openAI-math-dataset / lean /OAI /Probability /SKGap /Stability /ImplicitUniformControl.lean
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import Mathlib
import OAI.Probability.SKGap.Localization.CoefficientRow
import OAI.Probability.SKGap.Stability.ImplicitPerturb
import OAI.Probability.SKGap.Stability.ImplicitUniform
namespace OAI
section
noncomputable section
namespace SKGap.ImplicitSystem
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
[FiniteDimensional ℝ E] {ι : Type*} [Fintype ι]
def uniformControlBudget (j δ B : ℝ) : ℝ :=
let L:=B+|j| *B^2+2*|j| *B
let W:=(1+B^2*(δ/2)⁻¹*L)*B^2*(B+2*|j| *B)
let C:=B*W+B
let Y:=(B+|j| *B^2)*W+|j| *C
let F:=(1+B^2*(δ/2)⁻¹*L)*(B*(B+Y+|j| *C)+B^2*B+
|j| *B^2*W*B+|j| *B^2*C*B+|j| *B^2*2*(B*W+B))
let G:=B*W+B+B*F
let H:=(B+|j| *B^2)*F+|j| *W*B+|j| *C*B+|j| *G
W+C+Y+F+G+H
lemma uniformControlBudget_nonneg {j δ B : ℝ} (hδ : 0<δ) (hB : 0≤B) :
0≤uniformControlBudget j δ B := by unfold uniformControlBudget; positivity
theorem implicit_uniform_control (j χ b r p : ℝ) (X J : E→L[ℝ]E)
(u m t ell q w y : E) (c : ℝ)
(s χ' p' c' b' : ι→ℝ) (X' : ι→E→L[ℝ]E) (u' m' ell' w' y' q' : ι→E)
{δ d B : ℝ} (hδ : 0<δ) (hd : 0<d) (hr : 0≤r) (hscale : r*d^2=1) (hB : 0≤B)
(hX : ‖X‖≤B) (hX' : ∀i,‖X' i‖≤B) (hJ : ‖J‖≤B)
(hχ : |χ|≤B^2) (hχ' : ∀i,|χ' i|≤B^2)
(hu : ‖u‖≤B) (hm : ‖m‖≤d) (hm' : ∀i,‖m' i‖≤d) (ht : ‖t‖≤d)
(hell : ‖ell‖≤B*d) (hell' : ∀i,‖ell' i‖≤B*d) (hp : d*|p|≤B)
(hS : ∀v,δ*‖v‖^2≤ inner ℝ v (stableMatrix j b r X J q v))
(hS' : ∀i v,δ*‖v‖^2≤ inner ℝ v (stableMatrix j (b' i) r (X' i) J (q' i) v))
(hSmall : |j| *|χ-b| *‖X‖^2+|j*r| *‖X‖^2*
(‖m+t-(2:ℝ) • q‖*‖ell‖+2*‖q‖*‖ell+q‖)≤δ/2)
(hSmall' : ∀i,|j| *|χ' i-b' i| *‖X' i‖^2+|j*r| *‖X' i‖^2*
(‖m' i+t-(2:ℝ) • q' i‖*‖ell' i‖+2*‖q' i‖*‖ell' i+q' i‖)≤δ/2)
(h : Equations j χ r p (X*X) J u m t ell w y c)
(h' : ∀i,Equations j (χ' i) r (p' i) (X' i*X' i) J (u' i) (m' i) t (ell' i) (w' i) (y' i) (c' i))
(hDA : ∀V,columnNorm (fun i=>(s i • (X*X-X' i*X' i)) V)≤B*‖V‖)
(hDu : columnNorm (fun i=>s i • (u-u' i))≤B)
(hDχ : columnNorm (fun i=>s i*(χ-χ' i))≤B)
(hDm : columnNorm (fun i=>s i • (m-m' i))≤B*d)
(hDell : columnNorm (fun i=>s i • (ell-ell' i))≤B*d)
(hDp : d*columnNorm (fun i=>s i*(p-p' i))≤B) :
‖w‖+d*|c|+‖y‖+columnNorm (fun i=>s i • (w-w' i))+
d*columnNorm (fun i=>s i*(c-c' i))+columnNorm (fun i=>s i • (y-y' i))≤
uniformControlBudget j δ B := by
let L:=B+|j| *B^2+2*|j| *B
let W:=(1+B^2*(δ/2)⁻¹*L)*B^2*(B+2*|j| *B)
let C:=B*W+B
let Y:=(B+|j| *B^2)*W+|j| *C
let F:=(1+B^2*(δ/2)⁻¹*L)*(B*(B+Y+|j| *C)+B^2*B+
|j| *B^2*W*B+|j| *B^2*C*B+|j| *B^2*2*(B*W+B))
let G:=B*W+B+B*F
let H:=(B+|j| *B^2)*F+|j| *W*B+|j| *C*B+|j| *G
