))) μ :=
L.aestronglyMeasurable_comp₂ hf <| hg.comp_measurable <| measurable_id.const_sub x
theorem AEStronglyMeasurable.convolution_integrand_swap_snd' {x : G}
(hf : AEStronglyMeasurable f <| map (fun t => x - t) μ) (hg : AEStronglyMeasurable g μ) :
AEStronglyMeasurable (fun t => L (f (x - t)) (g t)) μ :=
L.aestronglyMeasurable_comp₂ (hf.comp_measurable <| measurable_id.const_sub x) hg
/-- A sufficient condition to prove that `f ⋆[L, μ] g` exists.
We assume that `f` is integrable on a set `s` and `g` is bounded and ae strongly measurable
on `x₀ - s` (note that both properties hold if `g` is continuous with compact support). -/
theorem _root_.BddAbove.convolutionExistsAt' {x₀ : G} {s : Set G}
(hbg : BddAbove ((fun i => ‖g i‖) '' ((fun t => -t + x₀) ⁻¹' s))) (hs : MeasurableSet s)
(h2s : (support fun t => L (f t) (g (x₀ - t))) ⊆ s) (hf : IntegrableOn f s μ)
(hmg : AEStronglyMeasurable g <| map (fun t => x₀ - t) (μ.restrict s)) :
ConvolutionExistsAt f g x₀ L μ := by
rw [ConvolutionExistsAt]
rw [← integrableOn_iff_integrable_of_support_subset h2s]
set s' := (fun t => -t + x₀) ⁻¹' s
have : ∀ᵐ t : G ∂μ.restrict s,
‖L (f t) (g (x₀ - t))‖ ≤ s.indicator (fun t => ‖L‖ * ‖f t‖ * ⨆ i : s', ‖g i‖) t := by
filter_upwards
refine le_indicator (fun t ht => ?_) fun t ht => ?_
· apply_rules [L.le_of_opNorm₂_le_of_le, le_rfl]
refine (le_ciSup_set hbg <| mem_preimage.mpr ?_)
rwa [neg_sub, sub_add_cancel]
· have : t ∉ support fun t => L (f t) (g (x₀ - t)) := mt (fun h => h2s h) ht
rw [nmem_support.mp this, norm_zero]
refine Integrable.mono' ?_ ?_ this
· rw [integrable_indicator_iff hs]; exact ((hf.norm.const_mul _).mul_const _).integrableOn
· exact hf.aestronglyMeasurable.convolution_integrand_snd' L hmg
/-- If `‖f‖ *[μ] ‖g‖` exists, then `f *[L, μ] g` exists. -/
theorem ConvolutionExistsAt.of_norm' {x₀ : G}
(h : ConvolutionExistsAt (fun x => ‖f x‖) (fun x => ‖g x‖) x₀ (mul ℝ ℝ) μ)
(hmf : AEStronglyMeasurable f μ) (hmg : AEStronglyMeasurable g <| map (fun t => x₀ - t) μ) :
ConvolutionExistsAt f g x₀ L μ := by
refine (h.const_mul ‖L‖).mono'
(hmf.convolution_integrand_snd' L hmg) (Eventually.of_forall fun x => ?_)
rw [mul_apply', ← mul_assoc]
apply L.le_opNorm₂
@[deprecated (since := "2025-02-07")]
alias ConvolutionExistsAt.ofNorm' := ConvolutionExistsAt.of_norm'
end
section Left
variable [MeasurableAdd₂ G] [MeasurableNeg G] [SFinite μ] [IsAddRightInvariant μ]
theorem AEStronglyMeasurable.convolution_integrand_snd (hf : AEStronglyMeasurable f μ)
(hg : AEStronglyMeasurable g μ) (x : G) :
AEStronglyMeasurable (fun t => L (f t) (g (x - t))) μ :=
hf.convolution_integrand_snd' L <|
hg.mono_ac <| (quasiMeasurePreserving_sub_left_of_right_invariant μ x).absolutelyContinuous
theorem AEStronglyMeasurable.convolution_integrand_swap_snd
(hf : AEStronglyMeasurable f μ) (hg : AEStronglyMeasurable g μ) (x : G) :
AEStronglyMeasurable (fun t => L (f (x - t)) (g t)) μ :=
(hf.mono_ac
(quasiMeasurePreserving_sub_left_of_right_invariant μ
x).absolutelyContinuous).convolution_integrand_swap_snd'
L hg
/-- If `‖f‖ *[μ] ‖g‖` exists, then `f *[L, μ] g` exists. -/
theorem ConvolutionExistsAt.of_norm {x₀ : G}
(h : ConvolutionExistsAt (fun x => ‖f x‖) (fun x => ‖g x‖) x₀ (mul ℝ ℝ) μ)
(hmf : AEStronglyMeasurable f μ) (hmg : AEStronglyMeasurable g μ) :
ConvolutionExistsAt f g x₀ L μ :=
h.of_norm' L hmf <|
hmg.mono_ac (quasiMeasurePreserving_sub_left_of_right_invariant μ x₀).absolutelyContinuous
@[deprecated (since := "2025-02-07")]
alias ConvolutionExistsAt.ofNorm := ConvolutionExistsAt.of_norm
end Left
section Right
variable [MeasurableAdd₂ G] [MeasurableNeg G] [SFinite μ] [IsAddRightInvariant μ] [SFinite ν]
theorem AEStronglyMeasurable.convolution_integrand (hf : AEStronglyMeasurable f ν)
(hg : AEStronglyMeasurable g μ) :
AEStronglyMeasurable (fun p : G × G => L (f p.2) (g (p.1 - p.2))) (μ.prod ν) :=
hf.convolution_integrand' L <|
hg.mono_ac (quasiMeasurePreserving_sub_of_right_invariant μ ν).absolutelyContinuous
theorem Integrable.convolution_integrand (hf : Integrable f ν) (hg : Integrable g μ) :
Integrable (fun p : G × G => L (f p.2) (g (p.1 - p.2))) (μ.prod ν) := by
have h_meas : AEStronglyMeasurable (fun p : G × G => L (f p.2) (g (p.1 - p.2))) (μ.prod ν) :=
hf.aestronglyMeasurable.convolution_integrand L hg.aestronglyMeasurable
have h2_meas : AEStronglyMeasurable (fun y : G => ∫ x : G, ‖L (f y) (g (x - y))‖ ∂μ) ν :=
h_meas.prod_swap.norm.integral_prod_right'
simp_rw [integrable_prod_iff' h_meas]
refine ⟨Eventually.of_forall fun t => (L (f t)).integrable_comp (hg.comp_sub_right t), ?_⟩
refine Integrable.mono' ?_ h2_meas
(Eventually.of_forall fun t => (?_ : _ ≤ ‖L‖ * ‖f t‖ * ∫ x, ‖g (x - t)‖ ∂μ))
· simp only [integral_sub_right_eq_self (‖g ·‖)]
exact (hf.norm.const_mul _).mul_const _
· simp_rw [← integral_const_mul]
rw [Real.norm_of_nonneg (by positivity)]
exact integral_mono_of_nonneg (Eventually.of_forall fun t => norm_nonneg _)
((hg.comp_sub_right t).norm.const_mul _) (Eventually.of_forall fun t => L.le_opNorm₂ _ _)
theorem Integrable.ae_convolution_exists (hf : Integrable f ν) (hg : Integrable g μ) :
∀ᵐ x ∂μ, ConvolutionExistsAt f g x L ν :=
((integrable_prod_iff <|
hf.aestronglyMeasurable.convolution_integrand L hg.aestronglyMeasurable).mp <|
hf.convolution_integrand L hg).1
end Right
variable [TopologicalSpace G] [IsTopologicalAddGroup G] [BorelSpace G]
theorem _root_.HasCompactSupport.convolutionExistsAt {x₀ : G}
(h : HasCompactSupport fun t => L (f t) (g (x₀ - t))) (hf : LocallyIntegrable f μ)
(hg : Continuous g) : ConvolutionExistsAt f g x₀ L μ := by
let u := (Homeomorph.neg G).trans (Homeomorph.addRight x₀)
let v := (Homeomorph.neg G).trans (Homeomorph.addLeft x₀)
apply ((u.isCompact_preimage.mpr h).bddAbove_image hg.norm.continuousOn).convolutionExistsAt' L
isClosed_closure.measurableSet subset_closure (hf.integrableOn_isCompact h)
have A : AEStronglyMeasurable (g ∘ v)
(μ.restrict (tsupport fun t : G => L (f t) (g (x₀ - t)))) := by
apply (hg.comp v.continuous).continuousOn.aestronglyMeasurable_of_isCompact h
exact (isClosed_tsupport _).measurableSet
convert ((v.continuous.measurable.measurePreserving
(μ.restrict (tsupport fun t => L (f t) (g (x₀ - t))))).aestronglyMeasurable_comp_iff
v.measurableEmbedding).1 A
ext x
simp only [v, Homeomorph.neg, sub_eq_add_neg, val_toAddUnits_apply, Homeomorph.trans_apply,
Equiv.neg_apply, Equiv.toFun_as_coe, Homeomorph.homeomorph_mk_coe, Equiv.coe_fn_mk,
Homeomorph.coe_addLeft]
theorem _root_.HasCompactSupport.convolutionExists_right (hcg : HasCompactSupport g)
(hf : LocallyIntegrable f μ) (hg : Continuous g) : ConvolutionExists f g L μ := by
intro x₀
refine HasCompactSupport.convolutionExistsAt L ?_ hf hg
refine (hcg.comp_homeomorph (Homeomorph.subLeft x₀)).mono ?_
refine fun t => mt fun ht : g (x₀ - t) = 0 => ?_
simp_rw [ht, (L _).map_zero]
theorem _root_.HasCompactSupport.convolutionExists_left_of_continuous_right
(hcf : HasCompactSupport f) (hf : LocallyIntegrable f μ) (hg : Continuous g) :
ConvolutionExists f g L μ := by
intro x₀
refine HasCompactSupport.convolutionExistsAt L ?_ hf hg
refine hcf.mono ?_
refine fun t => mt fun ht : f t = 0 => ?_
simp_rw [ht, L.map_zero₂]
end Group
section CommGroup
variable [AddCommGroup G]
section MeasurableGroup
variable [MeasurableNeg G] [IsAddLeftInvariant μ]
/-- A sufficient condition to prove that `f ⋆[L, μ] g` exists.
We assume that the integrand has compact support and `g` is bounded on this support (note that
both properties hold if `g` is continuous with compact support). We also require that `f` is
integrable on the support of the integrand, and that both functions are strongly measurable.
This is a variant of `BddAbove.convolutionExistsAt'` in an abelian group with a left-invariant
measure. This allows us to state the boundedness and measurability of `g` in a more natural way. -/
theorem _root_.BddAbove.convolutionExistsAt [MeasurableAdd₂ G] [SFinite μ] {x₀ : G} {s : Set G}
(hbg : BddAbove ((fun i => ‖g i‖) '' ((fun t => x₀ - t) ⁻¹' s))) (hs : MeasurableSet s)
(h2s : (support fun t => L (f t) (g (x₀ - t))) ⊆ s) (hf : IntegrableOn f s μ)
(hmg : AEStronglyMeasurable g μ) : ConvolutionExistsAt f g x₀ L μ := by
refine BddAbove.convolutionExistsAt' L ?_ hs h2s hf ?_
· simp_rw [← sub_eq_neg_add, hbg]
· have : AEStronglyMeasurable g (map (fun t : G => x₀ - t) μ) :=
hmg.mono_ac (quasiMeasurePreserving_sub_left_of_right_invariant μ x₀).absolutelyContinuous
apply this.mono_measure
exact map_mono restrict_le_self (measurable_const.sub measurable_id')
variable {L} [MeasurableAdd G] [IsNegInvariant μ]
theorem convolutionExistsAt_flip :
ConvolutionExistsAt g f x L.flip μ ↔ ConvolutionExistsAt f g x L μ := by
simp_rw [ConvolutionExistsAt, ← integrable_comp_sub_left (fun t => L (f t) (g (x - t))) x,
sub_sub_cancel, flip_apply]
theorem ConvolutionExistsAt.integrable_swap (h : ConvolutionExistsAt f g x L μ) :
Integrable (fun t => L (f (x - t)) (g t)) μ := by
convert h.comp_sub_left x
simp_rw [sub_sub_self]
theorem convolutionExistsAt_iff_integrable_swap :
ConvolutionExistsAt f g x L μ ↔ Integrable (fun t => L (f (x - t)) (g t)) μ :=
convolutionExistsAt_flip.symm
end MeasurableGroup
variable [TopologicalSpace G] [IsTopologicalAddGroup G] [BorelSpace G]
variable [IsAddLeftInvariant μ] [IsNegInvariant μ]
theorem _root_.HasCompactSupport.convolutionExists_left
(hcf : HasCompactSupport f) (hf : Continuous f)
(hg : LocallyIntegrable g μ) : ConvolutionExists f g L μ := fun x₀ =>
convolutionExistsAt_flip.mp <| hcf.convolutionExists_right L.flip hg hf x₀
@[deprecated (since := "2025-02-06")]
alias _root_.HasCompactSupport.convolutionExistsLeft := HasCompactSupport.convolutionExists_left
theorem _root_.HasCompactSupport.convolutionExists_right_of_continuous_left
(hcg : HasCompactSupport g) (hf : Continuous f) (hg : LocallyIntegrable g μ) :
ConvolutionExists f g L μ := fun x₀ =>
convolutionExistsAt_flip.mp <| hcg.convolutionExists_left_of_continuous_right L.flip hg hf x₀
@[deprecated (since := "2025-02-06")]
alias _root_.HasCompactSupport.convolutionExistsRightOfContinuousLeft :=
HasCompactSupport.convolutionExists_right_of_continuous_left
end CommGroup
end ConvolutionExists
variable [NormedSpace ℝ F]
/-- The convolution of two functions `f` and `g` with respect to a continuous bilinear map `L` and
measure `μ`. It is defined to be `(f ⋆[L, μ] g) x = ∫ t, L (f t) (g (x - t)) ∂μ`. -/
noncomputable def convolution [Sub G] (f : G → E) (g : G → E') (L : E →L[𝕜] E' →L[𝕜] F)
(μ : Measure G := by volume_tac) : G → F := fun x =>
∫ t, L (f t) (g (x - t)) ∂μ
/-- The convolution of two functions with respect to a bilinear operation `L` and a measure `μ`. -/
scoped[Convolution] notation:67 f " ⋆[" L:67 ", " μ:67 "] " g:66 => convolution f g L μ
/-- The convolution of two functions with respect to a bilinear operation `L` and the volume. -/
scoped[Convolution]
notation:67 f " ⋆[" L:67 "]" g:66 => convolution f g L MeasureSpace.volume
/-- The convolution of two real-valued functions with respect to volume. -/
scoped[Convolution]
notation:67 f " ⋆ " g:66 =>
convolution f g (ContinuousLinearMap.lsmul ℝ ℝ) MeasureSpace.volume
open scoped Convolution
theorem convolution_def [Sub G] : (f ⋆[L, μ] g) x = ∫ t, L (f t) (g (x - t)) ∂μ :=
rfl
/-- The definition of convolution where the bilinear operator is scalar multiplication.
Note: it often helps the elaborator to give the type of the convolution explicitly. -/
theorem convolution_lsmul [Sub G] {f : G → 𝕜} {g : G → F} :
(f ⋆[lsmul 𝕜 𝕜, μ] g : G → F) x = ∫ t, f t • g (x - t) ∂μ :=
rfl
/-- The definition of convolution where the bilinear operator is multiplication. -/
theorem convolution_mul [Sub G] [NormedSpace ℝ 𝕜] {f : G → 𝕜} {g : G → 𝕜} :
(f ⋆[mul 𝕜 𝕜, μ] g) x = ∫ t, f t * g (x - t) ∂μ :=
rfl
section Group
variable {L} [AddGroup G]
theorem smul_convolution [SMulCommClass ℝ 𝕜 F] {y : 𝕜} : y • f ⋆[L, μ] g = y • (f ⋆[L, μ] g) := by
ext; simp only [Pi.smul_apply, convolution_def, ← integral_smul, L.map_smul₂]
theorem convolution_smul [SMulCommClass ℝ 𝕜 F] {y : 𝕜} : f ⋆[L, μ] y • g = y • (f ⋆[L, μ] g) := by
ext; simp only [Pi.smul_apply, convolution_def, ← integral_smul, (L _).map_smul]
@[simp]
theorem zero_convolution : 0 ⋆[L, μ] g = 0 := by
ext
simp_rw [convolution_def, Pi.zero_apply, L.map_zero₂, integral_zero]
@[simp]
theorem convolution_zero : f ⋆[L, μ] 0 = 0 := by
ext
simp_rw [convolution_def, Pi.zero_apply, (L _).map_zero, integral_zero]
theorem ConvolutionExistsAt.distrib_add {x : G} (hfg : ConvolutionExistsAt f g x L μ)
(hfg' : ConvolutionExistsAt f g' x L μ) :
(f ⋆[L, μ] (g + g')) x = (f ⋆[L, μ] g) x + (f ⋆[L, μ] g') x := by
simp only [convolution_def, (L _).map_add, Pi.add_apply, integral_add hfg hfg']
theorem ConvolutionExists.distrib_add (hfg : ConvolutionExists f g L μ)
(hfg' : ConvolutionExists f g' L μ) : f ⋆[L, μ] (g + g') = f ⋆[L, μ] g + f ⋆[L, μ] g' := by
ext x
exact (hfg x).distrib_add (hfg' x)
theorem ConvolutionExistsAt.add_distrib {x : G} (hfg : ConvolutionExistsAt f g x L μ)
(hfg' : ConvolutionExistsAt f' g x L μ) :
((f + f') ⋆[L, μ] g) x = (f ⋆[L, μ] g) x + (f' ⋆[L, μ] g) x := by
simp only [convolution_def, L.map_add₂, Pi.add_apply, integral_add hfg hfg']
theorem ConvolutionExists.add_distrib (hfg : ConvolutionExists f g L μ)
(hfg' : ConvolutionExists f' g L μ) : (f + f') ⋆[L, μ] g = f ⋆[L, μ] g + f' ⋆[L, μ] g := by
ext x
exact (hfg x).add_distrib (hfg' x)
theorem convolution_mono_right {f g g' : G → ℝ} (hfg : ConvolutionExistsAt f g x (lsmul ℝ ℝ) μ)
(hfg' : ConvolutionExistsAt f g' x (lsmul ℝ ℝ) μ) (hf : ∀ x, 0 ≤ f x) (hg : ∀ x, g x ≤ g' x) :
(f ⋆[lsmul ℝ ℝ, μ] g) x ≤ (f ⋆[lsmul ℝ ℝ, μ] g') x := by
apply integral_mono hfg hfg'
simp only [lsmul_apply, Algebra.id.smul_eq_mul]
intro t
apply mul_le_mul_of_nonneg_left (hg _) (hf _)
theorem convolution_mono_right_of_nonneg {f g g' : G → ℝ}
(hfg' : ConvolutionExistsAt f g' x (lsmul ℝ ℝ) μ) (hf : ∀ x, 0 ≤ f x) (hg : ∀ x, g x ≤ g' x)
(hg' : ∀ x, 0 ≤ g' x) : (f ⋆[lsmul ℝ ℝ, μ] g) x ≤ (f ⋆[lsmul ℝ ℝ, μ] g') x := by
by_cases H : ConvolutionExistsAt f g x (lsmul ℝ ℝ) μ
· exact convolution_mono_right H hfg' hf hg
have : (f ⋆[lsmul ℝ ℝ, μ] g) x = 0 := integral_undef H
rw [this]
exact integral_nonneg fun y => mul_nonneg (hf y) (hg' (x - y))
variable (L)
theorem convolution_congr [MeasurableAdd₂ G] [MeasurableNeg G] [SFinite μ]
[IsAddRightInvariant μ] (h1 : f =ᵐ[μ] f') (h2 : g =ᵐ[μ] g') : f ⋆[L, μ] g = f' ⋆[L, μ] g' := by
ext x
apply integral_congr_ae
exact (h1.prodMk <| h2.comp_tendsto
(quasiMeasurePreserving_sub_left_of_right_invariant μ x).tendsto_ae).fun_comp ↿fun x y ↦ L x y
theorem support_convolution_subset_swap : support (f ⋆[L, μ] g) ⊆ support g + support f := by
intro x h2x
by_contra hx
apply h2x
simp_rw [Set.mem_add, ← exists_and_left, not_exists, not_and_or, nmem_support] at hx
rw [convolution_def]
convert integral_zero G F using 2
ext t
rcases hx (x - t) t with (h | h | h)
· rw [h, (L _).map_zero]
· rw [h, L.map_zero₂]
· exact (h <| sub_add_cancel x t).elim
section
variable [MeasurableAdd₂ G] [MeasurableNeg G] [SFinite μ] [IsAddRightInvariant μ]
theorem Integrable.integrable_convolution (hf : Integrable f μ)
(hg : Integrable g μ) : Integrable (f ⋆[L, μ] g) μ :=
(hf.convolution_integrand L hg).integral_prod_left
end
variable [TopologicalSpace G]
variable [IsTopologicalAddGroup G]
protected theorem _root_.HasCompactSupport.convolution [T2Space G] (hcf : HasCompactSupport f)
(hcg : HasCompactSupport g) : HasCompactSupport (f ⋆[L, μ] g) :=
(hcg.isCompact.add hcf).of_isClosed_subset isClosed_closure <|
closure_minimal
((support_convolution_subset_swap L).trans <| add_subset_add subset_closure subset_closure)
(hcg.isCompact.add hcf).isClosed
variable [BorelSpace G] [TopologicalSpace P]
/-- The convolution `f * g` is continuous if `f` is locally integrable and `g` is continuous and
compactly supported. Version where `g` depends on an additional parameter in a subset `s` of
a parameter space `P` (and the compact support `k` is independent of the parameter in `s`). -/
theorem continuousOn_convolution_right_with_param {g : P → G → E'} {s : Set P} {k : Set G}
(hk : IsCompact k) (hgs : ∀ p, ∀ x, p ∈ s → x ∉ k → g p x = 0)
(hf : LocallyIntegrable f μ) (hg : ContinuousOn (↿g) (s ×ˢ univ)) :
ContinuousOn (fun q : P × G => (f ⋆[L, μ] g q.1) q.2) (s ×ˢ univ) := by
/- First get rid of the case where the space is not locally compact. Then `g` vanishes everywhere
and the conclusion is trivial. -/
by_cases H : ∀ p ∈ s, ∀ x, g p x = 0
· apply (continuousOn_const (c := 0)).congr
rintro ⟨p, x⟩ ⟨hp, -⟩
apply integral_eq_zero_of_ae (Eventually.of_forall (fun y ↦ ?_))
simp [H p hp _]
have : LocallyCompactSpace G := by
push_neg at H
rcases H with ⟨p, hp, x, hx⟩
have A : support (g p) ⊆ k := support_subset_iff'.2 (fun y hy ↦ hgs p y hp hy)
have B : Continuous (g p) := by
refine hg.comp_continuous (.prodMk_right _) fun x => ?_
simpa only [prodMk_mem_set_prod_eq, mem_univ, and_true] using hp
rcases eq_zero_or_locallyCompactSpace_of_support_subset_isCompact_of_addGroup hk A B with H|H
· simp [H] at hx
· exact H
/- Since `G` is locally compact, one may thicken `k` a little bit into a larger compact set
`(-k) + t`, outside of which all functions that appear in the convolution vanish. Then we can
apply a continuity statement for integrals depending on a parameter, with respect to
locally integrable functions and compactly supported continuous functions. -/
rintro ⟨q₀, x₀⟩ ⟨hq₀, -⟩
obtain ⟨t, t_comp, ht⟩ : ∃ t, IsCompact t ∧ t ∈ 𝓝 x₀ := exists_compact_mem_nhds x₀
let k' : Set G := (-k) +ᵥ t
have k'_comp : IsCompact k' := IsCompact.vadd_set hk.neg t_comp
let g' : (P × G) → G → E' := fun p x ↦ g p.1 (p.2 - x)
let s' : Set (P × G) := s ×ˢ t
have A : ContinuousOn g'.uncurry (s' ×ˢ univ) := by
have : g'.uncurry = g.uncurry ∘ (fun w ↦ (w.1.1, w.1.2 - w.2)) := by ext y; rfl
rw [this]
refine hg.comp (by fun_prop) ?_
simp +contextual [s', MapsTo]
have B : ContinuousOn (fun a ↦ ∫ x, L (f x) (g' a x) ∂μ) s' := by
apply continuousOn_integral_bilinear_of_locally_integrable_of_compact_support L k'_comp A _
(hf.integrableOn_isCompact k'_comp)
rintro ⟨p, x⟩ y ⟨hp, hx⟩ hy
apply hgs p _ hp
contrapose! hy
exact ⟨y - x, by simpa using hy, x, hx, by simp⟩
apply ContinuousWithinAt.mono_of_mem_nhdsWithin (B (q₀, x₀) ⟨hq₀, mem_of_mem_nhds ht⟩)
exact mem_nhdsWithin_prod_iff.2 ⟨s, self_mem_nhdsWithin, t, nhdsWithin_le_nhds ht, Subset.rfl⟩
/-- The convolution `f * g` is continuous if `f` is locally integrable and `g` is continuous and
compactly supported. Version where `g` depends on an additional parameter in an open subset `s` of
a parameter space `P` (and the compact support `k` is independent of the parameter in `s`),
given in terms of compositions with an additional continuous map. -/
theorem continuousOn_convolution_right_with_param_comp {s : Set P} {v : P → G}
(hv : ContinuousOn v s) {g : P → G → E'} {k : Set G} (hk : IsCompact k)
(hgs : ∀ p, ∀ x, p ∈ s → x ∉ k → g p x = 0) (hf : LocallyIntegrable f μ)
(hg : ContinuousOn (↿g) (s ×ˢ univ)) : ContinuousOn (fun x => (f ⋆[L, μ] g x) (v x)) s := by
apply
(continuousOn_convolution_right_with_param L hk hgs hf hg).comp (continuousOn_id.prodMk hv)
intro x hx
simp only [hx, prodMk_mem_set_prod_eq, mem_univ, and_self_iff, _root_.id]
/-- The convolution is continuous if one function is locally integrable and the other has compact
support and is continuous. -/
theorem _root_.HasCompactSupport.continuous_convolution_right (hcg : HasCompactSupport g)
(hf : LocallyIntegrable f μ) (hg : Continuous g) : Continuous (f ⋆[L, μ] g) := by
rw [continuous_iff_continuousOn_univ]
let g' : G → G → E' := fun _ q => g q
have : ContinuousOn (↿g') (univ ×ˢ univ) := (hg.comp continuous_snd).continuousOn
exact continuousOn_convolution_right_with_param_comp L
(continuous_iff_continuousOn_univ.1 continuous_id) hcg
(fun p x _ hx => image_eq_zero_of_nmem_tsupport hx) hf this
/-- The convolution is continuous if one function is integrable and the other is bounded and
continuous. -/
theorem _root_.BddAbove.continuous_convolution_right_of_integrable
[FirstCountableTopology G] [SecondCountableTopologyEither G E']
(hbg : BddAbove (range fun x => ‖g x‖)) (hf : Integrable f μ) (hg : Continuous g) :
Continuous (f ⋆[L, μ] g) := by
refine continuous_iff_continuousAt.mpr fun x₀ => ?_
have : ∀ᶠ x in 𝓝 x₀, ∀ᵐ t : G ∂μ, ‖L (f t) (g (x - t))‖ ≤ ‖L‖ * ‖f t‖ * ⨆ i, ‖g i‖ := by
filter_upwards with x; filter_upwards with t
apply_rules [L.le_of_opNorm₂_le_of_le, le_rfl, le_ciSup hbg (x - t)]
refine continuousAt_of_dominated ?_ this ?_ ?_
· exact Eventually.of_forall fun x =>
hf.aestronglyMeasurable.convolution_integrand_snd' L hg.aestronglyMeasurable
· exact (hf.norm.const_mul _).mul_const _
· exact Eventually.of_forall fun t => (L.continuous₂.comp₂ continuous_const <|
hg.comp <| continuous_id.sub continuous_const).continuousAt
end Group
section CommGroup
variable [AddCommGroup G]
theorem support_convolution_subset : support (f ⋆[L, μ] g) ⊆ support f + support g :=
(support_convolution_subset_swap L).trans (add_comm _ _).subset
variable [IsAddLeftInvariant μ] [IsNegInvariant μ]
section Measurable
variable [MeasurableNeg G]
variable [MeasurableAdd G]
/-- Commutativity of convolution -/
theorem convolution_flip : g ⋆[L.flip, μ] f = f ⋆[L, μ] g := by
ext1 x
simp_rw [convolution_def]
rw [← integral_sub_left_eq_self _ μ x]
simp_rw [sub_sub_self, flip_apply]
/-- The symmetric definition of convolution. -/
theorem convolution_eq_swap : (f ⋆[L, μ] g) x = ∫ t, L (f (x - t)) (g t) ∂μ := by
rw [← convolution_flip]; rfl
/-- The symmetric definition of convolution where the bilinear operator is scalar multiplication. -/
theorem convolution_lsmul_swap {f : G → 𝕜} {g : G → F} :
(f ⋆[lsmul 𝕜 𝕜, μ] g : G → F) x = ∫ t, f (x - t) • g t ∂μ :=
convolution_eq_swap _
/-- The symmetric definition of convolution where the bilinear operator is multiplication. -/
theorem convolution_mul_swap [NormedSpace ℝ 𝕜] {f : G → 𝕜} {g : G → 𝕜} :
(f ⋆[mul 𝕜 𝕜, μ] g) x = ∫ t, f (x - t) * g t ∂μ :=
convolution_eq_swap _
/-- The convolution of two even functions is also even. -/
theorem convolution_neg_of_neg_eq (h1 : ∀ᵐ x ∂μ, f (-x) = f x) (h2 : ∀ᵐ x ∂μ, g (-x) = g x) :
(f ⋆[L, μ] g) (-x) = (f ⋆[L, μ] g) x :=
calc
∫ t : G, (L (f t)) (g (-x - t)) ∂μ = ∫ t : G, (L (f (-t))) (g (x + t)) ∂μ := by
apply integral_congr_ae
filter_upwards [h1, (eventually_add_left_iff μ x).2 h2] with t ht h't
simp_rw [ht, ← h't, neg_add']
_ = ∫ t : G, (L (f t)) (g (x - t)) ∂μ := by
rw [← integral_neg_eq_self]
simp only [neg_neg, ← sub_eq_add_neg]
end Measurable
variable [TopologicalSpace G]
variable [IsTopologicalAddGroup G]
variable [BorelSpace G]
theorem _root_.HasCompactSupport.continuous_convolution_left
(hcf : HasCompactSupport f) (hf : Continuous f) (hg : LocallyIntegrable g μ) :
Continuous (f ⋆[L, μ] g) := by
rw [← convolution_flip]
exact hcf.continuous_convolution_right L.flip hg hf
theorem _root_.BddAbove.continuous_convolution_left_of_integrable
[FirstCountableTopology G] [SecondCountableTopologyEither G E]
(hbf : BddAbove (range fun x => ‖f x‖)) (hf : Continuous f) (hg : Integrable g μ) :
Continuous (f ⋆[L, μ] g) := by
rw [← convolution_flip]
exact hbf.continuous_convolution_right_of_integrable L.flip hg hf
end CommGroup
section NormedAddCommGroup
variable [SeminormedAddCommGroup G]
/-- Compute `(f ⋆ g) x₀` if the support of the `f` is within `Metric.ball 0 R`, and `g` is constant
on `Metric.ball x₀ R`.
We can simplify the RHS further if we assume `f` is integrable, but also if `L = (•)` or more
generally if `L` has an `AntilipschitzWith`-condition. -/
theorem convolution_eq_right' {x₀ : G} {R : ℝ} (hf : support f ⊆ ball (0 : G) R)
(hg : ∀ x ∈ ball x₀ R, g x = g x₀) : (f ⋆[L, μ] g) x₀ = ∫ t, L (f t) (g x₀) ∂μ := by
have h2 : ∀ t, L (f t) (g (x₀ - t)) = L (f t) (g x₀) := fun t ↦ by
by_cases ht : t ∈ support f
· have h2t := hf ht
rw [mem_ball_zero_iff] at h2t
specialize hg (x₀ - t)
rw [sub_eq_add_neg, add_mem_ball_iff_norm, norm_neg, ← sub_eq_add_neg] at hg
rw [hg h2t]
· rw [nmem_support] at ht
simp_rw [ht, L.map_zero₂]
simp_rw [convolution_def, h2]
variable [BorelSpace G] [SecondCountableTopology G]
variable [IsAddLeftInvariant μ] [SFinite μ]
/-- Approximate `(f ⋆ g) x₀` if the support of the `f` is bounded within a ball, and `g` is near
`g x₀` on a ball with the same radius around `x₀`. See `dist_convolution_le` for a special case.
We can simplify the second argument of `dist` further if we add some extra type-classes on `E`
and `𝕜` or if `L` is scalar multiplication. -/
theorem dist_convolution_le' {x₀ : G} {R ε : ℝ} {z₀ : E'} (hε : 0 ≤ ε) (hif : Integrable f μ)
(hf : support f ⊆ ball (0 : G) R) (hmg : AEStronglyMeasurable g μ)
(hg : ∀ x ∈ ball x₀ R, dist (g x) z₀ ≤ ε) :
dist ((f ⋆[L, μ] g : G → F) x₀) (∫ t, L (f t) z₀ ∂μ) ≤ (‖L‖ * ∫ x, ‖f x‖ ∂μ) * ε := by
have hfg : ConvolutionExistsAt f g x₀ L μ := by
refine BddAbove.convolutionExistsAt L ?_ Metric.isOpen_ball.measurableSet (Subset.trans ?_ hf)
hif.integrableOn hmg
swap; · refine fun t => mt fun ht : f t = 0 => ?_; simp_rw [ht, L.map_zero₂]
rw [bddAbove_def]
refine ⟨‖z₀‖ + ε, ?_⟩
rintro _ ⟨x, hx, rfl⟩
refine norm_le_norm_add_const_of_dist_le (hg x ?_)
rwa [mem_ball_iff_norm, norm_sub_rev, ← mem_ball_zero_iff]
have h2 : ∀ t, dist (L (f t) (g (x₀ - t))) (L (f t) z₀) ≤ ‖L (f t)‖ * ε := by
intro t; by_cases ht : t ∈ support f
· have h2t := hf ht
rw [mem_ball_zero_iff] at h2t
specialize hg (x₀ - t)
rw [sub_eq_add_neg, add_mem_ball_iff_norm, norm_neg, ← sub_eq_add_neg] at hg
refine ((L (f t)).dist_le_opNorm _ _).trans ?_
exact mul_le_mul_of_nonneg_left (hg h2t) (norm_nonneg _)
· rw [nmem_support] at ht
simp_rw [ht, L.map_zero₂, L.map_zero, norm_zero, zero_mul, dist_self]
rfl
simp_rw [convolution_def]
simp_rw [dist_eq_norm] at h2 ⊢
rw [← integral_sub hfg.integrable]; swap; · exact (L.flip z₀).integrable_comp hif
refine (norm_integral_le_of_norm_le ((L.integrable_comp hif).norm.mul_const ε)
(Eventually.of_forall h2)).trans ?_
rw [integral_mul_const]
refine mul_le_mul_of_nonneg_right ?_ hε
have h3 : ∀ t, ‖L (f t)‖ ≤ ‖L‖ * ‖f t‖ := by
intro t
exact L.le_opNorm (f t)
refine (integral_mono (L.integrable_comp hif).norm (hif.norm.const_mul _) h3).trans_eq ?_
rw [integral_const_mul]
variable [NormedSpace ℝ E] [NormedSpace ℝ E'] [CompleteSpace E']
/-- Approximate `f ⋆ g` if the support of the `f` is bounded within a ball, and `g` is near `g x₀`
on a ball with the same radius around `x₀`.
This is a special case of `dist_convolution_le'` where `L` is `(•)`, `f` has integral 1 and `f` is
nonnegative. -/
theorem dist_convolution_le {f : G → ℝ} {x₀ : G} {R ε : ℝ} {z₀ : E'} (hε : 0 ≤ ε)
(hf : support f ⊆ ball (0 : G) R) (hnf : ∀ x, 0 ≤ f x) (hintf : ∫ x, f x ∂μ = 1)
(hmg : AEStronglyMeasurable g μ) (hg : ∀ x ∈ ball x₀ R, dist (g x) z₀ ≤ ε) :
dist ((f ⋆[lsmul ℝ ℝ, μ] g : G → E') x₀) z₀ ≤ ε := by
have hif : Integrable f μ := integrable_of_integral_eq_one hintf
convert (dist_convolution_le' (lsmul ℝ ℝ) hε hif hf hmg hg).trans _
· simp_rw [lsmul_apply, integral_smul_const, hintf, one_smul]
· simp_rw [Real.norm_of_nonneg (hnf _), hintf, mul_one]
exact (mul_le_mul_of_nonneg_right opNorm_lsmul_le hε).trans_eq (one_mul ε)
/-- `(φ i ⋆ g i) (k i)` tends to `z₀` as `i` tends to some filter `l` if
* `φ` is a sequence of nonnegative functions with integral `1` as `i` tends to `l`;
* The support of `φ` tends to small neighborhoods around `(0 : G)` as `i` tends to `l`;
* `g i` is `mu`-a.e. strongly measurable as `i` tends to `l`;
* `g i x` tends to `z₀` as `(i, x)` tends to `l ×ˢ 𝓝 x₀`;
* `k i` tends to `x₀`.
See also `ContDiffBump.convolution_tendsto_right`.
-/
theorem convolution_tendsto_right {ι} {g : ι → G → E'} {l : Filter ι} {x₀ : G} {z₀ : E'}
{φ : ι → G → ℝ} {k : ι → G} (hnφ : ∀ᶠ i in l, ∀ x, 0 ≤ φ i x)
(hiφ : ∀ᶠ i in l, ∫ x, φ i x ∂μ = 1)
-- todo: we could weaken this to "the integral tends to 1"
(hφ : Tendsto (fun n => support (φ n)) l (𝓝 0).smallSets)
(hmg : ∀ᶠ i in l, AEStronglyMeasurable (g i) μ) (hcg : Tendsto (uncurry g) (l ×ˢ 𝓝 x₀) (𝓝 z₀))
(hk : Tendsto k l (𝓝 x₀)) :
Tendsto (fun i : ι => (φ i ⋆[lsmul ℝ ℝ, μ] g i : G → E') (k i)) l (𝓝 z₀) := by
simp_rw [tendsto_smallSets_iff] at hφ
rw [Metric.tendsto_nhds] at hcg ⊢
simp_rw [Metric.eventually_prod_nhds_iff] at hcg
intro ε hε
have h2ε : 0 < ε / 3 := div_pos hε (by norm_num)
obtain ⟨p, hp, δ, hδ, hgδ⟩ := hcg _ h2ε
dsimp only [uncurry] at hgδ
have h2k := hk.eventually (ball_mem_nhds x₀ <| half_pos hδ)
have h2φ := hφ (ball (0 : G) _) <| ball_mem_nhds _ (half_pos hδ)
filter_upwards [hp, h2k, h2φ, hnφ, hiφ, hmg] with i hpi hki hφi hnφi hiφi hmgi
have hgi : dist (g i (k i)) z₀ < ε / 3 := hgδ hpi (hki.trans <| half_lt_self hδ)
have h1 : ∀ x' ∈ ball (k i) (δ / 2), dist (g i x') (g i (k i)) ≤ ε / 3 + ε / 3 := by
intro x' hx'
refine (dist_triangle_right _ _ _).trans (add_le_add (hgδ hpi ?_).le hgi.le)
exact ((dist_triangle _ _ _).trans_lt (add_lt_add hx'.out hki)).trans_eq (add_halves δ)
have := dist_convolution_le (add_pos h2ε h2ε).le hφi hnφi hiφi hmgi h1
refine ((dist_triangle _ _ _).trans_lt (add_lt_add_of_le_of_lt this hgi)).trans_eq ?_
field_simp; ring_nf
end NormedAddCommGroup
end Measurability
end NontriviallyNormedField
open scoped Convolution
section RCLike
variable [RCLike 𝕜]
variable [NormedSpace 𝕜 E]
variable [NormedSpace 𝕜 E']
variable [NormedSpace 𝕜 E'']
variable [NormedSpace ℝ F] [NormedSpace 𝕜 F]
variable {n : ℕ∞}
variable [MeasurableSpace G] {μ ν : Measure G}
variable (L : E →L[𝕜] E' →L[𝕜] F)
section Assoc
variable [CompleteSpace F]
variable [NormedAddCommGroup F'] [NormedSpace ℝ F'] [NormedSpace 𝕜 F'] [CompleteSpace F']
variable [NormedAddCommGroup F''] [NormedSpace ℝ F''] [NormedSpace 𝕜 F''] [CompleteSpace F'']
variable {k : G → E''}
variable (L₂ : F →L[𝕜] E'' →L[𝕜] F')
variable (L₃ : E →L[𝕜] F'' →L[𝕜] F')
variable (L₄ : E' →L[𝕜] E'' →L[𝕜] F'')
variable [AddGroup G]
variable [SFinite μ] [SFinite ν] [IsAddRightInvariant μ]
theorem integral_convolution [MeasurableAdd₂ G] [MeasurableNeg G] [NormedSpace ℝ E]
[NormedSpace ℝ E'] [CompleteSpace E] [CompleteSpace E'] (hf : Integrable f ν)
(hg : Integrable g μ) : ∫ x, (f ⋆[L, ν] g) x ∂μ = L (∫ x, f x ∂ν) (∫ x, g x ∂μ) := by
refine (integral_integral_swap (by apply hf.convolution_integrand L hg)).trans ?_
simp_rw [integral_comp_comm _ (hg.comp_sub_right _), integral_sub_right_eq_self]
exact (L.flip (∫ x, g x ∂μ)).integral_comp_comm hf
variable [MeasurableAdd₂ G] [IsAddRightInvariant ν] [MeasurableNeg G]
/-- Convolution is associative. This has a weak but inconvenient integrability condition.
