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110f4f3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 | import OAI.Analysis.BackwardIntertwiners.HaarBase
namespace OAI
namespace BackwardIntertwiners
open Filter
open scoped Topology
noncomputable section
open Topology MeasureTheory Set
open scoped ENNReal
def coordinateDistance (j : ℤ) : ℤ := max (j+1) (-j)
def powerCost (n : ℕ) : ℕ := (n+1)^2/4
lemma powerCost_add_two (n : ℕ) : powerCost (n+2) = powerCost n + n+2 := by
unfold powerCost
have he : (n+2+1)^2 = (n+1)^2 + 4*(n+2) := by ring
rw [he]
omega
lemma coordinateDistance_pos (j : ℤ) : 1 ≤ coordinateDistance j := by
unfold coordinateDistance
omega
lemma coordinateDistance_endpoints (j : ℤ) (n : ℕ) :
(n:ℤ)+2 ≤ coordinateDistance j + coordinateDistance (j+(n:ℤ)+1) := by
have h₁ : -j ≤ coordinateDistance j := le_max_right _ _
have h₂ : j+(n:ℤ)+1+1 ≤ coordinateDistance (j+(n:ℤ)+1) := le_max_left _ _
omega
lemma sum_coordinateDistance_lower (n : ℕ) (j : ℤ) :
(powerCost n : ℤ) ≤ ∑ r ∈ Finset.range n, coordinateDistance (j+(r:ℤ)) := by
induction n using Nat.twoStepInduction generalizing j with
| zero => simp [powerCost]
| one => simpa [powerCost] using coordinateDistance_pos j
| more n ih _ =>
have hsum : (∑ r ∈ Finset.range (n+2), coordinateDistance (j+(r:ℤ))) =
coordinateDistance j + (∑ r ∈ Finset.range n, coordinateDistance ((j+1)+(r:ℤ))) +
coordinateDistance (j+(n:ℤ)+1) := by
rw [Finset.sum_range_succ, Finset.sum_range_succ']
simp only [Nat.cast_add, Nat.cast_one, Nat.cast_zero, add_zero]
congr 1
· rw [add_comm]
congr 1
apply Finset.sum_congr rfl
intro r hr
congr 1
ring
· congr 1
ring
rw [hsum, powerCost_add_two]
have hmid := ih (j+1)
have hend := coordinateDistance_endpoints j n
push_cast
omega
def fiberReindexVector (e : ℤ ≃ ℤ) (v : Fiber) : Fiber :=
⟨fun j => v (e j), by
apply memℓp_gen
exact ((lp.memℓp v).summable (by norm_num)).comp_injective e.injective⟩
lemma fiberReindex_norm (e : ℤ ≃ ℤ) (v : Fiber) : ‖fiberReindexVector e v‖ = ‖v‖ := by
have he : ‖fiberReindexVector e v‖^2 = ‖v‖^2 := by
have h₁ := lp.norm_rpow_eq_tsum (by norm_num : (0:ℝ) < (2:ENNReal).toReal) (fiberReindexVector e v)
have h₂ := lp.norm_rpow_eq_tsum (by norm_num : (0:ℝ) < (2:ENNReal).toReal) v
simp only [ENNReal.toReal_ofNat, Real.rpow_two] at h₁ h₂
rw [h₁, h₂]
exact e.tsum_eq (fun j => ‖v j‖^2)
nlinarith [norm_nonneg (fiberReindexVector e v), norm_nonneg v]
def fiberReindex (e : ℤ ≃ ℤ) : Fiber ≃ₗᵢ[ℂ] Fiber where
toFun := fiberReindexVector e
invFun := fiberReindexVector e.symm
left_inv v := by ext j; exact congrArg v (e.apply_symm_apply j)
right_inv v := by ext j; exact congrArg v (e.symm_apply_apply j)
map_add' v z := by ext j; rfl
map_smul' c v := by ext j; rfl
norm_map' := fiberReindex_norm e
@[simp] lemma fiberReindex_apply (e : ℤ ≃ ℤ) (v : Fiber) (j : ℤ) :
(fiberReindex e v) j = v (e j) := rfl
lemma fiberMultiplier_mem {a : ℤ → ℂ} {C : ℝ} (hC : 0 ≤ C)
(ha : ∀ j, ‖a j‖ ≤ C) (v : Fiber) : Memℓp (fun j => a j*v j) 2 := by
apply ((lp.memℓp v).const_smul (C:ℂ)).mono'