have hW0 : 0≤W := by dsimp [W,L]; positivity
have hC0 : 0≤C := by dsimp [C]; positivity
have hY0 : 0≤Y := by dsimp [Y]; positivity
have hL0 : 0≤L := by dsimp [L]; positivity
have hF0 : 0≤F := by dsimp [F]; positivity
obtain ⟨hw,hc,hy⟩:=implicit_uniform_size j χ b r p X J u m t ell q w y c
hδ hd hr hscale (sq_nonneg B) hB hB hB hB
(pow_le_pow_left₀ (norm_nonneg X) hX 2) hJ hχ hu hm ht hell hp hS hSmall h
change ‖w‖≤W at hw
change d*|c|≤C at hc
change ‖y‖≤Y at hy
have hl : ∀i,‖L₂ j (χ' i) r J (m' i+t) (ell' i)‖≤L := by
intro i
have hv : ‖m' i+t‖≤2*d := (norm_add_le _ _).trans (by linarith [hm' i])
convert L₂_normalized_bound j (χ' i) r J (m' i+t) (ell' i) hr hd.le hscale
(by norm_num : (0:ℝ)≤2) hB hv (hell' i) (hχ' i) hJ using 1; dsimp [L]; ring
have hb : ‖u+J w-(j*χ) • w-(j*c) • (m+t)‖≤B+Y+|j| *C := by
have he : u+J w-(j*χ) • w-(j*c) • (m+t)=u+y-(j*c) • t := by
rw [h.2.1]; module
rw [he]
apply (norm_sub_le _ _).trans
have hct : ‖(j*c) • t‖≤|j| *C := by
rw [norm_smul,Real.norm_eq_abs,abs_mul]
calc
_ ≤ |j| *|c| *d := mul_le_mul_of_nonneg_left ht (by positivity)
_ = |j| *(d*|c|) := by ring
_ ≤ _ := mul_le_mul_of_nonneg_left hc (abs_nonneg j)
exact add_le_add ((norm_add_le _ _).trans (add_le_add hu hy)) hct
have hf:=implicit_frobenius_estimate j χ r p X J u m t ell w y c
s χ' p' c' X' u' m' ell' w' y' q' b' h h' hδ hB hL0 hd hr hscale
hB hB hB hB hB hB hC0 (by norm_num : (0:ℝ)≤2) hX' hl hS' hSmall'
hDA hDu hDχ hDm hDell hDp hc (fun i=>(norm_add_le _ _).trans (by linarith [hm' i]))
have hf' : columnNorm (fun i=>s i • (w-w' i))≤F := by
apply hf.trans
apply mul_le_mul_of_nonneg_left _ (by positivity)
exact add_le_add (add_le_add (add_le_add (add_le_add
(mul_le_mul_of_nonneg_left hb hB) le_rfl)
(mul_le_mul_of_nonneg_right (mul_le_mul_of_nonneg_left hw (by positivity)) hB)) le_rfl)
(mul_le_mul_of_nonneg_left (add_le_add (mul_le_mul_of_nonneg_left hw hB) le_rfl) (by positivity))
have hg : d*columnNorm (fun i=>s i*(c-c' i))≤G := by
exact (implicit_scalar_columns s r p ell w c p' c' ell' w' h.2.2 (fun i=>(h' i).2.2)
hr hd hscale hB hDell hDp hB hell').trans (add_le_add
(add_le_add (mul_le_mul_of_nonneg_left hw hB) le_rfl) (mul_le_mul_of_nonneg_left hf' hB))
have hh : columnNorm (fun i=>s i • (y-y' i))≤H := by
have hh:=implicit_field_columns s j χ r p (X*X) J u m t ell w y c χ' p' c'
(fun i=>X' i*X' i) u' m' ell' w' y' h h' hB (sq_nonneg B) hd hB hB hC0
(by norm_num : (0:ℝ)≤1) hJ hχ' hDχ hDm hc (by simpa only [one_mul] using hm') hg
apply hh.trans
simp only [mul_one]
exact add_le_add (add_le_add (add_le_add (mul_le_mul_of_nonneg_left hf' (by positivity))
(mul_le_mul_of_nonneg_right (mul_le_mul_of_nonneg_left hw (abs_nonneg j)) hB)) le_rfl) le_rfl