See also `MeasureTheory.convolution_assoc`. -/
theorem convolution_assoc' (hL : ∀ (x : E) (y : E') (z : E''), L₂ (L x y) z = L₃ x (L₄ y z))
{x₀ : G} (hfg : ∀ᵐ y ∂μ, ConvolutionExistsAt f g y L ν)
(hgk : ∀ᵐ x ∂ν, ConvolutionExistsAt g k x L₄ μ)
(hi : Integrable (uncurry fun x y => (L₃ (f y)) ((L₄ (g (x - y))) (k (x₀ - x)))) (μ.prod ν)) :
((f ⋆[L, ν] g) ⋆[L₂, μ] k) x₀ = (f ⋆[L₃, ν] g ⋆[L₄, μ] k) x₀ :=
calc
((f ⋆[L, ν] g) ⋆[L₂, μ] k) x₀ = ∫ t, L₂ (∫ s, L (f s) (g (t - s)) ∂ν) (k (x₀ - t)) ∂μ := rfl
_ = ∫ t, ∫ s, L₂ (L (f s) (g (t - s))) (k (x₀ - t)) ∂ν ∂μ :=
(integral_congr_ae (hfg.mono fun t ht => ((L₂.flip (k (x₀ - t))).integral_comp_comm ht).symm))
_ = ∫ t, ∫ s, L₃ (f s) (L₄ (g (t - s)) (k (x₀ - t))) ∂ν ∂μ := by simp_rw [hL]
_ = ∫ s, ∫ t, L₃ (f s) (L₄ (g (t - s)) (k (x₀ - t))) ∂μ ∂ν := by rw [integral_integral_swap hi]
_ = ∫ s, ∫ u, L₃ (f s) (L₄ (g u) (k (x₀ - s - u))) ∂μ ∂ν := by
congr; ext t
rw [eq_comm, ← integral_sub_right_eq_self _ t]
simp_rw [sub_sub_sub_cancel_right]
_ = ∫ s, L₃ (f s) (∫ u, L₄ (g u) (k (x₀ - s - u)) ∂μ) ∂ν := by
refine integral_congr_ae ?_
refine ((quasiMeasurePreserving_sub_left_of_right_invariant ν x₀).ae hgk).mono fun t ht => ?_
exact (L₃ (f t)).integral_comp_comm ht
_ = (f ⋆[L₃, ν] g ⋆[L₄, μ] k) x₀ := rfl
/-- Convolution is associative. This requires that
* all maps are a.e. strongly measurable w.r.t one of the measures
* `f ⋆[L, ν] g` exists almost everywhere
* `‖g‖ ⋆[μ] ‖k‖` exists almost everywhere
* `‖f‖ ⋆[ν] (‖g‖ ⋆[μ] ‖k‖)` exists at `x₀` -/
theorem convolution_assoc (hL : ∀ (x : E) (y : E') (z : E''), L₂ (L x y) z = L₃ x (L₄ y z)) {x₀ : G}
(hf : AEStronglyMeasurable f ν) (hg : AEStronglyMeasurable g μ) (hk : AEStronglyMeasurable k μ)
(hfg : ∀ᵐ y ∂μ, ConvolutionExistsAt f g y L ν)
(hgk : ∀ᵐ x ∂ν, ConvolutionExistsAt (fun x => ‖g x‖) (fun x => ‖k x‖) x (mul ℝ ℝ) μ)
(hfgk :
ConvolutionExistsAt (fun x => ‖f x‖) ((fun x => ‖g x‖) ⋆[mul ℝ ℝ, μ] fun x => ‖k x‖) x₀
(mul ℝ ℝ) ν) :
((f ⋆[L, ν] g) ⋆[L₂, μ] k) x₀ = (f ⋆[L₃, ν] g ⋆[L₄, μ] k) x₀ := by
refine convolution_assoc' L L₂ L₃ L₄ hL hfg (hgk.mono fun x hx => hx.of_norm L₄ hg hk) ?_
-- the following is similar to `Integrable.convolution_integrand`
have h_meas :
AEStronglyMeasurable (uncurry fun x y => L₃ (f y) (L₄ (g x) (k (x₀ - y - x))))
(μ.prod ν) := by
refine L₃.aestronglyMeasurable_comp₂ hf.snd ?_
refine L₄.aestronglyMeasurable_comp₂ hg.fst ?_
refine (hk.mono_ac ?_).comp_measurable
((measurable_const.sub measurable_snd).sub measurable_fst)
refine QuasiMeasurePreserving.absolutelyContinuous ?_
refine QuasiMeasurePreserving.prod_of_left
((measurable_const.sub measurable_snd).sub measurable_fst) (Eventually.of_forall fun y => ?_)
dsimp only
exact quasiMeasurePreserving_sub_left_of_right_invariant μ _
have h2_meas :
AEStronglyMeasurable (fun y => ∫ x, ‖L₃ (f y) (L₄ (g x) (k (x₀ - y - x)))‖ ∂μ) ν :=
h_meas.prod_swap.norm.integral_prod_right'
have h3 : map (fun z : G × G => (z.1 - z.2, z.2)) (μ.prod ν) = μ.prod ν :=
(measurePreserving_sub_prod μ ν).map_eq
suffices Integrable (uncurry fun x y => L₃ (f y) (L₄ (g x) (k (x₀ - y - x)))) (μ.prod ν) by
rw [← h3] at this
convert this.comp_measurable (measurable_sub.prodMk measurable_snd)
ext ⟨x, y⟩
simp +unfoldPartialApp only [uncurry, Function.comp_apply,
sub_sub_sub_cancel_right]
simp_rw [integrable_prod_iff' h_meas]
refine ⟨((quasiMeasurePreserving_sub_left_of_right_invariant ν x₀).ae hgk).mono fun t ht =>
(L₃ (f t)).integrable_comp <| ht.of_norm L₄ hg hk, ?_⟩
refine (hfgk.const_mul (‖L₃‖ * ‖L₄‖)).mono' h2_meas
(((quasiMeasurePreserving_sub_left_of_right_invariant ν x₀).ae hgk).mono fun t ht => ?_)
simp_rw [convolution_def, mul_apply', mul_mul_mul_comm ‖L₃‖ ‖L₄‖, ← integral_const_mul]
rw [Real.norm_of_nonneg (by positivity)]
refine integral_mono_of_nonneg (Eventually.of_forall fun t => norm_nonneg _)
((ht.const_mul _).const_mul _) (Eventually.of_forall fun s => ?_)
simp only [← mul_assoc ‖L₄‖]
apply_rules [ContinuousLinearMap.le_of_opNorm₂_le_of_le, le_rfl]
end Assoc
variable [NormedAddCommGroup G] [BorelSpace G]
theorem convolution_precompR_apply {g : G → E'' →L[𝕜] E'} (hf : LocallyIntegrable f μ)
(hcg : HasCompactSupport g) (hg : Continuous g) (x₀ : G) (x : E'') :
(f ⋆[L.precompR E'', μ] g) x₀ x = (f ⋆[L, μ] fun a => g a x) x₀ := by
have := hcg.convolutionExists_right (L.precompR E'' :) hf hg x₀
simp_rw [convolution_def, ContinuousLinearMap.integral_apply this]
rfl
variable [NormedSpace 𝕜 G] [SFinite μ] [IsAddLeftInvariant μ]
/-- Compute the total derivative of `f ⋆ g` if `g` is `C^1` with compact support and `f` is locally
integrable. To write down the total derivative as a convolution, we use
`ContinuousLinearMap.precompR`. -/
theorem _root_.HasCompactSupport.hasFDerivAt_convolution_right (hcg : HasCompactSupport g)
(hf : LocallyIntegrable f μ) (hg : ContDiff 𝕜 1 g) (x₀ : G) :
HasFDerivAt (f ⋆[L, μ] g) ((f ⋆[L.precompR G, μ] fderiv 𝕜 g) x₀) x₀ := by
rcases hcg.eq_zero_or_finiteDimensional 𝕜 hg.continuous with (rfl | fin_dim)
· have : fderiv 𝕜 (0 : G → E') = 0 := fderiv_const (0 : E')
simp only [this, convolution_zero, Pi.zero_apply]
exact hasFDerivAt_const (0 : F) x₀
have : ProperSpace G := FiniteDimensional.proper_rclike 𝕜 G
set L' := L.precompR G
have h1 : ∀ᶠ x in 𝓝 x₀, AEStronglyMeasurable (fun t => L (f t) (g (x - t))) μ :=
Eventually.of_forall
(hf.aestronglyMeasurable.convolution_integrand_snd L hg.continuous.aestronglyMeasurable)
have h2 : ∀ x, AEStronglyMeasurable (fun t => L' (f t) (fderiv 𝕜 g (x - t))) μ :=
hf.aestronglyMeasurable.convolution_integrand_snd L'
(hg.continuous_fderiv le_rfl).aestronglyMeasurable
have h3 : ∀ x t, HasFDerivAt (fun x => g (x - t)) (fderiv 𝕜 g (x - t)) x := fun x t ↦ by
simpa using
(hg.differentiable le_rfl).differentiableAt.hasFDerivAt.comp x
((hasFDerivAt_id x).sub (hasFDerivAt_const t x))
let K' := -tsupport (fderiv 𝕜 g) + closedBall x₀ 1
have hK' : IsCompact K' := (hcg.fderiv 𝕜).neg.add (isCompact_closedBall x₀ 1)
apply hasFDerivAt_integral_of_dominated_of_fderiv_le zero_lt_one h1 _ (h2 x₀)
· filter_upwards with t x hx using
(hcg.fderiv 𝕜).convolution_integrand_bound_right L' (hg.continuous_fderiv le_rfl)
(ball_subset_closedBall hx)
· rw [integrable_indicator_iff hK'.measurableSet]
exact ((hf.integrableOn_isCompact hK').norm.const_mul _).mul_const _
· exact Eventually.of_forall fun t x _ => (L _).hasFDerivAt.comp x (h3 x t)
· exact hcg.convolutionExists_right L hf hg.continuous x₀
theorem _root_.HasCompactSupport.hasFDerivAt_convolution_left [IsNegInvariant μ]
(hcf : HasCompactSupport f) (hf : ContDiff 𝕜 1 f) (hg : LocallyIntegrable g μ) (x₀ : G) :
HasFDerivAt (f ⋆[L, μ] g) ((fderiv 𝕜 f ⋆[L.precompL G, μ] g) x₀) x₀ := by
simp +singlePass only [← convolution_flip]
exact hcf.hasFDerivAt_convolution_right L.flip hg hf x₀
end RCLike
section Real
/-! The one-variable case -/
variable [RCLike 𝕜]
variable [NormedSpace 𝕜 E]
variable [NormedSpace 𝕜 E']
variable [NormedSpace ℝ F] [NormedSpace 𝕜 F]
variable {f₀ : 𝕜 → E} {g₀ : 𝕜 → E'}
variable {n : ℕ∞}
variable (L : E →L[𝕜] E' →L[𝕜] F)
variable {μ : Measure 𝕜}
variable [IsAddLeftInvariant μ] [SFinite μ]
theorem _root_.HasCompactSupport.hasDerivAt_convolution_right (hf : LocallyIntegrable f₀ μ)
(hcg : HasCompactSupport g₀) (hg : ContDiff 𝕜 1 g₀) (x₀ : 𝕜) :
HasDerivAt (f₀ ⋆[L, μ] g₀) ((f₀ ⋆[L, μ] deriv g₀) x₀) x₀ := by
convert (hcg.hasFDerivAt_convolution_right L hf hg x₀).hasDerivAt using 1
rw [convolution_precompR_apply L hf (hcg.fderiv 𝕜) (hg.continuous_fderiv le_rfl)]
rfl
theorem _root_.HasCompactSupport.hasDerivAt_convolution_left [IsNegInvariant μ]
(hcf : HasCompactSupport f₀) (hf : ContDiff 𝕜 1 f₀) (hg : LocallyIntegrable g₀ μ) (x₀ : 𝕜) :
HasDerivAt (f₀ ⋆[L, μ] g₀) ((deriv f₀ ⋆[L, μ] g₀) x₀) x₀ := by
simp +singlePass only [← convolution_flip]
exact hcf.hasDerivAt_convolution_right L.flip hg hf x₀
end Real
section WithParam
variable [RCLike 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 E'] [NormedSpace 𝕜 E''] [NormedSpace ℝ F]
[NormedSpace 𝕜 F] [MeasurableSpace G] [NormedAddCommGroup G] [BorelSpace G]
[NormedSpace 𝕜 G] [NormedAddCommGroup P] [NormedSpace 𝕜 P] {μ : Measure G}
(L : E →L[𝕜] E' →L[𝕜] F)
/-- The derivative of the convolution `f * g` is given by `f * Dg`, when `f` is locally integrable
and `g` is `C^1` and compactly supported. Version where `g` depends on an additional parameter in an
open subset `s` of a parameter space `P` (and the compact support `k` is independent of the
parameter in `s`). -/
theorem hasFDerivAt_convolution_right_with_param {g : P → G → E'} {s : Set P} {k : Set G}
(hs : IsOpen s) (hk : IsCompact k) (hgs : ∀ p, ∀ x, p ∈ s → x ∉ k → g p x = 0)
(hf : LocallyIntegrable f μ) (hg : ContDiffOn 𝕜 1 (↿g) (s ×ˢ univ)) (q₀ : P × G)
(hq₀ : q₀.1 ∈ s) :
HasFDerivAt (fun q : P × G => (f ⋆[L, μ] g q.1) q.2)
((f ⋆[L.precompR (P × G), μ] fun x : G => fderiv 𝕜 (↿g) (q₀.1, x)) q₀.2) q₀ := by
let g' := fderiv 𝕜 ↿g
have A : ∀ p ∈ s, Continuous (g p) := fun p hp ↦ by
refine hg.continuousOn.comp_continuous (.prodMk_right _) fun x => ?_
simpa only [prodMk_mem_set_prod_eq, mem_univ, and_true] using hp
have A' : ∀ q : P × G, q.1 ∈ s → s ×ˢ univ ∈ 𝓝 q := fun q hq ↦ by
apply (hs.prod isOpen_univ).mem_nhds
simpa only [mem_prod, mem_univ, and_true] using hq
-- The derivative of `g` vanishes away from `k`.
have g'_zero : ∀ p x, p ∈ s → x ∉ k → g' (p, x) = 0 := by
intro p x hp hx
refine (hasFDerivAt_zero_of_eventually_const 0 ?_).fderiv
have M2 : kᶜ ∈ 𝓝 x := hk.isClosed.isOpen_compl.mem_nhds hx
have M1 : s ∈ 𝓝 p := hs.mem_nhds hp
rw [nhds_prod_eq]
filter_upwards [prod_mem_prod M1 M2]
rintro ⟨p, y⟩ ⟨hp, hy⟩
exact hgs p y hp hy
/- We find a small neighborhood of `{q₀.1} × k` on which the derivative is uniformly bounded. This
follows from the continuity at all points of the compact set `k`. -/
obtain ⟨ε, C, εpos, h₀ε, hε⟩ :
∃ ε C, 0 < ε ∧ ball q₀.1 ε ⊆ s ∧ ∀ p x, ‖p - q₀.1‖ < ε → ‖g' (p, x)‖ ≤ C := by
have A : IsCompact ({q₀.1} ×ˢ k) := isCompact_singleton.prod hk
obtain ⟨t, kt, t_open, ht⟩ : ∃ t, {q₀.1} ×ˢ k ⊆ t ∧ IsOpen t ∧ IsBounded (g' '' t) := by
have B : ContinuousOn g' (s ×ˢ univ) :=
hg.continuousOn_fderiv_of_isOpen (hs.prod isOpen_univ) le_rfl
apply exists_isOpen_isBounded_image_of_isCompact_of_continuousOn A (hs.prod isOpen_univ) _ B
simp only [prod_subset_prod_iff, hq₀, singleton_subset_iff, subset_univ, and_self_iff,
true_or]
obtain ⟨ε, εpos, hε, h'ε⟩ :
∃ ε : ℝ, 0 < ε ∧ thickening ε ({q₀.fst} ×ˢ k) ⊆ t ∧ ball q₀.1 ε ⊆ s := by
obtain ⟨ε, εpos, hε⟩ : ∃ ε : ℝ, 0 < ε ∧ thickening ε (({q₀.fst} : Set P) ×ˢ k) ⊆ t :=
A.exists_thickening_subset_open t_open kt
obtain ⟨δ, δpos, hδ⟩ : ∃ δ : ℝ, 0 < δ ∧ ball q₀.1 δ ⊆ s := Metric.isOpen_iff.1 hs _ hq₀
refine ⟨min ε δ, lt_min εpos δpos, ?_, ?_⟩
· exact Subset.trans (thickening_mono (min_le_left _ _) _) hε
· exact Subset.trans (ball_subset_ball (min_le_right _ _)) hδ
obtain ⟨C, Cpos, hC⟩ : ∃ C, 0 < C ∧ g' '' t ⊆ closedBall 0 C := ht.subset_closedBall_lt 0 0
refine ⟨ε, C, εpos, h'ε, fun p x hp => ?_⟩
have hps : p ∈ s := h'ε (mem_ball_iff_norm.2 hp)
by_cases hx : x ∈ k
· have H : (p, x) ∈ t := by
apply hε
refine mem_thickening_iff.2 ⟨(q₀.1, x), ?_, ?_⟩
· simp only [hx, singleton_prod, mem_image, Prod.mk_inj, eq_self_iff_true, true_and,
exists_eq_right]
· rw [← dist_eq_norm] at hp
simpa only [Prod.dist_eq, εpos, dist_self, max_lt_iff, and_true] using hp
have : g' (p, x) ∈ closedBall (0 : P × G →L[𝕜] E') C := hC (mem_image_of_mem _ H)
rwa [mem_closedBall_zero_iff] at this
· have : g' (p, x) = 0 := g'_zero _ _ hps hx
rw [this]
simpa only [norm_zero] using Cpos.le
/- Now, we wish to apply a theorem on differentiation of integrals. For this, we need to check
trivial measurability or integrability assumptions (in `I1`, `I2`, `I3`), as well as a uniform
integrability assumption over the derivative (in `I4` and `I5`) and pointwise differentiability
in `I6`. -/
have I1 :
∀ᶠ x : P × G in 𝓝 q₀, AEStronglyMeasurable (fun a : G => L (f a) (g x.1 (x.2 - a))) μ := by
filter_upwards [A' q₀ hq₀]
rintro ⟨p, x⟩ ⟨hp, -⟩
refine (HasCompactSupport.convolutionExists_right L ?_ hf (A _ hp) _).1
apply hk.of_isClosed_subset (isClosed_tsupport _)
exact closure_minimal (support_subset_iff'.2 fun z hz => hgs _ _ hp hz) hk.isClosed
have I2 : Integrable (fun a : G => L (f a) (g q₀.1 (q₀.2 - a))) μ := by
have M : HasCompactSupport (g q₀.1) := HasCompactSupport.intro hk fun x hx => hgs q₀.1 x hq₀ hx
apply M.convolutionExists_right L hf (A q₀.1 hq₀) q₀.2
have I3 : AEStronglyMeasurable (fun a : G => (L (f a)).comp (g' (q₀.fst, q₀.snd - a))) μ := by
have T : HasCompactSupport fun y => g' (q₀.1, y) :=
HasCompactSupport.intro hk fun x hx => g'_zero q₀.1 x hq₀ hx
apply (HasCompactSupport.convolutionExists_right (L.precompR (P × G) :) T hf _ q₀.2).1
have : ContinuousOn g' (s ×ˢ univ) :=
hg.continuousOn_fderiv_of_isOpen (hs.prod isOpen_univ) le_rfl
apply this.comp_continuous (.prodMk_right _)
intro x
simpa only [prodMk_mem_set_prod_eq, mem_univ, and_true] using hq₀
set K' := (-k + {q₀.2} : Set G) with K'_def
have hK' : IsCompact K' := hk.neg.add isCompact_singleton
obtain ⟨U, U_open, K'U, hU⟩ : ∃ U, IsOpen U ∧ K' ⊆ U ∧ IntegrableOn f U μ :=
hf.integrableOn_nhds_isCompact hK'
obtain ⟨δ, δpos, δε, hδ⟩ : ∃ δ, (0 : ℝ) < δ ∧ δ ≤ ε ∧ K' + ball 0 δ ⊆ U := by
obtain ⟨V, V_mem, hV⟩ : ∃ V ∈ 𝓝 (0 : G), K' + V ⊆ U :=
compact_open_separated_add_right hK' U_open K'U
rcases Metric.mem_nhds_iff.1 V_mem with ⟨δ, δpos, hδ⟩
refine ⟨min δ ε, lt_min δpos εpos, min_le_right δ ε, ?_⟩
exact (add_subset_add_left ((ball_subset_ball (min_le_left _ _)).trans hδ)).trans hV
letI := ContinuousLinearMap.hasOpNorm (𝕜 := 𝕜) (𝕜₂ := 𝕜) (E := E)
(F := (P × G →L[𝕜] E') →L[𝕜] P × G →L[𝕜] F) (σ₁₂ := RingHom.id 𝕜)
let bound : G → ℝ := indicator U fun t => ‖(L.precompR (P × G))‖ * ‖f t‖ * C
have I4 : ∀ᵐ a : G ∂μ, ∀ x : P × G, dist x q₀ < δ →
‖L.precompR (P × G) (f a) (g' (x.fst, x.snd - a))‖ ≤ bound a := by
filter_upwards with a x hx
rw [Prod.dist_eq, dist_eq_norm, dist_eq_norm] at hx
have : (-tsupport fun a => g' (x.1, a)) + ball q₀.2 δ ⊆ U := by
apply Subset.trans _ hδ
rw [K'_def, add_assoc]
apply add_subset_add
· rw [neg_subset_neg]
refine closure_minimal (support_subset_iff'.2 fun z hz => ?_) hk.isClosed
apply g'_zero x.1 z (h₀ε _) hz
rw [mem_ball_iff_norm]
exact ((le_max_left _ _).trans_lt hx).trans_le δε
· simp only [add_ball, thickening_singleton, zero_vadd, subset_rfl]
apply convolution_integrand_bound_right_of_le_of_subset _ _ _ this
· intro y
exact hε _ _ (((le_max_left _ _).trans_lt hx).trans_le δε)
· rw [mem_ball_iff_norm]
exact (le_max_right _ _).trans_lt hx
have I5 : Integrable bound μ := by
rw [integrable_indicator_iff U_open.measurableSet]
exact (hU.norm.const_mul _).mul_const _
have I6 : ∀ᵐ a : G ∂μ, ∀ x : P × G, dist x q₀ < δ →
HasFDerivAt (fun x : P × G => L (f a) (g x.1 (x.2 - a)))
((L (f a)).comp (g' (x.fst, x.snd - a))) x := by
filter_upwards with a x hx
apply (L _).hasFDerivAt.comp x
have N : s ×ˢ univ ∈ 𝓝 (x.1, x.2 - a) := by
apply A'
apply h₀ε
rw [Prod.dist_eq] at hx
exact lt_of_lt_of_le (lt_of_le_of_lt (le_max_left _ _) hx) δε
have Z := ((hg.differentiableOn le_rfl).differentiableAt N).hasFDerivAt
have Z' :
HasFDerivAt (fun x : P × G => (x.1, x.2 - a)) (ContinuousLinearMap.id 𝕜 (P × G)) x := by
have : (fun x : P × G => (x.1, x.2 - a)) = _root_.id - fun x => (0, a) := by
ext x <;> simp only [Pi.sub_apply, _root_.id, Prod.fst_sub, sub_zero, Prod.snd_sub]
rw [this]
exact (hasFDerivAt_id x).sub_const (0, a)
exact Z.comp x Z'
exact hasFDerivAt_integral_of_dominated_of_fderiv_le δpos I1 I2 I3 I4 I5 I6
/-- The convolution `f * g` is `C^n` when `f` is locally integrable and `g` is `C^n` and compactly
supported. Version where `g` depends on an additional parameter in an open subset `s` of a
parameter space `P` (and the compact support `k` is independent of the parameter in `s`).
In this version, all the types belong to the same universe (to get an induction working in the
proof). Use instead `contDiffOn_convolution_right_with_param`, which removes this restriction. -/
theorem contDiffOn_convolution_right_with_param_aux {G : Type uP} {E' : Type uP} {F : Type uP}
{P : Type uP} [NormedAddCommGroup E'] [NormedAddCommGroup F] [NormedSpace 𝕜 E']
[NormedSpace ℝ F] [NormedSpace 𝕜 F] [MeasurableSpace G]
{μ : Measure G}
[NormedAddCommGroup G] [BorelSpace G] [NormedSpace 𝕜 G] [NormedAddCommGroup P] [NormedSpace 𝕜 P]
{f : G → E} {n : ℕ∞} (L : E →L[𝕜] E' →L[𝕜] F) {g : P → G → E'} {s : Set P} {k : Set G}
(hs : IsOpen s) (hk : IsCompact k) (hgs : ∀ p, ∀ x, p ∈ s → x ∉ k → g p x = 0)
(hf : LocallyIntegrable f μ) (hg : ContDiffOn 𝕜 n (↿g) (s ×ˢ univ)) :
ContDiffOn 𝕜 n (fun q : P × G => (f ⋆[L, μ] g q.1) q.2) (s ×ˢ univ) := by
/- We have a formula for the derivation of `f * g`, which is of the same form, thanks to
`hasFDerivAt_convolution_right_with_param`. Therefore, we can prove the result by induction on
`n` (but for this we need the spaces at the different steps of the induction to live in the same
universe, which is why we make the assumption in the lemma that all the relevant spaces
come from the same universe). -/
induction n using ENat.nat_induction generalizing g E' F with
| h0 =>
rw [WithTop.coe_zero, contDiffOn_zero] at hg ⊢
exact continuousOn_convolution_right_with_param L hk hgs hf hg
| hsuc n ih =>
simp only [Nat.succ_eq_add_one, Nat.cast_add, Nat.cast_one, WithTop.coe_add,
WithTop.coe_natCast, WithTop.coe_one] at hg ⊢
let f' : P → G → P × G →L[𝕜] F := fun p a =>
(f ⋆[L.precompR (P × G), μ] fun x : G => fderiv 𝕜 (uncurry g) (p, x)) a
have A : ∀ q₀ : P × G, q₀.1 ∈ s →
HasFDerivAt (fun q : P × G => (f ⋆[L, μ] g q.1) q.2) (f' q₀.1 q₀.2) q₀ :=
hasFDerivAt_convolution_right_with_param L hs hk hgs hf hg.one_of_succ
rw [contDiffOn_succ_iff_fderiv_of_isOpen (hs.prod (@isOpen_univ G _))] at hg ⊢
refine ⟨?_, by simp, ?_⟩
· rintro ⟨p, x⟩ ⟨hp, -⟩
exact (A (p, x) hp).differentiableAt.differentiableWithinAt
· suffices H : ContDiffOn 𝕜 n (↿f') (s ×ˢ univ) by
apply H.congr
rintro ⟨p, x⟩ ⟨hp, -⟩
exact (A (p, x) hp).fderiv
have B : ∀ (p : P) (x : G), p ∈ s → x ∉ k → fderiv 𝕜 (uncurry g) (p, x) = 0 := by
intro p x hp hx
apply (hasFDerivAt_zero_of_eventually_const (0 : E') _).fderiv
have M2 : kᶜ ∈ 𝓝 x := IsOpen.mem_nhds hk.isClosed.isOpen_compl hx
have M1 : s ∈ 𝓝 p := hs.mem_nhds hp
rw [nhds_prod_eq]
filter_upwards [prod_mem_prod M1 M2]
rintro ⟨p, y⟩ ⟨hp, hy⟩
exact hgs p y hp hy
apply ih (L.precompR (P × G) :) B
convert hg.2.2
| htop ih =>
rw [contDiffOn_infty] at hg ⊢
exact fun n ↦ ih n L hgs (hg n)
/-- The convolution `f * g` is `C^n` when `f` is locally integrable and `g` is `C^n` and compactly
supported. Version where `g` depends on an additional parameter in an open subset `s` of a
parameter space `P` (and the compact support `k` is independent of the parameter in `s`). -/
theorem contDiffOn_convolution_right_with_param {f : G → E} {n : ℕ∞} (L : E →L[𝕜] E' →L[𝕜] F)
{g : P → G → E'} {s : Set P} {k : Set G} (hs : IsOpen s) (hk : IsCompact k)
(hgs : ∀ p, ∀ x, p ∈ s → x ∉ k → g p x = 0) (hf : LocallyIntegrable f μ)
(hg : ContDiffOn 𝕜 n (↿g) (s ×ˢ univ)) :
ContDiffOn 𝕜 n (fun q : P × G => (f ⋆[L, μ] g q.1) q.2) (s ×ˢ univ) := by
/- The result is known when all the universes are the same, from
`contDiffOn_convolution_right_with_param_aux`. We reduce to this situation by pushing
everything through `ULift` continuous linear equivalences. -/
let eG : Type max uG uE' uF uP := ULift.{max uE' uF uP} G
borelize eG
let eE' : Type max uE' uG uF uP := ULift.{max uG uF uP} E'
let eF : Type max uF uG uE' uP := ULift.{max uG uE' uP} F
let eP : Type max uP uG uE' uF := ULift.{max uG uE' uF} P
let isoG : eG ≃L[𝕜] G := ContinuousLinearEquiv.ulift
let isoE' : eE' ≃L[𝕜] E' := ContinuousLinearEquiv.ulift
let isoF : eF ≃L[𝕜] F := ContinuousLinearEquiv.ulift
let isoP : eP ≃L[𝕜] P := ContinuousLinearEquiv.ulift
let ef := f ∘ isoG
let eμ : Measure eG := Measure.map isoG.symm μ
let eg : eP → eG → eE' := fun ep ex => isoE'.symm (g (isoP ep) (isoG ex))
let eL :=
ContinuousLinearMap.comp
((ContinuousLinearEquiv.arrowCongr isoE' isoF).symm : (E' →L[𝕜] F) →L[𝕜] eE' →L[𝕜] eF) L
let R := fun q : eP × eG => (ef ⋆[eL, eμ] eg q.1) q.2
have R_contdiff : ContDiffOn 𝕜 n R ((isoP ⁻¹' s) ×ˢ univ) := by
have hek : IsCompact (isoG ⁻¹' k) := isoG.toHomeomorph.isClosedEmbedding.isCompact_preimage hk
have hes : IsOpen (isoP ⁻¹' s) := isoP.continuous.isOpen_preimage _ hs
refine contDiffOn_convolution_right_with_param_aux eL hes hek ?_ ?_ ?_
· intro p x hp hx
simp only [eg, (· ∘ ·), ContinuousLinearEquiv.prod_apply, LinearIsometryEquiv.coe_coe,
ContinuousLinearEquiv.map_eq_zero_iff]
exact hgs _ _ hp hx
· exact (locallyIntegrable_map_homeomorph isoG.symm.toHomeomorph).2 hf
· apply isoE'.symm.contDiff.comp_contDiffOn
apply hg.comp (isoP.prod isoG).contDiff.contDiffOn
rintro ⟨p, x⟩ ⟨hp, -⟩
simpa only [mem_preimage, ContinuousLinearEquiv.prod_apply, prodMk_mem_set_prod_eq, mem_univ,
and_true] using hp
have A : ContDiffOn 𝕜 n (isoF ∘ R ∘ (isoP.prod isoG).symm) (s ×ˢ univ) := by
apply isoF.contDiff.comp_contDiffOn
apply R_contdiff.comp (ContinuousLinearEquiv.contDiff _).contDiffOn
rintro ⟨p, x⟩ ⟨hp, -⟩
simpa only [mem_preimage, mem_prod, mem_univ, and_true, ContinuousLinearEquiv.prod_symm,
ContinuousLinearEquiv.prod_apply, ContinuousLinearEquiv.apply_symm_apply] using hp
have : isoF ∘ R ∘ (isoP.prod isoG).symm = fun q : P × G => (f ⋆[L, μ] g q.1) q.2 := by
apply funext
rintro ⟨p, x⟩
simp only [LinearIsometryEquiv.coe_coe, (· ∘ ·), ContinuousLinearEquiv.prod_symm,
ContinuousLinearEquiv.prod_apply]
simp only [R, convolution, coe_comp', ContinuousLinearEquiv.coe_coe, (· ∘ ·)]
rw [IsClosedEmbedding.integral_map, ← isoF.integral_comp_comm]
· rfl
· exact isoG.symm.toHomeomorph.isClosedEmbedding
simp_rw [this] at A
exact A
/-- The convolution `f * g` is `C^n` when `f` is locally integrable and `g` is `C^n` and compactly
supported. Version where `g` depends on an additional parameter in an open subset `s` of a
parameter space `P` (and the compact support `k` is independent of the parameter in `s`),
given in terms of composition with an additional `C^n` function. -/
theorem contDiffOn_convolution_right_with_param_comp {n : ℕ∞} (L : E →L[𝕜] E' →L[𝕜] F) {s : Set P}
{v : P → G} (hv : ContDiffOn 𝕜 n v s) {f : G → E} {g : P → G → E'} {k : Set G} (hs : IsOpen s)
(hk : IsCompact k) (hgs : ∀ p, ∀ x, p ∈ s → x ∉ k → g p x = 0) (hf : LocallyIntegrable f μ)
(hg : ContDiffOn 𝕜 n (↿g) (s ×ˢ univ)) : ContDiffOn 𝕜 n (fun x => (f ⋆[L, μ] g x) (v x)) s := by
apply (contDiffOn_convolution_right_with_param L hs hk hgs hf hg).comp (contDiffOn_id.prodMk hv)
intro x hx
simp only [hx, mem_preimage, prodMk_mem_set_prod_eq, mem_univ, and_self_iff, _root_.id]
/-- The convolution `g * f` is `C^n` when `f` is locally integrable and `g` is `C^n` and compactly
supported. Version where `g` depends on an additional parameter in an open subset `s` of a
parameter space `P` (and the compact support `k` is independent of the parameter in `s`). -/
| theorem contDiffOn_convolution_left_with_param [μ.IsAddLeftInvariant] [μ.IsNegInvariant]
(L : E' →L[𝕜] E →L[𝕜] F) {f : G → E} {n : ℕ∞} {g : P → G → E'} {s : Set P} {k : Set G}
(hs : IsOpen s) (hk : IsCompact k) (hgs : ∀ p, ∀ x, p ∈ s → x ∉ k → g p x = 0)
(hf : LocallyIntegrable f μ) (hg : ContDiffOn 𝕜 n (↿g) (s ×ˢ univ)) :
ContDiffOn 𝕜 n (fun q : P × G => (g q.1 ⋆[L, μ] f) q.2) (s ×ˢ univ) := by
simpa only [convolution_flip] using contDiffOn_convolution_right_with_param L.flip hs hk hgs hf hg
/-- The convolution `g * f` is `C^n` when `f` is locally integrable and `g` is `C^n` and compactly
supported. Version where `g` depends on an additional parameter in an open subset `s` of a
parameter space `P` (and the compact support `k` is independent of the parameter in `s`),
given in terms of composition with additional `C^n` functions. -/
theorem contDiffOn_convolution_left_with_param_comp [μ.IsAddLeftInvariant] [μ.IsNegInvariant]
(L : E' →L[𝕜] E →L[𝕜] F) {s : Set P} {n : ℕ∞} {v : P → G} (hv : ContDiffOn 𝕜 n v s) {f : G → E}
{g : P → G → E'} {k : Set G} (hs : IsOpen s) (hk : IsCompact k)
(hgs : ∀ p, ∀ x, p ∈ s → x ∉ k → g p x = 0) (hf : LocallyIntegrable f μ)
(hg : ContDiffOn 𝕜 n (↿g) (s ×ˢ univ)) : ContDiffOn 𝕜 n (fun x => (g x ⋆[L, μ] f) (v x)) s := by
apply (contDiffOn_convolution_left_with_param L hs hk hgs hf hg).comp (contDiffOn_id.prodMk hv)
intro x hx
simp only [hx, mem_preimage, prodMk_mem_set_prod_eq, mem_univ, and_self_iff, _root_.id]
theorem _root_.HasCompactSupport.contDiff_convolution_right {n : ℕ∞} (hcg : HasCompactSupport g)
(hf : LocallyIntegrable f μ) (hg : ContDiff 𝕜 n g) : ContDiff 𝕜 n (f ⋆[L, μ] g) := by
rcases exists_compact_iff_hasCompactSupport.2 hcg with ⟨k, hk, h'k⟩
rw [← contDiffOn_univ]
exact contDiffOn_convolution_right_with_param_comp L contDiffOn_id isOpen_univ hk
(fun p x _ hx => h'k x hx) hf (hg.comp contDiff_snd).contDiffOn
theorem _root_.HasCompactSupport.contDiff_convolution_left [μ.IsAddLeftInvariant] [μ.IsNegInvariant]
{n : ℕ∞} (hcf : HasCompactSupport f) (hf : ContDiff 𝕜 n f) (hg : LocallyIntegrable g μ) :
ContDiff 𝕜 n (f ⋆[L, μ] g) := by
rw [← convolution_flip]
exact hcf.contDiff_convolution_right L.flip hg hf
end WithParam
section Nonneg
variable [NormedSpace ℝ E] [NormedSpace ℝ E'] [NormedSpace ℝ F]
/-- The forward convolution of two functions `f` and `g` on `ℝ`, with respect to a continuous
bilinear map `L` and measure `ν`. It is defined to be the function mapping `x` to
`∫ t in 0..x, L (f t) (g (x - t)) ∂ν` if `0 < x`, and 0 otherwise. -/
noncomputable def posConvolution (f : ℝ → E) (g : ℝ → E') (L : E →L[ℝ] E' →L[ℝ] F)
(ν : Measure ℝ := by volume_tac) : ℝ → F :=
indicator (Ioi (0 : ℝ)) fun x => ∫ t in (0)..x, L (f t) (g (x - t)) ∂ν
theorem posConvolution_eq_convolution_indicator (f : ℝ → E) (g : ℝ → E') (L : E →L[ℝ] E' →L[ℝ] F)
(ν : Measure ℝ := by volume_tac) [NoAtoms ν] :
posConvolution f g L ν = convolution (indicator (Ioi 0) f) (indicator (Ioi 0) g) L ν := by
ext1 x
rw [convolution, posConvolution, indicator]
split_ifs with h
· rw [intervalIntegral.integral_of_le (le_of_lt h), integral_Ioc_eq_integral_Ioo, ←
integral_indicator (measurableSet_Ioo : MeasurableSet (Ioo 0 x))]
congr 1 with t : 1
have : t ≤ 0 ∨ t ∈ Ioo 0 x ∨ x ≤ t := by
rcases le_or_lt t 0 with (h | h)
· exact Or.inl h
· rcases lt_or_le t x with (h' | h')
exacts [Or.inr (Or.inl ⟨h, h'⟩), Or.inr (Or.inr h')]
rcases this with (ht | ht | ht)
· rw [indicator_of_not_mem (not_mem_Ioo_of_le ht), indicator_of_not_mem (not_mem_Ioi.mpr ht),
ContinuousLinearMap.map_zero, ContinuousLinearMap.zero_apply]
· rw [indicator_of_mem ht, indicator_of_mem (mem_Ioi.mpr ht.1),
| Mathlib/Analysis/Convolution.lean | 1,298 | 1,361 |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Johan Commelin, Mario Carneiro
-/
import Mathlib.Algebra.MvPolynomial.Eval
/-!
# Renaming variables of polynomials
This file establishes the `rename` operation on multivariate polynomials,
which modifies the set of variables.
## Main declarations
* `MvPolynomial.rename`
* `MvPolynomial.renameEquiv`
## Notation
As in other polynomial files, we typically use the notation:
+ `σ τ α : Type*` (indexing the variables)
+ `R S : Type*` `[CommSemiring R]` `[CommSemiring S]` (the coefficients)
+ `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set.
This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s`
+ `r : R` elements of the coefficient ring
+ `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians
+ `p : MvPolynomial σ α`
-/
noncomputable section
open Set Function Finsupp AddMonoidAlgebra
variable {σ τ α R S : Type*} [CommSemiring R] [CommSemiring S]
namespace MvPolynomial
section Rename
/-- Rename all the variables in a multivariable polynomial. -/
def rename (f : σ → τ) : MvPolynomial σ R →ₐ[R] MvPolynomial τ R :=
aeval (X ∘ f)
theorem rename_C (f : σ → τ) (r : R) : rename f (C r) = C r :=
eval₂_C _ _ _
@[simp]
theorem rename_X (f : σ → τ) (i : σ) : rename f (X i : MvPolynomial σ R) = X (f i) :=
eval₂_X _ _ _
theorem map_rename (f : R →+* S) (g : σ → τ) (p : MvPolynomial σ R) :
map f (rename g p) = rename g (map f p) := by
apply MvPolynomial.induction_on p
(fun a => by simp only [map_C, rename_C])
(fun p q hp hq => by simp only [hp, hq, map_add]) fun p n hp => by
simp only [hp, rename_X, map_X, map_mul]
lemma map_comp_rename (f : R →+* S) (g : σ → τ) :
(map f).comp (rename g).toRingHom = (rename g).toRingHom.comp (map f) :=
RingHom.ext fun p ↦ map_rename f g p
@[simp]
theorem rename_rename (f : σ → τ) (g : τ → α) (p : MvPolynomial σ R) :
rename g (rename f p) = rename (g ∘ f) p :=
show rename g (eval₂ C (X ∘ f) p) = _ by
simp only [rename, aeval_eq_eval₂Hom]
-- Porting note: the Lean 3 proof of this was very fragile and included a nonterminal `simp`.