intro j
simp only [Pi.smul_apply, norm_smul, Complex.norm_real, Real.norm_of_nonneg hC, norm_mul]
exact mul_le_mul_of_nonneg_right (ha j) (norm_nonneg _)
def fiberMultiplierVector (a : ℤ → ℂ) (C : ℝ) (hC : 0 ≤ C) (ha : ∀ j, ‖a j‖ ≤ C)
(v : Fiber) : Fiber := ⟨fun j => a j*v j, fiberMultiplier_mem hC ha v⟩
lemma fiberMultiplierVector_bound (a : ℤ → ℂ) (C : ℝ) (hC : 0 ≤ C) (ha : ∀ j, ‖a j‖ ≤ C)
(v : Fiber) : ‖fiberMultiplierVector a C hC ha v‖ ≤ C*‖v‖ := by
calc
_ ≤ ‖(C:ℂ) • v‖ := by
apply lp.norm_mono (by norm_num : (2:ENNReal) ≠ 0)
intro j
change ‖a j*v j‖ ≤ ‖(C:ℂ)*v j‖
rw [norm_mul, norm_mul, Complex.norm_real, Real.norm_of_nonneg hC]
exact mul_le_mul_of_nonneg_right (ha j) (norm_nonneg _)
_ = C*‖v‖ := by rw [norm_smul, Complex.norm_real, Real.norm_of_nonneg hC]
def fiberMultiplier (a : ℤ → ℂ) (C : ℝ) (hC : 0 ≤ C) (ha : ∀ j, ‖a j‖ ≤ C) :
Fiber →L[ℂ] Fiber :=
LinearMap.mkContinuous
{ toFun := fiberMultiplierVector a C hC ha
map_add' := by intro v z; ext j; exact mul_add _ _ _
map_smul' := by intro c v; ext j; exact mul_left_comm _ _ _ }
C (fiberMultiplierVector_bound a C hC ha)
@[simp] lemma fiberMultiplier_apply (a : ℤ → ℂ) (C : ℝ) (hC : 0 ≤ C) (ha : ∀ j, ‖a j‖ ≤ C)
(v : Fiber) (j : ℤ) : fiberMultiplier a C hC ha v j = a j*v j := rfl
lemma fiberMultiplier_norm_le (a : ℤ → ℂ) (C : ℝ) (hC : 0 ≤ C) (ha : ∀ j, ‖a j‖ ≤ C) :
‖fiberMultiplier a C hC ha‖ ≤ C :=
ContinuousLinearMap.opNorm_le_bound _ hC (fiberMultiplierVector_bound a C hC ha)
def fiberWeightedPermutation (e : ℤ ≃ ℤ) (a : ℤ → ℂ) (C : ℝ) (hC : 0 ≤ C)
(ha : ∀ j, ‖a j‖ ≤ C) : Fiber →L[ℂ] Fiber :=
(fiberReindex e).toLinearIsometry.toContinuousLinearMap.comp (fiberMultiplier a C hC ha)
@[simp] lemma fiberWeightedPermutation_apply (e : ℤ ≃ ℤ) (a : ℤ → ℂ) (C : ℝ) (hC : 0 ≤ C)
(ha : ∀ j, ‖a j‖ ≤ C) (v : Fiber) (j : ℤ) :
fiberWeightedPermutation e a C hC ha v j = a (e j)*v (e j) := rfl
lemma fiberWeightedPermutation_norm_le (e : ℤ ≃ ℤ) (a : ℤ → ℂ) (C : ℝ) (hC : 0 ≤ C)
(ha : ∀ j, ‖a j‖ ≤ C) : ‖fiberWeightedPermutation e a C hC ha‖ ≤ C := by
apply ContinuousLinearMap.opNorm_le_bound _ hC
intro v
change ‖fiberReindex e (fiberMultiplier a C hC ha v)‖ ≤ _
rw [(fiberReindex e).norm_map]
exact fiberMultiplierVector_bound a C hC ha v
lemma fiberCoordinates_stronglyMeasurable {X : Type*} [MeasurableSpace X]
(f : X → Fiber) (hf : ∀ n : ℤ, Measurable (fun x => f x n)) : StronglyMeasurable f := by
apply stronglyMeasurable_of_tendsto (atTop : Filter (Finset ℤ))
(f := fun s x => ∑ n ∈ s, lp.single 2 n (f x n))
· intro s
have h (n : ℤ) : StronglyMeasurable (fun x => (lp.single 2 n (f x n) : Fiber)) :=
(lp.singleContinuousLinearMap ℂ (fun _ : ℤ => ℂ) 2 n).continuous.comp_stronglyMeasurable
(hf n).stronglyMeasurable
convert Finset.stronglyMeasurable_sum s (fun n _ => h n) using 1
funext x
simp only [Finset.sum_apply]
· rw [tendsto_pi_nhds]
intro x
exact lp.hasSum_single (by norm_num : (2 : ENNReal) ≠ ∞) (f x)
end
end BackwardIntertwiners
end OAI
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