change _≤W+C+Y+F+G+H
exact add_le_add (add_le_add (add_le_add (add_le_add (add_le_add hw hc) hy) hf') hg) hh
end SKGap.ImplicitSystem
end
end
section
noncomputable section
open scoped BigOperators Matrix.Norms.Frobenius
namespace SKGapCutoff.Recipe
open Primary SKGap.ImplicitSystem
variable {n : ℕ}
lemma halfDiff_column (U : VectorFields n) (x : Spin n) (k : Fin n) :
((spin x k/2) • ((WithLp.toLp 2 (U x) : Euclid n)-WithLp.toLp 2 (U (flip x k))))=
WithLp.toLp 2 (fun i=>derivativeMatrix U x i k) := by
ext i
change (spin x k/2)*(U x i-U (flip x k) i)=halfDiff k (fun y=>U y i) x
rw [halfDiff_as_flip]; ring
lemma columnNorm_halfDiff (U : VectorFields n) (x : Spin n) :
columnNorm (fun k=>(spin x k/2) •
((WithLp.toLp 2 (U x) : Euclid n)-WithLp.toLp 2 (U (flip x k))))=‖derivativeMatrix U x‖ := by
simp only [halfDiff_column]
exact columnNorm_matrix _
lemma columnNorm_scalar_halfDiff (f : Spin n→ℝ) (x : Spin n) :
columnNorm (fun k=>(spin x k/2)*(f x-f (flip x k)))=‖derivativeVector f x‖ := by
have he : (fun k=>(spin x k/2)*(f x-f (flip x k)))=fun k=>halfDiff k f x := by
ext k; rw [halfDiff_as_flip]; ring
rw [he]
rfl
lemma diagonal_halfDiff_columns (a : VectorFields n) (x : Spin n) {R : ℝ}
(hR : 0≤R) (ha : ∀i,∑k,(derivativeMatrix a x i k)^2≤R^2)
(V : Euclid n) :
columnNorm (fun k=>((spin x k/2) •
(Matrix.toEuclideanCLM (𝕜:=ℝ) (Matrix.diagonal (a x))-
Matrix.toEuclideanCLM (𝕜:=ℝ) (Matrix.diagonal (a (flip x k))))) V)≤R*‖V‖ := by
apply coefficient_diagonal_columns (fun _=>a x) (fun k=>a (flip x k)) (fun k=>spin x k/2) hR
intro i
convert ha i using 1
apply Finset.sum_congr rfl
intro k _
congr 1
rw [derivativeMatrix,halfDiff_as_flip]
ring
lemma implicit_tuple_small (w y : VectorFields n) (c : Spin n→ℝ) (x : Spin n)
{d C : ℝ} (hd : 0≤d) (hC : 0≤C)
(h : vectorNorm (w x)+d*|c x|+vectorNorm (y x)+‖derivativeMatrix w x‖+
d*‖derivativeVector c x‖+‖derivativeMatrix y x‖≤C) :
SmallBound w x C ∧ SmallBound y x C ∧
|d*c x|≤C ∧ ‖derivativeVector (fun z=>d*c z) x‖≤C := by
have hw0:=vectorNorm_nonneg (w x)
have hy0:=vectorNorm_nonneg (y x)
have hc0:=mul_nonneg hd (abs_nonneg (c x))
have hw1:=norm_nonneg (derivativeMatrix w x)
have hy1:=norm_nonneg (derivativeMatrix y x)
have hc1:=mul_nonneg hd (norm_nonneg (derivativeVector c x))
refine ⟨⟨hC,by linarith,by linarith⟩,⟨hC,by linarith,by linarith⟩,?_,?_⟩
· rw [abs_mul,abs_of_nonneg hd]; linarith
· have he : derivativeVector (fun z=>d*c z) x=d • derivativeVector c x := by
ext k
change halfDiff k (fun z=>d*c z) x=d*halfDiff k c x
simp [halfDiff]; ring
rw [he,norm_smul,Real.norm_eq_abs,abs_of_nonneg hd]
linarith
end SKGapCutoff.Recipe
end
end
end OAI