-- Hopefully this is less prone to breaking
rw [eval₂_comp_left (eval₂Hom (algebraMap R (MvPolynomial α R)) (X ∘ g)) C (X ∘ f) p]
simp only [comp_def, eval₂Hom_X']
refine eval₂Hom_congr ?_ rfl rfl
ext1; simp only [comp_apply, RingHom.coe_comp, eval₂Hom_C]
lemma rename_comp_rename (f : σ → τ) (g : τ → α) :
(rename (R := R) g).comp (rename f) = rename (g ∘ f) :=
AlgHom.ext fun p ↦ rename_rename f g p
@[simp]
theorem rename_id : rename id = AlgHom.id R (MvPolynomial σ R) :=
AlgHom.ext fun p ↦ eval₂_eta p
lemma rename_id_apply (p : MvPolynomial σ R) : rename id p = p := by
simp
theorem rename_monomial (f : σ → τ) (d : σ →₀ ℕ) (r : R) :
rename f (monomial d r) = monomial (d.mapDomain f) r := by
rw [rename, aeval_monomial, monomial_eq (s := Finsupp.mapDomain f d),
Finsupp.prod_mapDomain_index]
· rfl
· exact fun n => pow_zero _
· exact fun n i₁ i₂ => pow_add _ _ _
theorem rename_eq (f : σ → τ) (p : MvPolynomial σ R) :
rename f p = Finsupp.mapDomain (Finsupp.mapDomain f) p := by
simp only [rename, aeval_def, eval₂, Finsupp.mapDomain, algebraMap_eq, comp_apply,
X_pow_eq_monomial, ← monomial_finsupp_sum_index]
rfl
theorem rename_injective (f : σ → τ) (hf : Function.Injective f) :
Function.Injective (rename f : MvPolynomial σ R → MvPolynomial τ R) := by
have :
(rename f : MvPolynomial σ R → MvPolynomial τ R) = Finsupp.mapDomain (Finsupp.mapDomain f) :=
funext (rename_eq f)
rw [this]
exact Finsupp.mapDomain_injective (Finsupp.mapDomain_injective hf)
theorem rename_leftInverse {f : σ → τ} {g : τ → σ} (hf : Function.LeftInverse f g) :
Function.LeftInverse (rename f : MvPolynomial σ R → MvPolynomial τ R) (rename g) := by
intro x
simp [hf.comp_eq_id]
theorem rename_rightInverse {f : σ → τ} {g : τ → σ} (hf : Function.RightInverse f g) :
Function.RightInverse (rename f : MvPolynomial σ R → MvPolynomial τ R) (rename g) :=
rename_leftInverse hf
theorem rename_surjective (f : σ → τ) (hf : Function.Surjective f) :
Function.Surjective (rename f : MvPolynomial σ R → MvPolynomial τ R) :=
let ⟨_, hf⟩ := hf.hasRightInverse; rename_rightInverse hf |>.surjective
section
variable {f : σ → τ} (hf : Function.Injective f)
open Classical in
/-- Given a function between sets of variables `f : σ → τ` that is injective with proof `hf`,
`MvPolynomial.killCompl hf` is the `AlgHom` from `R[τ]` to `R[σ]` that is left inverse to
`rename f : R[σ] → R[τ]` and sends the variables in the complement of the range of `f` to `0`. -/
def killCompl : MvPolynomial τ R →ₐ[R] MvPolynomial σ R :=
aeval fun i => if h : i ∈ Set.range f then X <| (Equiv.ofInjective f hf).symm ⟨i, h⟩ else 0
theorem killCompl_C (r : R) : killCompl hf (C r) = C r := algHom_C _ _
theorem killCompl_comp_rename : (killCompl hf).comp (rename f) = AlgHom.id R _ :=
algHom_ext fun i => by
dsimp
rw [rename, killCompl, aeval_X, comp_apply, aeval_X, dif_pos, Equiv.ofInjective_symm_apply]
@[simp]
theorem killCompl_rename_app (p : MvPolynomial σ R) : killCompl hf (rename f p) = p :=
AlgHom.congr_fun (killCompl_comp_rename hf) p
end
section
variable (R)
/-- `MvPolynomial.rename e` is an equivalence when `e` is. -/
@[simps apply]
def renameEquiv (f : σ ≃ τ) : MvPolynomial σ R ≃ₐ[R] MvPolynomial τ R :=
{ rename f with
toFun := rename f
invFun := rename f.symm
left_inv := fun p => by rw [rename_rename, f.symm_comp_self, rename_id_apply]
right_inv := fun p => by rw [rename_rename, f.self_comp_symm, rename_id_apply] }
@[simp]
theorem renameEquiv_refl : renameEquiv R (Equiv.refl σ) = AlgEquiv.refl :=
AlgEquiv.ext (by simp)
@[simp]
theorem renameEquiv_symm (f : σ ≃ τ) : (renameEquiv R f).symm = renameEquiv R f.symm :=
rfl
@[simp]
theorem renameEquiv_trans (e : σ ≃ τ) (f : τ ≃ α) :
(renameEquiv R e).trans (renameEquiv R f) = renameEquiv R (e.trans f) :=
AlgEquiv.ext (rename_rename e f)
end
section
variable (f : R →+* S) (k : σ → τ) (g : τ → S) (p : MvPolynomial σ R)
theorem eval₂_rename : (rename k p).eval₂ f g = p.eval₂ f (g ∘ k) := by
apply MvPolynomial.induction_on p <;>
· intros
simp [*]
theorem eval_rename (g : τ → R) (p : MvPolynomial σ R) : eval g (rename k p) = eval (g ∘ k) p :=
eval₂_rename _ _ _ _
theorem eval₂Hom_rename : eval₂Hom f g (rename k p) = eval₂Hom f (g ∘ k) p :=
eval₂_rename _ _ _ _
theorem aeval_rename [Algebra R S] : aeval g (rename k p) = aeval (g ∘ k) p :=
eval₂Hom_rename _ _ _ _
lemma aeval_comp_rename [Algebra R S] :
(aeval (R := R) g).comp (rename k) = MvPolynomial.aeval (g ∘ k) :=
AlgHom.ext fun p ↦ aeval_rename k g p
theorem rename_eval₂ (g : τ → MvPolynomial σ R) :
rename k (p.eval₂ C (g ∘ k)) = (rename k p).eval₂ C (rename k ∘ g) := by
apply MvPolynomial.induction_on p <;>
· intros
simp [*]
theorem rename_prod_mk_eval₂ (j : τ) (g : σ → MvPolynomial σ R) :
rename (Prod.mk j) (p.eval₂ C g) = p.eval₂ C fun x => rename (Prod.mk j) (g x) := by
apply MvPolynomial.induction_on p <;>
· intros
simp [*]
theorem eval₂_rename_prod_mk (g : σ × τ → S) (i : σ) (p : MvPolynomial τ R) :
(rename (Prod.mk i) p).eval₂ f g = eval₂ f (fun j => g (i, j)) p := by
apply MvPolynomial.induction_on p <;>
· intros
simp [*]
theorem eval_rename_prod_mk (g : σ × τ → R) (i : σ) (p : MvPolynomial τ R) :
eval g (rename (Prod.mk i) p) = eval (fun j => g (i, j)) p :=
eval₂_rename_prod_mk (RingHom.id _) _ _ _
end
/-- Every polynomial is a polynomial in finitely many variables. -/
theorem exists_finset_rename (p : MvPolynomial σ R) :
∃ (s : Finset σ) (q : MvPolynomial { x // x ∈ s } R), p = rename (↑) q := by
classical
apply induction_on p
· intro r
exact ⟨∅, C r, by rw [rename_C]⟩
· rintro p q ⟨s, p, rfl⟩ ⟨t, q, rfl⟩
refine ⟨s ∪ t, ⟨?_, ?_⟩⟩
· refine rename (Subtype.map id ?_) p + rename (Subtype.map id ?_) q <;>
simp +contextual only [id, true_or, or_true,
Finset.mem_union, forall_true_iff]
· simp only [rename_rename, map_add]
rfl
· rintro p n ⟨s, p, rfl⟩
refine ⟨insert n s, ⟨?_, ?_⟩⟩
· refine rename (Subtype.map id ?_) p * X ⟨n, s.mem_insert_self n⟩
simp +contextual only [id, or_true, Finset.mem_insert, forall_true_iff]
· simp only [rename_rename, rename_X, Subtype.coe_mk, map_mul]
rfl
/-- `exists_finset_rename` for two polynomials at once: for any two polynomials `p₁`, `p₂` in a
polynomial semiring `R[σ]` of possibly infinitely many variables, `exists_finset_rename₂` yields
a finite subset `s` of `σ` such that both `p₁` and `p₂` are contained in the polynomial semiring
`R[s]` of finitely many variables. -/
theorem exists_finset_rename₂ (p₁ p₂ : MvPolynomial σ R) :
∃ (s : Finset σ) (q₁ q₂ : MvPolynomial s R), p₁ = rename (↑) q₁ ∧ p₂ = rename (↑) q₂ := by
obtain ⟨s₁, q₁, rfl⟩ := exists_finset_rename p₁
obtain ⟨s₂, q₂, rfl⟩ := exists_finset_rename p₂
classical
use s₁ ∪ s₂
use rename (Set.inclusion s₁.subset_union_left) q₁
use rename (Set.inclusion s₁.subset_union_right) q₂
constructor <;> simp [Function.comp_def]
/-- Every polynomial is a polynomial in finitely many variables. -/
theorem exists_fin_rename (p : MvPolynomial σ R) :
∃ (n : ℕ) (f : Fin n → σ) (_hf : Injective f) (q : MvPolynomial (Fin n) R), p = rename f q := by
obtain ⟨s, q, rfl⟩ := exists_finset_rename p
let n := Fintype.card { x // x ∈ s }
let e := Fintype.equivFin { x // x ∈ s }
refine ⟨n, (↑) ∘ e.symm, Subtype.val_injective.comp e.symm.injective, rename e q, ?_⟩
rw [← rename_rename, rename_rename e]
simp only [Function.comp_def, Equiv.symm_apply_apply, rename_rename]
end Rename
theorem eval₂_cast_comp (f : σ → τ) (c : ℤ →+* R) (g : τ → R) (p : MvPolynomial σ ℤ) :
eval₂ c (g ∘ f) p = eval₂ c g (rename f p) := by
apply MvPolynomial.induction_on p (fun n => by simp only [eval₂_C, rename_C])
(fun p q hp hq => by simp only [hp, hq, rename, eval₂_add, map_add])
fun p n hp => by simp only [eval₂_mul, hp, eval₂_X, comp_apply, map_mul, rename_X, eval₂_mul]
section Coeff
@[simp]
theorem coeff_rename_mapDomain (f : σ → τ) (hf : Injective f) (φ : MvPolynomial σ R) (d : σ →₀ ℕ) :
(rename f φ).coeff (d.mapDomain f) = φ.coeff d := by
classical
apply φ.induction_on' (P := fun ψ => coeff (Finsupp.mapDomain f d) ((rename f) ψ) = coeff d ψ)
-- Lean could no longer infer the motive
· intro u r
rw [rename_monomial, coeff_monomial, coeff_monomial]
simp only [(Finsupp.mapDomain_injective hf).eq_iff]
· intros
simp only [*, map_add, coeff_add]
@[simp]
theorem coeff_rename_embDomain (f : σ ↪ τ) (φ : MvPolynomial σ R) (d : σ →₀ ℕ) :
(rename f φ).coeff (d.embDomain f) = φ.coeff d := by
rw [Finsupp.embDomain_eq_mapDomain f, coeff_rename_mapDomain f f.injective]
theorem coeff_rename_eq_zero (f : σ → τ) (φ : MvPolynomial σ R) (d : τ →₀ ℕ)
(h : ∀ u : σ →₀ ℕ, u.mapDomain f = d → φ.coeff u = 0) : (rename f φ).coeff d = 0 := by
classical
rw [rename_eq, ← not_mem_support_iff]
intro H
replace H := mapDomain_support H
rw [Finset.mem_image] at H
obtain ⟨u, hu, rfl⟩ := H
specialize h u rfl
simp? at h hu says simp only [Finsupp.mem_support_iff, ne_eq] at h hu
contradiction
theorem coeff_rename_ne_zero (f : σ → τ) (φ : MvPolynomial σ R) (d : τ →₀ ℕ)
(h : (rename f φ).coeff d ≠ 0) : ∃ u : σ →₀ ℕ, u.mapDomain f = d ∧ φ.coeff u ≠ 0 := by
contrapose! h
apply coeff_rename_eq_zero _ _ _ h
@[simp]
theorem constantCoeff_rename {τ : Type*} (f : σ → τ) (φ : MvPolynomial σ R) :
constantCoeff (rename f φ) = constantCoeff φ := by
apply φ.induction_on
· intro a
simp only [constantCoeff_C, rename_C]
· intro p q hp hq
simp only [hp, hq, map_add]
· intro p n hp
simp only [hp, rename_X, constantCoeff_X, map_mul]
end Coeff
section Support
| theorem support_rename_of_injective {p : MvPolynomial σ R} {f : σ → τ} [DecidableEq τ]
(h : Function.Injective f) :
(rename f p).support = Finset.image (Finsupp.mapDomain f) p.support := by
rw [rename_eq]
exact Finsupp.mapDomain_support_of_injective (Finsupp.mapDomain_injective h) _
end Support
end MvPolynomial
| Mathlib/Algebra/MvPolynomial/Rename.lean | 331 | 339 |
/-
Copyright (c) 2018 Robert Y. Lewis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Robert Y. Lewis
-/
import Mathlib.RingTheory.Valuation.Basic
import Mathlib.NumberTheory.Padics.PadicNorm
import Mathlib.Analysis.Normed.Field.Lemmas
import Mathlib.Tactic.Peel
import Mathlib.Topology.MetricSpace.Ultra.Basic
/-!
# p-adic numbers
This file defines the `p`-adic numbers (rationals) `ℚ_[p]` as
the completion of `ℚ` with respect to the `p`-adic norm.
We show that the `p`-adic norm on `ℚ` extends to `ℚ_[p]`, that `ℚ` is embedded in `ℚ_[p]`,
and that `ℚ_[p]` is Cauchy complete.
## Important definitions
* `Padic` : the type of `p`-adic numbers
* `padicNormE` : the rational valued `p`-adic norm on `ℚ_[p]`
* `Padic.addValuation` : the additive `p`-adic valuation on `ℚ_[p]`, with values in `WithTop ℤ`
## Notation
We introduce the notation `ℚ_[p]` for the `p`-adic numbers.
## Implementation notes
Much, but not all, of this file assumes that `p` is prime. This assumption is inferred automatically
by taking `[Fact p.Prime]` as a type class argument.
We use the same concrete Cauchy sequence construction that is used to construct `ℝ`.
`ℚ_[p]` inherits a field structure from this construction.
The extension of the norm on `ℚ` to `ℚ_[p]` is *not* analogous to extending the absolute value to
`ℝ` and hence the proof that `ℚ_[p]` is complete is different from the proof that ℝ is complete.
`padicNormE` is the rational-valued `p`-adic norm on `ℚ_[p]`.
To instantiate `ℚ_[p]` as a normed field, we must cast this into an `ℝ`-valued norm.
The `ℝ`-valued norm, using notation `‖ ‖` from normed spaces,
is the canonical representation of this norm.
`simp` prefers `padicNorm` to `padicNormE` when possible.
Since `padicNormE` and `‖ ‖` have different types, `simp` does not rewrite one to the other.
Coercions from `ℚ` to `ℚ_[p]` are set up to work with the `norm_cast` tactic.
## References
* [F. Q. Gouvêa, *p-adic numbers*][gouvea1997]
* [R. Y. Lewis, *A formal proof of Hensel's lemma over the p-adic integers*][lewis2019]
* <https://en.wikipedia.org/wiki/P-adic_number>
## Tags
p-adic, p adic, padic, norm, valuation, cauchy, completion, p-adic completion
-/
noncomputable section
open Nat padicNorm CauSeq CauSeq.Completion Metric
/-- The type of Cauchy sequences of rationals with respect to the `p`-adic norm. -/
abbrev PadicSeq (p : ℕ) :=
CauSeq _ (padicNorm p)
namespace PadicSeq
section
variable {p : ℕ} [Fact p.Prime]
/-- The `p`-adic norm of the entries of a nonzero Cauchy sequence of rationals is eventually
constant. -/
theorem stationary {f : CauSeq ℚ (padicNorm p)} (hf : ¬f ≈ 0) :
∃ N, ∀ m n, N ≤ m → N ≤ n → padicNorm p (f n) = padicNorm p (f m) :=
have : ∃ ε > 0, ∃ N1, ∀ j ≥ N1, ε ≤ padicNorm p (f j) :=
CauSeq.abv_pos_of_not_limZero <| not_limZero_of_not_congr_zero hf
let ⟨ε, hε, N1, hN1⟩ := this
let ⟨N2, hN2⟩ := CauSeq.cauchy₂ f hε
⟨max N1 N2, fun n m hn hm ↦ by
have : padicNorm p (f n - f m) < ε := hN2 _ (max_le_iff.1 hn).2 _ (max_le_iff.1 hm).2
have : padicNorm p (f n - f m) < padicNorm p (f n) :=
lt_of_lt_of_le this <| hN1 _ (max_le_iff.1 hn).1
have : padicNorm p (f n - f m) < max (padicNorm p (f n)) (padicNorm p (f m)) :=
lt_max_iff.2 (Or.inl this)
by_contra hne
rw [← padicNorm.neg (f m)] at hne
have hnam := add_eq_max_of_ne hne
rw [padicNorm.neg, max_comm] at hnam
rw [← hnam, sub_eq_add_neg, add_comm] at this
apply _root_.lt_irrefl _ this⟩
/-- For all `n ≥ stationaryPoint f hf`, the `p`-adic norm of `f n` is the same. -/
def stationaryPoint {f : PadicSeq p} (hf : ¬f ≈ 0) : ℕ :=
Classical.choose <| stationary hf
theorem stationaryPoint_spec {f : PadicSeq p} (hf : ¬f ≈ 0) :
∀ {m n},
stationaryPoint hf ≤ m → stationaryPoint hf ≤ n → padicNorm p (f n) = padicNorm p (f m) :=
@(Classical.choose_spec <| stationary hf)
open Classical in
/-- Since the norm of the entries of a Cauchy sequence is eventually stationary,
we can lift the norm to sequences. -/
def norm (f : PadicSeq p) : ℚ :=
if hf : f ≈ 0 then 0 else padicNorm p (f (stationaryPoint hf))
theorem norm_zero_iff (f : PadicSeq p) : f.norm = 0 ↔ f ≈ 0 := by
constructor
· intro h
by_contra hf
unfold norm at h
split_ifs at h
apply hf
intro ε hε
exists stationaryPoint hf
intro j hj
have heq := stationaryPoint_spec hf le_rfl hj
simpa [h, heq]
· intro h
simp [norm, h]
end
section Embedding
open CauSeq
variable {p : ℕ} [Fact p.Prime]
theorem equiv_zero_of_val_eq_of_equiv_zero {f g : PadicSeq p}
(h : ∀ k, padicNorm p (f k) = padicNorm p (g k)) (hf : f ≈ 0) : g ≈ 0 := fun ε hε ↦
let ⟨i, hi⟩ := hf _ hε
⟨i, fun j hj ↦ by simpa [h] using hi _ hj⟩
theorem norm_nonzero_of_not_equiv_zero {f : PadicSeq p} (hf : ¬f ≈ 0) : f.norm ≠ 0 :=
hf ∘ f.norm_zero_iff.1
theorem norm_eq_norm_app_of_nonzero {f : PadicSeq p} (hf : ¬f ≈ 0) :
∃ k, f.norm = padicNorm p k ∧ k ≠ 0 :=
have heq : f.norm = padicNorm p (f <| stationaryPoint hf) := by simp [norm, hf]
⟨f <| stationaryPoint hf, heq, fun h ↦
norm_nonzero_of_not_equiv_zero hf (by simpa [h] using heq)⟩
theorem not_limZero_const_of_nonzero {q : ℚ} (hq : q ≠ 0) : ¬LimZero (const (padicNorm p) q) :=
fun h' ↦ hq <| const_limZero.1 h'
theorem not_equiv_zero_const_of_nonzero {q : ℚ} (hq : q ≠ 0) : ¬const (padicNorm p) q ≈ 0 :=
fun h : LimZero (const (padicNorm p) q - 0) ↦
not_limZero_const_of_nonzero (p := p) hq <| by simpa using h
theorem norm_nonneg (f : PadicSeq p) : 0 ≤ f.norm := by
classical exact if hf : f ≈ 0 then by simp [hf, norm] else by simp [norm, hf, padicNorm.nonneg]
/-- An auxiliary lemma for manipulating sequence indices. -/
theorem lift_index_left_left {f : PadicSeq p} (hf : ¬f ≈ 0) (v2 v3 : ℕ) :
padicNorm p (f (stationaryPoint hf)) =
padicNorm p (f (max (stationaryPoint hf) (max v2 v3))) := by
apply stationaryPoint_spec hf
· apply le_max_left
· exact le_rfl
/-- An auxiliary lemma for manipulating sequence indices. -/
theorem lift_index_left {f : PadicSeq p} (hf : ¬f ≈ 0) (v1 v3 : ℕ) :
padicNorm p (f (stationaryPoint hf)) =
padicNorm p (f (max v1 (max (stationaryPoint hf) v3))) := by
apply stationaryPoint_spec hf
· apply le_trans
· apply le_max_left _ v3
· apply le_max_right
· exact le_rfl
/-- An auxiliary lemma for manipulating sequence indices. -/
theorem lift_index_right {f : PadicSeq p} (hf : ¬f ≈ 0) (v1 v2 : ℕ) :
padicNorm p (f (stationaryPoint hf)) =
padicNorm p (f (max v1 (max v2 (stationaryPoint hf)))) := by
apply stationaryPoint_spec hf
· apply le_trans
· apply le_max_right v2
· apply le_max_right
· exact le_rfl
end Embedding
section Valuation
open CauSeq
variable {p : ℕ} [Fact p.Prime]
/-! ### Valuation on `PadicSeq` -/
open Classical in
/-- The `p`-adic valuation on `ℚ` lifts to `PadicSeq p`.
`Valuation f` is defined to be the valuation of the (`ℚ`-valued) stationary point of `f`. -/
def valuation (f : PadicSeq p) : ℤ :=
if hf : f ≈ 0 then 0 else padicValRat p (f (stationaryPoint hf))
theorem norm_eq_zpow_neg_valuation {f : PadicSeq p} (hf : ¬f ≈ 0) :
f.norm = (p : ℚ) ^ (-f.valuation : ℤ) := by
rw [norm, valuation, dif_neg hf, dif_neg hf, padicNorm, if_neg]
intro H
apply CauSeq.not_limZero_of_not_congr_zero hf
intro ε hε
use stationaryPoint hf
intro n hn
rw [stationaryPoint_spec hf le_rfl hn]
simpa [H] using hε
@[deprecated (since := "2024-12-10")] alias norm_eq_pow_val := norm_eq_zpow_neg_valuation
theorem val_eq_iff_norm_eq {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) :
f.valuation = g.valuation ↔ f.norm = g.norm := by
rw [norm_eq_zpow_neg_valuation hf, norm_eq_zpow_neg_valuation hg, ← neg_inj, zpow_right_inj₀]
· exact mod_cast (Fact.out : p.Prime).pos
· exact mod_cast (Fact.out : p.Prime).ne_one
end Valuation
end PadicSeq
section
open PadicSeq
-- Porting note: Commented out `padic_index_simp` tactic
/-
private unsafe def index_simp_core (hh hf hg : expr)
(at_ : Interactive.Loc := Interactive.Loc.ns [none]) : tactic Unit := do
let [v1, v2, v3] ← [hh, hf, hg].mapM fun n => tactic.mk_app `` stationary_point [n] <|> return n
let e1 ← tactic.mk_app `` lift_index_left_left [hh, v2, v3] <|> return q(True)
let e2 ← tactic.mk_app `` lift_index_left [hf, v1, v3] <|> return q(True)
let e3 ← tactic.mk_app `` lift_index_right [hg, v1, v2] <|> return q(True)
let sl ← [e1, e2, e3].foldlM (fun s e => simp_lemmas.add s e) simp_lemmas.mk
when at_ (tactic.simp_target sl >> tactic.skip)
let hs ← at_.get_locals
hs (tactic.simp_hyp sl [])
/-- This is a special-purpose tactic that lifts `padicNorm (f (stationary_point f))` to
`padicNorm (f (max _ _ _))`. -/
unsafe def tactic.interactive.padic_index_simp (l : interactive.parse interactive.types.pexpr_list)
(at_ : interactive.parse interactive.types.location) : tactic Unit := do
let [h, f, g] ← l.mapM tactic.i_to_expr
index_simp_core h f g at_
-/
end
namespace PadicSeq
section Embedding
open CauSeq
variable {p : ℕ} [hp : Fact p.Prime]
theorem norm_mul (f g : PadicSeq p) : (f * g).norm = f.norm * g.norm := by
classical
exact if hf : f ≈ 0 then by
have hg : f * g ≈ 0 := mul_equiv_zero' _ hf
simp only [hf, hg, norm, dif_pos, zero_mul]
else
if hg : g ≈ 0 then by
have hf : f * g ≈ 0 := mul_equiv_zero _ hg
simp only [hf, hg, norm, dif_pos, mul_zero]
else by
unfold norm
have hfg := mul_not_equiv_zero hf hg
simp only [hfg, hf, hg, dite_false]
-- Porting note: originally `padic_index_simp [hfg, hf, hg]`
rw [lift_index_left_left hfg, lift_index_left hf, lift_index_right hg]
apply padicNorm.mul
theorem eq_zero_iff_equiv_zero (f : PadicSeq p) : mk f = 0 ↔ f ≈ 0 :=
mk_eq
theorem ne_zero_iff_nequiv_zero (f : PadicSeq p) : mk f ≠ 0 ↔ ¬f ≈ 0 :=
eq_zero_iff_equiv_zero _ |>.not
theorem norm_const (q : ℚ) : norm (const (padicNorm p) q) = padicNorm p q := by
obtain rfl | hq := eq_or_ne q 0
· simp [norm]
· simp [norm, not_equiv_zero_const_of_nonzero hq]
theorem norm_values_discrete (a : PadicSeq p) (ha : ¬a ≈ 0) : ∃ z : ℤ, a.norm = (p : ℚ) ^ (-z) := by
let ⟨k, hk, hk'⟩ := norm_eq_norm_app_of_nonzero ha
simpa [hk] using padicNorm.values_discrete hk'
theorem norm_one : norm (1 : PadicSeq p) = 1 := by
have h1 : ¬(1 : PadicSeq p) ≈ 0 := one_not_equiv_zero _
simp [h1, norm, hp.1.one_lt]
private theorem norm_eq_of_equiv_aux {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) (hfg : f ≈ g)
(h : padicNorm p (f (stationaryPoint hf)) ≠ padicNorm p (g (stationaryPoint hg)))
(hlt : padicNorm p (g (stationaryPoint hg)) < padicNorm p (f (stationaryPoint hf))) :
False := by
have hpn : 0 < padicNorm p (f (stationaryPoint hf)) - padicNorm p (g (stationaryPoint hg)) :=
sub_pos_of_lt hlt
obtain ⟨N, hN⟩ := hfg _ hpn
let i := max N (max (stationaryPoint hf) (stationaryPoint hg))
have hi : N ≤ i := le_max_left _ _
have hN' := hN _ hi
-- Porting note: originally `padic_index_simp [N, hf, hg] at hN' h hlt`
rw [lift_index_left hf N (stationaryPoint hg), lift_index_right hg N (stationaryPoint hf)]
at hN' h hlt
have hpne : padicNorm p (f i) ≠ padicNorm p (-g i) := by rwa [← padicNorm.neg (g i)] at h
rw [CauSeq.sub_apply, sub_eq_add_neg, add_eq_max_of_ne hpne, padicNorm.neg, max_eq_left_of_lt hlt]
at hN'
have : padicNorm p (f i) < padicNorm p (f i) := by
apply lt_of_lt_of_le hN'
apply sub_le_self
apply padicNorm.nonneg
exact lt_irrefl _ this
private theorem norm_eq_of_equiv {f g : PadicSeq p} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) (hfg : f ≈ g) :
padicNorm p (f (stationaryPoint hf)) = padicNorm p (g (stationaryPoint hg)) := by
by_contra h
cases lt_or_le (padicNorm p (g (stationaryPoint hg))) (padicNorm p (f (stationaryPoint hf))) with
| inl hlt =>
exact norm_eq_of_equiv_aux hf hg hfg h hlt
| inr hle =>
apply norm_eq_of_equiv_aux hg hf (Setoid.symm hfg) (Ne.symm h)
exact lt_of_le_of_ne hle h
theorem norm_equiv {f g : PadicSeq p} (hfg : f ≈ g) : f.norm = g.norm := by
classical
exact if hf : f ≈ 0 then by
have hg : g ≈ 0 := Setoid.trans (Setoid.symm hfg) hf
simp [norm, hf, hg]
else by
have hg : ¬g ≈ 0 := hf ∘ Setoid.trans hfg
unfold norm; split_ifs; exact norm_eq_of_equiv hf hg hfg
private theorem norm_nonarchimedean_aux {f g : PadicSeq p} (hfg : ¬f + g ≈ 0) (hf : ¬f ≈ 0)
(hg : ¬g ≈ 0) : (f + g).norm ≤ max f.norm g.norm := by
unfold norm; split_ifs
-- Porting note: originally `padic_index_simp [hfg, hf, hg]`
rw [lift_index_left_left hfg, lift_index_left hf, lift_index_right hg]
apply padicNorm.nonarchimedean
theorem norm_nonarchimedean (f g : PadicSeq p) : (f + g).norm ≤ max f.norm g.norm := by
classical
exact if hfg : f + g ≈ 0 then by
have : 0 ≤ max f.norm g.norm := le_max_of_le_left (norm_nonneg _)
simpa only [hfg, norm]
else
if hf : f ≈ 0 then by
have hfg' : f + g ≈ g := by
change LimZero (f - 0) at hf
show LimZero (f + g - g); · simpa only [sub_zero, add_sub_cancel_right] using hf
have hcfg : (f + g).norm = g.norm := norm_equiv hfg'
have hcl : f.norm = 0 := (norm_zero_iff f).2 hf
have : max f.norm g.norm = g.norm := by rw [hcl]; exact max_eq_right (norm_nonneg _)
rw [this, hcfg]
else
if hg : g ≈ 0 then by
have hfg' : f + g ≈ f := by
change LimZero (g - 0) at hg
show LimZero (f + g - f); · simpa only [add_sub_cancel_left, sub_zero] using hg
have hcfg : (f + g).norm = f.norm := norm_equiv hfg'
have hcl : g.norm = 0 := (norm_zero_iff g).2 hg
have : max f.norm g.norm = f.norm := by rw [hcl]; exact max_eq_left (norm_nonneg _)
rw [this, hcfg]
else norm_nonarchimedean_aux hfg hf hg
theorem norm_eq {f g : PadicSeq p} (h : ∀ k, padicNorm p (f k) = padicNorm p (g k)) :
f.norm = g.norm := by
classical
exact if hf : f ≈ 0 then by
have hg : g ≈ 0 := equiv_zero_of_val_eq_of_equiv_zero h hf
simp only [hf, hg, norm, dif_pos]
else by
have hg : ¬g ≈ 0 := fun hg ↦
hf <| equiv_zero_of_val_eq_of_equiv_zero (by simp only [h, forall_const, eq_self_iff_true]) hg
simp only [hg, hf, norm, dif_neg, not_false_iff]
let i := max (stationaryPoint hf) (stationaryPoint hg)
have hpf : padicNorm p (f (stationaryPoint hf)) = padicNorm p (f i) := by
apply stationaryPoint_spec
· apply le_max_left
· exact le_rfl
have hpg : padicNorm p (g (stationaryPoint hg)) = padicNorm p (g i) := by
apply stationaryPoint_spec
· apply le_max_right
· exact le_rfl
rw [hpf, hpg, h]
theorem norm_neg (a : PadicSeq p) : (-a).norm = a.norm :=
norm_eq <| by simp
theorem norm_eq_of_add_equiv_zero {f g : PadicSeq p} (h : f + g ≈ 0) : f.norm = g.norm := by
have : LimZero (f + g - 0) := h
have : f ≈ -g := show LimZero (f - -g) by simpa only [sub_zero, sub_neg_eq_add]
have : f.norm = (-g).norm := norm_equiv this
simpa only [norm_neg] using this
theorem add_eq_max_of_ne {f g : PadicSeq p} (hfgne : f.norm ≠ g.norm) :
(f + g).norm = max f.norm g.norm := by
classical
have hfg : ¬f + g ≈ 0 := mt norm_eq_of_add_equiv_zero hfgne
exact if hf : f ≈ 0 then by
have : LimZero (f - 0) := hf
have : f + g ≈ g := show LimZero (f + g - g) by simpa only [sub_zero, add_sub_cancel_right]
have h1 : (f + g).norm = g.norm := norm_equiv this
have h2 : f.norm = 0 := (norm_zero_iff _).2 hf
rw [h1, h2, max_eq_right (norm_nonneg _)]
else
if hg : g ≈ 0 then by
have : LimZero (g - 0) := hg
have : f + g ≈ f := show LimZero (f + g - f) by simpa only [add_sub_cancel_left, sub_zero]
have h1 : (f + g).norm = f.norm := norm_equiv this
have h2 : g.norm = 0 := (norm_zero_iff _).2 hg
rw [h1, h2, max_eq_left (norm_nonneg _)]
else by
unfold norm at hfgne ⊢; split_ifs at hfgne ⊢
-- Porting note: originally `padic_index_simp [hfg, hf, hg] at hfgne ⊢`
rw [lift_index_left hf, lift_index_right hg] at hfgne
· rw [lift_index_left_left hfg, lift_index_left hf, lift_index_right hg]
exact padicNorm.add_eq_max_of_ne hfgne
end Embedding
end PadicSeq
/-- The `p`-adic numbers `ℚ_[p]` are the Cauchy completion of `ℚ` with respect to the `p`-adic norm.
-/
def Padic (p : ℕ) [Fact p.Prime] :=
CauSeq.Completion.Cauchy (padicNorm p)
/-- notation for p-padic rationals -/
notation "ℚ_[" p "]" => Padic p
namespace Padic
section Completion
variable {p : ℕ} [Fact p.Prime]
instance field : Field ℚ_[p] :=
Cauchy.field
instance : Inhabited ℚ_[p] :=
⟨0⟩
-- short circuits
instance : CommRing ℚ_[p] :=
Cauchy.commRing
instance : Ring ℚ_[p] :=
Cauchy.ring
instance : Zero ℚ_[p] := by infer_instance
instance : One ℚ_[p] := by infer_instance
instance : Add ℚ_[p] := by infer_instance
instance : Mul ℚ_[p] := by infer_instance
instance : Sub ℚ_[p] := by infer_instance
instance : Neg ℚ_[p] := by infer_instance
instance : Div ℚ_[p] := by infer_instance
instance : AddCommGroup ℚ_[p] := by infer_instance
/-- Builds the equivalence class of a Cauchy sequence of rationals. -/
def mk : PadicSeq p → ℚ_[p] :=
Quotient.mk'
variable (p)
theorem zero_def : (0 : ℚ_[p]) = ⟦0⟧ := rfl
theorem mk_eq {f g : PadicSeq p} : mk f = mk g ↔ f ≈ g :=
Quotient.eq'
theorem const_equiv {q r : ℚ} : const (padicNorm p) q ≈ const (padicNorm p) r ↔ q = r :=
⟨fun heq ↦ eq_of_sub_eq_zero <| const_limZero.1 heq, fun heq ↦ by
rw [heq]⟩
@[norm_cast]
theorem coe_inj {q r : ℚ} : (↑q : ℚ_[p]) = ↑r ↔ q = r :=
⟨(const_equiv p).1 ∘ Quotient.eq'.1, fun h ↦ by rw [h]⟩
instance : CharZero ℚ_[p] :=
⟨fun m n ↦ by
rw [← Rat.cast_natCast]
norm_cast
exact id⟩
@[norm_cast]
theorem coe_add : ∀ {x y : ℚ}, (↑(x + y) : ℚ_[p]) = ↑x + ↑y :=
Rat.cast_add _ _
@[norm_cast]
theorem coe_neg : ∀ {x : ℚ}, (↑(-x) : ℚ_[p]) = -↑x :=
Rat.cast_neg _
@[norm_cast]
theorem coe_mul : ∀ {x y : ℚ}, (↑(x * y) : ℚ_[p]) = ↑x * ↑y :=
Rat.cast_mul _ _
@[norm_cast]
theorem coe_sub : ∀ {x y : ℚ}, (↑(x - y) : ℚ_[p]) = ↑x - ↑y :=
Rat.cast_sub _ _
@[norm_cast]
theorem coe_div : ∀ {x y : ℚ}, (↑(x / y) : ℚ_[p]) = ↑x / ↑y :=
Rat.cast_div _ _
@[norm_cast]
theorem coe_one : (↑(1 : ℚ) : ℚ_[p]) = 1 := rfl
@[norm_cast]
theorem coe_zero : (↑(0 : ℚ) : ℚ_[p]) = 0 := rfl
end Completion
end Padic
/-- The rational-valued `p`-adic norm on `ℚ_[p]` is lifted from the norm on Cauchy sequences. The
canonical form of this function is the normed space instance, with notation `‖ ‖`. -/
def padicNormE {p : ℕ} [hp : Fact p.Prime] : AbsoluteValue ℚ_[p] ℚ where
toFun := Quotient.lift PadicSeq.norm <| @PadicSeq.norm_equiv _ _
map_mul' q r := Quotient.inductionOn₂ q r <| PadicSeq.norm_mul
nonneg' q := Quotient.inductionOn q <| PadicSeq.norm_nonneg
eq_zero' q := Quotient.inductionOn q fun r ↦ by
rw [Padic.zero_def, Quotient.eq]
exact PadicSeq.norm_zero_iff r
add_le' q r := by
trans
max ((Quotient.lift PadicSeq.norm <| @PadicSeq.norm_equiv _ _) q)
((Quotient.lift PadicSeq.norm <| @PadicSeq.norm_equiv _ _) r)
· exact Quotient.inductionOn₂ q r <| PadicSeq.norm_nonarchimedean
refine max_le_add_of_nonneg (Quotient.inductionOn q <| PadicSeq.norm_nonneg) ?_
exact Quotient.inductionOn r <| PadicSeq.norm_nonneg
namespace padicNormE
section Embedding
open PadicSeq
variable {p : ℕ} [Fact p.Prime]
theorem defn (f : PadicSeq p) {ε : ℚ} (hε : 0 < ε) :
∃ N, ∀ i ≥ N, padicNormE (Padic.mk f - f i : ℚ_[p]) < ε := by
dsimp [padicNormE]
-- `change ∃ N, ∀ i ≥ N, (f - const _ (f i)).norm < ε` also works, but is very slow
suffices hyp : ∃ N, ∀ i ≥ N, (f - const _ (f i)).norm < ε by peel hyp with N; use N
by_contra! h
obtain ⟨N, hN⟩ := cauchy₂ f hε
rcases h N with ⟨i, hi, hge⟩
have hne : ¬f - const (padicNorm p) (f i) ≈ 0 := fun h ↦ by
rw [PadicSeq.norm, dif_pos h] at hge
exact not_lt_of_ge hge hε
unfold PadicSeq.norm at hge; split_ifs at hge
apply not_le_of_gt _ hge
cases _root_.le_total N (stationaryPoint hne) with
| inl hgen =>
exact hN _ hgen _ hi
| inr hngen =>
have := stationaryPoint_spec hne le_rfl hngen
rw [← this]
exact hN _ le_rfl _ hi
/-- Theorems about `padicNormE` are named with a `'` so the names do not conflict with the
equivalent theorems about `norm` (`‖ ‖`). -/
theorem nonarchimedean' (q r : ℚ_[p]) :
padicNormE (q + r : ℚ_[p]) ≤ max (padicNormE q) (padicNormE r) :=
Quotient.inductionOn₂ q r <| norm_nonarchimedean
/-- Theorems about `padicNormE` are named with a `'` so the names do not conflict with the
equivalent theorems about `norm` (`‖ ‖`). -/
theorem add_eq_max_of_ne' {q r : ℚ_[p]} :
padicNormE q ≠ padicNormE r → padicNormE (q + r : ℚ_[p]) = max (padicNormE q) (padicNormE r) :=
Quotient.inductionOn₂ q r fun _ _ ↦ PadicSeq.add_eq_max_of_ne
@[simp]
theorem eq_padic_norm' (q : ℚ) : padicNormE (q : ℚ_[p]) = padicNorm p q :=
norm_const _
protected theorem image' {q : ℚ_[p]} : q ≠ 0 → ∃ n : ℤ, padicNormE q = (p : ℚ) ^ (-n) :=
Quotient.inductionOn q fun f hf ↦
have : ¬f ≈ 0 := (ne_zero_iff_nequiv_zero f).1 hf
norm_values_discrete f this
end Embedding
end padicNormE
namespace Padic
section Complete
open PadicSeq Padic
variable {p : ℕ} [Fact p.Prime] (f : CauSeq _ (@padicNormE p _))
theorem rat_dense' (q : ℚ_[p]) {ε : ℚ} (hε : 0 < ε) : ∃ r : ℚ, padicNormE (q - r : ℚ_[p]) < ε :=
Quotient.inductionOn q fun q' ↦
have : ∃ N, ∀ m ≥ N, ∀ n ≥ N, padicNorm p (q' m - q' n) < ε := cauchy₂ _ hε
let ⟨N, hN⟩ := this
⟨q' N, by
classical
dsimp [padicNormE]
-- Porting note: this used to be `change`, but that times out.
convert_to PadicSeq.norm (q' - const _ (q' N)) < ε
rcases Decidable.em (q' - const (padicNorm p) (q' N) ≈ 0) with heq | hne'
· simpa only [heq, PadicSeq.norm, dif_pos]
· simp only [PadicSeq.norm, dif_neg hne']
change padicNorm p (q' _ - q' _) < ε
rcases Decidable.em (stationaryPoint hne' ≤ N) with hle | hle
· have := (stationaryPoint_spec hne' le_rfl hle).symm
simp only [const_apply, sub_apply, padicNorm.zero, sub_self] at this
simpa only [this]
· exact hN _ (lt_of_not_ge hle).le _ le_rfl⟩
private theorem div_nat_pos (n : ℕ) : 0 < 1 / (n + 1 : ℚ) :=
div_pos zero_lt_one (mod_cast succ_pos _)
/-- `limSeq f`, for `f` a Cauchy sequence of `p`-adic numbers, is a sequence of rationals with the
same limit point as `f`. -/
def limSeq : ℕ → ℚ :=
fun n ↦ Classical.choose (rat_dense' (f n) (div_nat_pos n))
theorem exi_rat_seq_conv {ε : ℚ} (hε : 0 < ε) :
∃ N, ∀ i ≥ N, padicNormE (f i - (limSeq f i : ℚ_[p]) : ℚ_[p]) < ε := by
refine (exists_nat_gt (1 / ε)).imp fun N hN i hi ↦ ?_
have h := Classical.choose_spec (rat_dense' (f i) (div_nat_pos i))
refine lt_of_lt_of_le h ((div_le_iff₀' <| mod_cast succ_pos _).mpr ?_)
rw [right_distrib]
apply le_add_of_le_of_nonneg
· exact (div_le_iff₀ hε).mp (le_trans (le_of_lt hN) (mod_cast hi))
· apply le_of_lt
simpa
theorem exi_rat_seq_conv_cauchy : IsCauSeq (padicNorm p) (limSeq f) := fun ε hε ↦ by
have hε3 : 0 < ε / 3 := div_pos hε (by norm_num)
let ⟨N, hN⟩ := exi_rat_seq_conv f hε3
let ⟨N2, hN2⟩ := f.cauchy₂ hε3
exists max N N2
intro j hj
suffices
padicNormE (limSeq f j - f (max N N2) + (f (max N N2) - limSeq f (max N N2)) : ℚ_[p]) < ε by
ring_nf at this ⊢
rw [← padicNormE.eq_padic_norm']
exact mod_cast this
apply lt_of_le_of_lt
· apply padicNormE.add_le
· rw [← add_thirds ε]
apply _root_.add_lt_add
· suffices padicNormE (limSeq f j - f j + (f j - f (max N N2)) : ℚ_[p]) < ε / 3 + ε / 3 by
simpa only [sub_add_sub_cancel]
apply lt_of_le_of_lt
· apply padicNormE.add_le
· apply _root_.add_lt_add
· rw [padicNormE.map_sub]
apply mod_cast hN j
exact le_of_max_le_left hj
· exact hN2 _ (le_of_max_le_right hj) _ (le_max_right _ _)
· apply mod_cast hN (max N N2)
apply le_max_left
private def lim' : PadicSeq p :=
⟨_, exi_rat_seq_conv_cauchy f⟩
private def lim : ℚ_[p] :=
⟦lim' f⟧
theorem complete' : ∃ q : ℚ_[p], ∀ ε > 0, ∃ N, ∀ i ≥ N, padicNormE (q - f i : ℚ_[p]) < ε :=
⟨lim f, fun ε hε ↦ by
obtain ⟨N, hN⟩ := exi_rat_seq_conv f (half_pos hε)
obtain ⟨N2, hN2⟩ := padicNormE.defn (lim' f) (half_pos hε)
refine ⟨max N N2, fun i hi ↦ ?_⟩
rw [← sub_add_sub_cancel _ (lim' f i : ℚ_[p]) _]
refine (padicNormE.add_le _ _).trans_lt ?_
rw [← add_halves ε]
apply _root_.add_lt_add
· apply hN2 _ (le_of_max_le_right hi)
· rw [padicNormE.map_sub]
exact hN _ (le_of_max_le_left hi)⟩
theorem complete'' : ∃ q : ℚ_[p], ∀ ε > 0, ∃ N, ∀ i ≥ N, padicNormE (f i - q : ℚ_[p]) < ε := by
obtain ⟨x, hx⟩ := complete' f
refine ⟨x, fun ε hε => ?_⟩
obtain ⟨N, hN⟩ := hx ε hε
refine ⟨N, fun i hi => ?_⟩
rw [padicNormE.map_sub]
exact hN i hi
end Complete
section NormedSpace
variable (p : ℕ) [Fact p.Prime]
instance : Dist ℚ_[p] :=
⟨fun x y ↦ padicNormE (x - y : ℚ_[p])⟩
instance : IsUltrametricDist ℚ_[p] :=
⟨fun x y z ↦ by simpa [dist] using padicNormE.nonarchimedean' (x - y) (y - z)⟩
instance metricSpace : MetricSpace ℚ_[p] where
dist_self := by simp [dist]
dist := dist
dist_comm x y := by simp [dist, ← padicNormE.map_neg (x - y : ℚ_[p])]
dist_triangle x y z := by
dsimp [dist]
exact mod_cast padicNormE.sub_le x y z
eq_of_dist_eq_zero := by
dsimp [dist]; intro _ _ h
apply eq_of_sub_eq_zero
apply padicNormE.eq_zero.1
exact mod_cast h
instance : Norm ℚ_[p] :=
⟨fun x ↦ padicNormE x⟩
instance normedField : NormedField ℚ_[p] :=
{ Padic.field,
Padic.metricSpace p with
dist_eq := fun _ _ ↦ rfl
norm_mul := by simp [Norm.norm, map_mul]
norm := norm }
instance isAbsoluteValue : IsAbsoluteValue fun a : ℚ_[p] ↦ ‖a‖ where
abv_nonneg' := norm_nonneg
abv_eq_zero' := norm_eq_zero
abv_add' := norm_add_le
abv_mul' := by simp [Norm.norm, map_mul]
theorem rat_dense (q : ℚ_[p]) {ε : ℝ} (hε : 0 < ε) : ∃ r : ℚ, ‖q - r‖ < ε :=
let ⟨ε', hε'l, hε'r⟩ := exists_rat_btwn hε
let ⟨r, hr⟩ := rat_dense' q (ε := ε') (by simpa using hε'l)
⟨r, lt_trans (by simpa [Norm.norm] using hr) hε'r⟩
end NormedSpace
end Padic
namespace padicNormE
section NormedSpace
variable {p : ℕ} [hp : Fact p.Prime]
-- Porting note: Linter thinks this is a duplicate simp lemma, so `priority` is assigned
@[simp (high)]
protected theorem mul (q r : ℚ_[p]) : ‖q * r‖ = ‖q‖ * ‖r‖ := by simp [Norm.norm, map_mul]
protected theorem is_norm (q : ℚ_[p]) : ↑(padicNormE q) = ‖q‖ := rfl
theorem nonarchimedean (q r : ℚ_[p]) : ‖q + r‖ ≤ max ‖q‖ ‖r‖ := by
dsimp [norm]
exact mod_cast nonarchimedean' _ _
theorem add_eq_max_of_ne {q r : ℚ_[p]} (h : ‖q‖ ≠ ‖r‖) : ‖q + r‖ = max ‖q‖ ‖r‖ := by
dsimp [norm] at h ⊢
have : padicNormE q ≠ padicNormE r := mod_cast h
exact mod_cast add_eq_max_of_ne' this
@[simp]
theorem eq_padicNorm (q : ℚ) : ‖(q : ℚ_[p])‖ = padicNorm p q := by
dsimp [norm]
rw [← padicNormE.eq_padic_norm']
@[simp]
theorem norm_p : ‖(p : ℚ_[p])‖ = (p : ℝ)⁻¹ := by
rw [← @Rat.cast_natCast ℝ _ p]
rw [← @Rat.cast_natCast ℚ_[p] _ p]
simp [hp.1.ne_zero, hp.1.ne_one, norm, padicNorm, padicValRat, padicValInt, zpow_neg,
-Rat.cast_natCast]
theorem norm_p_lt_one : ‖(p : ℚ_[p])‖ < 1 := by
rw [norm_p]
exact inv_lt_one_of_one_lt₀ <| mod_cast hp.1.one_lt
-- Porting note: Linter thinks this is a duplicate simp lemma, so `priority` is assigned
@[simp (high)]
theorem norm_p_zpow (n : ℤ) : ‖(p : ℚ_[p]) ^ n‖ = (p : ℝ) ^ (-n) := by
rw [norm_zpow, norm_p, zpow_neg, inv_zpow]
-- Porting note: Linter thinks this is a duplicate simp lemma, so `priority` is assigned
@[simp (high)]
theorem norm_p_pow (n : ℕ) : ‖(p : ℚ_[p]) ^ n‖ = (p : ℝ) ^ (-n : ℤ) := by
rw [← norm_p_zpow, zpow_natCast]
instance : NontriviallyNormedField ℚ_[p] :=
{ Padic.normedField p with
non_trivial :=
⟨p⁻¹, by
rw [norm_inv, norm_p, inv_inv]
exact mod_cast hp.1.one_lt⟩ }
protected theorem image {q : ℚ_[p]} : q ≠ 0 → ∃ n : ℤ, ‖q‖ = ↑((p : ℚ) ^ (-n)) :=
Quotient.inductionOn q fun f hf ↦
have : ¬f ≈ 0 := (PadicSeq.ne_zero_iff_nequiv_zero f).1 hf
let ⟨n, hn⟩ := PadicSeq.norm_values_discrete f this
⟨n, by rw [← hn]; rfl⟩
protected theorem is_rat (q : ℚ_[p]) : ∃ q' : ℚ, ‖q‖ = q' := by
classical
exact if h : q = 0 then ⟨0, by simp [h]⟩
else
let ⟨n, hn⟩ := padicNormE.image h
⟨_, hn⟩
/-- `ratNorm q`, for a `p`-adic number `q` is the `p`-adic norm of `q`, as rational number.
The lemma `padicNormE.eq_ratNorm` asserts `‖q‖ = ratNorm q`. -/
def ratNorm (q : ℚ_[p]) : ℚ :=
Classical.choose (padicNormE.is_rat q)
theorem eq_ratNorm (q : ℚ_[p]) : ‖q‖ = ratNorm q :=
Classical.choose_spec (padicNormE.is_rat q)
theorem norm_rat_le_one : ∀ {q : ℚ} (_ : ¬p ∣ q.den), ‖(q : ℚ_[p])‖ ≤ 1
| ⟨n, d, hn, hd⟩ => fun hq : ¬p ∣ d ↦
if hnz : n = 0 then by
have : (⟨n, d, hn, hd⟩ : ℚ) = 0 := Rat.zero_iff_num_zero.mpr hnz
| norm_num [this]
else by
have hnz' : (⟨n, d, hn, hd⟩ : ℚ) ≠ 0 := mt Rat.zero_iff_num_zero.1 hnz
rw [padicNormE.eq_padicNorm]
| Mathlib/NumberTheory/Padics/PadicNumbers.lean | 824 | 827 |
/-
Copyright (c) 2022 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Combinatorics.Additive.AP.Three.Defs
import Mathlib.Combinatorics.Additive.Corner.Defs
import Mathlib.Combinatorics.SimpleGraph.Triangle.Removal
import Mathlib.Combinatorics.SimpleGraph.Triangle.Tripartite
/-!
# The corners theorem and Roth's theorem
This file proves the corners theorem and Roth's theorem on arithmetic progressions of length three.
## References
* [Yaël Dillies, Bhavik Mehta, *Formalising Szemerédi’s Regularity Lemma in Lean*][srl_itp]
* [Wikipedia, *Corners theorem*](https://en.wikipedia.org/wiki/Corners_theorem)
-/
open Finset SimpleGraph TripartiteFromTriangles
open Function hiding graph
open Fintype (card)
variable {G : Type*} [AddCommGroup G] {A : Finset (G × G)} {a b c : G} {n : ℕ} {ε : ℝ}
namespace Corners
/-- The triangle indices for the proof of the corners theorem construction. -/
private def triangleIndices (A : Finset (G × G)) : Finset (G × G × G) :=
A.map ⟨fun (a, b) ↦ (a, b, a + b), by rintro ⟨x₁, x₂⟩ ⟨y₁, y₂⟩ ⟨⟩; rfl⟩
@[simp]
private lemma mk_mem_triangleIndices : (a, b, c) ∈ triangleIndices A ↔ (a, b) ∈ A ∧ c = a + b := by
simp only [triangleIndices, Prod.ext_iff, mem_map, Embedding.coeFn_mk, exists_prop, Prod.exists,
eq_comm]
refine ⟨?_, fun h ↦ ⟨_, _, h.1, rfl, rfl, h.2⟩⟩
rintro ⟨_, _, h₁, rfl, rfl, h₂⟩
exact ⟨h₁, h₂⟩
@[simp] private lemma card_triangleIndices : #(triangleIndices A) = #A := card_map _
private instance triangleIndices.instExplicitDisjoint : ExplicitDisjoint (triangleIndices A) := by
constructor
all_goals
simp only [mk_mem_triangleIndices, Prod.mk_inj, exists_prop, forall_exists_index, and_imp]
rintro a b _ a' - rfl - h'
simp [Fin.val_eq_val, *] at * <;> assumption
private lemma noAccidental (hs : IsCornerFree (A : Set (G × G))) :
NoAccidental (triangleIndices A) where
eq_or_eq_or_eq a a' b b' c c' ha hb hc := by
simp only [mk_mem_triangleIndices] at ha hb hc
exact .inl <| hs ⟨hc.1, hb.1, ha.1, hb.2.symm.trans ha.2⟩
private lemma farFromTriangleFree_graph [Fintype G] [DecidableEq G] (hε : ε * card G ^ 2 ≤ #A) :
(graph <| triangleIndices A).FarFromTriangleFree (ε / 9) := by
refine farFromTriangleFree _ ?_
simp_rw [card_triangleIndices, mul_comm_div, Nat.cast_pow, Nat.cast_add]
ring_nf
simpa only [mul_comm] using hε
end Corners
variable [Fintype G]
open Corners
/-- An explicit form for the constant in the corners theorem.
Note that this depends on `SzemerediRegularity.bound`, which is a tower-type exponential. This means
`cornersTheoremBound` is in practice absolutely tiny. -/
noncomputable def cornersTheoremBound (ε : ℝ) : ℕ := ⌊(triangleRemovalBound (ε / 9) * 27)⁻¹⌋₊ + 1
/-- The **corners theorem** for finite abelian groups.
The maximum density of a corner-free set in `G × G` goes to zero as `|G|` tends to infinity. -/
theorem corners_theorem (ε : ℝ) (hε : 0 < ε) (hG : cornersTheoremBound ε ≤ card G)
(A : Finset (G × G)) (hAε : ε * card G ^ 2 ≤ #A) : ¬ IsCornerFree (A : Set (G × G)) := by
rintro hA
rw [cornersTheoremBound, Nat.add_one_le_iff] at hG
have hε₁ : ε ≤ 1 := by
have := hAε.trans (Nat.cast_le.2 A.card_le_univ)
simp only [sq, Nat.cast_mul, Fintype.card_prod, Fintype.card_fin] at this
rwa [mul_le_iff_le_one_left] at this
positivity
have := noAccidental hA
rw [Nat.floor_lt' (by positivity), inv_lt_iff_one_lt_mul₀'] at hG
swap
· have : ε / 9 ≤ 1 := by linarith
positivity
refine hG.not_le (le_of_mul_le_mul_right ?_ (by positivity : (0 : ℝ) < card G ^ 2))
classical
have h₁ := (farFromTriangleFree_graph hAε).le_card_cliqueFinset
rw [card_triangles, card_triangleIndices] at h₁
convert h₁.trans (Nat.cast_le.2 <| card_le_univ _) using 1 <;> simp <;> ring
/-- The **corners theorem** for `ℕ`.
The maximum density of a corner-free set in `{1, ..., n} × {1, ..., n}` goes to zero as `n` tends to
infinity. -/
theorem corners_theorem_nat (hε : 0 < ε) (hn : cornersTheoremBound (ε / 9) ≤ n)
(A : Finset (ℕ × ℕ)) (hAn : A ⊆ range n ×ˢ range n) (hAε : ε * n ^ 2 ≤ #A) :
¬ IsCornerFree (A : Set (ℕ × ℕ)) := by
rintro hA
rw [← coe_subset, coe_product] at hAn
have : A = Prod.map Fin.val Fin.val ''
(Prod.map Nat.cast Nat.cast '' A : Set (Fin (2 * n).succ × Fin (2 * n).succ)) := by
rw [Set.image_image, Set.image_congr, Set.image_id]
simp only [mem_coe, Nat.succ_eq_add_one, Prod.map_apply, Fin.val_natCast, id_eq, Prod.forall,
Prod.mk.injEq, Nat.mod_succ_eq_iff_lt]
rintro a b hab
have := hAn hab
simp at this
omega
rw [this] at hA
have := Fin.isAddFreimanIso_Iio two_ne_zero (le_refl (2 * n))
have := hA.of_image this.isAddFreimanHom Fin.val_injective.injOn <| by
refine Set.image_subset_iff.2 <| hAn.trans fun x hx ↦ ?_
simp only [coe_range, Set.mem_prod, Set.mem_Iio] at hx
exact ⟨Fin.natCast_strictMono (by omega) hx.1, Fin.natCast_strictMono (by omega) hx.2⟩
rw [← coe_image] at this
refine corners_theorem (ε / 9) (by positivity) (by simp; omega) _ ?_ this
calc
_ = ε / 9 * (2 * n + 1) ^ 2 := by simp
_ ≤ ε / 9 * (2 * n + n) ^ 2 := by gcongr; simp; unfold cornersTheoremBound at hn; omega
_ = ε * n ^ 2 := by ring
_ ≤ #A := hAε
_ = _ := by
rw [card_image_of_injOn]
have : Set.InjOn Nat.cast (range n) :=
(CharP.natCast_injOn_Iio (Fin (2 * n).succ) (2 * n).succ).mono (by simp; omega)
exact (this.prodMap this).mono hAn
/-- **Roth's theorem** for finite abelian groups.
The maximum density of a 3AP-free set in `G` goes to zero as `|G|` tends to infinity. -/
theorem roth_3ap_theorem (ε : ℝ) (hε : 0 < ε) (hG : cornersTheoremBound ε ≤ card G)
(A : Finset G) (hAε : ε * card G ≤ #A) : ¬ ThreeAPFree (A : Set G) := by
rintro hA
classical
let B : Finset (G × G) := univ.filter fun (x, y) ↦ y - x ∈ A
have : ε * card G ^ 2 ≤ #B := by
calc
_ = card G * (ε * card G) := by ring
_ ≤ card G * #A := by gcongr
_ = #B := ?_
norm_cast
rw [← card_univ, ← card_product]
exact card_equiv ((Equiv.refl _).prodShear fun a ↦ Equiv.addLeft a) (by simp [B])
obtain ⟨x₁, y₁, x₂, y₂, hx₁y₁, hx₁y₂, hx₂y₁, hxy, hx₁x₂⟩ :
∃ x₁ y₁ x₂ y₂, y₁ - x₁ ∈ A ∧ y₂ - x₁ ∈ A ∧ y₁ - x₂ ∈ A ∧ x₁ + y₂ = x₂ + y₁ ∧ x₁ ≠ x₂ := by
simpa [IsCornerFree, isCorner_iff, B, -exists_and_left, -exists_and_right]
using corners_theorem ε hε hG B this
have := hA hx₂y₁ hx₁y₁ hx₁y₂ <| by -- TODO: This really ought to just be `by linear_combination h`
rw [sub_add_sub_comm, add_comm, add_sub_add_comm, add_right_cancel_iff,
sub_eq_sub_iff_add_eq_add, add_comm, hxy, add_comm]
exact hx₁x₂ <| by simpa using this.symm
/-- **Roth's theorem** for `ℕ`.
|
The maximum density of a 3AP-free set in `{1, ..., n}` goes to zero as `n` tends to infinity. -/
theorem roth_3ap_theorem_nat (ε : ℝ) (hε : 0 < ε) (hG : cornersTheoremBound (ε / 3) ≤ n)
(A : Finset ℕ) (hAn : A ⊆ range n) (hAε : ε * n ≤ #A) : ¬ ThreeAPFree (A : Set ℕ) := by
rintro hA
rw [← coe_subset, coe_range] at hAn
have : A = Fin.val '' (Nat.cast '' A : Set (Fin (2 * n).succ)) := by
rw [Set.image_image, Set.image_congr, Set.image_id]
simp only [mem_coe, Nat.succ_eq_add_one, Fin.val_natCast, id_eq, Nat.mod_succ_eq_iff_lt]
rintro a ha
have := hAn ha
simp at this
omega
rw [this] at hA
have := Fin.isAddFreimanIso_Iio two_ne_zero (le_refl (2 * n))
have := hA.of_image this.isAddFreimanHom Fin.val_injective.injOn <| Set.image_subset_iff.2 <|
hAn.trans fun x hx ↦ Fin.natCast_strictMono (by omega) <| by
simpa only [coe_range, Set.mem_Iio] using hx
rw [← coe_image] at this
refine roth_3ap_theorem (ε / 3) (by positivity) (by simp; omega) _ ?_ this
calc
_ = ε / 3 * (2 * n + 1) := by simp
_ ≤ ε / 3 * (2 * n + n) := by gcongr; simp; unfold cornersTheoremBound at hG; omega
_ = ε * n := by ring
_ ≤ #A := hAε
_ = _ := by
rw [card_image_of_injOn]
| Mathlib/Combinatorics/Additive/Corner/Roth.lean | 163 | 189 |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Yury Kudryashov
-/
import Mathlib.Algebra.Order.Ring.WithTop
import Mathlib.Algebra.Order.Sub.WithTop
import Mathlib.Data.NNReal.Defs
import Mathlib.Order.Interval.Set.WithBotTop
/-!
# Extended non-negative reals
We define `ENNReal = ℝ≥0∞ := WithTop ℝ≥0` to be the type of extended nonnegative real numbers,
i.e., the interval `[0, +∞]`. This type is used as the codomain of a `MeasureTheory.Measure`,
and of the extended distance `edist` in an `EMetricSpace`.
In this file we set up many of the instances on `ℝ≥0∞`, and provide relationships between `ℝ≥0∞` and
`ℝ≥0`, and between `ℝ≥0∞` and `ℝ`. In particular, we provide a coercion from `ℝ≥0` to `ℝ≥0∞` as well
as functions `ENNReal.toNNReal`, `ENNReal.ofReal` and `ENNReal.toReal`, all of which take the value
zero wherever they cannot be the identity. Also included is the relationship between `ℝ≥0∞` and `ℕ`.
The interaction of these functions, especially `ENNReal.ofReal` and `ENNReal.toReal`, with the
algebraic and lattice structure can be found in `Data.ENNReal.Real`.
This file proves many of the order properties of `ℝ≥0∞`, with the exception of the ways those relate
to the algebraic structure, which are included in `Data.ENNReal.Operations`.
This file also defines inversion and division: this includes `Inv` and `Div` instances on `ℝ≥0∞`
making it into a `DivInvOneMonoid`.
As a consequence of being a `DivInvOneMonoid`, `ℝ≥0∞` inherits a power operation with integer
exponent: this and other properties is shown in `Data.ENNReal.Inv`.
## Main definitions
* `ℝ≥0∞`: the extended nonnegative real numbers `[0, ∞]`; defined as `WithTop ℝ≥0`; it is
equipped with the following structures:
- coercion from `ℝ≥0` defined in the natural way;
- the natural structure of a complete dense linear order: `↑p ≤ ↑q ↔ p ≤ q` and `∀ a, a ≤ ∞`;
- `a + b` is defined so that `↑p + ↑q = ↑(p + q)` for `(p q : ℝ≥0)` and `a + ∞ = ∞ + a = ∞`;
- `a * b` is defined so that `↑p * ↑q = ↑(p * q)` for `(p q : ℝ≥0)`, `0 * ∞ = ∞ * 0 = 0`, and
`a * ∞ = ∞ * a = ∞` for `a ≠ 0`;
- `a - b` is defined as the minimal `d` such that `a ≤ d + b`; this way we have
`↑p - ↑q = ↑(p - q)`, `∞ - ↑p = ∞`, `↑p - ∞ = ∞ - ∞ = 0`; note that there is no negation, only
subtraction;
The addition and multiplication defined this way together with `0 = ↑0` and `1 = ↑1` turn
`ℝ≥0∞` into a canonically ordered commutative semiring of characteristic zero.
- `a⁻¹` is defined as `Inf {b | 1 ≤ a * b}`. This way we have `(↑p)⁻¹ = ↑(p⁻¹)` for
`p : ℝ≥0`, `p ≠ 0`, `0⁻¹ = ∞`, and `∞⁻¹ = 0`.
- `a / b` is defined as `a * b⁻¹`.
This inversion and division include `Inv` and `Div` instances on `ℝ≥0∞`,
making it into a `DivInvOneMonoid`. Further properties of these are shown in `Data.ENNReal.Inv`.
* Coercions to/from other types:
- coercion `ℝ≥0 → ℝ≥0∞` is defined as `Coe`, so one can use `(p : ℝ≥0)` in a context that
expects `a : ℝ≥0∞`, and Lean will apply `coe` automatically;
- `ENNReal.toNNReal` sends `↑p` to `p` and `∞` to `0`;
- `ENNReal.toReal := coe ∘ ENNReal.toNNReal` sends `↑p`, `p : ℝ≥0` to `(↑p : ℝ)` and `∞` to `0`;
- `ENNReal.ofReal := coe ∘ Real.toNNReal` sends `x : ℝ` to `↑⟨max x 0, _⟩`
- `ENNReal.neTopEquivNNReal` is an equivalence between `{a : ℝ≥0∞ // a ≠ 0}` and `ℝ≥0`.
## Implementation notes
We define a `CanLift ℝ≥0∞ ℝ≥0` instance, so one of the ways to prove theorems about an `ℝ≥0∞`
number `a` is to consider the cases `a = ∞` and `a ≠ ∞`, and use the tactic `lift a to ℝ≥0 using ha`
in the second case. This instance is even more useful if one already has `ha : a ≠ ∞` in the
context, or if we have `(f : α → ℝ≥0∞) (hf : ∀ x, f x ≠ ∞)`.
## Notations
* `ℝ≥0∞`: the type of the extended nonnegative real numbers;
* `ℝ≥0`: the type of nonnegative real numbers `[0, ∞)`; defined in `Data.Real.NNReal`;
* `∞`: a localized notation in `ENNReal` for `⊤ : ℝ≥0∞`.
-/
assert_not_exists Finset
open Function Set NNReal
variable {α : Type*}
/-- The extended nonnegative real numbers. This is usually denoted [0, ∞],
and is relevant as the codomain of a measure. -/
def ENNReal := WithTop ℝ≥0
deriving Zero, Top, AddCommMonoidWithOne, SemilatticeSup, DistribLattice, Nontrivial
@[inherit_doc]
scoped[ENNReal] notation "ℝ≥0∞" => ENNReal
/-- Notation for infinity as an `ENNReal` number. -/
scoped[ENNReal] notation "∞" => (⊤ : ENNReal)
namespace ENNReal
instance : OrderBot ℝ≥0∞ := inferInstanceAs (OrderBot (WithTop ℝ≥0))
instance : OrderTop ℝ≥0∞ := inferInstanceAs (OrderTop (WithTop ℝ≥0))
instance : BoundedOrder ℝ≥0∞ := inferInstanceAs (BoundedOrder (WithTop ℝ≥0))
instance : CharZero ℝ≥0∞ := inferInstanceAs (CharZero (WithTop ℝ≥0))
instance : Min ℝ≥0∞ := SemilatticeInf.toMin
instance : Max ℝ≥0∞ := SemilatticeSup.toMax
noncomputable instance : CommSemiring ℝ≥0∞ :=
inferInstanceAs (CommSemiring (WithTop ℝ≥0))
instance : PartialOrder ℝ≥0∞ :=
inferInstanceAs (PartialOrder (WithTop ℝ≥0))
instance : IsOrderedRing ℝ≥0∞ :=
inferInstanceAs (IsOrderedRing (WithTop ℝ≥0))
instance : CanonicallyOrderedAdd ℝ≥0∞ :=
inferInstanceAs (CanonicallyOrderedAdd (WithTop ℝ≥0))
instance : NoZeroDivisors ℝ≥0∞ :=
inferInstanceAs (NoZeroDivisors (WithTop ℝ≥0))
noncomputable instance : CompleteLinearOrder ℝ≥0∞ :=
inferInstanceAs (CompleteLinearOrder (WithTop ℝ≥0))
instance : DenselyOrdered ℝ≥0∞ := inferInstanceAs (DenselyOrdered (WithTop ℝ≥0))
instance : AddCommMonoid ℝ≥0∞ :=
inferInstanceAs (AddCommMonoid (WithTop ℝ≥0))
noncomputable instance : LinearOrder ℝ≥0∞ :=
inferInstanceAs (LinearOrder (WithTop ℝ≥0))
instance : IsOrderedAddMonoid ℝ≥0∞ :=
inferInstanceAs (IsOrderedAddMonoid (WithTop ℝ≥0))
instance instSub : Sub ℝ≥0∞ := inferInstanceAs (Sub (WithTop ℝ≥0))
instance : OrderedSub ℝ≥0∞ := inferInstanceAs (OrderedSub (WithTop ℝ≥0))
noncomputable instance : LinearOrderedAddCommMonoidWithTop ℝ≥0∞ :=
inferInstanceAs (LinearOrderedAddCommMonoidWithTop (WithTop ℝ≥0))
-- RFC: redefine using pattern matching?
noncomputable instance : Inv ℝ≥0∞ := ⟨fun a => sInf { b | 1 ≤ a * b }⟩
noncomputable instance : DivInvMonoid ℝ≥0∞ where
variable {a b c d : ℝ≥0∞} {r p q : ℝ≥0}
-- TODO: add a `WithTop` instance and use it here
noncomputable instance : LinearOrderedCommMonoidWithZero ℝ≥0∞ :=
{ inferInstanceAs (LinearOrderedAddCommMonoidWithTop ℝ≥0∞),
inferInstanceAs (CommSemiring ℝ≥0∞) with
bot_le _ := bot_le
mul_le_mul_left := fun _ _ => mul_le_mul_left'
zero_le_one := zero_le 1 }
instance : Unique (AddUnits ℝ≥0∞) where
default := 0
uniq a := AddUnits.ext <| le_zero_iff.1 <| by rw [← a.add_neg]; exact le_self_add
instance : Inhabited ℝ≥0∞ := ⟨0⟩
/-- Coercion from `ℝ≥0` to `ℝ≥0∞`. -/
@[coe, match_pattern] def ofNNReal : ℝ≥0 → ℝ≥0∞ := WithTop.some
instance : Coe ℝ≥0 ℝ≥0∞ := ⟨ofNNReal⟩
/-- A version of `WithTop.recTopCoe` that uses `ENNReal.ofNNReal`. -/
@[elab_as_elim, induction_eliminator, cases_eliminator]
def recTopCoe {C : ℝ≥0∞ → Sort*} (top : C ∞) (coe : ∀ x : ℝ≥0, C x) (x : ℝ≥0∞) : C x :=
WithTop.recTopCoe top coe x
instance canLift : CanLift ℝ≥0∞ ℝ≥0 ofNNReal (· ≠ ∞) := WithTop.canLift
@[simp] theorem none_eq_top : (none : ℝ≥0∞) = ∞ := rfl
@[simp] theorem some_eq_coe (a : ℝ≥0) : (Option.some a : ℝ≥0∞) = (↑a : ℝ≥0∞) := rfl
@[simp] theorem some_eq_coe' (a : ℝ≥0) : (WithTop.some a : ℝ≥0∞) = (↑a : ℝ≥0∞) := rfl
lemma coe_injective : Injective ((↑) : ℝ≥0 → ℝ≥0∞) := WithTop.coe_injective
@[simp, norm_cast] lemma coe_inj : (p : ℝ≥0∞) = q ↔ p = q := coe_injective.eq_iff
lemma coe_ne_coe : (p : ℝ≥0∞) ≠ q ↔ p ≠ q := coe_inj.not
theorem range_coe' : range ofNNReal = Iio ∞ := WithTop.range_coe
theorem range_coe : range ofNNReal = {∞}ᶜ := (isCompl_range_some_none ℝ≥0).symm.compl_eq.symm
instance : NNRatCast ℝ≥0∞ where
nnratCast r := ofNNReal r
@[norm_cast]
theorem coe_nnratCast (q : ℚ≥0) : ↑(q : ℝ≥0) = (q : ℝ≥0∞) := rfl
/-- `toNNReal x` returns `x` if it is real, otherwise 0. -/
protected def toNNReal : ℝ≥0∞ → ℝ≥0 := WithTop.untopD 0
/-- `toReal x` returns `x` if it is real, `0` otherwise. -/
protected def toReal (a : ℝ≥0∞) : Real := a.toNNReal
/-- `ofReal x` returns `x` if it is nonnegative, `0` otherwise. -/
protected def ofReal (r : Real) : ℝ≥0∞ := r.toNNReal
@[simp, norm_cast] lemma toNNReal_coe (r : ℝ≥0) : (r : ℝ≥0∞).toNNReal = r := rfl
@[simp]
theorem coe_toNNReal : ∀ {a : ℝ≥0∞}, a ≠ ∞ → ↑a.toNNReal = a
| ofNNReal _, _ => rfl
| ⊤, h => (h rfl).elim
@[simp]
theorem coe_comp_toNNReal_comp {ι : Type*} {f : ι → ℝ≥0∞} (hf : ∀ x, f x ≠ ∞) :
(fun (x : ℝ≥0) => (x : ℝ≥0∞)) ∘ ENNReal.toNNReal ∘ f = f := by
ext x
simp [coe_toNNReal (hf x)]
@[simp]
theorem ofReal_toReal {a : ℝ≥0∞} (h : a ≠ ∞) : ENNReal.ofReal a.toReal = a := by
simp [ENNReal.toReal, ENNReal.ofReal, h]
@[simp]
theorem toReal_ofReal {r : ℝ} (h : 0 ≤ r) : (ENNReal.ofReal r).toReal = r :=
max_eq_left h
theorem toReal_ofReal' {r : ℝ} : (ENNReal.ofReal r).toReal = max r 0 := rfl
theorem coe_toNNReal_le_self : ∀ {a : ℝ≥0∞}, ↑a.toNNReal ≤ a
| ofNNReal r => by rw [toNNReal_coe]
| ⊤ => le_top
theorem coe_nnreal_eq (r : ℝ≥0) : (r : ℝ≥0∞) = ENNReal.ofReal r := by
rw [ENNReal.ofReal, Real.toNNReal_coe]
theorem ofReal_eq_coe_nnreal {x : ℝ} (h : 0 ≤ x) :
ENNReal.ofReal x = ofNNReal ⟨x, h⟩ :=
(coe_nnreal_eq ⟨x, h⟩).symm
theorem ofNNReal_toNNReal (x : ℝ) : (Real.toNNReal x : ℝ≥0∞) = ENNReal.ofReal x := rfl
@[simp] theorem ofReal_coe_nnreal : ENNReal.ofReal p = p := (coe_nnreal_eq p).symm
@[simp, norm_cast] theorem coe_zero : ↑(0 : ℝ≥0) = (0 : ℝ≥0∞) := rfl
@[simp, norm_cast] theorem coe_one : ↑(1 : ℝ≥0) = (1 : ℝ≥0∞) := rfl
@[simp] theorem toReal_nonneg {a : ℝ≥0∞} : 0 ≤ a.toReal := a.toNNReal.2
@[norm_cast] theorem coe_toNNReal_eq_toReal (z : ℝ≥0∞) : (z.toNNReal : ℝ) = z.toReal := rfl
@[simp] theorem toNNReal_toReal_eq (z : ℝ≥0∞) : z.toReal.toNNReal = z.toNNReal := by
ext; simp [coe_toNNReal_eq_toReal]
@[simp] theorem toNNReal_top : ∞.toNNReal = 0 := rfl
@[deprecated (since := "2025-03-20")] alias top_toNNReal := toNNReal_top
@[simp] theorem toReal_top : ∞.toReal = 0 := rfl
@[deprecated (since := "2025-03-20")] alias top_toReal := toReal_top
@[simp] theorem toReal_one : (1 : ℝ≥0∞).toReal = 1 := rfl
@[deprecated (since := "2025-03-20")] alias one_toReal := toReal_one
| @[simp] theorem toNNReal_one : (1 : ℝ≥0∞).toNNReal = 1 := rfl
| Mathlib/Data/ENNReal/Basic.lean | 274 | 274 |
/-
Copyright (c) 2022 Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kyle Miller, Vincent Beffara, Rida Hamadani
-/
import Mathlib.Combinatorics.SimpleGraph.Path
import Mathlib.Data.ENat.Lattice
/-!
# Graph metric
This module defines the `SimpleGraph.edist` function, which takes pairs of vertices to the length of
the shortest walk between them, or `⊤` if they are disconnected. It also defines `SimpleGraph.dist`
which is the `ℕ`-valued version of `SimpleGraph.edist`.
## Main definitions
- `SimpleGraph.edist` is the graph extended metric.
- `SimpleGraph.dist` is the graph metric.
## TODO
- Provide an additional computable version of `SimpleGraph.dist`
for when `G` is connected.
- When directed graphs exist, a directed notion of distance,
likely `ENat`-valued.
## Tags
graph metric, distance
-/
assert_not_exists Field
namespace SimpleGraph
variable {V : Type*} (G : SimpleGraph V)
/-! ## Metric -/
section edist
/--
The extended distance between two vertices is the length of the shortest walk between them.
It is `⊤` if no such walk exists.
-/
noncomputable def edist (u v : V) : ℕ∞ :=
⨅ w : G.Walk u v, w.length
variable {G} {u v w : V}
theorem edist_eq_sInf : G.edist u v = sInf (Set.range fun w : G.Walk u v ↦ (w.length : ℕ∞)) := rfl
protected theorem Reachable.exists_walk_length_eq_edist (hr : G.Reachable u v) :
∃ p : G.Walk u v, p.length = G.edist u v :=
csInf_mem <| Set.range_nonempty_iff_nonempty.mpr hr
protected theorem Connected.exists_walk_length_eq_edist (hconn : G.Connected) (u v : V) :
∃ p : G.Walk u v, p.length = G.edist u v :=
(hconn u v).exists_walk_length_eq_edist
theorem edist_le (p : G.Walk u v) :
G.edist u v ≤ p.length :=
sInf_le ⟨p, rfl⟩
protected alias Walk.edist_le := edist_le
@[simp]
theorem edist_eq_zero_iff :
G.edist u v = 0 ↔ u = v := by
apply Iff.intro <;> simp [edist, ENat.iInf_eq_zero]
| @[simp]
| Mathlib/Combinatorics/SimpleGraph/Metric.lean | 74 | 74 |
/-
Copyright (c) 2019 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison, Yaël Dillies
-/
import Mathlib.Order.Cover
import Mathlib.Order.Interval.Finset.Defs
/-!
# Intervals as finsets
This file provides basic results about all the `Finset.Ixx`, which are defined in
`Order.Interval.Finset.Defs`.
In addition, it shows that in a locally finite order `≤` and `<` are the transitive closures of,
respectively, `⩿` and `⋖`, which then leads to a characterization of monotone and strictly
functions whose domain is a locally finite order. In particular, this file proves:
* `le_iff_transGen_wcovBy`: `≤` is the transitive closure of `⩿`
* `lt_iff_transGen_covBy`: `<` is the transitive closure of `⋖`
* `monotone_iff_forall_wcovBy`: Characterization of monotone functions
* `strictMono_iff_forall_covBy`: Characterization of strictly monotone functions
## TODO
This file was originally only about `Finset.Ico a b` where `a b : ℕ`. No care has yet been taken to
generalize these lemmas properly and many lemmas about `Icc`, `Ioc`, `Ioo` are missing. In general,
what's to do is taking the lemmas in `Data.X.Intervals` and abstract away the concrete structure.
Complete the API. See
https://github.com/leanprover-community/mathlib/pull/14448#discussion_r906109235
for some ideas.
-/
assert_not_exists MonoidWithZero Finset.sum
open Function OrderDual
open FinsetInterval
variable {ι α : Type*} {a a₁ a₂ b b₁ b₂ c x : α}
namespace Finset
section Preorder
variable [Preorder α]
section LocallyFiniteOrder
variable [LocallyFiniteOrder α]
@[simp]
theorem nonempty_Icc : (Icc a b).Nonempty ↔ a ≤ b := by
rw [← coe_nonempty, coe_Icc, Set.nonempty_Icc]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Icc_of_le⟩ := nonempty_Icc
@[simp]
theorem nonempty_Ico : (Ico a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ico, Set.nonempty_Ico]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Ico_of_lt⟩ := nonempty_Ico
@[simp]
theorem nonempty_Ioc : (Ioc a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ioc, Set.nonempty_Ioc]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Ioc_of_lt⟩ := nonempty_Ioc
-- TODO: This is nonsense. A locally finite order is never densely ordered
@[simp]
theorem nonempty_Ioo [DenselyOrdered α] : (Ioo a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ioo, Set.nonempty_Ioo]
@[simp]
theorem Icc_eq_empty_iff : Icc a b = ∅ ↔ ¬a ≤ b := by
rw [← coe_eq_empty, coe_Icc, Set.Icc_eq_empty_iff]
@[simp]
theorem Ico_eq_empty_iff : Ico a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ico, Set.Ico_eq_empty_iff]
@[simp]
theorem Ioc_eq_empty_iff : Ioc a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ioc, Set.Ioc_eq_empty_iff]
-- TODO: This is nonsense. A locally finite order is never densely ordered
@[simp]
theorem Ioo_eq_empty_iff [DenselyOrdered α] : Ioo a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ioo, Set.Ioo_eq_empty_iff]
alias ⟨_, Icc_eq_empty⟩ := Icc_eq_empty_iff
alias ⟨_, Ico_eq_empty⟩ := Ico_eq_empty_iff
alias ⟨_, Ioc_eq_empty⟩ := Ioc_eq_empty_iff
@[simp]
theorem Ioo_eq_empty (h : ¬a < b) : Ioo a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ hx => h ((mem_Ioo.1 hx).1.trans (mem_Ioo.1 hx).2)
@[simp]
theorem Icc_eq_empty_of_lt (h : b < a) : Icc a b = ∅ :=
Icc_eq_empty h.not_le
@[simp]
theorem Ico_eq_empty_of_le (h : b ≤ a) : Ico a b = ∅ :=
Ico_eq_empty h.not_lt
@[simp]
theorem Ioc_eq_empty_of_le (h : b ≤ a) : Ioc a b = ∅ :=
Ioc_eq_empty h.not_lt
@[simp]
theorem Ioo_eq_empty_of_le (h : b ≤ a) : Ioo a b = ∅ :=
Ioo_eq_empty h.not_lt
theorem left_mem_Icc : a ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, true_and, le_rfl]
theorem left_mem_Ico : a ∈ Ico a b ↔ a < b := by simp only [mem_Ico, true_and, le_refl]
theorem right_mem_Icc : b ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, and_true, le_rfl]
theorem right_mem_Ioc : b ∈ Ioc a b ↔ a < b := by simp only [mem_Ioc, and_true, le_rfl]
theorem left_not_mem_Ioc : a ∉ Ioc a b := fun h => lt_irrefl _ (mem_Ioc.1 h).1
theorem left_not_mem_Ioo : a ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).1
theorem right_not_mem_Ico : b ∉ Ico a b := fun h => lt_irrefl _ (mem_Ico.1 h).2
theorem right_not_mem_Ioo : b ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).2
@[gcongr]
theorem Icc_subset_Icc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Icc a₁ b₁ ⊆ Icc a₂ b₂ := by
simpa [← coe_subset] using Set.Icc_subset_Icc ha hb
@[gcongr]
theorem Ico_subset_Ico (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ico a₁ b₁ ⊆ Ico a₂ b₂ := by
simpa [← coe_subset] using Set.Ico_subset_Ico ha hb
@[gcongr]
theorem Ioc_subset_Ioc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioc a₁ b₁ ⊆ Ioc a₂ b₂ := by
simpa [← coe_subset] using Set.Ioc_subset_Ioc ha hb
@[gcongr]
theorem Ioo_subset_Ioo (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioo a₁ b₁ ⊆ Ioo a₂ b₂ := by
simpa [← coe_subset] using Set.Ioo_subset_Ioo ha hb
@[gcongr]
theorem Icc_subset_Icc_left (h : a₁ ≤ a₂) : Icc a₂ b ⊆ Icc a₁ b :=
Icc_subset_Icc h le_rfl
@[gcongr]
theorem Ico_subset_Ico_left (h : a₁ ≤ a₂) : Ico a₂ b ⊆ Ico a₁ b :=
Ico_subset_Ico h le_rfl
@[gcongr]
theorem Ioc_subset_Ioc_left (h : a₁ ≤ a₂) : Ioc a₂ b ⊆ Ioc a₁ b :=
Ioc_subset_Ioc h le_rfl
@[gcongr]
theorem Ioo_subset_Ioo_left (h : a₁ ≤ a₂) : Ioo a₂ b ⊆ Ioo a₁ b :=
Ioo_subset_Ioo h le_rfl
@[gcongr]
theorem Icc_subset_Icc_right (h : b₁ ≤ b₂) : Icc a b₁ ⊆ Icc a b₂ :=
Icc_subset_Icc le_rfl h
@[gcongr]
theorem Ico_subset_Ico_right (h : b₁ ≤ b₂) : Ico a b₁ ⊆ Ico a b₂ :=
Ico_subset_Ico le_rfl h
@[gcongr]
theorem Ioc_subset_Ioc_right (h : b₁ ≤ b₂) : Ioc a b₁ ⊆ Ioc a b₂ :=
Ioc_subset_Ioc le_rfl h
@[gcongr]
theorem Ioo_subset_Ioo_right (h : b₁ ≤ b₂) : Ioo a b₁ ⊆ Ioo a b₂ :=
Ioo_subset_Ioo le_rfl h
theorem Ico_subset_Ioo_left (h : a₁ < a₂) : Ico a₂ b ⊆ Ioo a₁ b := by
rw [← coe_subset, coe_Ico, coe_Ioo]
exact Set.Ico_subset_Ioo_left h
theorem Ioc_subset_Ioo_right (h : b₁ < b₂) : Ioc a b₁ ⊆ Ioo a b₂ := by
rw [← coe_subset, coe_Ioc, coe_Ioo]
exact Set.Ioc_subset_Ioo_right h
theorem Icc_subset_Ico_right (h : b₁ < b₂) : Icc a b₁ ⊆ Ico a b₂ := by
rw [← coe_subset, coe_Icc, coe_Ico]
exact Set.Icc_subset_Ico_right h
theorem Ioo_subset_Ico_self : Ioo a b ⊆ Ico a b := by
rw [← coe_subset, coe_Ioo, coe_Ico]
exact Set.Ioo_subset_Ico_self
theorem Ioo_subset_Ioc_self : Ioo a b ⊆ Ioc a b := by
rw [← coe_subset, coe_Ioo, coe_Ioc]
exact Set.Ioo_subset_Ioc_self
theorem Ico_subset_Icc_self : Ico a b ⊆ Icc a b := by
rw [← coe_subset, coe_Ico, coe_Icc]
exact Set.Ico_subset_Icc_self
theorem Ioc_subset_Icc_self : Ioc a b ⊆ Icc a b := by
rw [← coe_subset, coe_Ioc, coe_Icc]
exact Set.Ioc_subset_Icc_self
theorem Ioo_subset_Icc_self : Ioo a b ⊆ Icc a b :=
Ioo_subset_Ico_self.trans Ico_subset_Icc_self
theorem Icc_subset_Icc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Icc a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ := by
rw [← coe_subset, coe_Icc, coe_Icc, Set.Icc_subset_Icc_iff h₁]
theorem Icc_subset_Ioo_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioo a₂ b₂ ↔ a₂ < a₁ ∧ b₁ < b₂ := by
rw [← coe_subset, coe_Icc, coe_Ioo, Set.Icc_subset_Ioo_iff h₁]
theorem Icc_subset_Ico_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ico a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ < b₂ := by
rw [← coe_subset, coe_Icc, coe_Ico, Set.Icc_subset_Ico_iff h₁]
theorem Icc_subset_Ioc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioc a₂ b₂ ↔ a₂ < a₁ ∧ b₁ ≤ b₂ :=
(Icc_subset_Ico_iff h₁.dual).trans and_comm
--TODO: `Ico_subset_Ioo_iff`, `Ioc_subset_Ioo_iff`
theorem Icc_ssubset_Icc_left (hI : a₂ ≤ b₂) (ha : a₂ < a₁) (hb : b₁ ≤ b₂) :
Icc a₁ b₁ ⊂ Icc a₂ b₂ := by
rw [← coe_ssubset, coe_Icc, coe_Icc]
exact Set.Icc_ssubset_Icc_left hI ha hb
theorem Icc_ssubset_Icc_right (hI : a₂ ≤ b₂) (ha : a₂ ≤ a₁) (hb : b₁ < b₂) :
Icc a₁ b₁ ⊂ Icc a₂ b₂ := by
rw [← coe_ssubset, coe_Icc, coe_Icc]
exact Set.Icc_ssubset_Icc_right hI ha hb
@[simp]
theorem Ioc_disjoint_Ioc_of_le {d : α} (hbc : b ≤ c) : Disjoint (Ioc a b) (Ioc c d) :=
disjoint_left.2 fun _ h1 h2 ↦ not_and_of_not_left _
((mem_Ioc.1 h1).2.trans hbc).not_lt (mem_Ioc.1 h2)
variable (a)
theorem Ico_self : Ico a a = ∅ :=
Ico_eq_empty <| lt_irrefl _
theorem Ioc_self : Ioc a a = ∅ :=
Ioc_eq_empty <| lt_irrefl _
theorem Ioo_self : Ioo a a = ∅ :=
Ioo_eq_empty <| lt_irrefl _
variable {a}
/-- A set with upper and lower bounds in a locally finite order is a fintype -/
def _root_.Set.fintypeOfMemBounds {s : Set α} [DecidablePred (· ∈ s)] (ha : a ∈ lowerBounds s)
(hb : b ∈ upperBounds s) : Fintype s :=
Set.fintypeSubset (Set.Icc a b) fun _ hx => ⟨ha hx, hb hx⟩
section Filter
theorem Ico_filter_lt_of_le_left [DecidablePred (· < c)] (hca : c ≤ a) :
{x ∈ Ico a b | x < c} = ∅ :=
filter_false_of_mem fun _ hx => (hca.trans (mem_Ico.1 hx).1).not_lt
theorem Ico_filter_lt_of_right_le [DecidablePred (· < c)] (hbc : b ≤ c) :
{x ∈ Ico a b | x < c} = Ico a b :=
filter_true_of_mem fun _ hx => (mem_Ico.1 hx).2.trans_le hbc
theorem Ico_filter_lt_of_le_right [DecidablePred (· < c)] (hcb : c ≤ b) :
{x ∈ Ico a b | x < c} = Ico a c := by
ext x
rw [mem_filter, mem_Ico, mem_Ico, and_right_comm]
exact and_iff_left_of_imp fun h => h.2.trans_le hcb
theorem Ico_filter_le_of_le_left {a b c : α} [DecidablePred (c ≤ ·)] (hca : c ≤ a) :
{x ∈ Ico a b | c ≤ x} = Ico a b :=
filter_true_of_mem fun _ hx => hca.trans (mem_Ico.1 hx).1
theorem Ico_filter_le_of_right_le {a b : α} [DecidablePred (b ≤ ·)] :
{x ∈ Ico a b | b ≤ x} = ∅ :=
filter_false_of_mem fun _ hx => (mem_Ico.1 hx).2.not_le
theorem Ico_filter_le_of_left_le {a b c : α} [DecidablePred (c ≤ ·)] (hac : a ≤ c) :
{x ∈ Ico a b | c ≤ x} = Ico c b := by
ext x
rw [mem_filter, mem_Ico, mem_Ico, and_comm, and_left_comm]
exact and_iff_right_of_imp fun h => hac.trans h.1
theorem Icc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) :
{x ∈ Icc a b | x < c} = Icc a b :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Icc.1 hx).2 h
theorem Ioc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) :
{x ∈ Ioc a b | x < c} = Ioc a b :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Ioc.1 hx).2 h
theorem Iic_filter_lt_of_lt_right {α} [Preorder α] [LocallyFiniteOrderBot α] {a c : α}
[DecidablePred (· < c)] (h : a < c) : {x ∈ Iic a | x < c} = Iic a :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Iic.1 hx) h
variable (a b) [Fintype α]
theorem filter_lt_lt_eq_Ioo [DecidablePred fun j => a < j ∧ j < b] :
({j | a < j ∧ j < b} : Finset _) = Ioo a b := by ext; simp
theorem filter_lt_le_eq_Ioc [DecidablePred fun j => a < j ∧ j ≤ b] :
({j | a < j ∧ j ≤ b} : Finset _) = Ioc a b := by ext; simp
theorem filter_le_lt_eq_Ico [DecidablePred fun j => a ≤ j ∧ j < b] :
({j | a ≤ j ∧ j < b} : Finset _) = Ico a b := by ext; simp
theorem filter_le_le_eq_Icc [DecidablePred fun j => a ≤ j ∧ j ≤ b] :
({j | a ≤ j ∧ j ≤ b} : Finset _) = Icc a b := by ext; simp
end Filter
end LocallyFiniteOrder
section LocallyFiniteOrderTop
variable [LocallyFiniteOrderTop α]
@[simp]
theorem Ioi_eq_empty : Ioi a = ∅ ↔ IsMax a := by
rw [← coe_eq_empty, coe_Ioi, Set.Ioi_eq_empty_iff]
@[simp] alias ⟨_, _root_.IsMax.finsetIoi_eq⟩ := Ioi_eq_empty
@[simp] lemma Ioi_nonempty : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [nonempty_iff_ne_empty]
theorem Ioi_top [OrderTop α] : Ioi (⊤ : α) = ∅ := Ioi_eq_empty.mpr isMax_top
@[simp]
theorem Ici_bot [OrderBot α] [Fintype α] : Ici (⊥ : α) = univ := by
ext a; simp only [mem_Ici, bot_le, mem_univ]
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
lemma nonempty_Ici : (Ici a).Nonempty := ⟨a, mem_Ici.2 le_rfl⟩
lemma nonempty_Ioi : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [Finset.Nonempty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Ioi_of_not_isMax⟩ := nonempty_Ioi
@[simp]
theorem Ici_subset_Ici : Ici a ⊆ Ici b ↔ b ≤ a := by
simp [← coe_subset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Ici_subset_Ici⟩ := Ici_subset_Ici
@[simp]
theorem Ici_ssubset_Ici : Ici a ⊂ Ici b ↔ b < a := by
simp [← coe_ssubset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Ici_ssubset_Ici⟩ := Ici_ssubset_Ici
@[gcongr]
theorem Ioi_subset_Ioi (h : a ≤ b) : Ioi b ⊆ Ioi a := by
simpa [← coe_subset] using Set.Ioi_subset_Ioi h
@[gcongr]
theorem Ioi_ssubset_Ioi (h : a < b) : Ioi b ⊂ Ioi a := by
simpa [← coe_ssubset] using Set.Ioi_ssubset_Ioi h
variable [LocallyFiniteOrder α]
theorem Icc_subset_Ici_self : Icc a b ⊆ Ici a := by
simpa [← coe_subset] using Set.Icc_subset_Ici_self
theorem Ico_subset_Ici_self : Ico a b ⊆ Ici a := by
simpa [← coe_subset] using Set.Ico_subset_Ici_self
theorem Ioc_subset_Ioi_self : Ioc a b ⊆ Ioi a := by
simpa [← coe_subset] using Set.Ioc_subset_Ioi_self
theorem Ioo_subset_Ioi_self : Ioo a b ⊆ Ioi a := by
simpa [← coe_subset] using Set.Ioo_subset_Ioi_self
theorem Ioc_subset_Ici_self : Ioc a b ⊆ Ici a :=
Ioc_subset_Icc_self.trans Icc_subset_Ici_self
theorem Ioo_subset_Ici_self : Ioo a b ⊆ Ici a :=
Ioo_subset_Ico_self.trans Ico_subset_Ici_self
end LocallyFiniteOrderTop
section LocallyFiniteOrderBot
variable [LocallyFiniteOrderBot α]
@[simp]
theorem Iio_eq_empty : Iio a = ∅ ↔ IsMin a := Ioi_eq_empty (α := αᵒᵈ)
@[simp] alias ⟨_, _root_.IsMin.finsetIio_eq⟩ := Iio_eq_empty
@[simp] lemma Iio_nonempty : (Iio a).Nonempty ↔ ¬ IsMin a := by simp [nonempty_iff_ne_empty]
theorem Iio_bot [OrderBot α] : Iio (⊥ : α) = ∅ := Iio_eq_empty.mpr isMin_bot
@[simp]
theorem Iic_top [OrderTop α] [Fintype α] : Iic (⊤ : α) = univ := by
ext a; simp only [mem_Iic, le_top, mem_univ]
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
lemma nonempty_Iic : (Iic a).Nonempty := ⟨a, mem_Iic.2 le_rfl⟩
lemma nonempty_Iio : (Iio a).Nonempty ↔ ¬ IsMin a := by simp [Finset.Nonempty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Iio_of_not_isMin⟩ := nonempty_Iio
@[simp]
theorem Iic_subset_Iic : Iic a ⊆ Iic b ↔ a ≤ b := by
simp [← coe_subset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Iic_subset_Iic⟩ := Iic_subset_Iic
@[simp]
theorem Iic_ssubset_Iic : Iic a ⊂ Iic b ↔ a < b := by
simp [← coe_ssubset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Iic_ssubset_Iic⟩ := Iic_ssubset_Iic
@[gcongr]
theorem Iio_subset_Iio (h : a ≤ b) : Iio a ⊆ Iio b := by
simpa [← coe_subset] using Set.Iio_subset_Iio h
@[gcongr]
theorem Iio_ssubset_Iio (h : a < b) : Iio a ⊂ Iio b := by
simpa [← coe_ssubset] using Set.Iio_ssubset_Iio h
variable [LocallyFiniteOrder α]
theorem Icc_subset_Iic_self : Icc a b ⊆ Iic b := by
simpa [← coe_subset] using Set.Icc_subset_Iic_self
theorem Ioc_subset_Iic_self : Ioc a b ⊆ Iic b := by
simpa [← coe_subset] using Set.Ioc_subset_Iic_self
theorem Ico_subset_Iio_self : Ico a b ⊆ Iio b := by
simpa [← coe_subset] using Set.Ico_subset_Iio_self
theorem Ioo_subset_Iio_self : Ioo a b ⊆ Iio b := by
simpa [← coe_subset] using Set.Ioo_subset_Iio_self
theorem Ico_subset_Iic_self : Ico a b ⊆ Iic b :=
Ico_subset_Icc_self.trans Icc_subset_Iic_self
theorem Ioo_subset_Iic_self : Ioo a b ⊆ Iic b :=
Ioo_subset_Ioc_self.trans Ioc_subset_Iic_self
theorem Iic_disjoint_Ioc (h : a ≤ b) : Disjoint (Iic a) (Ioc b c) :=
disjoint_left.2 fun _ hax hbcx ↦ (mem_Iic.1 hax).not_lt <| lt_of_le_of_lt h (mem_Ioc.1 hbcx).1
/-- An equivalence between `Finset.Iic a` and `Set.Iic a`. -/
def _root_.Equiv.IicFinsetSet (a : α) : Iic a ≃ Set.Iic a where
toFun b := ⟨b.1, coe_Iic a ▸ mem_coe.2 b.2⟩
invFun b := ⟨b.1, by rw [← mem_coe, coe_Iic a]; exact b.2⟩
left_inv := fun _ ↦ rfl
right_inv := fun _ ↦ rfl
end LocallyFiniteOrderBot
section LocallyFiniteOrderTop
variable [LocallyFiniteOrderTop α] {a : α}
theorem Ioi_subset_Ici_self : Ioi a ⊆ Ici a := by
simpa [← coe_subset] using Set.Ioi_subset_Ici_self
theorem _root_.BddBelow.finite {s : Set α} (hs : BddBelow s) : s.Finite :=
let ⟨a, ha⟩ := hs
(Ici a).finite_toSet.subset fun _ hx => mem_Ici.2 <| ha hx
theorem _root_.Set.Infinite.not_bddBelow {s : Set α} : s.Infinite → ¬BddBelow s :=
mt BddBelow.finite
variable [Fintype α]
theorem filter_lt_eq_Ioi [DecidablePred (a < ·)] : ({x | a < x} : Finset _) = Ioi a := by ext; simp
theorem filter_le_eq_Ici [DecidablePred (a ≤ ·)] : ({x | a ≤ x} : Finset _) = Ici a := by ext; simp
end LocallyFiniteOrderTop
section LocallyFiniteOrderBot
variable [LocallyFiniteOrderBot α] {a : α}
theorem Iio_subset_Iic_self : Iio a ⊆ Iic a := by
simpa [← coe_subset] using Set.Iio_subset_Iic_self
theorem _root_.BddAbove.finite {s : Set α} (hs : BddAbove s) : s.Finite :=
hs.dual.finite
theorem _root_.Set.Infinite.not_bddAbove {s : Set α} : s.Infinite → ¬BddAbove s :=
mt BddAbove.finite
variable [Fintype α]
theorem filter_gt_eq_Iio [DecidablePred (· < a)] : ({x | x < a} : Finset _) = Iio a := by ext; simp
theorem filter_ge_eq_Iic [DecidablePred (· ≤ a)] : ({x | x ≤ a} : Finset _) = Iic a := by ext; simp
end LocallyFiniteOrderBot
section LocallyFiniteOrder
variable [LocallyFiniteOrder α]
@[simp]
theorem Icc_bot [OrderBot α] : Icc (⊥ : α) a = Iic a := rfl
@[simp]
theorem Icc_top [OrderTop α] : Icc a (⊤ : α) = Ici a := rfl
@[simp]
theorem Ico_bot [OrderBot α] : Ico (⊥ : α) a = Iio a := rfl
@[simp]
theorem Ioc_top [OrderTop α] : Ioc a (⊤ : α) = Ioi a := rfl
theorem Icc_bot_top [BoundedOrder α] [Fintype α] : Icc (⊥ : α) (⊤ : α) = univ := by
rw [Icc_bot, Iic_top]
end LocallyFiniteOrder
variable [LocallyFiniteOrderTop α] [LocallyFiniteOrderBot α]
theorem disjoint_Ioi_Iio (a : α) : Disjoint (Ioi a) (Iio a) :=
disjoint_left.2 fun _ hab hba => (mem_Ioi.1 hab).not_lt <| mem_Iio.1 hba
end Preorder
section PartialOrder
variable [PartialOrder α] [LocallyFiniteOrder α] {a b c : α}
@[simp]
theorem Icc_self (a : α) : Icc a a = {a} := by rw [← coe_eq_singleton, coe_Icc, Set.Icc_self]
@[simp]
theorem Icc_eq_singleton_iff : Icc a b = {c} ↔ a = c ∧ b = c := by
rw [← coe_eq_singleton, coe_Icc, Set.Icc_eq_singleton_iff]
theorem Ico_disjoint_Ico_consecutive (a b c : α) : Disjoint (Ico a b) (Ico b c) :=
disjoint_left.2 fun _ hab hbc => (mem_Ico.mp hab).2.not_le (mem_Ico.mp hbc).1
@[simp]
theorem Ici_top [OrderTop α] : Ici (⊤ : α) = {⊤} := Icc_eq_singleton_iff.2 ⟨rfl, rfl⟩
@[simp]
theorem Iic_bot [OrderBot α] : Iic (⊥ : α) = {⊥} := Icc_eq_singleton_iff.2 ⟨rfl, rfl⟩
section DecidableEq
variable [DecidableEq α]
@[simp]
theorem Icc_erase_left (a b : α) : (Icc a b).erase a = Ioc a b := by simp [← coe_inj]
@[simp]
theorem Icc_erase_right (a b : α) : (Icc a b).erase b = Ico a b := by simp [← coe_inj]
@[simp]
theorem Ico_erase_left (a b : α) : (Ico a b).erase a = Ioo a b := by simp [← coe_inj]
@[simp]
theorem Ioc_erase_right (a b : α) : (Ioc a b).erase b = Ioo a b := by simp [← coe_inj]
@[simp]
theorem Icc_diff_both (a b : α) : Icc a b \ {a, b} = Ioo a b := by simp [← coe_inj]
@[simp]
theorem Ico_insert_right (h : a ≤ b) : insert b (Ico a b) = Icc a b := by
rw [← coe_inj, coe_insert, coe_Icc, coe_Ico, Set.insert_eq, Set.union_comm, Set.Ico_union_right h]
@[simp]
theorem Ioc_insert_left (h : a ≤ b) : insert a (Ioc a b) = Icc a b := by
rw [← coe_inj, coe_insert, coe_Ioc, coe_Icc, Set.insert_eq, Set.union_comm, Set.Ioc_union_left h]
@[simp]
theorem Ioo_insert_left (h : a < b) : insert a (Ioo a b) = Ico a b := by
rw [← coe_inj, coe_insert, coe_Ioo, coe_Ico, Set.insert_eq, Set.union_comm, Set.Ioo_union_left h]
@[simp]
theorem Ioo_insert_right (h : a < b) : insert b (Ioo a b) = Ioc a b := by
rw [← coe_inj, coe_insert, coe_Ioo, coe_Ioc, Set.insert_eq, Set.union_comm, Set.Ioo_union_right h]
@[simp]
theorem Icc_diff_Ico_self (h : a ≤ b) : Icc a b \ Ico a b = {b} := by simp [← coe_inj, h]
@[simp]
theorem Icc_diff_Ioc_self (h : a ≤ b) : Icc a b \ Ioc a b = {a} := by simp [← coe_inj, h]
@[simp]
theorem Icc_diff_Ioo_self (h : a ≤ b) : Icc a b \ Ioo a b = {a, b} := by simp [← coe_inj, h]
@[simp]
theorem Ico_diff_Ioo_self (h : a < b) : Ico a b \ Ioo a b = {a} := by simp [← coe_inj, h]
@[simp]
theorem Ioc_diff_Ioo_self (h : a < b) : Ioc a b \ Ioo a b = {b} := by simp [← coe_inj, h]
@[simp]
theorem Ico_inter_Ico_consecutive (a b c : α) : Ico a b ∩ Ico b c = ∅ :=
(Ico_disjoint_Ico_consecutive a b c).eq_bot
end DecidableEq
-- Those lemmas are purposefully the other way around
/-- `Finset.cons` version of `Finset.Ico_insert_right`. -/
theorem Icc_eq_cons_Ico (h : a ≤ b) : Icc a b = (Ico a b).cons b right_not_mem_Ico := by
classical rw [cons_eq_insert, Ico_insert_right h]
/-- `Finset.cons` version of `Finset.Ioc_insert_left`. -/
theorem Icc_eq_cons_Ioc (h : a ≤ b) : Icc a b = (Ioc a b).cons a left_not_mem_Ioc := by
classical rw [cons_eq_insert, Ioc_insert_left h]
/-- `Finset.cons` version of `Finset.Ioo_insert_right`. -/
theorem Ioc_eq_cons_Ioo (h : a < b) : Ioc a b = (Ioo a b).cons b right_not_mem_Ioo := by
classical rw [cons_eq_insert, Ioo_insert_right h]
/-- `Finset.cons` version of `Finset.Ioo_insert_left`. -/
theorem Ico_eq_cons_Ioo (h : a < b) : Ico a b = (Ioo a b).cons a left_not_mem_Ioo := by
classical rw [cons_eq_insert, Ioo_insert_left h]
theorem Ico_filter_le_left {a b : α} [DecidablePred (· ≤ a)] (hab : a < b) :
{x ∈ Ico a b | x ≤ a} = {a} := by
ext x
rw [mem_filter, mem_Ico, mem_singleton, and_right_comm, ← le_antisymm_iff, eq_comm]
exact and_iff_left_of_imp fun h => h.le.trans_lt hab
theorem card_Ico_eq_card_Icc_sub_one (a b : α) : #(Ico a b) = #(Icc a b) - 1 := by
classical
by_cases h : a ≤ b
· rw [Icc_eq_cons_Ico h, card_cons]
exact (Nat.add_sub_cancel _ _).symm
· rw [Ico_eq_empty fun h' => h h'.le, Icc_eq_empty h, card_empty, Nat.zero_sub]
theorem card_Ioc_eq_card_Icc_sub_one (a b : α) : #(Ioc a b) = #(Icc a b) - 1 :=
@card_Ico_eq_card_Icc_sub_one αᵒᵈ _ _ _ _
theorem card_Ioo_eq_card_Ico_sub_one (a b : α) : #(Ioo a b) = #(Ico a b) - 1 := by
classical
by_cases h : a < b
· rw [Ico_eq_cons_Ioo h, card_cons]
exact (Nat.add_sub_cancel _ _).symm
· rw [Ioo_eq_empty h, Ico_eq_empty h, card_empty, Nat.zero_sub]
theorem card_Ioo_eq_card_Ioc_sub_one (a b : α) : #(Ioo a b) = #(Ioc a b) - 1 :=
@card_Ioo_eq_card_Ico_sub_one αᵒᵈ _ _ _ _
theorem card_Ioo_eq_card_Icc_sub_two (a b : α) : #(Ioo a b) = #(Icc a b) - 2 := by
rw [card_Ioo_eq_card_Ico_sub_one, card_Ico_eq_card_Icc_sub_one]
rfl
end PartialOrder
section Prod
variable {β : Type*}
section sectL
lemma uIcc_map_sectL [Lattice α] [Lattice β] [LocallyFiniteOrder α] [LocallyFiniteOrder β]
[DecidableLE (α × β)] (a b : α) (c : β) :
(uIcc a b).map (.sectL _ c) = uIcc (a, c) (b, c) := by
aesop (add safe forward [le_antisymm])
variable [Preorder α] [PartialOrder β] [LocallyFiniteOrder α] [LocallyFiniteOrder β]
[DecidableLE (α × β)] (a b : α) (c : β)
lemma Icc_map_sectL : (Icc a b).map (.sectL _ c) = Icc (a, c) (b, c) := by
aesop (add safe forward [le_antisymm])
lemma Ioc_map_sectL : (Ioc a b).map (.sectL _ c) = Ioc (a, c) (b, c) := by
aesop (add safe forward [le_antisymm, le_of_lt])
lemma Ico_map_sectL : (Ico a b).map (.sectL _ c) = Ico (a, c) (b, c) := by
aesop (add safe forward [le_antisymm, le_of_lt])
lemma Ioo_map_sectL : (Ioo a b).map (.sectL _ c) = Ioo (a, c) (b, c) := by
aesop (add safe forward [le_antisymm, le_of_lt])
end sectL
section sectR
lemma uIcc_map_sectR [Lattice α] [Lattice β] [LocallyFiniteOrder α] [LocallyFiniteOrder β]
[DecidableLE (α × β)] (c : α) (a b : β) :
(uIcc a b).map (.sectR c _) = uIcc (c, a) (c, b) := by
aesop (add safe forward [le_antisymm])
variable [PartialOrder α] [Preorder β] [LocallyFiniteOrder α] [LocallyFiniteOrder β]
[DecidableLE (α × β)] (c : α) (a b : β)
lemma Icc_map_sectR : (Icc a b).map (.sectR c _) = Icc (c, a) (c, b) := by
aesop (add safe forward [le_antisymm])
lemma Ioc_map_sectR : (Ioc a b).map (.sectR c _) = Ioc (c, a) (c, b) := by
aesop (add safe forward [le_antisymm, le_of_lt])
lemma Ico_map_sectR : (Ico a b).map (.sectR c _) = Ico (c, a) (c, b) := by
aesop (add safe forward [le_antisymm, le_of_lt])
lemma Ioo_map_sectR : (Ioo a b).map (.sectR c _) = Ioo (c, a) (c, b) := by
aesop (add safe forward [le_antisymm, le_of_lt])
end sectR
end Prod
section BoundedPartialOrder
variable [PartialOrder α]
section OrderTop
variable [LocallyFiniteOrderTop α]
@[simp]
theorem Ici_erase [DecidableEq α] (a : α) : (Ici a).erase a = Ioi a := by
ext
simp_rw [Finset.mem_erase, mem_Ici, mem_Ioi, lt_iff_le_and_ne, and_comm, ne_comm]
@[simp]
theorem Ioi_insert [DecidableEq α] (a : α) : insert a (Ioi a) = Ici a := by
ext
simp_rw [Finset.mem_insert, mem_Ici, mem_Ioi, le_iff_lt_or_eq, or_comm, eq_comm]
theorem not_mem_Ioi_self {b : α} : b ∉ Ioi b := fun h => lt_irrefl _ (mem_Ioi.1 h)
-- Purposefully written the other way around
/-- `Finset.cons` version of `Finset.Ioi_insert`. -/
theorem Ici_eq_cons_Ioi (a : α) : Ici a = (Ioi a).cons a not_mem_Ioi_self := by
classical rw [cons_eq_insert, Ioi_insert]
theorem card_Ioi_eq_card_Ici_sub_one (a : α) : #(Ioi a) = #(Ici a) - 1 := by
rw [Ici_eq_cons_Ioi, card_cons, Nat.add_sub_cancel_right]
end OrderTop
section OrderBot
variable [LocallyFiniteOrderBot α]
@[simp]
theorem Iic_erase [DecidableEq α] (b : α) : (Iic b).erase b = Iio b := by
ext
simp_rw [Finset.mem_erase, mem_Iic, mem_Iio, lt_iff_le_and_ne, and_comm]
@[simp]
theorem Iio_insert [DecidableEq α] (b : α) : insert b (Iio b) = Iic b := by
ext
simp_rw [Finset.mem_insert, mem_Iic, mem_Iio, le_iff_lt_or_eq, or_comm]
theorem not_mem_Iio_self {b : α} : b ∉ Iio b := fun h => lt_irrefl _ (mem_Iio.1 h)
-- Purposefully written the other way around
/-- `Finset.cons` version of `Finset.Iio_insert`. -/
theorem Iic_eq_cons_Iio (b : α) : Iic b = (Iio b).cons b not_mem_Iio_self := by
classical rw [cons_eq_insert, Iio_insert]
theorem card_Iio_eq_card_Iic_sub_one (a : α) : #(Iio a) = #(Iic a) - 1 := by
rw [Iic_eq_cons_Iio, card_cons, Nat.add_sub_cancel_right]
end OrderBot
end BoundedPartialOrder
section SemilatticeSup
variable [SemilatticeSup α] [LocallyFiniteOrderBot α]
-- TODO: Why does `id_eq` simplify the LHS here but not the LHS of `Finset.sup_Iic`?
lemma sup'_Iic (a : α) : (Iic a).sup' nonempty_Iic id = a :=
le_antisymm (sup'_le _ _ fun _ ↦ mem_Iic.1) <| le_sup' (f := id) <| mem_Iic.2 <| le_refl a
@[simp] lemma sup_Iic [OrderBot α] (a : α) : (Iic a).sup id = a :=
le_antisymm (Finset.sup_le fun _ ↦ mem_Iic.1) <| le_sup (f := id) <| mem_Iic.2 <| le_refl a
lemma image_subset_Iic_sup [OrderBot α] [DecidableEq α] (f : ι → α) (s : Finset ι) :
s.image f ⊆ Iic (s.sup f) := by
refine fun i hi ↦ mem_Iic.2 ?_
obtain ⟨j, hj, rfl⟩ := mem_image.1 hi
exact le_sup hj
lemma subset_Iic_sup_id [OrderBot α] (s : Finset α) : s ⊆ Iic (s.sup id) :=
fun _ h ↦ mem_Iic.2 <| le_sup (f := id) h
end SemilatticeSup
section SemilatticeInf
variable [SemilatticeInf α] [LocallyFiniteOrderTop α]
lemma inf'_Ici (a : α) : (Ici a).inf' nonempty_Ici id = a :=
ge_antisymm (le_inf' _ _ fun _ ↦ mem_Ici.1) <| inf'_le (f := id) <| mem_Ici.2 <| le_refl a
@[simp] lemma inf_Ici [OrderTop α] (a : α) : (Ici a).inf id = a :=
le_antisymm (inf_le (f := id) <| mem_Ici.2 <| le_refl a) <| Finset.le_inf fun _ ↦ mem_Ici.1
end SemilatticeInf
section LinearOrder
variable [LinearOrder α]
section LocallyFiniteOrder
variable [LocallyFiniteOrder α]
theorem Ico_subset_Ico_iff {a₁ b₁ a₂ b₂ : α} (h : a₁ < b₁) :
Ico a₁ b₁ ⊆ Ico a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ := by
rw [← coe_subset, coe_Ico, coe_Ico, Set.Ico_subset_Ico_iff h]
theorem Ico_union_Ico_eq_Ico {a b c : α} (hab : a ≤ b) (hbc : b ≤ c) :
Ico a b ∪ Ico b c = Ico a c := by
rw [← coe_inj, coe_union, coe_Ico, coe_Ico, coe_Ico, Set.Ico_union_Ico_eq_Ico hab hbc]
@[simp]
theorem Ioc_union_Ioc_eq_Ioc {a b c : α} (h₁ : a ≤ b) (h₂ : b ≤ c) :
Ioc a b ∪ Ioc b c = Ioc a c := by
rw [← coe_inj, coe_union, coe_Ioc, coe_Ioc, coe_Ioc, Set.Ioc_union_Ioc_eq_Ioc h₁ h₂]
theorem Ico_subset_Ico_union_Ico {a b c : α} : Ico a c ⊆ Ico a b ∪ Ico b c := by
rw [← coe_subset, coe_union, coe_Ico, coe_Ico, coe_Ico]
exact Set.Ico_subset_Ico_union_Ico
theorem Ico_union_Ico' {a b c d : α} (hcb : c ≤ b) (had : a ≤ d) :
Ico a b ∪ Ico c d = Ico (min a c) (max b d) := by
rw [← coe_inj, coe_union, coe_Ico, coe_Ico, coe_Ico, Set.Ico_union_Ico' hcb had]
theorem Ico_union_Ico {a b c d : α} (h₁ : min a b ≤ max c d) (h₂ : min c d ≤ max a b) :
Ico a b ∪ Ico c d = Ico (min a c) (max b d) := by
rw [← coe_inj, coe_union, coe_Ico, coe_Ico, coe_Ico, Set.Ico_union_Ico h₁ h₂]
theorem Ico_inter_Ico {a b c d : α} : Ico a b ∩ Ico c d = Ico (max a c) (min b d) := by
rw [← coe_inj, coe_inter, coe_Ico, coe_Ico, coe_Ico, Set.Ico_inter_Ico]
theorem Ioc_inter_Ioc {a b c d : α} : Ioc a b ∩ Ioc c d = Ioc (max a c) (min b d) := by
rw [← coe_inj]
push_cast
exact Set.Ioc_inter_Ioc
@[simp]
theorem Ico_filter_lt (a b c : α) : {x ∈ Ico a b | x < c} = Ico a (min b c) := by
cases le_total b c with
| inl h => rw [Ico_filter_lt_of_right_le h, min_eq_left h]
| inr h => rw [Ico_filter_lt_of_le_right h, min_eq_right h]
@[simp]
theorem Ico_filter_le (a b c : α) : {x ∈ Ico a b | c ≤ x} = Ico (max a c) b := by
cases le_total a c with
| inl h => rw [Ico_filter_le_of_left_le h, max_eq_right h]
| inr h => rw [Ico_filter_le_of_le_left h, max_eq_left h]
@[simp]
theorem Ioo_filter_lt (a b c : α) : {x ∈ Ioo a b | x < c} = Ioo a (min b c) := by
ext
simp [and_assoc]
@[simp]
theorem Iio_filter_lt {α} [LinearOrder α] [LocallyFiniteOrderBot α] (a b : α) :
{x ∈ Iio a | x < b} = Iio (min a b) := by
ext
simp [and_assoc]
@[simp]
theorem Ico_diff_Ico_left (a b c : α) : Ico a b \ Ico a c = Ico (max a c) b := by
cases le_total a c with
| inl h =>
ext x
rw [mem_sdiff, mem_Ico, mem_Ico, mem_Ico, max_eq_right h, and_right_comm, not_and, not_lt]
exact and_congr_left' ⟨fun hx => hx.2 hx.1, fun hx => ⟨h.trans hx, fun _ => hx⟩⟩
| inr h => rw [Ico_eq_empty_of_le h, sdiff_empty, max_eq_left h]
@[simp]
theorem Ico_diff_Ico_right (a b c : α) : Ico a b \ Ico c b = Ico a (min b c) := by
cases le_total b c with
| inl h => rw [Ico_eq_empty_of_le h, sdiff_empty, min_eq_left h]
| inr h =>
ext x
rw [mem_sdiff, mem_Ico, mem_Ico, mem_Ico, min_eq_right h, and_assoc, not_and', not_le]
exact and_congr_right' ⟨fun hx => hx.2 hx.1, fun hx => ⟨hx.trans_le h, fun _ => hx⟩⟩
@[simp]
theorem Ioc_disjoint_Ioc : Disjoint (Ioc a₁ a₂) (Ioc b₁ b₂) ↔ min a₂ b₂ ≤ max a₁ b₁ := by
simp_rw [disjoint_iff_inter_eq_empty, Ioc_inter_Ioc, Ioc_eq_empty_iff, not_lt]
section LocallyFiniteOrderBot
variable [LocallyFiniteOrderBot α]
theorem Iic_diff_Ioc : Iic b \ Ioc a b = Iic (a ⊓ b) := by
rw [← coe_inj]
push_cast
exact Set.Iic_diff_Ioc
theorem Iic_diff_Ioc_self_of_le (hab : a ≤ b) : Iic b \ Ioc a b = Iic a := by
rw [Iic_diff_Ioc, min_eq_left hab]
theorem Iic_union_Ioc_eq_Iic (h : a ≤ b) : Iic a ∪ Ioc a b = Iic b := by
rw [← coe_inj]
push_cast
exact Set.Iic_union_Ioc_eq_Iic h
end LocallyFiniteOrderBot
end LocallyFiniteOrder
section LocallyFiniteOrderBot
variable [LocallyFiniteOrderBot α] {s : Set α}
theorem _root_.Set.Infinite.exists_gt (hs : s.Infinite) : ∀ a, ∃ b ∈ s, a < b :=
not_bddAbove_iff.1 hs.not_bddAbove
theorem _root_.Set.infinite_iff_exists_gt [Nonempty α] : s.Infinite ↔ ∀ a, ∃ b ∈ s, a < b :=
⟨Set.Infinite.exists_gt, Set.infinite_of_forall_exists_gt⟩
end LocallyFiniteOrderBot
section LocallyFiniteOrderTop
variable [LocallyFiniteOrderTop α] {s : Set α}
theorem _root_.Set.Infinite.exists_lt (hs : s.Infinite) : ∀ a, ∃ b ∈ s, b < a :=
not_bddBelow_iff.1 hs.not_bddBelow
theorem _root_.Set.infinite_iff_exists_lt [Nonempty α] : s.Infinite ↔ ∀ a, ∃ b ∈ s, b < a :=
⟨Set.Infinite.exists_lt, Set.infinite_of_forall_exists_lt⟩
end LocallyFiniteOrderTop
variable [Fintype α] [LocallyFiniteOrderTop α] [LocallyFiniteOrderBot α]
theorem Ioi_disjUnion_Iio (a : α) :
(Ioi a).disjUnion (Iio a) (disjoint_Ioi_Iio a) = ({a} : Finset α)ᶜ := by
ext
simp [eq_comm]
end LinearOrder
section Lattice
variable [Lattice α] [LocallyFiniteOrder α] {a a₁ a₂ b b₁ b₂ x : α}
theorem uIcc_toDual (a b : α) : [[toDual a, toDual b]] = [[a, b]].map toDual.toEmbedding :=
Icc_toDual (a ⊔ b) (a ⊓ b)
@[simp]
theorem uIcc_of_le (h : a ≤ b) : [[a, b]] = Icc a b := by
rw [uIcc, inf_eq_left.2 h, sup_eq_right.2 h]
@[simp]
theorem uIcc_of_ge (h : b ≤ a) : [[a, b]] = Icc b a := by
rw [uIcc, inf_eq_right.2 h, sup_eq_left.2 h]
theorem uIcc_comm (a b : α) : [[a, b]] = [[b, a]] := by
rw [uIcc, uIcc, inf_comm, sup_comm]
theorem uIcc_self : [[a, a]] = {a} := by simp [uIcc]
@[simp]
theorem nonempty_uIcc : Finset.Nonempty [[a, b]] :=
nonempty_Icc.2 inf_le_sup
theorem Icc_subset_uIcc : Icc a b ⊆ [[a, b]] :=
Icc_subset_Icc inf_le_left le_sup_right
theorem Icc_subset_uIcc' : Icc b a ⊆ [[a, b]] :=
Icc_subset_Icc inf_le_right le_sup_left
theorem left_mem_uIcc : a ∈ [[a, b]] :=
mem_Icc.2 ⟨inf_le_left, le_sup_left⟩
theorem right_mem_uIcc : b ∈ [[a, b]] :=
mem_Icc.2 ⟨inf_le_right, le_sup_right⟩
theorem mem_uIcc_of_le (ha : a ≤ x) (hb : x ≤ b) : x ∈ [[a, b]] :=
Icc_subset_uIcc <| mem_Icc.2 ⟨ha, hb⟩
theorem mem_uIcc_of_ge (hb : b ≤ x) (ha : x ≤ a) : x ∈ [[a, b]] :=
Icc_subset_uIcc' <| mem_Icc.2 ⟨hb, ha⟩
theorem uIcc_subset_uIcc (h₁ : a₁ ∈ [[a₂, b₂]]) (h₂ : b₁ ∈ [[a₂, b₂]]) :
[[a₁, b₁]] ⊆ [[a₂, b₂]] := by
rw [mem_uIcc] at h₁ h₂
exact Icc_subset_Icc (_root_.le_inf h₁.1 h₂.1) (_root_.sup_le h₁.2 h₂.2)
theorem uIcc_subset_Icc (ha : a₁ ∈ Icc a₂ b₂) (hb : b₁ ∈ Icc a₂ b₂) : [[a₁, b₁]] ⊆ Icc a₂ b₂ := by
rw [mem_Icc] at ha hb
exact Icc_subset_Icc (_root_.le_inf ha.1 hb.1) (_root_.sup_le ha.2 hb.2)
theorem uIcc_subset_uIcc_iff_mem : [[a₁, b₁]] ⊆ [[a₂, b₂]] ↔ a₁ ∈ [[a₂, b₂]] ∧ b₁ ∈ [[a₂, b₂]] :=
⟨fun h => ⟨h left_mem_uIcc, h right_mem_uIcc⟩, fun h => uIcc_subset_uIcc h.1 h.2⟩
theorem uIcc_subset_uIcc_iff_le' :
[[a₁, b₁]] ⊆ [[a₂, b₂]] ↔ a₂ ⊓ b₂ ≤ a₁ ⊓ b₁ ∧ a₁ ⊔ b₁ ≤ a₂ ⊔ b₂ :=
Icc_subset_Icc_iff inf_le_sup
theorem uIcc_subset_uIcc_right (h : x ∈ [[a, b]]) : [[x, b]] ⊆ [[a, b]] :=
uIcc_subset_uIcc h right_mem_uIcc
theorem uIcc_subset_uIcc_left (h : x ∈ [[a, b]]) : [[a, x]] ⊆ [[a, b]] :=
uIcc_subset_uIcc left_mem_uIcc h
end Lattice
section DistribLattice
variable [DistribLattice α] [LocallyFiniteOrder α] {a b c : α}
theorem eq_of_mem_uIcc_of_mem_uIcc : a ∈ [[b, c]] → b ∈ [[a, c]] → a = b := by
simp_rw [mem_uIcc]
exact Set.eq_of_mem_uIcc_of_mem_uIcc
theorem eq_of_mem_uIcc_of_mem_uIcc' : b ∈ [[a, c]] → c ∈ [[a, b]] → b = c := by
simp_rw [mem_uIcc]
exact Set.eq_of_mem_uIcc_of_mem_uIcc'
theorem uIcc_injective_right (a : α) : Injective fun b => [[b, a]] := fun b c h => by
rw [Finset.ext_iff] at h
exact eq_of_mem_uIcc_of_mem_uIcc ((h _).1 left_mem_uIcc) ((h _).2 left_mem_uIcc)
theorem uIcc_injective_left (a : α) : Injective (uIcc a) := by
simpa only [uIcc_comm] using uIcc_injective_right a
end DistribLattice
section LinearOrder
variable [LinearOrder α] [LocallyFiniteOrder α] {a a₁ a₂ b b₁ b₂ c : α}
theorem Icc_min_max : Icc (min a b) (max a b) = [[a, b]] :=
rfl
theorem uIcc_of_not_le (h : ¬a ≤ b) : [[a, b]] = Icc b a :=
uIcc_of_ge <| le_of_not_ge h
theorem uIcc_of_not_ge (h : ¬b ≤ a) : [[a, b]] = Icc a b :=
uIcc_of_le <| le_of_not_ge h
theorem uIcc_eq_union : [[a, b]] = Icc a b ∪ Icc b a :=
coe_injective <| by
push_cast
exact Set.uIcc_eq_union
theorem mem_uIcc' : a ∈ [[b, c]] ↔ b ≤ a ∧ a ≤ c ∨ c ≤ a ∧ a ≤ b := by simp [uIcc_eq_union]
theorem not_mem_uIcc_of_lt : c < a → c < b → c ∉ [[a, b]] := by
rw [mem_uIcc]
exact Set.not_mem_uIcc_of_lt
theorem not_mem_uIcc_of_gt : a < c → b < c → c ∉ [[a, b]] := by
rw [mem_uIcc]
exact Set.not_mem_uIcc_of_gt
theorem uIcc_subset_uIcc_iff_le :
[[a₁, b₁]] ⊆ [[a₂, b₂]] ↔ min a₂ b₂ ≤ min a₁ b₁ ∧ max a₁ b₁ ≤ max a₂ b₂ :=
uIcc_subset_uIcc_iff_le'
/-- A sort of triangle inequality. -/
theorem uIcc_subset_uIcc_union_uIcc : [[a, c]] ⊆ [[a, b]] ∪ [[b, c]] :=
coe_subset.1 <| by
push_cast
exact Set.uIcc_subset_uIcc_union_uIcc
end LinearOrder
end Finset
/-! ### `⩿`, `⋖` and monotonicity -/
section Cover
open Finset Relation
set_option linter.unusedVariables false in -- `have` for wf induction triggers linter
lemma transGen_wcovBy_of_le [Preorder α] [LocallyFiniteOrder α] {x y : α} (hxy : x ≤ y) :
TransGen (· ⩿ ·) x y := by
-- We proceed by well-founded induction on the cardinality of `Icc x y`.
-- It's impossible for the cardinality to be zero since `x ≤ y`
have : #(Ico x y) < #(Icc x y) := card_lt_card <|
⟨Ico_subset_Icc_self, not_subset.mpr ⟨y, ⟨right_mem_Icc.mpr hxy, right_not_mem_Ico⟩⟩⟩
by_cases hxy' : y ≤ x
-- If `y ≤ x`, then `x ⩿ y`
· exact .single <| wcovBy_of_le_of_le hxy hxy'
/- and if `¬ y ≤ x`, then `x < y`, not because it is a linear order, but because `x ≤ y`
already. In that case, since `z` is maximal in `Ico x y`, then `z ⩿ y` and we can use the
induction hypothesis to show that `Relation.TransGen (· ⩿ ·) x z`. -/
· have h_non : (Ico x y).Nonempty := ⟨x, mem_Ico.mpr ⟨le_rfl, lt_of_le_not_le hxy hxy'⟩⟩
obtain ⟨z, z_mem, hz⟩ := (Ico x y).exists_maximal h_non
have z_card := calc
#(Icc x z) ≤ #(Ico x y) := card_le_card <| Icc_subset_Ico_right (mem_Ico.mp z_mem).2
_ < #(Icc x y) := this
have h₁ := transGen_wcovBy_of_le (mem_Ico.mp z_mem).1
have h₂ : z ⩿ y := by
refine ⟨(mem_Ico.mp z_mem).2.le, fun c hzc hcy ↦ hz c ?_ hzc⟩
exact mem_Ico.mpr <| ⟨(mem_Ico.mp z_mem).1.trans hzc.le, hcy⟩
| exact .tail h₁ h₂
termination_by #(Icc x y)
/-- In a locally finite preorder, `≤` is the transitive closure of `⩿`. -/
lemma le_iff_transGen_wcovBy [Preorder α] [LocallyFiniteOrder α] {x y : α} :
x ≤ y ↔ TransGen (· ⩿ ·) x y := by
refine ⟨transGen_wcovBy_of_le, fun h ↦ ?_⟩
| Mathlib/Order/Interval/Finset/Basic.lean | 1,103 | 1,109 |
/-
Copyright (c) 2024 Theodore Hwa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Kim Morrison, Violeta Hernández Palacios, Junyan Xu, Theodore Hwa
-/
import Mathlib.Logic.Hydra
import Mathlib.SetTheory.Surreal.Basic
/-!
### Surreal multiplication
In this file, we show that multiplication of surreal numbers is well-defined, and thus the
surreal numbers form a linear ordered commutative ring.
An inductive argument proves the following three main theorems:
* P1: being numeric is closed under multiplication,
* P2: multiplying a numeric pregame by equivalent numeric pregames results in equivalent pregames,
* P3: the product of two positive numeric pregames is positive (`mul_pos`).
This is Theorem 8 in [Conway2001], or Theorem 3.8 in [SchleicherStoll]. P1 allows us to define
multiplication as an operation on numeric pregames, P2 says that this is well-defined as an
operation on the quotient by `PGame.Equiv`, namely the surreal numbers, and P3 is an axiom that
needs to be satisfied for the surreals to be a `OrderedRing`.
We follow the proof in [SchleicherStoll], except that we use the well-foundedness of
the hydra relation `CutExpand` on `Multiset PGame` instead of the argument based
on a depth function in the paper.
In the argument, P3 is stated with four variables `x₁`, `x₂`, `y₁`, `y₂` satisfying `x₁ < x₂` and
`y₁ < y₂`, and says that `x₁ * y₂ + x₂ * x₁ < x₁ * y₁ + x₂ * y₂`, which is equivalent to
`0 < x₂ - x₁ → 0 < y₂ - y₁ → 0 < (x₂ - x₁) * (y₂ - y₁)`, i.e.
`@mul_pos PGame _ (x₂ - x₁) (y₂ - y₁)`. It has to be stated in this form and not in terms of
`mul_pos` because we need to show P1, P2 and (a specialized form of) P3 simultaneously, and
for example `P1 x y` will be deduced from P3 with variables taking values simpler than `x` or `y`
(among other induction hypotheses), but if you subtract two pregames simpler than `x` or `y`,
the result may no longer be simpler.
The specialized version of P3 is called P4, which takes only three arguments `x₁`, `x₂`, `y` and
requires that `y₂ = y` or `-y` and that `y₁` is a left option of `y₂`. After P1, P2 and P4 are
shown, a further inductive argument (this time using the `GameAdd` relation) proves P3 in full.
Implementation strategy of the inductive argument: we
* extract specialized versions (`IH1`, `IH2`, `IH3`, `IH4` and `IH24`) of the induction hypothesis
that are easier to apply (taking `IsOption` arguments directly), and
* show they are invariant under certain symmetries (permutation and negation of arguments) and that
the induction hypothesis indeed implies the specialized versions.
* utilize the symmetries to minimize calculation.
The whole proof features a clear separation into lemmas of different roles:
* verification of symmetry properties of P and IH (`P3_comm`, `ih1_neg_left`, etc.),
* calculations that connect P1, P2, P3, and inequalities between the product of
two surreals and its options (`mulOption_lt_iff_P1`, etc.),
* specializations of the induction hypothesis
(`numeric_option_mul`, `ih1`, `ih1_swap`, `ih₁₂`, `ih4`, etc.),
* application of specialized induction hypothesis
(`P1_of_ih`, `mul_right_le_of_equiv`, `P3_of_lt`, etc.).
## References
* [Conway, *On numbers and games*][Conway2001]
* [Schleicher, Stoll, *An introduction to Conway's games and numbers*][SchleicherStoll]
-/
universe u
open SetTheory Game PGame WellFounded
namespace Surreal.Multiplication
/-- The nontrivial part of P1 in [SchleicherStoll] says that the left options of `x * y` are less
than the right options, and this is the general form of these statements. -/
def P1 (x₁ x₂ x₃ y₁ y₂ y₃ : PGame) :=
⟦x₁ * y₁⟧ + ⟦x₂ * y₂⟧ - ⟦x₁ * y₂⟧ < ⟦x₃ * y₁⟧ + ⟦x₂ * y₃⟧ - (⟦x₃ * y₃⟧ : Game)
/-- The proposition P2, without numericity assumptions. -/
def P2 (x₁ x₂ y : PGame) := x₁ ≈ x₂ → ⟦x₁ * y⟧ = (⟦x₂ * y⟧ : Game)
/-- The proposition P3, without the `x₁ < x₂` and `y₁ < y₂` assumptions. -/
def P3 (x₁ x₂ y₁ y₂ : PGame) := ⟦x₁ * y₂⟧ + ⟦x₂ * y₁⟧ < ⟦x₁ * y₁⟧ + (⟦x₂ * y₂⟧ : Game)
/-- The proposition P4, without numericity assumptions. In the references, the second part of the
conjunction is stated as `∀ j, P3 x₁ x₂ y (y.moveRight j)`, which is equivalent to our statement
by `P3_comm` and `P3_neg`. We choose to state everything in terms of left options for uniform
treatment. -/
def P4 (x₁ x₂ y : PGame) :=
x₁ < x₂ → (∀ i, P3 x₁ x₂ (y.moveLeft i) y) ∧ ∀ j, P3 x₁ x₂ ((-y).moveLeft j) (-y)
/-- The conjunction of P2 and P4. -/
def P24 (x₁ x₂ y : PGame) : Prop := P2 x₁ x₂ y ∧ P4 x₁ x₂ y
variable {x x₁ x₂ x₃ x' y y₁ y₂ y₃ y' : PGame.{u}}
/-! #### Symmetry properties of P1, P2, P3, and P4 -/
lemma P3_comm : P3 x₁ x₂ y₁ y₂ ↔ P3 y₁ y₂ x₁ x₂ := by
rw [P3, P3, add_comm]
congr! 2 <;> rw [quot_mul_comm]
lemma P3.trans (h₁ : P3 x₁ x₂ y₁ y₂) (h₂ : P3 x₂ x₃ y₁ y₂) : P3 x₁ x₃ y₁ y₂ := by
rw [P3] at h₁ h₂
rw [P3, ← add_lt_add_iff_left (⟦x₂ * y₁⟧ + ⟦x₂ * y₂⟧)]
convert add_lt_add h₁ h₂ using 1 <;> abel
lemma P3_neg : P3 x₁ x₂ y₁ y₂ ↔ P3 (-x₂) (-x₁) y₁ y₂ := by
simp_rw [P3, quot_neg_mul]
rw [← _root_.neg_lt_neg_iff]
abel_nf
lemma P2_neg_left : P2 x₁ x₂ y ↔ P2 (-x₂) (-x₁) y := by
rw [P2, P2]
constructor
· rw [quot_neg_mul, quot_neg_mul, eq_comm, neg_inj, neg_equiv_neg_iff, PGame.equiv_comm]
exact (· ·)
· rw [PGame.equiv_comm, neg_equiv_neg_iff, quot_neg_mul, quot_neg_mul, neg_inj, eq_comm]
exact (· ·)
lemma P2_neg_right : P2 x₁ x₂ y ↔ P2 x₁ x₂ (-y) := by
rw [P2, P2, quot_mul_neg, quot_mul_neg, neg_inj]
lemma P4_neg_left : P4 x₁ x₂ y ↔ P4 (-x₂) (-x₁) y := by
simp_rw [P4, PGame.neg_lt_neg_iff, moveLeft_neg, ← P3_neg]
lemma P4_neg_right : P4 x₁ x₂ y ↔ P4 x₁ x₂ (-y) := by
rw [P4, P4, neg_neg, and_comm]
lemma P24_neg_left : P24 x₁ x₂ y ↔ P24 (-x₂) (-x₁) y := by rw [P24, P24, P2_neg_left, P4_neg_left]
lemma P24_neg_right : P24 x₁ x₂ y ↔ P24 x₁ x₂ (-y) := by rw [P24, P24, P2_neg_right, P4_neg_right]
/-! #### Explicit calculations necessary for the main proof -/
lemma mulOption_lt_iff_P1 {i j k l} :
(⟦mulOption x y i k⟧ : Game) < -⟦mulOption x (-y) j l⟧ ↔
P1 (x.moveLeft i) x (x.moveLeft j) y (y.moveLeft k) (-(-y).moveLeft l) := by
dsimp only [P1, mulOption, quot_sub, quot_add]
simp_rw [neg_sub', neg_add, quot_mul_neg, neg_neg]
lemma mulOption_lt_mul_iff_P3 {i j} :
⟦mulOption x y i j⟧ < (⟦x * y⟧ : Game) ↔ P3 (x.moveLeft i) x (y.moveLeft j) y := by
dsimp only [mulOption, quot_sub, quot_add]
exact sub_lt_iff_lt_add'
lemma P1_of_eq (he : x₁ ≈ x₃) (h₁ : P2 x₁ x₃ y₁) (h₃ : P2 x₁ x₃ y₃) (h3 : P3 x₁ x₂ y₂ y₃) :
P1 x₁ x₂ x₃ y₁ y₂ y₃ := by
rw [P1, ← h₁ he, ← h₃ he, sub_lt_sub_iff]
convert add_lt_add_left h3 ⟦x₁ * y₁⟧ using 1 <;> abel
lemma P1_of_lt (h₁ : P3 x₃ x₂ y₂ y₃) (h₂ : P3 x₁ x₃ y₂ y₁) : P1 x₁ x₂ x₃ y₁ y₂ y₃ := by
rw [P1, sub_lt_sub_iff, ← add_lt_add_iff_left ⟦x₃ * y₂⟧]
convert add_lt_add h₁ h₂ using 1 <;> abel
/-- The type of lists of arguments for P1, P2, and P4. -/
inductive Args : Type (u + 1)
| P1 (x y : PGame.{u}) : Args
| P24 (x₁ x₂ y : PGame.{u}) : Args
/-- The multiset associated to a list of arguments. -/
def Args.toMultiset : Args → Multiset PGame
| (Args.P1 x y) => {x, y}
| (Args.P24 x₁ x₂ y) => {x₁, x₂, y}
/-- A list of arguments is numeric if all the arguments are. -/
def Args.Numeric (a : Args) := ∀ x ∈ a.toMultiset, SetTheory.PGame.Numeric x
lemma Args.numeric_P1 {x y} : (Args.P1 x y).Numeric ↔ x.Numeric ∧ y.Numeric := by
simp [Args.Numeric, Args.toMultiset]
lemma Args.numeric_P24 {x₁ x₂ y} :
(Args.P24 x₁ x₂ y).Numeric ↔ x₁.Numeric ∧ x₂.Numeric ∧ y.Numeric := by
simp [Args.Numeric, Args.toMultiset]
open Relation
/-- The relation specifying when a list of (pregame) arguments is considered simpler than another:
`ArgsRel a₁ a₂` is true if `a₁`, considered as a multiset, can be obtained from `a₂` by
repeatedly removing a pregame from `a₂` and adding back one or two options of the pregame. -/
def ArgsRel := InvImage (TransGen <| CutExpand IsOption) Args.toMultiset
/-- `ArgsRel` is well-founded. -/
theorem argsRel_wf : WellFounded ArgsRel := InvImage.wf _ wf_isOption.cutExpand.transGen
/-- The statement that we will show by induction using the well-founded relation `ArgsRel`. -/
def P124 : Args → Prop
| (Args.P1 x y) => Numeric (x * y)
| (Args.P24 x₁ x₂ y) => P24 x₁ x₂ y
/-- The property that all arguments are numeric is leftward-closed under `ArgsRel`. -/
lemma ArgsRel.numeric_closed {a' a} : ArgsRel a' a → a.Numeric → a'.Numeric :=
TransGen.closed' <| @cutExpand_closed _ IsOption ⟨wf_isOption.isIrrefl.1⟩ _ Numeric.isOption
/-- A specialized induction hypothesis used to prove P1. -/
def IH1 (x y : PGame) : Prop :=
∀ ⦃x₁ x₂ y'⦄, IsOption x₁ x → IsOption x₂ x → (y' = y ∨ IsOption y' y) → P24 x₁ x₂ y'
/-! #### Symmetry properties of `IH1` -/
lemma ih1_neg_left : IH1 x y → IH1 (-x) y :=
fun h x₁ x₂ y' h₁ h₂ hy ↦ by
rw [isOption_neg] at h₁ h₂
exact P24_neg_left.2 (h h₂ h₁ hy)
lemma ih1_neg_right : IH1 x y → IH1 x (-y) :=
fun h x₁ x₂ y' ↦ by
rw [← neg_eq_iff_eq_neg, isOption_neg, P24_neg_right]
apply h
/-! #### Specialize `ih` to obtain specialized induction hypotheses for P1 -/
lemma numeric_option_mul (ih : ∀ a, ArgsRel a (Args.P1 x y) → P124 a) (h : IsOption x' x) :
(x' * y).Numeric :=
ih (Args.P1 x' y) (TransGen.single <| cutExpand_pair_left h)
lemma numeric_mul_option (ih : ∀ a, ArgsRel a (Args.P1 x y) → P124 a) (h : IsOption y' y) :
(x * y').Numeric :=
ih (Args.P1 x y') (TransGen.single <| cutExpand_pair_right h)
lemma numeric_option_mul_option (ih : ∀ a, ArgsRel a (Args.P1 x y) → P124 a) (hx : IsOption x' x)
(hy : IsOption y' y) : (x' * y').Numeric :=
ih (Args.P1 x' y') ((TransGen.single <| cutExpand_pair_right hy).tail <| cutExpand_pair_left hx)
lemma ih1 (ih : ∀ a, ArgsRel a (Args.P1 x y) → P124 a) : IH1 x y := by
rintro x₁ x₂ y' h₁ h₂ (rfl|hy) <;> apply ih (Args.P24 _ _ _)
on_goal 2 => refine TransGen.tail ?_ (cutExpand_pair_right hy)
all_goals exact TransGen.single (cutExpand_double_left h₁ h₂)
lemma ih1_swap (ih : ∀ a, ArgsRel a (Args.P1 x y) → P124 a) : IH1 y x := ih1 <| by
simp_rw [ArgsRel, InvImage, Args.toMultiset, Multiset.pair_comm] at ih ⊢
exact ih
lemma P3_of_ih (hy : Numeric y) (ihyx : IH1 y x) (i k l) :
P3 (x.moveLeft i) x (y.moveLeft k) (-(-y).moveLeft l) :=
P3_comm.2 <| ((ihyx (IsOption.moveLeft k) (isOption_neg.1 <| .moveLeft l) <| Or.inl rfl).2
(by rw [moveLeft_neg, neg_neg]; apply hy.left_lt_right)).1 i
lemma P24_of_ih (ihxy : IH1 x y) (i j) : P24 (x.moveLeft i) (x.moveLeft j) y :=
ihxy (IsOption.moveLeft i) (IsOption.moveLeft j) (Or.inl rfl)
section
lemma mulOption_lt_of_lt (hy : y.Numeric) (ihxy : IH1 x y) (ihyx : IH1 y x) (i j k l)
(h : x.moveLeft i < x.moveLeft j) :
(⟦mulOption x y i k⟧ : Game) < -⟦mulOption x (-y) j l⟧ :=
mulOption_lt_iff_P1.2 <| P1_of_lt (P3_of_ih hy ihyx j k l) <| ((P24_of_ih ihxy i j).2 h).1 k
lemma mulOption_lt (hx : x.Numeric) (hy : y.Numeric) (ihxy : IH1 x y) (ihyx : IH1 y x) (i j k l) :
(⟦mulOption x y i k⟧ : Game) < -⟦mulOption x (-y) j l⟧ := by
obtain (h|h|h) := lt_or_equiv_or_gt (hx.moveLeft i) (hx.moveLeft j)
· exact mulOption_lt_of_lt hy ihxy ihyx i j k l h
· have ml := @IsOption.moveLeft
exact mulOption_lt_iff_P1.2 (P1_of_eq h (P24_of_ih ihxy i j).1
(ihxy (ml i) (ml j) <| Or.inr <| isOption_neg.1 <| ml l).1 <| P3_of_ih hy ihyx i k l)
· rw [mulOption_neg_neg, lt_neg]
exact mulOption_lt_of_lt hy.neg (ih1_neg_right ihxy) (ih1_neg_left ihyx) j i l _ h
end
/-- P1 follows from the induction hypothesis. -/
theorem P1_of_ih (ih : ∀ a, ArgsRel a (Args.P1 x y) → P124 a) (hx : x.Numeric) (hy : y.Numeric) :
(x * y).Numeric := by
have ihxy := ih1 ih
have ihyx := ih1_swap ih
have ihxyn := ih1_neg_left (ih1_neg_right ihxy)
have ihyxn := ih1_neg_left (ih1_neg_right ihyx)
refine numeric_def.mpr ⟨?_, ?_, ?_⟩
· simp_rw [lt_iff_game_lt]
intro i
rw [rightMoves_mul_iff]
constructor <;> (intro j l; revert i; rw [leftMoves_mul_iff (_ > ·)]; constructor <;> intro i k)
· apply mulOption_lt hx hy ihxy ihyx
· simp_rw [← mulOption_symm (-y), mulOption_neg_neg x]
apply mulOption_lt hy.neg hx.neg ihyxn ihxyn
· simp only [← mulOption_symm y]
apply mulOption_lt hy hx ihyx ihxy
· rw [mulOption_neg_neg y]
apply mulOption_lt hx.neg hy.neg ihxyn ihyxn
all_goals
cases x; cases y
rintro (⟨i,j⟩|⟨i,j⟩) <;>
refine ((numeric_option_mul ih ?_).add <| numeric_mul_option ih ?_).sub
(numeric_option_mul_option ih ?_ ?_) <;>
solve_by_elim [IsOption.mk_left, IsOption.mk_right]
/-- A specialized induction hypothesis used to prove P2 and P4. -/
def IH24 (x₁ x₂ y : PGame) : Prop :=
∀ ⦃z⦄, (IsOption z x₁ → P24 z x₂ y) ∧ (IsOption z x₂ → P24 x₁ z y) ∧ (IsOption z y → P24 x₁ x₂ z)
/-- A specialized induction hypothesis used to prove P4. -/
def IH4 (x₁ x₂ y : PGame) : Prop :=
∀ ⦃z w⦄, IsOption w y → (IsOption z x₁ → P2 z x₂ w) ∧ (IsOption z x₂ → P2 x₁ z w)
/-! #### Specialize `ih'` to obtain specialized induction hypotheses for P2 and P4 -/
lemma ih₁₂ (ih' : ∀ a, ArgsRel a (Args.P24 x₁ x₂ y) → P124 a) : IH24 x₁ x₂ y := by
rw [IH24]
refine fun z ↦ ⟨?_, ?_, ?_⟩ <;>
refine fun h ↦ ih' (Args.P24 _ _ _) (TransGen.single ?_)
· exact (cutExpand_add_right {y}).2 (cutExpand_pair_left h)
· exact (cutExpand_add_left {x₁}).2 (cutExpand_pair_left h)
· exact (cutExpand_add_left {x₁}).2 (cutExpand_pair_right h)
lemma ih₂₁ (ih' : ∀ a, ArgsRel a (Args.P24 x₁ x₂ y) → P124 a) : IH24 x₂ x₁ y := ih₁₂ <| by
simp_rw [ArgsRel, InvImage, Args.toMultiset, Multiset.pair_comm] at ih' ⊢
suffices {x₁, y, x₂} = {x₂, y, x₁} by rwa [← this]
dsimp only [Multiset.insert_eq_cons, ← Multiset.singleton_add] at ih' ⊢
abel
lemma ih4 (ih' : ∀ a, ArgsRel a (Args.P24 x₁ x₂ y) → P124 a) : IH4 x₁ x₂ y := by
refine fun z w h ↦ ⟨?_, ?_⟩
all_goals
intro h'
apply (ih' (Args.P24 _ _ _) <| (TransGen.single _).tail <|
(cutExpand_add_left {x₁}).2 <| cutExpand_pair_right h).1
try exact (cutExpand_add_right {w}).2 <| cutExpand_pair_left h'
try exact (cutExpand_add_right {w}).2 <| cutExpand_pair_right h'
lemma numeric_of_ih (ih' : ∀ a, ArgsRel a (Args.P24 x₁ x₂ y) → P124 a) :
(x₁ * y).Numeric ∧ (x₂ * y).Numeric := by
constructor <;> refine ih' (Args.P1 _ _) (TransGen.single ?_)
· exact (cutExpand_add_right {y}).2 <| (cutExpand_add_left {x₁}).2 cutExpand_zero
· exact (cutExpand_add_right {x₂, y}).2 cutExpand_zero
/-- Symmetry properties of `IH24`. -/
lemma ih24_neg : IH24 x₁ x₂ y → IH24 (-x₂) (-x₁) y ∧ IH24 x₁ x₂ (-y) := by
simp_rw [IH24, ← P24_neg_right, isOption_neg]
refine fun h ↦ ⟨fun z ↦ ⟨?_, ?_, ?_⟩,
fun z ↦ ⟨(@h z).1, (@h z).2.1, P24_neg_right.2 ∘ (@h <| -z).2.2⟩⟩
all_goals
rw [P24_neg_left]
simp only [neg_neg]
first | exact (@h <| -z).2.1 | exact (@h <| -z).1 | exact (@h z).2.2
/-- Symmetry properties of `IH4`. -/
lemma ih4_neg : IH4 x₁ x₂ y → IH4 (-x₂) (-x₁) y ∧ IH4 x₁ x₂ (-y) := by
simp_rw [IH4, isOption_neg]
refine fun h ↦ ⟨fun z w h' ↦ ?_, fun z w h' ↦ ?_⟩
· convert (h h').symm using 2 <;> rw [P2_neg_left, neg_neg]
· convert h h' using 2 <;> rw [P2_neg_right]
lemma mulOption_lt_mul_of_equiv (hn : x₁.Numeric) (h : IH24 x₁ x₂ y) (he : x₁ ≈ x₂) (i j) :
⟦mulOption x₁ y i j⟧ < (⟦x₂ * y⟧ : Game) := by
convert sub_lt_iff_lt_add'.2 ((((@h _).1 <| IsOption.moveLeft i).2 _).1 j) using 1
· rw [← ((@h _).2.2 <| IsOption.moveLeft j).1 he]
rfl
· rw [← lt_congr_right he]
apply hn.moveLeft_lt
/-- P2 follows from specialized induction hypotheses (one half of the equality). -/
theorem mul_right_le_of_equiv (h₁ : x₁.Numeric) (h₂ : x₂.Numeric)
(h₁₂ : IH24 x₁ x₂ y) (h₂₁ : IH24 x₂ x₁ y) (he : x₁ ≈ x₂) : x₁ * y ≤ x₂ * y := by
have he' := neg_equiv_neg_iff.2 he
apply PGame.le_of_forall_lt <;> simp_rw [lt_iff_game_lt]
· rw [leftMoves_mul_iff (_ > ·)]
refine ⟨mulOption_lt_mul_of_equiv h₁ h₁₂ he, ?_⟩
rw [← quot_neg_mul_neg]
exact mulOption_lt_mul_of_equiv h₁.neg (ih24_neg <| (ih24_neg h₂₁).1).2 he'
· rw [rightMoves_mul_iff]
constructor <;> intros <;> rw [lt_neg]
· rw [← quot_mul_neg]
apply mulOption_lt_mul_of_equiv h₂ (ih24_neg h₂₁).2 (symm he)
· rw [← quot_neg_mul]
apply mulOption_lt_mul_of_equiv h₂.neg (ih24_neg h₁₂).1 (symm he')
/-- The statement that all left options of `x * y` of the first kind are less than itself. -/
def MulOptionsLTMul (x y : PGame) : Prop := ∀ ⦃i j⦄, ⟦mulOption x y i j⟧ < (⟦x * y⟧ : Game)
/-- That the left options of `x * y` are less than itself and the right options are greater, which
is part of the condition that `x * y` is numeric, is equivalent to the conjunction of various
`MulOptionsLTMul` statements for `x`, `y` and their negations. We only show the forward
direction. -/
lemma mulOptionsLTMul_of_numeric (hn : (x * y).Numeric) :
(MulOptionsLTMul x y ∧ MulOptionsLTMul (-x) (-y)) ∧
(MulOptionsLTMul x (-y) ∧ MulOptionsLTMul (-x) y) := by
constructor
· have h := hn.moveLeft_lt
simp_rw [lt_iff_game_lt] at h
convert (leftMoves_mul_iff <| GT.gt _).1 h
rw [← quot_neg_mul_neg]
rfl
· have h := hn.lt_moveRight
simp_rw [lt_iff_game_lt, rightMoves_mul_iff] at h
refine h.imp ?_ ?_ <;> refine forall₂_imp fun a b ↦ ?_
all_goals
rw [lt_neg]
first | rw [quot_mul_neg] | rw [quot_neg_mul]
exact id
/-- A condition just enough to deduce P3, which will always be used with `x'` being a left
option of `x₂`. When `y₁` is a left option of `y₂`, it can be deduced from induction hypotheses
`IH24 x₁ x₂ y₂`, `IH4 x₁ x₂ y₂`, and `(x₂ * y₂).Numeric` (`ih3_of_ih`); when `y₁` is
not necessarily an option of `y₂`, it follows from the induction hypothesis for P3 (with `x₂`
replaced by a left option `x'`) after the `main` theorem (P124) is established, and is used to
prove P3 in full (`P3_of_lt_of_lt`). -/
def IH3 (x₁ x' x₂ y₁ y₂ : PGame) : Prop :=
P2 x₁ x' y₁ ∧ P2 x₁ x' y₂ ∧ P3 x' x₂ y₁ y₂ ∧ (x₁ < x' → P3 x₁ x' y₁ y₂)
lemma ih3_of_ih (h24 : IH24 x₁ x₂ y) (h4 : IH4 x₁ x₂ y) (hl : MulOptionsLTMul x₂ y) (i j) :
IH3 x₁ (x₂.moveLeft i) x₂ (y.moveLeft j) y :=
have ml := @IsOption.moveLeft
have h24 := (@h24 _).2.1 (ml i)
⟨(h4 <| ml j).2 (ml i), h24.1, mulOption_lt_mul_iff_P3.1 (@hl i j), fun l ↦ (h24.2 l).1 _⟩
lemma P3_of_le_left {y₁ y₂} (i) (h : IH3 x₁ (x₂.moveLeft i) x₂ y₁ y₂) (hl : x₁ ≤ x₂.moveLeft i) :
P3 x₁ x₂ y₁ y₂ := by
obtain (hl|he) := lt_or_equiv_of_le hl
· exact (h.2.2.2 hl).trans h.2.2.1
· rw [P3, h.1 he, h.2.1 he]
exact h.2.2.1
/-- P3 follows from `IH3` (so P4 (with `y₁` a left option of `y₂`) follows from the induction
hypothesis). -/
theorem P3_of_lt {y₁ y₂} (h : ∀ i, IH3 x₁ (x₂.moveLeft i) x₂ y₁ y₂)
(hs : ∀ i, IH3 (-x₂) ((-x₁).moveLeft i) (-x₁) y₁ y₂) (hl : x₁ < x₂) :
P3 x₁ x₂ y₁ y₂ := by
obtain (⟨i,hi⟩|⟨i,hi⟩) := lf_iff_exists_le.1 (lf_of_lt hl)
· exact P3_of_le_left i (h i) hi
· apply P3_neg.2 <| P3_of_le_left _ (hs (toLeftMovesNeg i)) _
simpa
/-- The main chunk of Theorem 8 in [Conway2001] / Theorem 3.8 in [SchleicherStoll]. -/
theorem main (a : Args) : a.Numeric → P124 a := by
apply argsRel_wf.induction a
intros a ih ha
replace ih : ∀ a', ArgsRel a' a → P124 a' := fun a' hr ↦ ih a' hr (hr.numeric_closed ha)
cases a with
/- P1 -/
| P1 x y =>
rw [Args.numeric_P1] at ha
exact P1_of_ih ih ha.1 ha.2
| P24 x₁ x₂ y =>
have h₁₂ := ih₁₂ ih
have h₂₁ := ih₂₁ ih
have h4 := ih4 ih
obtain ⟨h₁₂x, h₁₂y⟩ := ih24_neg h₁₂
obtain ⟨h4x, h4y⟩ := ih4_neg h4
refine ⟨fun he ↦ Quotient.sound ?_, fun hl ↦ ?_⟩
· /- P2 -/
rw [Args.numeric_P24] at ha
exact ⟨mul_right_le_of_equiv ha.1 ha.2.1 h₁₂ h₂₁ he,
mul_right_le_of_equiv ha.2.1 ha.1 h₂₁ h₁₂ (symm he)⟩
· /- P4 -/
obtain ⟨hn₁, hn₂⟩ := numeric_of_ih ih
obtain ⟨⟨h₁, -⟩, h₂, -⟩ := mulOptionsLTMul_of_numeric hn₂
obtain ⟨⟨-, h₃⟩, -, h₄⟩ := mulOptionsLTMul_of_numeric hn₁
constructor <;> intro <;> refine P3_of_lt ?_ ?_ hl <;> intro <;> apply ih3_of_ih
any_goals assumption
exacts [(ih24_neg h₁₂y).1, (ih4_neg h4y).1]
end Surreal.Multiplication
namespace SetTheory.PGame
open Surreal.Multiplication
variable {x x₁ x₂ y y₁ y₂ : PGame.{u}}
theorem Numeric.mul (hx : x.Numeric) (hy : y.Numeric) : Numeric (x * y) :=
main _ <| Args.numeric_P1.mpr ⟨hx, hy⟩
theorem P24 (hx₁ : x₁.Numeric) (hx₂ : x₂.Numeric) (hy : y.Numeric) : P24 x₁ x₂ y :=
main _ <| Args.numeric_P24.mpr ⟨hx₁, hx₂, hy⟩
theorem Equiv.mul_congr_left (hx₁ : x₁.Numeric) (hx₂ : x₂.Numeric) (hy : y.Numeric)
(he : x₁ ≈ x₂) : x₁ * y ≈ x₂ * y :=
equiv_iff_game_eq.2 <| (P24 hx₁ hx₂ hy).1 he
theorem Equiv.mul_congr_right (hx : x.Numeric) (hy₁ : y₁.Numeric) (hy₂ : y₂.Numeric)
(he : y₁ ≈ y₂) : x * y₁ ≈ x * y₂ :=
.trans (mul_comm_equiv _ _) <| .trans (mul_congr_left hy₁ hy₂ hx he) (mul_comm_equiv _ _)
theorem Equiv.mul_congr (hx₁ : x₁.Numeric) (hx₂ : x₂.Numeric)
(hy₁ : y₁.Numeric) (hy₂ : y₂.Numeric) (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ * y₁ ≈ x₂ * y₂ :=
.trans (mul_congr_left hx₁ hx₂ hy₁ hx) (mul_congr_right hx₂ hy₁ hy₂ hy)
open Prod.GameAdd
| /-- One additional inductive argument that supplies the last missing part of Theorem 8. -/
theorem P3_of_lt_of_lt (hx₁ : x₁.Numeric) (hx₂ : x₂.Numeric) (hy₁ : y₁.Numeric) (hy₂ : y₂.Numeric)
(hx : x₁ < x₂) (hy : y₁ < y₂) : P3 x₁ x₂ y₁ y₂ := by
revert x₁ x₂
rw [← Prod.forall']
refine (wf_isOption.prod_gameAdd wf_isOption).fix ?_
rintro ⟨x₁, x₂⟩ ih hx₁ hx₂ hx
refine P3_of_lt ?_ ?_ hx <;> intro i
· have hi := hx₂.moveLeft i
exact ⟨(P24 hx₁ hi hy₁).1, (P24 hx₁ hi hy₂).1,
P3_comm.2 <| ((P24 hy₁ hy₂ hx₂).2 hy).1 _,
ih _ (snd <| IsOption.moveLeft i) hx₁ hi⟩
· have hi := hx₁.neg.moveLeft i
exact ⟨(P24 hx₂.neg hi hy₁).1, (P24 hx₂.neg hi hy₂).1,
P3_comm.2 <| ((P24 hy₁ hy₂ hx₁).2 hy).2 _, by
| Mathlib/SetTheory/Surreal/Multiplication.lean | 475 | 489 |
/-
Copyright (c) 2022 Xavier Roblot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Xavier Roblot
-/
import Mathlib.Algebra.Module.ZLattice.Basic
import Mathlib.Analysis.InnerProductSpace.ProdL2
import Mathlib.MeasureTheory.Measure.Haar.Unique
import Mathlib.NumberTheory.NumberField.FractionalIdeal
import Mathlib.NumberTheory.NumberField.Units.Basic
/-!
# Canonical embedding of a number field
The canonical embedding of a number field `K` of degree `n` is the ring homomorphism
`K →+* ℂ^n` that sends `x ∈ K` to `(φ_₁(x),...,φ_n(x))` where the `φ_i`'s are the complex
embeddings of `K`. Note that we do not choose an ordering of the embeddings, but instead map `K`
into the type `(K →+* ℂ) → ℂ` of `ℂ`-vectors indexed by the complex embeddings.
## Main definitions and results
* `NumberField.canonicalEmbedding`: the ring homomorphism `K →+* ((K →+* ℂ) → ℂ)` defined by
sending `x : K` to the vector `(φ x)` indexed by `φ : K →+* ℂ`.
* `NumberField.canonicalEmbedding.integerLattice.inter_ball_finite`: the intersection of the
image of the ring of integers by the canonical embedding and any ball centered at `0` of finite
radius is finite.
* `NumberField.mixedEmbedding`: the ring homomorphism from `K` to the mixed space
`K →+* ({ w // IsReal w } → ℝ) × ({ w // IsComplex w } → ℂ)` that sends `x ∈ K` to `(φ_w x)_w`
where `φ_w` is the embedding associated to the infinite place `w`. In particular, if `w` is real
then `φ_w : K →+* ℝ` and, if `w` is complex, `φ_w` is an arbitrary choice between the two complex
embeddings defining the place `w`.
## Tags
number field, infinite places
-/
variable (K : Type*) [Field K]
namespace NumberField.canonicalEmbedding
/-- The canonical embedding of a number field `K` of degree `n` into `ℂ^n`. -/
def _root_.NumberField.canonicalEmbedding : K →+* ((K →+* ℂ) → ℂ) := Pi.ringHom fun φ => φ
theorem _root_.NumberField.canonicalEmbedding_injective [NumberField K] :
Function.Injective (NumberField.canonicalEmbedding K) := RingHom.injective _
variable {K}
@[simp]
theorem apply_at (φ : K →+* ℂ) (x : K) : (NumberField.canonicalEmbedding K x) φ = φ x := rfl
open scoped ComplexConjugate
/-- The image of `canonicalEmbedding` lives in the `ℝ`-submodule of the `x ∈ ((K →+* ℂ) → ℂ)` such
that `conj x_φ = x_(conj φ)` for all `∀ φ : K →+* ℂ`. -/
theorem conj_apply {x : ((K →+* ℂ) → ℂ)} (φ : K →+* ℂ)
(hx : x ∈ Submodule.span ℝ (Set.range (canonicalEmbedding K))) :
conj (x φ) = x (ComplexEmbedding.conjugate φ) := by
refine Submodule.span_induction ?_ ?_ (fun _ _ _ _ hx hy => ?_) (fun a _ _ hx => ?_) hx
· rintro _ ⟨x, rfl⟩
rw [apply_at, apply_at, ComplexEmbedding.conjugate_coe_eq]
· rw [Pi.zero_apply, Pi.zero_apply, map_zero]
· rw [Pi.add_apply, Pi.add_apply, map_add, hx, hy]
· rw [Pi.smul_apply, Complex.real_smul, map_mul, Complex.conj_ofReal]
exact congrArg ((a : ℂ) * ·) hx
theorem nnnorm_eq [NumberField K] (x : K) :
‖canonicalEmbedding K x‖₊ = Finset.univ.sup (fun φ : K →+* ℂ => ‖φ x‖₊) := by
simp_rw [Pi.nnnorm_def, apply_at]
theorem norm_le_iff [NumberField K] (x : K) (r : ℝ) :
‖canonicalEmbedding K x‖ ≤ r ↔ ∀ φ : K →+* ℂ, ‖φ x‖ ≤ r := by
| obtain hr | hr := lt_or_le r 0
· obtain ⟨φ⟩ := (inferInstance : Nonempty (K →+* ℂ))
refine iff_of_false ?_ ?_
· exact (hr.trans_le (norm_nonneg _)).not_le
· exact fun h => hr.not_le (le_trans (norm_nonneg _) (h φ))
· lift r to NNReal using hr
simp_rw [← coe_nnnorm, nnnorm_eq, NNReal.coe_le_coe, Finset.sup_le_iff, Finset.mem_univ,
forall_true_left]
variable (K)
| Mathlib/NumberTheory/NumberField/CanonicalEmbedding/Basic.lean | 76 | 85 |
/-
Copyright (c) 2021 Henry Swanson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Henry Swanson
-/
import Mathlib.Dynamics.FixedPoints.Basic
import Mathlib.GroupTheory.Perm.Option
import Mathlib.Logic.Equiv.Defs
import Mathlib.Logic.Equiv.Option
import Mathlib.Tactic.ApplyFun
/-!
# Derangements on types
In this file we define `derangements α`, the set of derangements on a type `α`.
We also define some equivalences involving various subtypes of `Perm α` and `derangements α`:
* `derangementsOptionEquivSigmaAtMostOneFixedPoint`: An equivalence between
`derangements (Option α)` and the sigma-type `Σ a : α, {f : Perm α // fixed_points f ⊆ a}`.
* `derangementsRecursionEquiv`: An equivalence between `derangements (Option α)` and the
sigma-type `Σ a : α, (derangements (({a}ᶜ : Set α) : Type*) ⊕ derangements α)` which is later
used to inductively count the number of derangements.
In order to prove the above, we also prove some results about the effect of `Equiv.removeNone`
on derangements: `RemoveNone.fiber_none` and `RemoveNone.fiber_some`.
-/
open Equiv Function
/-- A permutation is a derangement if it has no fixed points. -/
def derangements (α : Type*) : Set (Perm α) :=
{ f : Perm α | ∀ x : α, f x ≠ x }
variable {α β : Type*}
theorem mem_derangements_iff_fixedPoints_eq_empty {f : Perm α} :
f ∈ derangements α ↔ fixedPoints f = ∅ :=
Set.eq_empty_iff_forall_not_mem.symm
/-- If `α` is equivalent to `β`, then `derangements α` is equivalent to `derangements β`. -/
def Equiv.derangementsCongr (e : α ≃ β) : derangements α ≃ derangements β :=
e.permCongr.subtypeEquiv fun {f} => e.forall_congr <| by
intro b; simp only [ne_eq, permCongr_apply, symm_apply_apply, EmbeddingLike.apply_eq_iff_eq]
namespace derangements
/-- Derangements on a subtype are equivalent to permutations on the original type where points are
fixed iff they are not in the subtype. -/
protected def subtypeEquiv (p : α → Prop) [DecidablePred p] :
derangements (Subtype p) ≃ { f : Perm α // ∀ a, ¬p a ↔ a ∈ fixedPoints f } :=
calc
derangements (Subtype p) ≃ { f : { f : Perm α // ∀ a, ¬p a → a ∈ fixedPoints f } //
∀ a, a ∈ fixedPoints f → ¬p a } := by
refine (Perm.subtypeEquivSubtypePerm p).subtypeEquiv fun f => ⟨fun hf a hfa ha => ?_, ?_⟩
· refine hf ⟨a, ha⟩ (Subtype.ext ?_)
simp_rw [mem_fixedPoints, IsFixedPt, Perm.subtypeEquivSubtypePerm,
Equiv.coe_fn_mk, Perm.ofSubtype_apply_of_mem _ ha] at hfa
assumption
rintro hf ⟨a, ha⟩ hfa
refine hf _ ?_ ha
simp only [Perm.subtypeEquivSubtypePerm_apply_coe, mem_fixedPoints]
dsimp [IsFixedPt]
simp_rw [Perm.ofSubtype_apply_of_mem _ ha, hfa]
_ ≃ { f : Perm α // ∃ _h : ∀ a, ¬p a → a ∈ fixedPoints f, ∀ a, a ∈ fixedPoints f → ¬p a } :=
subtypeSubtypeEquivSubtypeExists _ _
_ ≃ { f : Perm α // ∀ a, ¬p a ↔ a ∈ fixedPoints f } :=
subtypeEquivRight fun f => by
simp_rw [exists_prop, ← forall_and, ← iff_iff_implies_and_implies]
universe u
/-- The set of permutations that fix either `a` or nothing is equivalent to the sum of:
- derangements on `α`
- derangements on `α` minus `a`. -/
def atMostOneFixedPointEquivSum_derangements [DecidableEq α] (a : α) :
{ f : Perm α // fixedPoints f ⊆ {a} } ≃ (derangements ({a}ᶜ : Set α)) ⊕ (derangements α) :=
calc
{ f : Perm α // fixedPoints f ⊆ {a} } ≃
{ f : { f : Perm α // fixedPoints f ⊆ {a} } // a ∈ fixedPoints f } ⊕
{ f : { f : Perm α // fixedPoints f ⊆ {a} } // a ∉ fixedPoints f } :=
(Equiv.sumCompl _).symm
_ ≃ { f : Perm α // fixedPoints f ⊆ {a} ∧ a ∈ fixedPoints f } ⊕
{ f : Perm α // fixedPoints f ⊆ {a} ∧ a ∉ fixedPoints f } := by
-- Porting note: `subtypeSubtypeEquivSubtypeInter` no longer works with placeholder `_`s.
refine Equiv.sumCongr ?_ ?_
· exact subtypeSubtypeEquivSubtypeInter
(fun x : Perm α => fixedPoints x ⊆ {a})
(a ∈ fixedPoints ·)
· exact subtypeSubtypeEquivSubtypeInter
(fun x : Perm α => fixedPoints x ⊆ {a})
(¬a ∈ fixedPoints ·)
_ ≃ { f : Perm α // fixedPoints f = {a} } ⊕ { f : Perm α // fixedPoints f = ∅ } := by
refine Equiv.sumCongr (subtypeEquivRight fun f => ?_) (subtypeEquivRight fun f => ?_)
· rw [Set.eq_singleton_iff_unique_mem, and_comm]
rfl
· rw [Set.eq_empty_iff_forall_not_mem]
exact ⟨fun h x hx => h.2 (h.1 hx ▸ hx), fun h => ⟨fun x hx => (h _ hx).elim, h _⟩⟩
_ ≃ derangements ({a}ᶜ : Set α) ⊕ derangements α := by
refine
Equiv.sumCongr ((derangements.subtypeEquiv _).trans <|
subtypeEquivRight fun x => ?_).symm
(subtypeEquivRight fun f => mem_derangements_iff_fixedPoints_eq_empty.symm)
rw [eq_comm, Set.ext_iff]
simp_rw [Set.mem_compl_iff, Classical.not_not]
namespace Equiv
variable [DecidableEq α]
/-- The set of permutations `f` such that the preimage of `(a, f)` under
`Equiv.Perm.decomposeOption` is a derangement. -/
def RemoveNone.fiber (a : Option α) : Set (Perm α) :=
{ f : Perm α | (a, f) ∈ Equiv.Perm.decomposeOption '' derangements (Option α) }
theorem RemoveNone.mem_fiber (a : Option α) (f : Perm α) :
f ∈ RemoveNone.fiber a ↔
∃ F : Perm (Option α), F ∈ derangements (Option α) ∧ F none = a ∧ removeNone F = f := by
simp [RemoveNone.fiber, derangements]
theorem RemoveNone.fiber_none : RemoveNone.fiber (@none α) = ∅ := by
rw [Set.eq_empty_iff_forall_not_mem]
intro f hyp
rw [RemoveNone.mem_fiber] at hyp
rcases hyp with ⟨F, F_derangement, F_none, _⟩
exact F_derangement none F_none
/-- For any `a : α`, the fiber over `some a` is the set of permutations
where `a` is the only possible fixed point. -/
theorem RemoveNone.fiber_some (a : α) :
RemoveNone.fiber (some a) = { f : Perm α | fixedPoints f ⊆ {a} } := by
ext f
constructor
· rw [RemoveNone.mem_fiber]
rintro ⟨F, F_derangement, F_none, rfl⟩ x x_fixed
rw [mem_fixedPoints_iff] at x_fixed
apply_fun some at x_fixed
rcases Fx : F (some x) with - | y
· rwa [removeNone_none F Fx, F_none, Option.some_inj, eq_comm] at x_fixed
| · exfalso
rw [removeNone_some F ⟨y, Fx⟩] at x_fixed
exact F_derangement _ x_fixed
· intro h_opfp
use Equiv.Perm.decomposeOption.symm (some a, f)
constructor
· intro x
apply_fun fun x => Equiv.swap none (some a) x
simp only [Perm.decomposeOption_symm_apply, swap_apply_self, Perm.coe_mul]
rcases x with - | x
· simp
simp only [comp, optionCongr_apply, Option.map_some', swap_apply_self]
by_cases x_vs_a : x = a
· rw [x_vs_a, swap_apply_right]
apply Option.some_ne_none
have ne_1 : some x ≠ none := Option.some_ne_none _
have ne_2 : some x ≠ some a := (Option.some_injective α).ne_iff.mpr x_vs_a
rw [swap_apply_of_ne_of_ne ne_1 ne_2, (Option.some_injective α).ne_iff]
intro contra
exact x_vs_a (h_opfp contra)
· rw [apply_symm_apply]
end Equiv
section Option
variable [DecidableEq α]
/-- The set of derangements on `Option α` is equivalent to the union over `a : α`
of "permutations with `a` the only possible fixed point". -/
def derangementsOptionEquivSigmaAtMostOneFixedPoint :
| Mathlib/Combinatorics/Derangements/Basic.lean | 139 | 169 |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Algebra.Order.Archimedean.Basic
import Mathlib.Algebra.Order.BigOperators.Ring.Finset
import Mathlib.Topology.Algebra.InfiniteSum.NatInt
import Mathlib.Topology.Algebra.Order.Field
import Mathlib.Topology.Order.MonotoneConvergence
/-!
# Infinite sum or product in an order
This file provides lemmas about the interaction of infinite sums and products and order operations.
-/
open Finset Filter Function
variable {ι κ α : Type*}
section Preorder
variable [Preorder α] [CommMonoid α] [TopologicalSpace α] {a c : α} {f : ι → α}
@[to_additive]
lemma hasProd_le_of_prod_le [ClosedIicTopology α]
(hf : HasProd f a) (h : ∀ s, ∏ i ∈ s, f i ≤ c) : a ≤ c :=
le_of_tendsto' hf h
@[to_additive]
theorem le_hasProd_of_le_prod [ClosedIciTopology α]
(hf : HasProd f a) (h : ∀ s, c ≤ ∏ i ∈ s, f i) : c ≤ a :=
ge_of_tendsto' hf h
@[to_additive]
protected theorem Multipliable.tprod_le_of_prod_range_le [ClosedIicTopology α] {f : ℕ → α}
(hf : Multipliable f) (h : ∀ n, ∏ i ∈ range n, f i ≤ c) : ∏' n, f n ≤ c :=
le_of_tendsto' hf.hasProd.tendsto_prod_nat h
@[deprecated (since := "2025-04-12")] alias tsum_le_of_sum_range_le :=
Summable.tsum_le_of_sum_range_le
@[to_additive existing, deprecated (since := "2025-04-12")] alias tprod_le_of_prod_range_le :=
Multipliable.tprod_le_of_prod_range_le
end Preorder
section OrderedCommMonoid
variable [CommMonoid α] [PartialOrder α] [IsOrderedMonoid α]
[TopologicalSpace α] [OrderClosedTopology α] {f g : ι → α}
{a a₁ a₂ : α}
@[to_additive]
theorem hasProd_le (h : ∀ i, f i ≤ g i) (hf : HasProd f a₁) (hg : HasProd g a₂) : a₁ ≤ a₂ :=
le_of_tendsto_of_tendsto' hf hg fun _ ↦ prod_le_prod' fun i _ ↦ h i
@[to_additive]
theorem hasProd_mono (hf : HasProd f a₁) (hg : HasProd g a₂) (h : f ≤ g) : a₁ ≤ a₂ :=
hasProd_le h hf hg
@[to_additive]
theorem hasProd_le_inj {g : κ → α} (e : ι → κ) (he : Injective e)
(hs : ∀ c, c ∉ Set.range e → 1 ≤ g c) (h : ∀ i, f i ≤ g (e i)) (hf : HasProd f a₁)
(hg : HasProd g a₂) : a₁ ≤ a₂ := by
rw [← hasProd_extend_one he] at hf
refine hasProd_le (fun c ↦ ?_) hf hg
obtain ⟨i, rfl⟩ | h := em (c ∈ Set.range e)
· rw [he.extend_apply]
exact h _
· rw [extend_apply' _ _ _ h]
exact hs _ h
@[to_additive]
protected theorem Multipliable.tprod_le_tprod_of_inj {g : κ → α} (e : ι → κ) (he : Injective e)
(hs : ∀ c, c ∉ Set.range e → 1 ≤ g c) (h : ∀ i, f i ≤ g (e i)) (hf : Multipliable f)
(hg : Multipliable g) : tprod f ≤ tprod g :=
hasProd_le_inj _ he hs h hf.hasProd hg.hasProd
@[deprecated (since := "2025-04-12")] alias tsum_le_tsum_of_inj := Summable.tsum_le_tsum_of_inj
@[to_additive existing, deprecated (since := "2025-04-12")] alias tprod_le_tprod_of_inj :=
Multipliable.tprod_le_tprod_of_inj
| @[to_additive]
protected lemma Multipliable.tprod_subtype_le {κ γ : Type*} [CommGroup γ] [PartialOrder γ]
[IsOrderedMonoid γ] [UniformSpace γ] [IsUniformGroup γ] [OrderClosedTopology γ]
[CompleteSpace γ] (f : κ → γ) (β : Set κ) (h : ∀ a : κ, 1 ≤ f a) (hf : Multipliable f) :
(∏' (b : β), f b) ≤ (∏' (a : κ), f a) := by
apply Multipliable.tprod_le_tprod_of_inj _
(Subtype.coe_injective)
(by simp only [Subtype.range_coe_subtype, Set.setOf_mem_eq, h, implies_true])
(by simp only [le_refl, Subtype.forall, implies_true])
(by apply hf.subtype)
| Mathlib/Topology/Algebra/InfiniteSum/Order.lean | 84 | 93 |
/-
Copyright (c) 2018 Andreas Swerdlow. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andreas Swerdlow, Kexing Ying
-/
import Mathlib.LinearAlgebra.BilinearForm.Hom
import Mathlib.LinearAlgebra.Dual.Lemmas
/-!
# Bilinear form
This file defines various properties of bilinear forms, including reflexivity, symmetry,
alternativity, adjoint, and non-degeneracy.
For orthogonality, see `Mathlib/LinearAlgebra/BilinearForm/Orthogonal.lean`.
## Notations
Given any term `B` of type `BilinForm`, due to a coercion, can use
the notation `B x y` to refer to the function field, ie. `B x y = B.bilin x y`.
In this file we use the following type variables:
- `M`, `M'`, ... are modules over the commutative semiring `R`,
- `M₁`, `M₁'`, ... are modules over the commutative ring `R₁`,
- `V`, ... is a vector space over the field `K`.
## References
* <https://en.wikipedia.org/wiki/Bilinear_form>
## Tags
Bilinear form,
-/
open LinearMap (BilinForm)
universe u v w
variable {R : Type*} {M : Type*} [CommSemiring R] [AddCommMonoid M] [Module R M]
variable {R₁ : Type*} {M₁ : Type*} [CommRing R₁] [AddCommGroup M₁] [Module R₁ M₁]
variable {V : Type*} {K : Type*} [Field K] [AddCommGroup V] [Module K V]
variable {M' : Type*} [AddCommMonoid M'] [Module R M']
variable {B : BilinForm R M} {B₁ : BilinForm R₁ M₁}
namespace LinearMap
namespace BilinForm
/-! ### Reflexivity, symmetry, and alternativity -/
/-- The proposition that a bilinear form is reflexive -/
def IsRefl (B : BilinForm R M) : Prop := LinearMap.IsRefl B
namespace IsRefl
theorem eq_zero (H : B.IsRefl) : ∀ {x y : M}, B x y = 0 → B y x = 0 := fun {x y} => H x y
protected theorem neg {B : BilinForm R₁ M₁} (hB : B.IsRefl) : (-B).IsRefl := fun x y =>
neg_eq_zero.mpr ∘ hB x y ∘ neg_eq_zero.mp
protected theorem smul {α} [Semiring α] [Module α R] [SMulCommClass R α R]
[NoZeroSMulDivisors α R] (a : α) {B : BilinForm R M} (hB : B.IsRefl) :
(a • B).IsRefl := fun _ _ h =>
(smul_eq_zero.mp h).elim (fun ha => smul_eq_zero_of_left ha _) fun hBz =>
smul_eq_zero_of_right _ (hB _ _ hBz)
protected theorem groupSMul {α} [Group α] [DistribMulAction α R] [SMulCommClass R α R] (a : α)
{B : BilinForm R M} (hB : B.IsRefl) : (a • B).IsRefl := fun x y =>
(smul_eq_zero_iff_eq _).mpr ∘ hB x y ∘ (smul_eq_zero_iff_eq _).mp
end IsRefl
@[simp]
theorem isRefl_zero : (0 : BilinForm R M).IsRefl := fun _ _ _ => rfl
@[simp]
theorem isRefl_neg {B : BilinForm R₁ M₁} : (-B).IsRefl ↔ B.IsRefl :=
⟨fun h => neg_neg B ▸ h.neg, IsRefl.neg⟩
/-- The proposition that a bilinear form is symmetric -/
def IsSymm (B : BilinForm R M) : Prop := LinearMap.IsSymm B
namespace IsSymm
protected theorem eq (H : B.IsSymm) (x y : M) : B x y = B y x :=
H x y
theorem isRefl (H : B.IsSymm) : B.IsRefl := fun x y H1 => H x y ▸ H1
protected theorem add {B₁ B₂ : BilinForm R M} (hB₁ : B₁.IsSymm) (hB₂ : B₂.IsSymm) :
(B₁ + B₂).IsSymm := fun x y => (congr_arg₂ (· + ·) (hB₁ x y) (hB₂ x y) :)
protected theorem sub {B₁ B₂ : BilinForm R₁ M₁} (hB₁ : B₁.IsSymm) (hB₂ : B₂.IsSymm) :
(B₁ - B₂).IsSymm := fun x y => (congr_arg₂ Sub.sub (hB₁ x y) (hB₂ x y) :)
protected theorem neg {B : BilinForm R₁ M₁} (hB : B.IsSymm) : (-B).IsSymm := fun x y =>
congr_arg Neg.neg (hB x y)
protected theorem smul {α} [Monoid α] [DistribMulAction α R] [SMulCommClass R α R] (a : α)
{B : BilinForm R M} (hB : B.IsSymm) : (a • B).IsSymm := fun x y =>
congr_arg (a • ·) (hB x y)
/-- The restriction of a symmetric bilinear form on a submodule is also symmetric. -/
theorem restrict {B : BilinForm R M} (b : B.IsSymm) (W : Submodule R M) :
(B.restrict W).IsSymm := fun x y => b x y
end IsSymm
@[simp]
theorem isSymm_zero : (0 : BilinForm R M).IsSymm := fun _ _ => rfl
@[simp]
theorem isSymm_neg {B : BilinForm R₁ M₁} : (-B).IsSymm ↔ B.IsSymm :=
⟨fun h => neg_neg B ▸ h.neg, IsSymm.neg⟩
theorem isSymm_iff_flip : B.IsSymm ↔ flipHom B = B :=
(forall₂_congr fun _ _ => by exact eq_comm).trans BilinForm.ext_iff.symm
/-- The proposition that a bilinear form is alternating -/
def IsAlt (B : BilinForm R M) : Prop := LinearMap.IsAlt B
namespace IsAlt
theorem self_eq_zero (H : B.IsAlt) (x : M) : B x x = 0 := LinearMap.IsAlt.self_eq_zero H x
theorem neg_eq (H : B₁.IsAlt) (x y : M₁) : -B₁ x y = B₁ y x := LinearMap.IsAlt.neg H x y
theorem isRefl (H : B₁.IsAlt) : B₁.IsRefl := LinearMap.IsAlt.isRefl H
theorem eq_of_add_add_eq_zero [IsCancelAdd R] {a b c : M} (H : B.IsAlt) (hAdd : a + b + c = 0) :
B a b = B b c := LinearMap.IsAlt.eq_of_add_add_eq_zero H hAdd
protected theorem add {B₁ B₂ : BilinForm R M} (hB₁ : B₁.IsAlt) (hB₂ : B₂.IsAlt) : (B₁ + B₂).IsAlt :=
fun x => (congr_arg₂ (· + ·) (hB₁ x) (hB₂ x) :).trans <| add_zero _
protected theorem sub {B₁ B₂ : BilinForm R₁ M₁} (hB₁ : B₁.IsAlt) (hB₂ : B₂.IsAlt) :
(B₁ - B₂).IsAlt := fun x => (congr_arg₂ Sub.sub (hB₁ x) (hB₂ x)).trans <| sub_zero _
protected theorem neg {B : BilinForm R₁ M₁} (hB : B.IsAlt) : (-B).IsAlt := fun x =>
neg_eq_zero.mpr <| hB x
protected theorem smul {α} [Monoid α] [DistribMulAction α R] [SMulCommClass R α R] (a : α)
{B : BilinForm R M} (hB : B.IsAlt) : (a • B).IsAlt := fun x =>
(congr_arg (a • ·) (hB x)).trans <| smul_zero _
end IsAlt
@[simp]
theorem isAlt_zero : (0 : BilinForm R M).IsAlt := fun _ => rfl
@[simp]
theorem isAlt_neg {B : BilinForm R₁ M₁} : (-B).IsAlt ↔ B.IsAlt :=
⟨fun h => neg_neg B ▸ h.neg, IsAlt.neg⟩
end BilinForm
namespace BilinForm
/-- A nondegenerate bilinear form is a bilinear form such that the only element that is orthogonal
to every other element is `0`; i.e., for all nonzero `m` in `M`, there exists `n` in `M` with
`B m n ≠ 0`.
Note that for general (neither symmetric nor antisymmetric) bilinear forms this definition has a
chirality; in addition to this "left" nondegeneracy condition one could define a "right"
nondegeneracy condition that in the situation described, `B n m ≠ 0`. This variant definition is
not currently provided in mathlib. In finite dimension either definition implies the other. -/
def Nondegenerate (B : BilinForm R M) : Prop :=
∀ m : M, (∀ n : M, B m n = 0) → m = 0
section
variable (R M)
/-- In a non-trivial module, zero is not non-degenerate. -/
theorem not_nondegenerate_zero [Nontrivial M] : ¬(0 : BilinForm R M).Nondegenerate :=
let ⟨m, hm⟩ := exists_ne (0 : M)
fun h => hm (h m fun _ => rfl)
end
variable {M' : Type*}
variable [AddCommMonoid M'] [Module R M']
theorem Nondegenerate.ne_zero [Nontrivial M] {B : BilinForm R M} (h : B.Nondegenerate) : B ≠ 0 :=
fun h0 => not_nondegenerate_zero R M <| h0 ▸ h
theorem Nondegenerate.congr {B : BilinForm R M} (e : M ≃ₗ[R] M') (h : B.Nondegenerate) :
(congr e B).Nondegenerate := fun m hm =>
e.symm.map_eq_zero_iff.1 <|
h (e.symm m) fun n => (congr_arg _ (e.symm_apply_apply n).symm).trans (hm (e n))
@[simp]
theorem nondegenerate_congr_iff {B : BilinForm R M} (e : M ≃ₗ[R] M') :
(congr e B).Nondegenerate ↔ B.Nondegenerate :=
⟨fun h => by
convert h.congr e.symm
rw [congr_congr, e.self_trans_symm, congr_refl, LinearEquiv.refl_apply], Nondegenerate.congr e⟩
/-- A bilinear form is nondegenerate if and only if it has a trivial kernel. -/
theorem nondegenerate_iff_ker_eq_bot {B : BilinForm R M} :
B.Nondegenerate ↔ LinearMap.ker B = ⊥ := by
rw [LinearMap.ker_eq_bot']
simp [Nondegenerate, LinearMap.ext_iff]
theorem Nondegenerate.ker_eq_bot {B : BilinForm R M} (h : B.Nondegenerate) :
LinearMap.ker B = ⊥ := nondegenerate_iff_ker_eq_bot.mp h
theorem compLeft_injective (B : BilinForm R₁ M₁) (b : B.Nondegenerate) :
Function.Injective B.compLeft := fun φ ψ h => by
ext w
refine eq_of_sub_eq_zero (b _ ?_)
intro v
rw [sub_left, ← compLeft_apply, ← compLeft_apply, ← h, sub_self]
theorem isAdjointPair_unique_of_nondegenerate (B : BilinForm R₁ M₁) (b : B.Nondegenerate)
(φ ψ₁ ψ₂ : M₁ →ₗ[R₁] M₁) (hψ₁ : IsAdjointPair B B ψ₁ φ) (hψ₂ : IsAdjointPair B B ψ₂ φ) :
ψ₁ = ψ₂ :=
B.compLeft_injective b <| ext fun v w => by rw [compLeft_apply, compLeft_apply, hψ₁, hψ₂]
section FiniteDimensional
variable [FiniteDimensional K V]
/-- Given a nondegenerate bilinear form `B` on a finite-dimensional vector space, `B.toDual` is
the linear equivalence between a vector space and its dual. -/
noncomputable def toDual (B : BilinForm K V) (b : B.Nondegenerate) : V ≃ₗ[K] Module.Dual K V :=
B.linearEquivOfInjective (LinearMap.ker_eq_bot.mp <| b.ker_eq_bot)
Subspace.dual_finrank_eq.symm
theorem toDual_def {B : BilinForm K V} (b : B.SeparatingLeft) {m n : V} : B.toDual b m n = B m n :=
rfl
@[simp]
lemma apply_toDual_symm_apply {B : BilinForm K V} {hB : B.Nondegenerate}
(f : Module.Dual K V) (v : V) :
B ((B.toDual hB).symm f) v = f v := by
change B.toDual hB ((B.toDual hB).symm f) v = f v
simp only [LinearEquiv.apply_symm_apply]
lemma Nondegenerate.flip {B : BilinForm K V} (hB : B.Nondegenerate) :
B.flip.Nondegenerate := by
intro x hx
apply (Module.evalEquiv K V).injective
ext f
obtain ⟨y, rfl⟩ := (B.toDual hB).surjective f
simpa using hx y
lemma nonDegenerateFlip_iff {B : BilinForm K V} :
B.flip.Nondegenerate ↔ B.Nondegenerate := ⟨Nondegenerate.flip, Nondegenerate.flip⟩
end FiniteDimensional
section DualBasis
variable {ι : Type*} [DecidableEq ι] [Finite ι]
/-- The `B`-dual basis `B.dualBasis hB b` to a finite basis `b` satisfies
`B (B.dualBasis hB b i) (b j) = B (b i) (B.dualBasis hB b j) = if i = j then 1 else 0`,
where `B` is a nondegenerate (symmetric) bilinear form and `b` is a finite basis. -/
noncomputable def dualBasis (B : BilinForm K V) (hB : B.Nondegenerate) (b : Basis ι K V) :
Basis ι K V :=
haveI := FiniteDimensional.of_fintype_basis b
b.dualBasis.map (B.toDual hB).symm
@[simp]
theorem dualBasis_repr_apply
(B : BilinForm K V) (hB : B.Nondegenerate) (b : Basis ι K V) (x i) :
(B.dualBasis hB b).repr x i = B x (b i) := by
#adaptation_note /-- https://github.com/leanprover/lean4/pull/4814
we did not need the `@` in front of `toDual_def` in the `rw`.
I'm confused! -/
rw [dualBasis, Basis.map_repr, LinearEquiv.symm_symm, LinearEquiv.trans_apply,
Basis.dualBasis_repr, @toDual_def]
theorem apply_dualBasis_left (B : BilinForm K V) (hB : B.Nondegenerate) (b : Basis ι K V) (i j) :
B (B.dualBasis hB b i) (b j) = if j = i then 1 else 0 := by
have := FiniteDimensional.of_fintype_basis b
rw [dualBasis, Basis.map_apply, Basis.coe_dualBasis, ← toDual_def hB,
LinearEquiv.apply_symm_apply, Basis.coord_apply, Basis.repr_self, Finsupp.single_apply]
theorem apply_dualBasis_right (B : BilinForm K V) (hB : B.Nondegenerate) (sym : B.IsSymm)
(b : Basis ι K V) (i j) : B (b i) (B.dualBasis hB b j) = if i = j then 1 else 0 := by
rw [sym.eq, apply_dualBasis_left]
@[simp]
lemma dualBasis_dualBasis_flip [FiniteDimensional K V]
(B : BilinForm K V) (hB : B.Nondegenerate) {ι : Type*}
[Finite ι] [DecidableEq ι] (b : Basis ι K V) :
B.dualBasis hB (B.flip.dualBasis hB.flip b) = b := by
ext i
refine LinearMap.ker_eq_bot.mp hB.ker_eq_bot ((B.flip.dualBasis hB.flip b).ext (fun j ↦ ?_))
simp_rw [apply_dualBasis_left, ← B.flip_apply, apply_dualBasis_left, @eq_comm _ i j]
@[simp]
lemma dualBasis_flip_dualBasis (B : BilinForm K V) (hB : B.Nondegenerate) {ι}
[Finite ι] [DecidableEq ι] [FiniteDimensional K V] (b : Basis ι K V) :
B.flip.dualBasis hB.flip (B.dualBasis hB b) = b :=
dualBasis_dualBasis_flip _ hB.flip b
@[simp]
lemma dualBasis_dualBasis (B : BilinForm K V) (hB : B.Nondegenerate) (hB' : B.IsSymm) {ι}
[Finite ι] [DecidableEq ι] [FiniteDimensional K V] (b : Basis ι K V) :
B.dualBasis hB (B.dualBasis hB b) = b := by
convert dualBasis_dualBasis_flip _ hB.flip b
rwa [eq_comm, ← isSymm_iff_flip]
end DualBasis
section LinearAdjoints
variable [FiniteDimensional K V]
/-- Given bilinear forms `B₁, B₂` where `B₂` is nondegenerate, `symmCompOfNondegenerate`
is the linear map `B₂ ∘ B₁`. -/
noncomputable def symmCompOfNondegenerate (B₁ B₂ : BilinForm K V) (b₂ : B₂.Nondegenerate) :
V →ₗ[K] V :=
(B₂.toDual b₂).symm.toLinearMap.comp B₁
theorem comp_symmCompOfNondegenerate_apply (B₁ : BilinForm K V) {B₂ : BilinForm K V}
(b₂ : B₂.Nondegenerate) (v : V) :
B₂ (B₁.symmCompOfNondegenerate B₂ b₂ v) = B₁ v := by
rw [symmCompOfNondegenerate]
simp only [coe_comp, LinearEquiv.coe_coe, Function.comp_apply, DFunLike.coe_fn_eq]
erw [LinearEquiv.apply_symm_apply (B₂.toDual b₂)]
@[simp]
theorem symmCompOfNondegenerate_left_apply (B₁ : BilinForm K V) {B₂ : BilinForm K V}
(b₂ : B₂.Nondegenerate) (v w : V) : B₂ (symmCompOfNondegenerate B₁ B₂ b₂ w) v = B₁ w v := by
conv_lhs => rw [comp_symmCompOfNondegenerate_apply]
/-- Given the nondegenerate bilinear form `B` and the linear map `φ`,
`leftAdjointOfNondegenerate` provides the left adjoint of `φ` with respect to `B`.
The lemma proving this property is `BilinForm.isAdjointPairLeftAdjointOfNondegenerate`. -/
noncomputable def leftAdjointOfNondegenerate (B : BilinForm K V) (b : B.Nondegenerate)
(φ : V →ₗ[K] V) : V →ₗ[K] V :=
symmCompOfNondegenerate (B.compRight φ) B b
theorem isAdjointPairLeftAdjointOfNondegenerate (B : BilinForm K V) (b : B.Nondegenerate)
(φ : V →ₗ[K] V) : IsAdjointPair B B (B.leftAdjointOfNondegenerate b φ) φ := fun x y =>
(B.compRight φ).symmCompOfNondegenerate_left_apply b y x
/-- Given the nondegenerate bilinear form `B`, the linear map `φ` has a unique left adjoint given by
`BilinForm.leftAdjointOfNondegenerate`. -/
theorem isAdjointPair_iff_eq_of_nondegenerate (B : BilinForm K V) (b : B.Nondegenerate)
(ψ φ : V →ₗ[K] V) : IsAdjointPair B B ψ φ ↔ ψ = B.leftAdjointOfNondegenerate b φ :=
⟨fun h =>
B.isAdjointPair_unique_of_nondegenerate b φ ψ _ h
(isAdjointPairLeftAdjointOfNondegenerate _ _ _),
fun h => h.symm ▸ isAdjointPairLeftAdjointOfNondegenerate _ _ _⟩
end LinearAdjoints
end BilinForm
end LinearMap
| Mathlib/LinearAlgebra/BilinearForm/Properties.lean | 393 | 403 | |
/-
Copyright (c) 2020 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp
-/
import Mathlib.Algebra.Algebra.Spectrum.Basic
import Mathlib.Algebra.Module.LinearMap.Basic
import Mathlib.LinearAlgebra.FiniteDimensional.Lemmas
import Mathlib.LinearAlgebra.GeneralLinearGroup
import Mathlib.RingTheory.Nilpotent.Basic
import Mathlib.RingTheory.Nilpotent.Defs
import Mathlib.RingTheory.Nilpotent.Lemmas
import Mathlib.Tactic.Peel
/-!
# Eigenvectors and eigenvalues
This file defines eigenspaces, eigenvalues, and eigenvalues, as well as their generalized
counterparts. We follow Axler's approach [axler2015] because it allows us to derive many properties
without choosing a basis and without using matrices.
An eigenspace of a linear map `f` for a scalar `μ` is the kernel of the map `(f - μ • id)`. The
nonzero elements of an eigenspace are eigenvectors `x`. They have the property `f x = μ • x`. If
there are eigenvectors for a scalar `μ`, the scalar `μ` is called an eigenvalue.
There is no consensus in the literature whether `0` is an eigenvector. Our definition of
`HasEigenvector` permits only nonzero vectors. For an eigenvector `x` that may also be `0`, we
write `x ∈ f.eigenspace μ`.
A generalized eigenspace of a linear map `f` for a natural number `k` and a scalar `μ` is the kernel
of the map `(f - μ • id) ^ k`. The nonzero elements of a generalized eigenspace are generalized
eigenvectors `x`. If there are generalized eigenvectors for a natural number `k` and a scalar `μ`,
the scalar `μ` is called a generalized eigenvalue.
The fact that the eigenvalues are the roots of the minimal polynomial is proved in
`LinearAlgebra.Eigenspace.Minpoly`.
The existence of eigenvalues over an algebraically closed field
(and the fact that the generalized eigenspaces then span) is deferred to
`LinearAlgebra.Eigenspace.IsAlgClosed`.
## References
* [Sheldon Axler, *Linear Algebra Done Right*][axler2015]
* https://en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors
## Tags
eigenspace, eigenvector, eigenvalue, eigen
-/
universe u v w
namespace Module
namespace End
open Module Set
variable {K R : Type v} {V M : Type w} [CommRing R] [AddCommGroup M] [Module R M] [Field K]
[AddCommGroup V] [Module K V]
/-- The submodule `genEigenspace f μ k` for a linear map `f`, a scalar `μ`,
and a number `k : ℕ∞` is the kernel of `(f - μ • id) ^ k` if `k` is a natural number
(see Def 8.10 of [axler2015]), or the union of all these kernels if `k = ∞`.
A generalized eigenspace for some exponent `k` is contained in
the generalized eigenspace for exponents larger than `k`. -/
def genEigenspace (f : End R M) (μ : R) : ℕ∞ →o Submodule R M where
toFun k := ⨆ l : ℕ, ⨆ _ : l ≤ k, LinearMap.ker ((f - μ • 1) ^ l)
monotone' _ _ hkl := biSup_mono fun _ hi ↦ hi.trans hkl
lemma mem_genEigenspace {f : End R M} {μ : R} {k : ℕ∞} {x : M} :
x ∈ f.genEigenspace μ k ↔ ∃ l : ℕ, l ≤ k ∧ x ∈ LinearMap.ker ((f - μ • 1) ^ l) := by
have : Nonempty {l : ℕ // l ≤ k} := ⟨⟨0, zero_le _⟩⟩
have : Directed (ι := { i : ℕ // i ≤ k }) (· ≤ ·) fun i ↦ LinearMap.ker ((f - μ • 1) ^ (i : ℕ)) :=
Monotone.directed_le fun m n h ↦ by simpa using (f - μ • 1).iterateKer.monotone h
simp_rw [genEigenspace, OrderHom.coe_mk, LinearMap.mem_ker, iSup_subtype',
Submodule.mem_iSup_of_directed _ this, LinearMap.mem_ker, Subtype.exists, exists_prop]
lemma genEigenspace_directed {f : End R M} {μ : R} {k : ℕ∞} :
Directed (· ≤ ·) (fun l : {l : ℕ // l ≤ k} ↦ f.genEigenspace μ l) := by
have aux : Monotone ((↑) : {l : ℕ // l ≤ k} → ℕ∞) := fun x y h ↦ by simpa using h
exact ((genEigenspace f μ).monotone.comp aux).directed_le
lemma mem_genEigenspace_nat {f : End R M} {μ : R} {k : ℕ} {x : M} :
x ∈ f.genEigenspace μ k ↔ x ∈ LinearMap.ker ((f - μ • 1) ^ k) := by
rw [mem_genEigenspace]
constructor
· rintro ⟨l, hl, hx⟩
simp only [Nat.cast_le] at hl
exact (f - μ • 1).iterateKer.monotone hl hx
· intro hx
exact ⟨k, le_rfl, hx⟩
lemma mem_genEigenspace_top {f : End R M} {μ : R} {x : M} :
x ∈ f.genEigenspace μ ⊤ ↔ ∃ k : ℕ, x ∈ LinearMap.ker ((f - μ • 1) ^ k) := by
simp [mem_genEigenspace]
lemma genEigenspace_nat {f : End R M} {μ : R} {k : ℕ} :
f.genEigenspace μ k = LinearMap.ker ((f - μ • 1) ^ k) := by
ext; simp [mem_genEigenspace_nat]
lemma genEigenspace_eq_iSup_genEigenspace_nat (f : End R M) (μ : R) (k : ℕ∞) :
f.genEigenspace μ k = ⨆ l : {l : ℕ // l ≤ k}, f.genEigenspace μ l := by
simp_rw [genEigenspace_nat, genEigenspace, OrderHom.coe_mk, iSup_subtype]
lemma genEigenspace_top (f : End R M) (μ : R) :
f.genEigenspace μ ⊤ = ⨆ k : ℕ, f.genEigenspace μ k := by
rw [genEigenspace_eq_iSup_genEigenspace_nat, iSup_subtype]
simp only [le_top, iSup_pos, OrderHom.coe_mk]
lemma genEigenspace_one {f : End R M} {μ : R} :
f.genEigenspace μ 1 = LinearMap.ker (f - μ • 1) := by
rw [← Nat.cast_one, genEigenspace_nat, pow_one]
@[simp]
lemma mem_genEigenspace_one {f : End R M} {μ : R} {x : M} :
x ∈ f.genEigenspace μ 1 ↔ f x = μ • x := by
rw [genEigenspace_one, LinearMap.mem_ker, LinearMap.sub_apply,
sub_eq_zero, LinearMap.smul_apply, Module.End.one_apply]
-- `simp` can prove this using `genEigenspace_zero`
lemma mem_genEigenspace_zero {f : End R M} {μ : R} {x : M} :
x ∈ f.genEigenspace μ 0 ↔ x = 0 := by
rw [← Nat.cast_zero, mem_genEigenspace_nat, pow_zero, LinearMap.mem_ker, Module.End.one_apply]
@[simp]
lemma genEigenspace_zero {f : End R M} {μ : R} :
f.genEigenspace μ 0 = ⊥ := by
ext; apply mem_genEigenspace_zero
@[simp]
lemma genEigenspace_zero_nat (f : End R M) (k : ℕ) :
f.genEigenspace 0 k = LinearMap.ker (f ^ k) := by
ext; simp [mem_genEigenspace_nat]
/-- Let `M` be an `R`-module, and `f` an `R`-linear endomorphism of `M`,
and let `μ : R` and `k : ℕ∞` be given.
Then `x : M` satisfies `HasUnifEigenvector f μ k x` if
`x ∈ f.genEigenspace μ k` and `x ≠ 0`.
For `k = 1`, this means that `x` is an eigenvector of `f` with eigenvalue `μ`. -/
def HasUnifEigenvector (f : End R M) (μ : R) (k : ℕ∞) (x : M) : Prop :=
x ∈ f.genEigenspace μ k ∧ x ≠ 0
/-- Let `M` be an `R`-module, and `f` an `R`-linear endomorphism of `M`.
Then `μ : R` and `k : ℕ∞` satisfy `HasUnifEigenvalue f μ k` if
`f.genEigenspace μ k ≠ ⊥`.
For `k = 1`, this means that `μ` is an eigenvalue of `f`. -/
def HasUnifEigenvalue (f : End R M) (μ : R) (k : ℕ∞) : Prop :=
f.genEigenspace μ k ≠ ⊥
/-- Let `M` be an `R`-module, and `f` an `R`-linear endomorphism of `M`.
For `k : ℕ∞`, we define `UnifEigenvalues f k` to be the type of all
`μ : R` that satisfy `f.HasUnifEigenvalue μ k`.
For `k = 1` this is the type of all eigenvalues of `f`. -/
def UnifEigenvalues (f : End R M) (k : ℕ∞) : Type _ :=
{ μ : R // f.HasUnifEigenvalue μ k }
/-- The underlying value of a bundled eigenvalue. -/
@[coe]
def UnifEigenvalues.val (f : Module.End R M) (k : ℕ∞) : UnifEigenvalues f k → R := Subtype.val
instance UnifEigenvalues.instCoeOut {f : Module.End R M} (k : ℕ∞) :
CoeOut (UnifEigenvalues f k) R where
coe := UnifEigenvalues.val f k
instance UnivEigenvalues.instDecidableEq [DecidableEq R] (f : Module.End R M) (k : ℕ∞) :
DecidableEq (UnifEigenvalues f k) :=
inferInstanceAs (DecidableEq (Subtype (fun x : R ↦ f.HasUnifEigenvalue x k)))
lemma HasUnifEigenvector.hasUnifEigenvalue {f : End R M} {μ : R} {k : ℕ∞} {x : M}
(h : f.HasUnifEigenvector μ k x) : f.HasUnifEigenvalue μ k := by
rw [HasUnifEigenvalue, Submodule.ne_bot_iff]
use x; exact h
lemma HasUnifEigenvector.apply_eq_smul {f : End R M} {μ : R} {x : M}
(hx : f.HasUnifEigenvector μ 1 x) : f x = μ • x :=
mem_genEigenspace_one.mp hx.1
lemma HasUnifEigenvector.pow_apply {f : End R M} {μ : R} {v : M} (hv : f.HasUnifEigenvector μ 1 v)
(n : ℕ) : (f ^ n) v = μ ^ n • v := by
induction n <;> simp [*, pow_succ f, hv.apply_eq_smul, smul_smul, pow_succ' μ]
theorem HasUnifEigenvalue.exists_hasUnifEigenvector
{f : End R M} {μ : R} {k : ℕ∞} (hμ : f.HasUnifEigenvalue μ k) :
∃ v, f.HasUnifEigenvector μ k v :=
Submodule.exists_mem_ne_zero_of_ne_bot hμ
lemma HasUnifEigenvalue.pow {f : End R M} {μ : R} (h : f.HasUnifEigenvalue μ 1) (n : ℕ) :
(f ^ n).HasUnifEigenvalue (μ ^ n) 1 := by
rw [HasUnifEigenvalue, Submodule.ne_bot_iff]
obtain ⟨m : M, hm⟩ := h.exists_hasUnifEigenvector
exact ⟨m, by simpa [mem_genEigenspace_one] using hm.pow_apply n, hm.2⟩
/-- A nilpotent endomorphism has nilpotent eigenvalues.
See also `LinearMap.isNilpotent_trace_of_isNilpotent`. -/
lemma HasUnifEigenvalue.isNilpotent_of_isNilpotent [NoZeroSMulDivisors R M] {f : End R M}
(hfn : IsNilpotent f) {μ : R} (hf : f.HasUnifEigenvalue μ 1) :
IsNilpotent μ := by
obtain ⟨m : M, hm⟩ := hf.exists_hasUnifEigenvector
obtain ⟨n : ℕ, hn : f ^ n = 0⟩ := hfn
exact ⟨n, by simpa [hn, hm.2, eq_comm (a := (0 : M))] using hm.pow_apply n⟩
lemma HasUnifEigenvalue.mem_spectrum {f : End R M} {μ : R} (hμ : HasUnifEigenvalue f μ 1) :
μ ∈ spectrum R f := by
refine spectrum.mem_iff.mpr fun h_unit ↦ ?_
set f' := LinearMap.GeneralLinearGroup.toLinearEquiv h_unit.unit
rcases hμ.exists_hasUnifEigenvector with ⟨v, hv⟩
refine hv.2 ((LinearMap.ker_eq_bot'.mp f'.ker) v (?_ : μ • v - f v = 0))
rw [hv.apply_eq_smul, sub_self]
lemma hasUnifEigenvalue_iff_mem_spectrum [FiniteDimensional K V] {f : End K V} {μ : K} :
f.HasUnifEigenvalue μ 1 ↔ μ ∈ spectrum K f := by
rw [spectrum.mem_iff, IsUnit.sub_iff, LinearMap.isUnit_iff_ker_eq_bot,
HasUnifEigenvalue, genEigenspace_one, ne_eq, not_iff_not]
simp [Submodule.ext_iff, LinearMap.mem_ker]
alias ⟨_, HasUnifEigenvalue.of_mem_spectrum⟩ := hasUnifEigenvalue_iff_mem_spectrum
lemma genEigenspace_div (f : End K V) (a b : K) (hb : b ≠ 0) :
genEigenspace f (a / b) 1 = LinearMap.ker (b • f - a • 1) :=
calc
genEigenspace f (a / b) 1 = genEigenspace f (b⁻¹ * a) 1 := by rw [div_eq_mul_inv, mul_comm]
_ = LinearMap.ker (f - (b⁻¹ * a) • 1) := by rw [genEigenspace_one]
_ = LinearMap.ker (f - b⁻¹ • a • 1) := by rw [smul_smul]
_ = LinearMap.ker (b • (f - b⁻¹ • a • 1)) := by rw [LinearMap.ker_smul _ b hb]
_ = LinearMap.ker (b • f - a • 1) := by rw [smul_sub, smul_inv_smul₀ hb]
/-- The generalized eigenrange for a linear map `f`, a scalar `μ`, and an exponent `k ∈ ℕ∞`
is the range of `(f - μ • id) ^ k` if `k` is a natural number,
or the infimum of these ranges if `k = ∞`. -/
def genEigenrange (f : End R M) (μ : R) (k : ℕ∞) : Submodule R M :=
⨅ l : ℕ, ⨅ (_ : l ≤ k), LinearMap.range ((f - μ • 1) ^ l)
lemma genEigenrange_nat {f : End R M} {μ : R} {k : ℕ} :
f.genEigenrange μ k = LinearMap.range ((f - μ • 1) ^ k) := by
ext x
simp only [genEigenrange, Nat.cast_le, Submodule.mem_iInf, LinearMap.mem_range]
constructor
· intro h
exact h _ le_rfl
· rintro ⟨x, rfl⟩ i hi
have : k = i + (k - i) := by omega
rw [this, pow_add]
exact ⟨_, rfl⟩
/-- The exponent of a generalized eigenvalue is never 0. -/
lemma HasUnifEigenvalue.exp_ne_zero {f : End R M} {μ : R} {k : ℕ}
(h : f.HasUnifEigenvalue μ k) : k ≠ 0 := by
rintro rfl
simp [HasUnifEigenvalue, Nat.cast_zero, genEigenspace_zero] at h
/-- If there exists a natural number `k` such that the kernel of `(f - μ • id) ^ k` is the
maximal generalized eigenspace, then this value is the least such `k`. If not, this value is not
meaningful. -/
noncomputable def maxUnifEigenspaceIndex (f : End R M) (μ : R) :=
monotonicSequenceLimitIndex <| (f.genEigenspace μ).comp <| WithTop.coeOrderHom.toOrderHom
/-- For an endomorphism of a Noetherian module, the maximal eigenspace is always of the form kernel
`(f - μ • id) ^ k` for some `k`. -/
lemma genEigenspace_top_eq_maxUnifEigenspaceIndex [IsNoetherian R M] (f : End R M) (μ : R) :
genEigenspace f μ ⊤ = f.genEigenspace μ (maxUnifEigenspaceIndex f μ) := by
have := WellFoundedGT.iSup_eq_monotonicSequenceLimit <|
(f.genEigenspace μ).comp <| WithTop.coeOrderHom.toOrderHom
convert this using 1
simp only [genEigenspace, OrderHom.coe_mk, le_top, iSup_pos, OrderHom.comp_coe,
Function.comp_def]
rw [iSup_prod', iSup_subtype', ← sSup_range, ← sSup_range]
congr
aesop
lemma genEigenspace_le_genEigenspace_maxUnifEigenspaceIndex [IsNoetherian R M] (f : End R M)
(μ : R) (k : ℕ∞) :
f.genEigenspace μ k ≤ f.genEigenspace μ (maxUnifEigenspaceIndex f μ) := by
rw [← genEigenspace_top_eq_maxUnifEigenspaceIndex]
exact (f.genEigenspace μ).monotone le_top
/-- Generalized eigenspaces for exponents at least `finrank K V` are equal to each other. -/
theorem genEigenspace_eq_genEigenspace_maxUnifEigenspaceIndex_of_le [IsNoetherian R M]
(f : End R M) (μ : R) {k : ℕ} (hk : maxUnifEigenspaceIndex f μ ≤ k) :
f.genEigenspace μ k = f.genEigenspace μ (maxUnifEigenspaceIndex f μ) :=
le_antisymm
(genEigenspace_le_genEigenspace_maxUnifEigenspaceIndex _ _ _)
((f.genEigenspace μ).monotone <| by simpa using hk)
/-- A generalized eigenvalue for some exponent `k` is also
a generalized eigenvalue for exponents larger than `k`. -/
lemma HasUnifEigenvalue.le {f : End R M} {μ : R} {k m : ℕ∞}
(hm : k ≤ m) (hk : f.HasUnifEigenvalue μ k) :
f.HasUnifEigenvalue μ m := by
unfold HasUnifEigenvalue at *
contrapose! hk
rw [← le_bot_iff, ← hk]
exact (f.genEigenspace _).monotone hm
/-- A generalized eigenvalue for some exponent `k` is also
a generalized eigenvalue for positive exponents. -/
lemma HasUnifEigenvalue.lt {f : End R M} {μ : R} {k m : ℕ∞}
(hm : 0 < m) (hk : f.HasUnifEigenvalue μ k) :
f.HasUnifEigenvalue μ m := by
apply HasUnifEigenvalue.le (k := 1) (Order.one_le_iff_pos.mpr hm)
intro contra; apply hk
rw [genEigenspace_one, LinearMap.ker_eq_bot] at contra
rw [eq_bot_iff]
intro x hx
rw [mem_genEigenspace] at hx
rcases hx with ⟨l, -, hx⟩
rwa [LinearMap.ker_eq_bot.mpr] at hx
rw [Module.End.coe_pow (f - μ • 1) l]
exact Function.Injective.iterate contra l
/-- Generalized eigenvalues are actually just eigenvalues. -/
@[simp]
lemma hasUnifEigenvalue_iff_hasUnifEigenvalue_one {f : End R M} {μ : R} {k : ℕ∞} (hk : 0 < k) :
f.HasUnifEigenvalue μ k ↔ f.HasUnifEigenvalue μ 1 :=
⟨HasUnifEigenvalue.lt zero_lt_one, HasUnifEigenvalue.lt hk⟩
lemma maxUnifEigenspaceIndex_le_finrank [FiniteDimensional K V] (f : End K V) (μ : K) :
maxUnifEigenspaceIndex f μ ≤ finrank K V := by
apply Nat.sInf_le
intro n hn
apply le_antisymm
· exact (f.genEigenspace μ).monotone <| WithTop.coeOrderHom.monotone hn
· show (f.genEigenspace μ) n ≤ (f.genEigenspace μ) (finrank K V)
rw [genEigenspace_nat, genEigenspace_nat]
apply ker_pow_le_ker_pow_finrank
/-- Every generalized eigenvector is a generalized eigenvector for exponent `finrank K V`.
(Lemma 8.11 of [axler2015]) -/
lemma genEigenspace_le_genEigenspace_finrank [FiniteDimensional K V] (f : End K V)
(μ : K) (k : ℕ∞) : f.genEigenspace μ k ≤ f.genEigenspace μ (finrank K V) := by
calc f.genEigenspace μ k
≤ f.genEigenspace μ ⊤ := (f.genEigenspace _).monotone le_top
_ ≤ f.genEigenspace μ (finrank K V) := by
rw [genEigenspace_top_eq_maxUnifEigenspaceIndex]
exact (f.genEigenspace _).monotone <| by simpa using maxUnifEigenspaceIndex_le_finrank f μ
/-- Generalized eigenspaces for exponents at least `finrank K V` are equal to each other. -/
theorem genEigenspace_eq_genEigenspace_finrank_of_le [FiniteDimensional K V]
(f : End K V) (μ : K) {k : ℕ} (hk : finrank K V ≤ k) :
f.genEigenspace μ k = f.genEigenspace μ (finrank K V) :=
le_antisymm
(genEigenspace_le_genEigenspace_finrank _ _ _)
((f.genEigenspace μ).monotone <| by simpa using hk)
lemma mapsTo_genEigenspace_of_comm {f g : End R M} (h : Commute f g) (μ : R) (k : ℕ∞) :
MapsTo g (f.genEigenspace μ k) (f.genEigenspace μ k) := by
intro x hx
simp only [SetLike.mem_coe, mem_genEigenspace, LinearMap.mem_ker] at hx ⊢
rcases hx with ⟨l, hl, hx⟩
replace h : Commute ((f - μ • (1 : End R M)) ^ l) g :=
(h.sub_left <| Algebra.commute_algebraMap_left μ g).pow_left l
use l, hl
rw [← LinearMap.comp_apply, ← Module.End.mul_eq_comp, h.eq, Module.End.mul_eq_comp,
LinearMap.comp_apply, hx, map_zero]
/-- The restriction of `f - μ • 1` to the `k`-fold generalized `μ`-eigenspace is nilpotent. -/
lemma isNilpotent_restrict_genEigenspace_nat (f : End R M) (μ : R) (k : ℕ)
(h : MapsTo (f - μ • (1 : End R M))
(f.genEigenspace μ k) (f.genEigenspace μ k) :=
mapsTo_genEigenspace_of_comm (Algebra.mul_sub_algebraMap_commutes f μ) μ k) :
IsNilpotent ((f - μ • 1).restrict h) := by
use k
ext ⟨x, hx⟩
rw [mem_genEigenspace_nat] at hx
rw [LinearMap.zero_apply, ZeroMemClass.coe_zero, ZeroMemClass.coe_eq_zero,
Module.End.pow_restrict, LinearMap.restrict_apply]
ext
| simpa
/-- The restriction of `f - μ • 1` to the generalized `μ`-eigenspace is nilpotent. -/
lemma isNilpotent_restrict_genEigenspace_top [IsNoetherian R M] (f : End R M) (μ : R)
(h : MapsTo (f - μ • (1 : End R M))
(f.genEigenspace μ ⊤) (f.genEigenspace μ ⊤) :=
| Mathlib/LinearAlgebra/Eigenspace/Basic.lean | 374 | 379 |
/-
Copyright (c) 2021 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Algebra.GroupWithZero.Indicator
import Mathlib.Topology.Piecewise
import Mathlib.Topology.Instances.ENNReal.Lemmas
/-!
# Semicontinuous maps
A function `f` from a topological space `α` to an ordered space `β` is lower semicontinuous at a
point `x` if, for any `y < f x`, for any `x'` close enough to `x`, one has `f x' > y`. In other
words, `f` can jump up, but it can not jump down.
Upper semicontinuous functions are defined similarly.
This file introduces these notions, and a basic API around them mimicking the API for continuous
functions.
## Main definitions and results
We introduce 4 definitions related to lower semicontinuity:
* `LowerSemicontinuousWithinAt f s x`
* `LowerSemicontinuousAt f x`
* `LowerSemicontinuousOn f s`
* `LowerSemicontinuous f`
We build a basic API using dot notation around these notions, and we prove that
* constant functions are lower semicontinuous;
* `indicator s (fun _ ↦ y)` is lower semicontinuous when `s` is open and `0 ≤ y`,
or when `s` is closed and `y ≤ 0`;
* continuous functions are lower semicontinuous;
* left composition with a continuous monotone functions maps lower semicontinuous functions to lower
semicontinuous functions. If the function is anti-monotone, it instead maps lower semicontinuous
functions to upper semicontinuous functions;
* right composition with continuous functions preserves lower and upper semicontinuity;
* a sum of two (or finitely many) lower semicontinuous functions is lower semicontinuous;
* a supremum of a family of lower semicontinuous functions is lower semicontinuous;
* An infinite sum of `ℝ≥0∞`-valued lower semicontinuous functions is lower semicontinuous.
Similar results are stated and proved for upper semicontinuity.
We also prove that a function is continuous if and only if it is both lower and upper
semicontinuous.
We have some equivalent definitions of lower- and upper-semicontinuity (under certain
restrictions on the order on the codomain):
* `lowerSemicontinuous_iff_isOpen_preimage` in a linear order;
* `lowerSemicontinuous_iff_isClosed_preimage` in a linear order;
* `lowerSemicontinuousAt_iff_le_liminf` in a dense complete linear order;
* `lowerSemicontinuous_iff_isClosed_epigraph` in a dense complete linear order with the order
topology.
## Implementation details
All the nontrivial results for upper semicontinuous functions are deduced from the corresponding
ones for lower semicontinuous functions using `OrderDual`.
## References
* <https://en.wikipedia.org/wiki/Closed_convex_function>
* <https://en.wikipedia.org/wiki/Semi-continuity>
-/
open Topology ENNReal
open Set Function Filter
variable {α : Type*} [TopologicalSpace α] {β : Type*} [Preorder β] {f g : α → β} {x : α}
{s t : Set α} {y z : β}
/-! ### Main definitions -/
/-- A real function `f` is lower semicontinuous at `x` within a set `s` if, for any `ε > 0`, for all
`x'` close enough to `x` in `s`, then `f x'` is at least `f x - ε`. We formulate this in a general
preordered space, using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuousWithinAt (f : α → β) (s : Set α) (x : α) :=
∀ y < f x, ∀ᶠ x' in 𝓝[s] x, y < f x'
/-- A real function `f` is lower semicontinuous on a set `s` if, for any `ε > 0`, for any `x ∈ s`,
for all `x'` close enough to `x` in `s`, then `f x'` is at least `f x - ε`. We formulate this in
a general preordered space, using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuousOn (f : α → β) (s : Set α) :=
∀ x ∈ s, LowerSemicontinuousWithinAt f s x
/-- A real function `f` is lower semicontinuous at `x` if, for any `ε > 0`, for all `x'` close
enough to `x`, then `f x'` is at least `f x - ε`. We formulate this in a general preordered space,
using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuousAt (f : α → β) (x : α) :=
∀ y < f x, ∀ᶠ x' in 𝓝 x, y < f x'
/-- A real function `f` is lower semicontinuous if, for any `ε > 0`, for any `x`, for all `x'` close
enough to `x`, then `f x'` is at least `f x - ε`. We formulate this in a general preordered space,
using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuous (f : α → β) :=
∀ x, LowerSemicontinuousAt f x
/-- A real function `f` is upper semicontinuous at `x` within a set `s` if, for any `ε > 0`, for all
`x'` close enough to `x` in `s`, then `f x'` is at most `f x + ε`. We formulate this in a general
preordered space, using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuousWithinAt (f : α → β) (s : Set α) (x : α) :=
∀ y, f x < y → ∀ᶠ x' in 𝓝[s] x, f x' < y
/-- A real function `f` is upper semicontinuous on a set `s` if, for any `ε > 0`, for any `x ∈ s`,
for all `x'` close enough to `x` in `s`, then `f x'` is at most `f x + ε`. We formulate this in a
general preordered space, using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuousOn (f : α → β) (s : Set α) :=
∀ x ∈ s, UpperSemicontinuousWithinAt f s x
/-- A real function `f` is upper semicontinuous at `x` if, for any `ε > 0`, for all `x'` close
enough to `x`, then `f x'` is at most `f x + ε`. We formulate this in a general preordered space,
using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuousAt (f : α → β) (x : α) :=
∀ y, f x < y → ∀ᶠ x' in 𝓝 x, f x' < y
/-- A real function `f` is upper semicontinuous if, for any `ε > 0`, for any `x`, for all `x'`
close enough to `x`, then `f x'` is at most `f x + ε`. We formulate this in a general preordered
space, using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuous (f : α → β) :=
∀ x, UpperSemicontinuousAt f x
/-!
### Lower semicontinuous functions
-/
/-! #### Basic dot notation interface for lower semicontinuity -/
theorem LowerSemicontinuousWithinAt.mono (h : LowerSemicontinuousWithinAt f s x) (hst : t ⊆ s) :
LowerSemicontinuousWithinAt f t x := fun y hy =>
Filter.Eventually.filter_mono (nhdsWithin_mono _ hst) (h y hy)
theorem lowerSemicontinuousWithinAt_univ_iff :
LowerSemicontinuousWithinAt f univ x ↔ LowerSemicontinuousAt f x := by
simp [LowerSemicontinuousWithinAt, LowerSemicontinuousAt, nhdsWithin_univ]
theorem LowerSemicontinuousAt.lowerSemicontinuousWithinAt (s : Set α)
(h : LowerSemicontinuousAt f x) : LowerSemicontinuousWithinAt f s x := fun y hy =>
Filter.Eventually.filter_mono nhdsWithin_le_nhds (h y hy)
theorem LowerSemicontinuousOn.lowerSemicontinuousWithinAt (h : LowerSemicontinuousOn f s)
(hx : x ∈ s) : LowerSemicontinuousWithinAt f s x :=
h x hx
theorem LowerSemicontinuousOn.mono (h : LowerSemicontinuousOn f s) (hst : t ⊆ s) :
LowerSemicontinuousOn f t := fun x hx => (h x (hst hx)).mono hst
theorem lowerSemicontinuousOn_univ_iff : LowerSemicontinuousOn f univ ↔ LowerSemicontinuous f := by
simp [LowerSemicontinuousOn, LowerSemicontinuous, lowerSemicontinuousWithinAt_univ_iff]
theorem LowerSemicontinuous.lowerSemicontinuousAt (h : LowerSemicontinuous f) (x : α) :
LowerSemicontinuousAt f x :=
h x
theorem LowerSemicontinuous.lowerSemicontinuousWithinAt (h : LowerSemicontinuous f) (s : Set α)
(x : α) : LowerSemicontinuousWithinAt f s x :=
(h x).lowerSemicontinuousWithinAt s
theorem LowerSemicontinuous.lowerSemicontinuousOn (h : LowerSemicontinuous f) (s : Set α) :
LowerSemicontinuousOn f s := fun x _hx => h.lowerSemicontinuousWithinAt s x
/-! #### Constants -/
theorem lowerSemicontinuousWithinAt_const : LowerSemicontinuousWithinAt (fun _x => z) s x :=
fun _y hy => Filter.Eventually.of_forall fun _x => hy
theorem lowerSemicontinuousAt_const : LowerSemicontinuousAt (fun _x => z) x := fun _y hy =>
Filter.Eventually.of_forall fun _x => hy
theorem lowerSemicontinuousOn_const : LowerSemicontinuousOn (fun _x => z) s := fun _x _hx =>
lowerSemicontinuousWithinAt_const
theorem lowerSemicontinuous_const : LowerSemicontinuous fun _x : α => z := fun _x =>
lowerSemicontinuousAt_const
/-! #### Indicators -/
section
variable [Zero β]
theorem IsOpen.lowerSemicontinuous_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuous (indicator s fun _x => y) := by
intro x z hz
by_cases h : x ∈ s <;> simp [h] at hz
· filter_upwards [hs.mem_nhds h]
simp +contextual [hz]
· refine Filter.Eventually.of_forall fun x' => ?_
by_cases h' : x' ∈ s <;> simp [h', hz.trans_le hy, hz]
theorem IsOpen.lowerSemicontinuousOn_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuousOn (indicator s fun _x => y) t :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousOn t
theorem IsOpen.lowerSemicontinuousAt_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuousAt (indicator s fun _x => y) x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousAt x
theorem IsOpen.lowerSemicontinuousWithinAt_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuousWithinAt (indicator s fun _x => y) t x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousWithinAt t x
theorem IsClosed.lowerSemicontinuous_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuous (indicator s fun _x => y) := by
intro x z hz
by_cases h : x ∈ s <;> simp [h] at hz
· refine Filter.Eventually.of_forall fun x' => ?_
by_cases h' : x' ∈ s <;> simp [h', hz, hz.trans_le hy]
· filter_upwards [hs.isOpen_compl.mem_nhds h]
simp +contextual [hz]
theorem IsClosed.lowerSemicontinuousOn_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuousOn (indicator s fun _x => y) t :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousOn t
theorem IsClosed.lowerSemicontinuousAt_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuousAt (indicator s fun _x => y) x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousAt x
theorem IsClosed.lowerSemicontinuousWithinAt_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuousWithinAt (indicator s fun _x => y) t x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousWithinAt t x
end
/-! #### Relationship with continuity -/
theorem lowerSemicontinuous_iff_isOpen_preimage :
LowerSemicontinuous f ↔ ∀ y, IsOpen (f ⁻¹' Ioi y) :=
⟨fun H y => isOpen_iff_mem_nhds.2 fun x hx => H x y hx, fun H _x y y_lt =>
IsOpen.mem_nhds (H y) y_lt⟩
theorem LowerSemicontinuous.isOpen_preimage (hf : LowerSemicontinuous f) (y : β) :
IsOpen (f ⁻¹' Ioi y) :=
lowerSemicontinuous_iff_isOpen_preimage.1 hf y
section
variable {γ : Type*} [LinearOrder γ]
theorem lowerSemicontinuous_iff_isClosed_preimage {f : α → γ} :
LowerSemicontinuous f ↔ ∀ y, IsClosed (f ⁻¹' Iic y) := by
rw [lowerSemicontinuous_iff_isOpen_preimage]
simp only [← isOpen_compl_iff, ← preimage_compl, compl_Iic]
theorem LowerSemicontinuous.isClosed_preimage {f : α → γ} (hf : LowerSemicontinuous f) (y : γ) :
IsClosed (f ⁻¹' Iic y) :=
lowerSemicontinuous_iff_isClosed_preimage.1 hf y
variable [TopologicalSpace γ] [OrderTopology γ]
theorem ContinuousWithinAt.lowerSemicontinuousWithinAt {f : α → γ} (h : ContinuousWithinAt f s x) :
LowerSemicontinuousWithinAt f s x := fun _y hy => h (Ioi_mem_nhds hy)
theorem ContinuousAt.lowerSemicontinuousAt {f : α → γ} (h : ContinuousAt f x) :
LowerSemicontinuousAt f x := fun _y hy => h (Ioi_mem_nhds hy)
theorem ContinuousOn.lowerSemicontinuousOn {f : α → γ} (h : ContinuousOn f s) :
LowerSemicontinuousOn f s := fun x hx => (h x hx).lowerSemicontinuousWithinAt
theorem Continuous.lowerSemicontinuous {f : α → γ} (h : Continuous f) : LowerSemicontinuous f :=
fun _x => h.continuousAt.lowerSemicontinuousAt
end
/-! #### Equivalent definitions -/
section
variable {γ : Type*} [CompleteLinearOrder γ] [DenselyOrdered γ]
theorem lowerSemicontinuousWithinAt_iff_le_liminf {f : α → γ} :
LowerSemicontinuousWithinAt f s x ↔ f x ≤ liminf f (𝓝[s] x) := by
constructor
· intro hf; unfold LowerSemicontinuousWithinAt at hf
contrapose! hf
obtain ⟨y, lty, ylt⟩ := exists_between hf; use y
exact ⟨ylt, fun h => lty.not_le
(le_liminf_of_le (by isBoundedDefault) (h.mono fun _ hx => le_of_lt hx))⟩
exact fun hf y ylt => eventually_lt_of_lt_liminf (ylt.trans_le hf)
alias ⟨LowerSemicontinuousWithinAt.le_liminf, _⟩ := lowerSemicontinuousWithinAt_iff_le_liminf
theorem lowerSemicontinuousAt_iff_le_liminf {f : α → γ} :
LowerSemicontinuousAt f x ↔ f x ≤ liminf f (𝓝 x) := by
rw [← lowerSemicontinuousWithinAt_univ_iff, lowerSemicontinuousWithinAt_iff_le_liminf,
← nhdsWithin_univ]
alias ⟨LowerSemicontinuousAt.le_liminf, _⟩ := lowerSemicontinuousAt_iff_le_liminf
theorem lowerSemicontinuous_iff_le_liminf {f : α → γ} :
LowerSemicontinuous f ↔ ∀ x, f x ≤ liminf f (𝓝 x) := by
simp only [← lowerSemicontinuousAt_iff_le_liminf, LowerSemicontinuous]
alias ⟨LowerSemicontinuous.le_liminf, _⟩ := lowerSemicontinuous_iff_le_liminf
theorem lowerSemicontinuousOn_iff_le_liminf {f : α → γ} :
LowerSemicontinuousOn f s ↔ ∀ x ∈ s, f x ≤ liminf f (𝓝[s] x) := by
simp only [← lowerSemicontinuousWithinAt_iff_le_liminf, LowerSemicontinuousOn]
alias ⟨LowerSemicontinuousOn.le_liminf, _⟩ := lowerSemicontinuousOn_iff_le_liminf
variable [TopologicalSpace γ] [OrderTopology γ]
theorem lowerSemicontinuous_iff_isClosed_epigraph {f : α → γ} :
LowerSemicontinuous f ↔ IsClosed {p : α × γ | f p.1 ≤ p.2} := by
constructor
· rw [lowerSemicontinuous_iff_le_liminf, isClosed_iff_forall_filter]
rintro hf ⟨x, y⟩ F F_ne h h'
rw [nhds_prod_eq, le_prod] at h'
calc f x ≤ liminf f (𝓝 x) := hf x
_ ≤ liminf f (map Prod.fst F) := liminf_le_liminf_of_le h'.1
_ = liminf (f ∘ Prod.fst) F := (Filter.liminf_comp _ _ _).symm
_ ≤ liminf Prod.snd F := liminf_le_liminf <| by
simpa using (eventually_principal.2 fun (_ : α × γ) ↦ id).filter_mono h
_ = y := h'.2.liminf_eq
· rw [lowerSemicontinuous_iff_isClosed_preimage]
exact fun hf y ↦ hf.preimage (.prodMk_left y)
alias ⟨LowerSemicontinuous.isClosed_epigraph, _⟩ := lowerSemicontinuous_iff_isClosed_epigraph
end
/-! ### Composition -/
section
variable {γ : Type*} [LinearOrder γ] [TopologicalSpace γ] [OrderTopology γ]
variable {δ : Type*} [LinearOrder δ] [TopologicalSpace δ] [OrderTopology δ]
variable {ι : Type*} [TopologicalSpace ι]
theorem ContinuousAt.comp_lowerSemicontinuousWithinAt {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : LowerSemicontinuousWithinAt f s x) (gmon : Monotone g) :
LowerSemicontinuousWithinAt (g ∘ f) s x := by
intro y hy
by_cases h : ∃ l, l < f x
· obtain ⟨z, zlt, hz⟩ : ∃ z < f x, Ioc z (f x) ⊆ g ⁻¹' Ioi y :=
exists_Ioc_subset_of_mem_nhds (hg (Ioi_mem_nhds hy)) h
filter_upwards [hf z zlt] with a ha
calc
y < g (min (f x) (f a)) := hz (by simp [zlt, ha, le_refl])
_ ≤ g (f a) := gmon (min_le_right _ _)
· simp only [not_exists, not_lt] at h
exact Filter.Eventually.of_forall fun a => hy.trans_le (gmon (h (f a)))
theorem ContinuousAt.comp_lowerSemicontinuousAt {g : γ → δ} {f : α → γ} (hg : ContinuousAt g (f x))
(hf : LowerSemicontinuousAt f x) (gmon : Monotone g) : LowerSemicontinuousAt (g ∘ f) x := by
simp only [← lowerSemicontinuousWithinAt_univ_iff] at hf ⊢
exact hg.comp_lowerSemicontinuousWithinAt hf gmon
theorem Continuous.comp_lowerSemicontinuousOn {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuousOn f s) (gmon : Monotone g) : LowerSemicontinuousOn (g ∘ f) s :=
fun x hx => hg.continuousAt.comp_lowerSemicontinuousWithinAt (hf x hx) gmon
theorem Continuous.comp_lowerSemicontinuous {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuous f) (gmon : Monotone g) : LowerSemicontinuous (g ∘ f) := fun x =>
hg.continuousAt.comp_lowerSemicontinuousAt (hf x) gmon
theorem ContinuousAt.comp_lowerSemicontinuousWithinAt_antitone {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : LowerSemicontinuousWithinAt f s x) (gmon : Antitone g) :
UpperSemicontinuousWithinAt (g ∘ f) s x :=
@ContinuousAt.comp_lowerSemicontinuousWithinAt α _ x s γ _ _ _ δᵒᵈ _ _ _ g f hg hf gmon
theorem ContinuousAt.comp_lowerSemicontinuousAt_antitone {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : LowerSemicontinuousAt f x) (gmon : Antitone g) :
UpperSemicontinuousAt (g ∘ f) x :=
@ContinuousAt.comp_lowerSemicontinuousAt α _ x γ _ _ _ δᵒᵈ _ _ _ g f hg hf gmon
theorem Continuous.comp_lowerSemicontinuousOn_antitone {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuousOn f s) (gmon : Antitone g) : UpperSemicontinuousOn (g ∘ f) s :=
fun x hx => hg.continuousAt.comp_lowerSemicontinuousWithinAt_antitone (hf x hx) gmon
theorem Continuous.comp_lowerSemicontinuous_antitone {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuous f) (gmon : Antitone g) : UpperSemicontinuous (g ∘ f) := fun x =>
hg.continuousAt.comp_lowerSemicontinuousAt_antitone (hf x) gmon
theorem LowerSemicontinuousAt.comp_continuousAt {f : α → β} {g : ι → α} {x : ι}
(hf : LowerSemicontinuousAt f (g x)) (hg : ContinuousAt g x) :
LowerSemicontinuousAt (fun x ↦ f (g x)) x :=
fun _ lt ↦ hg.eventually (hf _ lt)
theorem LowerSemicontinuousAt.comp_continuousAt_of_eq {f : α → β} {g : ι → α} {y : α} {x : ι}
(hf : LowerSemicontinuousAt f y) (hg : ContinuousAt g x) (hy : g x = y) :
LowerSemicontinuousAt (fun x ↦ f (g x)) x := by
rw [← hy] at hf
exact comp_continuousAt hf hg
theorem LowerSemicontinuous.comp_continuous {f : α → β} {g : ι → α}
(hf : LowerSemicontinuous f) (hg : Continuous g) : LowerSemicontinuous fun x ↦ f (g x) :=
fun x ↦ (hf (g x)).comp_continuousAt hg.continuousAt
end
/-! #### Addition -/
section
variable {ι : Type*} {γ : Type*} [AddCommMonoid γ] [LinearOrder γ] [IsOrderedAddMonoid γ]
[TopologicalSpace γ] [OrderTopology γ]
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuousWithinAt.add' {f g : α → γ} (hf : LowerSemicontinuousWithinAt f s x)
(hg : LowerSemicontinuousWithinAt g s x)
(hcont : ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuousWithinAt (fun z => f z + g z) s x := by
intro y hy
obtain ⟨u, v, u_open, xu, v_open, xv, h⟩ :
∃ u v : Set γ,
IsOpen u ∧ f x ∈ u ∧ IsOpen v ∧ g x ∈ v ∧ u ×ˢ v ⊆ { p : γ × γ | y < p.fst + p.snd } :=
mem_nhds_prod_iff'.1 (hcont (isOpen_Ioi.mem_nhds hy))
by_cases hx₁ : ∃ l, l < f x
· obtain ⟨z₁, z₁lt, h₁⟩ : ∃ z₁ < f x, Ioc z₁ (f x) ⊆ u :=
exists_Ioc_subset_of_mem_nhds (u_open.mem_nhds xu) hx₁
by_cases hx₂ : ∃ l, l < g x
· obtain ⟨z₂, z₂lt, h₂⟩ : ∃ z₂ < g x, Ioc z₂ (g x) ⊆ v :=
exists_Ioc_subset_of_mem_nhds (v_open.mem_nhds xv) hx₂
filter_upwards [hf z₁ z₁lt, hg z₂ z₂lt] with z h₁z h₂z
have A1 : min (f z) (f x) ∈ u := by
by_cases H : f z ≤ f x
· simpa [H] using h₁ ⟨h₁z, H⟩
· simpa [le_of_not_le H]
have A2 : min (g z) (g x) ∈ v := by
by_cases H : g z ≤ g x
· simpa [H] using h₂ ⟨h₂z, H⟩
· simpa [le_of_not_le H]
have : (min (f z) (f x), min (g z) (g x)) ∈ u ×ˢ v := ⟨A1, A2⟩
calc
y < min (f z) (f x) + min (g z) (g x) := h this
_ ≤ f z + g z := add_le_add (min_le_left _ _) (min_le_left _ _)
· simp only [not_exists, not_lt] at hx₂
filter_upwards [hf z₁ z₁lt] with z h₁z
have A1 : min (f z) (f x) ∈ u := by
by_cases H : f z ≤ f x
· simpa [H] using h₁ ⟨h₁z, H⟩
· simpa [le_of_not_le H]
have : (min (f z) (f x), g x) ∈ u ×ˢ v := ⟨A1, xv⟩
calc
y < min (f z) (f x) + g x := h this
_ ≤ f z + g z := add_le_add (min_le_left _ _) (hx₂ (g z))
· simp only [not_exists, not_lt] at hx₁
by_cases hx₂ : ∃ l, l < g x
· obtain ⟨z₂, z₂lt, h₂⟩ : ∃ z₂ < g x, Ioc z₂ (g x) ⊆ v :=
exists_Ioc_subset_of_mem_nhds (v_open.mem_nhds xv) hx₂
filter_upwards [hg z₂ z₂lt] with z h₂z
have A2 : min (g z) (g x) ∈ v := by
by_cases H : g z ≤ g x
· simpa [H] using h₂ ⟨h₂z, H⟩
· simpa [le_of_not_le H] using h₂ ⟨z₂lt, le_rfl⟩
have : (f x, min (g z) (g x)) ∈ u ×ˢ v := ⟨xu, A2⟩
calc
y < f x + min (g z) (g x) := h this
_ ≤ f z + g z := add_le_add (hx₁ (f z)) (min_le_left _ _)
· simp only [not_exists, not_lt] at hx₁ hx₂
apply Filter.Eventually.of_forall
intro z
have : (f x, g x) ∈ u ×ˢ v := ⟨xu, xv⟩
calc
y < f x + g x := h this
_ ≤ f z + g z := add_le_add (hx₁ (f z)) (hx₂ (g z))
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuousAt.add' {f g : α → γ} (hf : LowerSemicontinuousAt f x)
(hg : LowerSemicontinuousAt g x)
(hcont : ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuousAt (fun z => f z + g z) x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
exact hf.add' hg hcont
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuousOn.add' {f g : α → γ} (hf : LowerSemicontinuousOn f s)
(hg : LowerSemicontinuousOn g s)
(hcont : ∀ x ∈ s, ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuousOn (fun z => f z + g z) s := fun x hx =>
(hf x hx).add' (hg x hx) (hcont x hx)
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuous.add' {f g : α → γ} (hf : LowerSemicontinuous f)
(hg : LowerSemicontinuous g)
(hcont : ∀ x, ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuous fun z => f z + g z := fun x => (hf x).add' (hg x) (hcont x)
variable [ContinuousAdd γ]
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuousWithinAt.add {f g : α → γ} (hf : LowerSemicontinuousWithinAt f s x)
(hg : LowerSemicontinuousWithinAt g s x) :
LowerSemicontinuousWithinAt (fun z => f z + g z) s x :=
hf.add' hg continuous_add.continuousAt
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuousAt.add {f g : α → γ} (hf : LowerSemicontinuousAt f x)
(hg : LowerSemicontinuousAt g x) : LowerSemicontinuousAt (fun z => f z + g z) x :=
hf.add' hg continuous_add.continuousAt
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuousOn.add {f g : α → γ} (hf : LowerSemicontinuousOn f s)
(hg : LowerSemicontinuousOn g s) : LowerSemicontinuousOn (fun z => f z + g z) s :=
hf.add' hg fun _x _hx => continuous_add.continuousAt
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuous.add {f g : α → γ} (hf : LowerSemicontinuous f)
(hg : LowerSemicontinuous g) : LowerSemicontinuous fun z => f z + g z :=
hf.add' hg fun _x => continuous_add.continuousAt
theorem lowerSemicontinuousWithinAt_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun z => ∑ i ∈ a, f i z) s x := by
classical
induction a using Finset.induction_on with
| empty => exact lowerSemicontinuousWithinAt_const
| insert _ _ ia IH =>
simp only [ia, Finset.sum_insert, not_false_iff]
exact
LowerSemicontinuousWithinAt.add (ha _ (Finset.mem_insert_self ..))
(IH fun j ja => ha j (Finset.mem_insert_of_mem ja))
theorem lowerSemicontinuousAt_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun z => ∑ i ∈ a, f i z) x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
exact lowerSemicontinuousWithinAt_sum ha
theorem lowerSemicontinuousOn_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun z => ∑ i ∈ a, f i z) s := fun x hx =>
lowerSemicontinuousWithinAt_sum fun i hi => ha i hi x hx
theorem lowerSemicontinuous_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuous (f i)) : LowerSemicontinuous fun z => ∑ i ∈ a, f i z :=
fun x => lowerSemicontinuousAt_sum fun i hi => ha i hi x
end
/-! #### Supremum -/
section
variable {ι : Sort*} {δ δ' : Type*} [CompleteLinearOrder δ] [ConditionallyCompleteLinearOrder δ']
theorem lowerSemicontinuousWithinAt_ciSup {f : ι → α → δ'}
(bdd : ∀ᶠ y in 𝓝[s] x, BddAbove (range fun i => f i y))
(h : ∀ i, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun x' => ⨆ i, f i x') s x := by
cases isEmpty_or_nonempty ι
· simpa only [iSup_of_empty'] using lowerSemicontinuousWithinAt_const
· intro y hy
rcases exists_lt_of_lt_ciSup hy with ⟨i, hi⟩
filter_upwards [h i y hi, bdd] with y hy hy' using hy.trans_le (le_ciSup hy' i)
theorem lowerSemicontinuousWithinAt_iSup {f : ι → α → δ}
(h : ∀ i, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun x' => ⨆ i, f i x') s x :=
lowerSemicontinuousWithinAt_ciSup (by simp) h
theorem lowerSemicontinuousWithinAt_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuousWithinAt (f i hi) s x) :
LowerSemicontinuousWithinAt (fun x' => ⨆ (i) (hi), f i hi x') s x :=
lowerSemicontinuousWithinAt_iSup fun i => lowerSemicontinuousWithinAt_iSup fun hi => h i hi
theorem lowerSemicontinuousAt_ciSup {f : ι → α → δ'}
(bdd : ∀ᶠ y in 𝓝 x, BddAbove (range fun i => f i y)) (h : ∀ i, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun x' => ⨆ i, f i x') x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
rw [← nhdsWithin_univ] at bdd
exact lowerSemicontinuousWithinAt_ciSup bdd h
theorem lowerSemicontinuousAt_iSup {f : ι → α → δ} (h : ∀ i, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun x' => ⨆ i, f i x') x :=
lowerSemicontinuousAt_ciSup (by simp) h
theorem lowerSemicontinuousAt_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuousAt (f i hi) x) :
LowerSemicontinuousAt (fun x' => ⨆ (i) (hi), f i hi x') x :=
lowerSemicontinuousAt_iSup fun i => lowerSemicontinuousAt_iSup fun hi => h i hi
theorem lowerSemicontinuousOn_ciSup {f : ι → α → δ'}
(bdd : ∀ x ∈ s, BddAbove (range fun i => f i x)) (h : ∀ i, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun x' => ⨆ i, f i x') s := fun x hx =>
lowerSemicontinuousWithinAt_ciSup (eventually_nhdsWithin_of_forall bdd) fun i => h i x hx
theorem lowerSemicontinuousOn_iSup {f : ι → α → δ} (h : ∀ i, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun x' => ⨆ i, f i x') s :=
lowerSemicontinuousOn_ciSup (by simp) h
theorem lowerSemicontinuousOn_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuousOn (f i hi) s) :
LowerSemicontinuousOn (fun x' => ⨆ (i) (hi), f i hi x') s :=
lowerSemicontinuousOn_iSup fun i => lowerSemicontinuousOn_iSup fun hi => h i hi
theorem lowerSemicontinuous_ciSup {f : ι → α → δ'} (bdd : ∀ x, BddAbove (range fun i => f i x))
(h : ∀ i, LowerSemicontinuous (f i)) : LowerSemicontinuous fun x' => ⨆ i, f i x' := fun x =>
lowerSemicontinuousAt_ciSup (Eventually.of_forall bdd) fun i => h i x
theorem lowerSemicontinuous_iSup {f : ι → α → δ} (h : ∀ i, LowerSemicontinuous (f i)) :
LowerSemicontinuous fun x' => ⨆ i, f i x' :=
lowerSemicontinuous_ciSup (by simp) h
theorem lowerSemicontinuous_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuous (f i hi)) :
LowerSemicontinuous fun x' => ⨆ (i) (hi), f i hi x' :=
lowerSemicontinuous_iSup fun i => lowerSemicontinuous_iSup fun hi => h i hi
end
/-! #### Infinite sums -/
section
variable {ι : Type*}
theorem lowerSemicontinuousWithinAt_tsum {f : ι → α → ℝ≥0∞}
(h : ∀ i, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun x' => ∑' i, f i x') s x := by
simp_rw [ENNReal.tsum_eq_iSup_sum]
refine lowerSemicontinuousWithinAt_iSup fun b => ?_
exact lowerSemicontinuousWithinAt_sum fun i _hi => h i
theorem lowerSemicontinuousAt_tsum {f : ι → α → ℝ≥0∞} (h : ∀ i, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun x' => ∑' i, f i x') x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
exact lowerSemicontinuousWithinAt_tsum h
theorem lowerSemicontinuousOn_tsum {f : ι → α → ℝ≥0∞} (h : ∀ i, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun x' => ∑' i, f i x') s := fun x hx =>
lowerSemicontinuousWithinAt_tsum fun i => h i x hx
theorem lowerSemicontinuous_tsum {f : ι → α → ℝ≥0∞} (h : ∀ i, LowerSemicontinuous (f i)) :
LowerSemicontinuous fun x' => ∑' i, f i x' := fun x => lowerSemicontinuousAt_tsum fun i => h i x
end
/-!
### Upper semicontinuous functions
-/
/-! #### Basic dot notation interface for upper semicontinuity -/
theorem UpperSemicontinuousWithinAt.mono (h : UpperSemicontinuousWithinAt f s x) (hst : t ⊆ s) :
UpperSemicontinuousWithinAt f t x := fun y hy =>
Filter.Eventually.filter_mono (nhdsWithin_mono _ hst) (h y hy)
theorem upperSemicontinuousWithinAt_univ_iff :
UpperSemicontinuousWithinAt f univ x ↔ UpperSemicontinuousAt f x := by
simp [UpperSemicontinuousWithinAt, UpperSemicontinuousAt, nhdsWithin_univ]
theorem UpperSemicontinuousAt.upperSemicontinuousWithinAt (s : Set α)
(h : UpperSemicontinuousAt f x) : UpperSemicontinuousWithinAt f s x := fun y hy =>
Filter.Eventually.filter_mono nhdsWithin_le_nhds (h y hy)
theorem UpperSemicontinuousOn.upperSemicontinuousWithinAt (h : UpperSemicontinuousOn f s)
(hx : x ∈ s) : UpperSemicontinuousWithinAt f s x :=
h x hx
theorem UpperSemicontinuousOn.mono (h : UpperSemicontinuousOn f s) (hst : t ⊆ s) :
UpperSemicontinuousOn f t := fun x hx => (h x (hst hx)).mono hst
theorem upperSemicontinuousOn_univ_iff : UpperSemicontinuousOn f univ ↔ UpperSemicontinuous f := by
simp [UpperSemicontinuousOn, UpperSemicontinuous, upperSemicontinuousWithinAt_univ_iff]
theorem UpperSemicontinuous.upperSemicontinuousAt (h : UpperSemicontinuous f) (x : α) :
UpperSemicontinuousAt f x :=
h x
theorem UpperSemicontinuous.upperSemicontinuousWithinAt (h : UpperSemicontinuous f) (s : Set α)
(x : α) : UpperSemicontinuousWithinAt f s x :=
(h x).upperSemicontinuousWithinAt s
theorem UpperSemicontinuous.upperSemicontinuousOn (h : UpperSemicontinuous f) (s : Set α) :
UpperSemicontinuousOn f s := fun x _hx => h.upperSemicontinuousWithinAt s x
/-! #### Constants -/
theorem upperSemicontinuousWithinAt_const : UpperSemicontinuousWithinAt (fun _x => z) s x :=
fun _y hy => Filter.Eventually.of_forall fun _x => hy
theorem upperSemicontinuousAt_const : UpperSemicontinuousAt (fun _x => z) x := fun _y hy =>
Filter.Eventually.of_forall fun _x => hy
theorem upperSemicontinuousOn_const : UpperSemicontinuousOn (fun _x => z) s := fun _x _hx =>
upperSemicontinuousWithinAt_const
theorem upperSemicontinuous_const : UpperSemicontinuous fun _x : α => z := fun _x =>
upperSemicontinuousAt_const
/-! #### Indicators -/
section
variable [Zero β]
theorem IsOpen.upperSemicontinuous_indicator (hs : IsOpen s) (hy : y ≤ 0) :
UpperSemicontinuous (indicator s fun _x => y) :=
@IsOpen.lowerSemicontinuous_indicator α _ βᵒᵈ _ s y _ hs hy
theorem IsOpen.upperSemicontinuousOn_indicator (hs : IsOpen s) (hy : y ≤ 0) :
UpperSemicontinuousOn (indicator s fun _x => y) t :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousOn t
theorem IsOpen.upperSemicontinuousAt_indicator (hs : IsOpen s) (hy : y ≤ 0) :
UpperSemicontinuousAt (indicator s fun _x => y) x :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousAt x
theorem IsOpen.upperSemicontinuousWithinAt_indicator (hs : IsOpen s) (hy : y ≤ 0) :
UpperSemicontinuousWithinAt (indicator s fun _x => y) t x :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousWithinAt t x
theorem IsClosed.upperSemicontinuous_indicator (hs : IsClosed s) (hy : 0 ≤ y) :
UpperSemicontinuous (indicator s fun _x => y) :=
@IsClosed.lowerSemicontinuous_indicator α _ βᵒᵈ _ s y _ hs hy
theorem IsClosed.upperSemicontinuousOn_indicator (hs : IsClosed s) (hy : 0 ≤ y) :
UpperSemicontinuousOn (indicator s fun _x => y) t :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousOn t
theorem IsClosed.upperSemicontinuousAt_indicator (hs : IsClosed s) (hy : 0 ≤ y) :
UpperSemicontinuousAt (indicator s fun _x => y) x :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousAt x
theorem IsClosed.upperSemicontinuousWithinAt_indicator (hs : IsClosed s) (hy : 0 ≤ y) :
UpperSemicontinuousWithinAt (indicator s fun _x => y) t x :=
(hs.upperSemicontinuous_indicator hy).upperSemicontinuousWithinAt t x
end
/-! #### Relationship with continuity -/
theorem upperSemicontinuous_iff_isOpen_preimage :
| UpperSemicontinuous f ↔ ∀ y, IsOpen (f ⁻¹' Iio y) :=
⟨fun H y => isOpen_iff_mem_nhds.2 fun x hx => H x y hx, fun H _x y y_lt =>
IsOpen.mem_nhds (H y) y_lt⟩
| Mathlib/Topology/Semicontinuous.lean | 765 | 767 |
/-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.LinearAlgebra.AffineSpace.Independent
import Mathlib.LinearAlgebra.AffineSpace.Pointwise
import Mathlib.LinearAlgebra.Basis.SMul
/-!
# Affine bases and barycentric coordinates
Suppose `P` is an affine space modelled on the module `V` over the ring `k`, and `p : ι → P` is an
affine-independent family of points spanning `P`. Given this data, each point `q : P` may be written
uniquely as an affine combination: `q = w₀ p₀ + w₁ p₁ + ⋯` for some (finitely-supported) weights
`wᵢ`. For each `i : ι`, we thus have an affine map `P →ᵃ[k] k`, namely `q ↦ wᵢ`. This family of
maps is known as the family of barycentric coordinates. It is defined in this file.
## The construction
Fixing `i : ι`, and allowing `j : ι` to range over the values `j ≠ i`, we obtain a basis `bᵢ` of `V`
defined by `bᵢ j = p j -ᵥ p i`. Let `fᵢ j : V →ₗ[k] k` be the corresponding dual basis and let
`fᵢ = ∑ j, fᵢ j : V →ₗ[k] k` be the corresponding "sum of all coordinates" form. Then the `i`th
barycentric coordinate of `q : P` is `1 - fᵢ (q -ᵥ p i)`.
## Main definitions
* `AffineBasis`: a structure representing an affine basis of an affine space.
* `AffineBasis.coord`: the map `P →ᵃ[k] k` corresponding to `i : ι`.
* `AffineBasis.coord_apply_eq`: the behaviour of `AffineBasis.coord i` on `p i`.
* `AffineBasis.coord_apply_ne`: the behaviour of `AffineBasis.coord i` on `p j` when `j ≠ i`.
* `AffineBasis.coord_apply`: the behaviour of `AffineBasis.coord i` on `p j` for general `j`.
* `AffineBasis.coord_apply_combination`: the characterisation of `AffineBasis.coord i` in terms
of affine combinations, i.e., `AffineBasis.coord i (w₀ p₀ + w₁ p₁ + ⋯) = wᵢ`.
## TODO
* Construct the affine equivalence between `P` and `{ f : ι →₀ k | f.sum = 1 }`.
-/
open Affine Set
open scoped Pointwise
universe u₁ u₂ u₃ u₄
/-- An affine basis is a family of affine-independent points whose span is the top subspace. -/
structure AffineBasis (ι : Type u₁) (k : Type u₂) {V : Type u₃} (P : Type u₄) [AddCommGroup V]
[AffineSpace V P] [Ring k] [Module k V] where
protected toFun : ι → P
protected ind' : AffineIndependent k toFun
protected tot' : affineSpan k (range toFun) = ⊤
variable {ι ι' G G' k V P : Type*} [AddCommGroup V] [AffineSpace V P]
namespace AffineBasis
section Ring
variable [Ring k] [Module k V] (b : AffineBasis ι k P) {s : Finset ι} {i j : ι} (e : ι ≃ ι')
/-- The unique point in a single-point space is the simplest example of an affine basis. -/
instance : Inhabited (AffineBasis PUnit k PUnit) :=
⟨⟨id, affineIndependent_of_subsingleton k id, by simp⟩⟩
instance instFunLike : FunLike (AffineBasis ι k P) ι P where
coe := AffineBasis.toFun
coe_injective' f g h := by cases f; cases g; congr
@[ext]
theorem ext {b₁ b₂ : AffineBasis ι k P} (h : (b₁ : ι → P) = b₂) : b₁ = b₂ :=
DFunLike.coe_injective h
theorem ind : AffineIndependent k b :=
b.ind'
theorem tot : affineSpan k (range b) = ⊤ :=
b.tot'
include b in
protected theorem nonempty : Nonempty ι :=
not_isEmpty_iff.mp fun hι => by
simpa only [@range_eq_empty _ _ hι, AffineSubspace.span_empty, bot_ne_top] using b.tot
/-- Composition of an affine basis and an equivalence of index types. -/
def reindex (e : ι ≃ ι') : AffineBasis ι' k P :=
⟨b ∘ e.symm, b.ind.comp_embedding e.symm.toEmbedding, by
rw [e.symm.surjective.range_comp]
exact b.3⟩
@[simp, norm_cast]
theorem coe_reindex : ⇑(b.reindex e) = b ∘ e.symm :=
rfl
@[simp]
theorem reindex_apply (i' : ι') : b.reindex e i' = b (e.symm i') :=
rfl
@[simp]
theorem reindex_refl : b.reindex (Equiv.refl _) = b :=
ext rfl
/-- Given an affine basis for an affine space `P`, if we single out one member of the family, we
obtain a linear basis for the model space `V`.
The linear basis corresponding to the singled-out member `i : ι` is indexed by `{j : ι // j ≠ i}`
and its `j`th element is `b j -ᵥ b i`. (See `basisOf_apply`.) -/
noncomputable def basisOf (i : ι) : Basis { j : ι // j ≠ i } k V :=
Basis.mk ((affineIndependent_iff_linearIndependent_vsub k b i).mp b.ind)
(by
suffices
Submodule.span k (range fun j : { x // x ≠ i } => b ↑j -ᵥ b i) = vectorSpan k (range b) by
rw [this, ← direction_affineSpan, b.tot, AffineSubspace.direction_top]
conv_rhs => rw [← image_univ]
rw [vectorSpan_image_eq_span_vsub_set_right_ne k b (mem_univ i)]
congr
ext v
simp)
@[simp]
theorem basisOf_apply (i : ι) (j : { j : ι // j ≠ i }) : b.basisOf i j = b ↑j -ᵥ b i := by
simp [basisOf]
@[simp]
theorem basisOf_reindex (i : ι') :
(b.reindex e).basisOf i =
(b.basisOf <| e.symm i).reindex (e.subtypeEquiv fun _ => e.eq_symm_apply.not) := by
ext j
simp
/-- The `i`th barycentric coordinate of a point. -/
noncomputable def coord (i : ι) : P →ᵃ[k] k where
toFun q := 1 - (b.basisOf i).sumCoords (q -ᵥ b i)
linear := -(b.basisOf i).sumCoords
map_vadd' q v := by
rw [vadd_vsub_assoc, LinearMap.map_add, vadd_eq_add, LinearMap.neg_apply,
sub_add_eq_sub_sub_swap, add_comm, sub_eq_add_neg]
@[simp]
theorem linear_eq_sumCoords (i : ι) : (b.coord i).linear = -(b.basisOf i).sumCoords :=
rfl
@[simp]
theorem coord_reindex (i : ι') : (b.reindex e).coord i = b.coord (e.symm i) := by
ext
classical simp [AffineBasis.coord]
@[simp]
theorem coord_apply_eq (i : ι) : b.coord i (b i) = 1 := by
simp only [coord, Basis.coe_sumCoords, LinearEquiv.map_zero, LinearEquiv.coe_coe, sub_zero,
AffineMap.coe_mk, Finsupp.sum_zero_index, vsub_self]
@[simp]
theorem coord_apply_ne (h : i ≠ j) : b.coord i (b j) = 0 := by
rw [coord, AffineMap.coe_mk, ← Subtype.coe_mk (p := (· ≠ i)) j h.symm, ← b.basisOf_apply,
Basis.sumCoords_self_apply, sub_self]
theorem coord_apply [DecidableEq ι] (i j : ι) : b.coord i (b j) = if i = j then 1 else 0 := by
rcases eq_or_ne i j with h | h <;> simp [h]
@[simp]
theorem coord_apply_combination_of_mem (hi : i ∈ s) {w : ι → k} (hw : s.sum w = 1) :
b.coord i (s.affineCombination k b w) = w i := by
classical simp only [coord_apply, hi, Finset.affineCombination_eq_linear_combination, if_true,
mul_boole, hw, Function.comp_apply, smul_eq_mul, s.sum_ite_eq,
s.map_affineCombination b w hw]
@[simp]
theorem coord_apply_combination_of_not_mem (hi : i ∉ s) {w : ι → k} (hw : s.sum w = 1) :
b.coord i (s.affineCombination k b w) = 0 := by
classical simp only [coord_apply, hi, Finset.affineCombination_eq_linear_combination, if_false,
mul_boole, hw, Function.comp_apply, smul_eq_mul, s.sum_ite_eq,
s.map_affineCombination b w hw]
@[simp]
theorem sum_coord_apply_eq_one [Fintype ι] (q : P) : ∑ i, b.coord i q = 1 := by
have hq : q ∈ affineSpan k (range b) := by
rw [b.tot]
exact AffineSubspace.mem_top k V q
obtain ⟨w, hw, rfl⟩ := eq_affineCombination_of_mem_affineSpan_of_fintype hq
convert hw
exact b.coord_apply_combination_of_mem (Finset.mem_univ _) hw
@[simp]
theorem affineCombination_coord_eq_self [Fintype ι] (q : P) :
(Finset.univ.affineCombination k b fun i => b.coord i q) = q := by
have hq : q ∈ affineSpan k (range b) := by
rw [b.tot]
exact AffineSubspace.mem_top k V q
obtain ⟨w, hw, rfl⟩ := eq_affineCombination_of_mem_affineSpan_of_fintype hq
congr
ext i
exact b.coord_apply_combination_of_mem (Finset.mem_univ i) hw
/-- A variant of `AffineBasis.affineCombination_coord_eq_self` for the special case when the
affine space is a module so we can talk about linear combinations. -/
@[simp]
theorem linear_combination_coord_eq_self [Fintype ι] (b : AffineBasis ι k V) (v : V) :
∑ i, b.coord i v • b i = v := by
have hb := b.affineCombination_coord_eq_self v
rwa [Finset.univ.affineCombination_eq_linear_combination _ _ (b.sum_coord_apply_eq_one v)] at hb
theorem ext_elem [Finite ι] {q₁ q₂ : P} (h : ∀ i, b.coord i q₁ = b.coord i q₂) : q₁ = q₂ := by
cases nonempty_fintype ι
rw [← b.affineCombination_coord_eq_self q₁, ← b.affineCombination_coord_eq_self q₂]
simp only [h]
@[simp]
theorem coe_coord_of_subsingleton_eq_one [Subsingleton ι] (i : ι) : (b.coord i : P → k) = 1 := by
ext q
have hp : (range b).Subsingleton := by
rw [← image_univ]
| apply Subsingleton.image
apply subsingleton_of_subsingleton
haveI := AffineSubspace.subsingleton_of_subsingleton_span_eq_top hp b.tot
let s : Finset ι := {i}
have hi : i ∈ s := by simp [s]
have hw : s.sum (Function.const ι (1 : k)) = 1 := by simp [s]
have hq : q = s.affineCombination k b (Function.const ι (1 : k)) := by
simp [eq_iff_true_of_subsingleton]
rw [Pi.one_apply, hq, b.coord_apply_combination_of_mem hi hw, Function.const_apply]
| Mathlib/LinearAlgebra/AffineSpace/Basis.lean | 213 | 221 |
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