roseking's picture
Add lean source and binary files (part 120)
f205175 verified
Raw History Blame Contribute Delete
26.5 kB
import Mathlib
import OAI.Probability.CoordinateSweeps.Perturbation
namespace OAI
open scoped Matrix.Norms.L2Operator
namespace CoordinateSweeps
lemma moment_le_exp_of_logMoment_le {t B : ℝ} (ht : 0≤t)
(h : logMoment t ≤ (B:EReal)) : t ≤ Real.exp B := by
by_cases hz : t=0
· rw [hz]; exact (Real.exp_pos _).le
· rw [logMoment,ite_eq_right hz] at h
have hh : Real.log t ≤ B := by exact_mod_cast h
simpa only [Real.exp_log (lt_of_le_of_ne ht (Ne.symm hz))] using Real.exp_le_exp.mpr hh
lemma logMoment_le_of_moment_le_exp {t B : ℝ} (ht : 0≤t) (h : t≤Real.exp B) :
logMoment t ≤ (B:EReal) := by
simpa only [Real.log_exp] using logMoment_le_of_le ht (Real.exp_pos B) h
end CoordinateSweeps
namespace CoordinateSweeps.Grid.Holes
open SparseScalar SparseDimension ScalarInduction
variable {G : Grid} {h r : ℕ} (H : G.Holes h)
lemma conditionalAverage_free_cancel (hf : H.Feasible) (z : ℝ) (σ : UnitaryIrrep H.stabilizer) :
H.conditionalAverage hf z ((σ.pullback H.stabilizerFreeEquiv.symm).pullback H.stabilizerFreeEquiv)=
H.conditionalAverage hf z σ := by
rw [H.conditionalAverage_eq_sum,H.conditionalAverage_eq_sum]
apply Finset.sum_congr rfl
intro ω hω
change (_:ℂ) • σ.matrix (H.stabilizerFreeEquiv.symm (H.stabilizerFreeEquiv (H.residual hf ω)))=_
rw [MulEquiv.symm_apply_apply]
/-- Entire nonautomatic sparse-dimension branch of the conditional main,
with the actual stabilizer irrep, actual feasible paths and a common real z interval. -/
theorem conditional_sparse_main (hr : ScaleLarge r) (hrS : ScaleReady r)
(hG : G.Allowed r) (hS : MainSizeReady SparseScalar.q G.size)
(hf : H.Feasible) {zStar : ℝ} (hζ : SparsePerturb r zStar) {z : ℝ} (hz : z∈Set.Icc 0 zStar)
(σ : UnitaryIrrep H.stabilizer) (hσ : σ.dimension≠1)
(ha : ¬ (1+c G.size)*Real.log σ.dimension ≤ e G.size*h*Real.log G.size-H.cost)
(hF : Real.log σ.dimension < (G.size:ℝ)^(1-a/4)) :
schattenMoment SparseScalar.q (H.conditionalAverage hf z σ) ≤
Real.exp (-c G.size*Real.log σ.dimension+e G.size*h*Real.log G.size-H.cost) := by
let ρ := σ.pullback H.stabilizerFreeEquiv.symm
obtain ⟨k,t,hkt,ht,hD,hkM,⟨L⟩⟩ := exists_level ρ
have hΩ : Fintype.card (H.FreeAt 0)≤G.size := by rw [H.card_freeAt]; exact Nat.sub_le _ _
have hks := hkM.trans hΩ
have hlogs := level_log_bounds ρ G.size_pos hΩ hkt ht hD
change Real.log σ.dimension≤k*Real.log G.size ∧ (k:ℝ)≤4*Real.log σ.dimension at hlogs
have hk : 1≤k := by
by_contra hh
have he : k=0 := by omega
rw [he,pow_zero] at hD
have hdim : σ.dimension=1 := by have hh0:=σ.positive; change σ.dimension≤1 at hD; omega
exact hσ hdim
have hL := (scale_coefficients hr G hG).1
have hc := (scale_coefficients hr G hG).2.1
have hc1 : c G.size≤1 := hc.trans (by norm_num [c0,a])
have hF0 : 0≤Real.log σ.dimension := Real.log_nonneg (by exact_mod_cast σ.positive)
have hallow := H.allowance_lower hr hG
have hn := lt_of_not_ge ha
have hhh : (h:ℝ)*Real.log G.size ≤ K0*Real.log σ.dimension := by
have hm := mul_le_mul_of_nonneg_right hc1 hF0
norm_num [e0,a,K0] at hallow ⊢
nlinarith
have hh : (h:ℝ)≤K0*k := by
have hm := mul_le_mul_of_nonneg_left hlogs.1 (by norm_num [K0] : 0≤K0)
exact (mul_le_mul_iff_right₀ hL).mp (by nlinarith)
have hsp : ((h+k:ℕ):ℝ)≤(G.size:ℝ)^(1-theta) := by
have hh0 := (Nat.cast_nonneg h : (0:ℝ)≤h)
have hhle : (h:ℝ)≤K0*Real.log σ.dimension := by nlinarith [hS.one]
have hsum : ((h+k:ℕ):ℝ)≤(100004:ℝ)*Real.log σ.dimension := by
push_cast
norm_num [K0] at hhle
linarith [hlogs.2]
apply hsum.trans
apply (mul_le_mul_of_nonneg_left hF.le (by norm_num : (0:ℝ)≤100004)).trans
simpa only [theta] using hS.sparse
have hnorm := H.level_sparse_norm hrS hG hf hζ hz hk hks hh hsp ρ L
rw [show ρ=σ.pullback H.stabilizerFreeEquiv.symm from rfl,H.conditionalAverage_free_cancel] at hnorm
let : NeZero σ.dimension := ⟨σ.positive.ne'⟩
have hp := pow_le_pow_left₀ (norm_nonneg (H.conditionalAverage hf z σ)) hnorm (2*SparseScalar.q)
calc
_ ≤ (σ.dimension:ℝ)*‖H.conditionalAverage hf z σ‖^(2*SparseScalar.q) := trace_moment_le _ _
_ ≤ (σ.dimension:ℝ)*((G.size:ℝ)^(-rho*k))^(2*SparseScalar.q) :=
mul_le_mul_of_nonneg_left hp (Nat.cast_nonneg _)
_ = Real.exp (Real.log σ.dimension-4*k*Real.log G.size) := by
rw [rpow_exp _ _ (by exact_mod_cast G.size_pos),←Real.exp_nat_mul]
nth_rw 1 [←Real.exp_log (by exact_mod_cast σ.positive : (0:ℝ)<σ.dimension)]
rw [←Real.exp_add]
congr 1
norm_num [SparseScalar.q,rho]
ring
_ ≤ Real.exp (-3*Real.log σ.dimension) := Real.exp_le_exp.mpr (by nlinarith [hlogs.1])
_ ≤ _ := Real.exp_le_exp.mpr (by
have hm := mul_le_mul_of_nonneg_right hc1 hF0
have ha0 := H.allowance_nonneg hr hG
linarith)
end CoordinateSweeps.Grid.Holes
namespace CoordinateSweeps
/-- Real exponential version of the exact conditional main estimate, used only
as the induction predicate; its equivalence to logMoment includes zero moments. -/
def MomentBound (G : Grid) (q : ℕ) (z : ℝ) : Prop :=
∀ (h : ℕ) (H : G.Holes h) (hf : H.Feasible) (σ : UnitaryIrrep H.stabilizer),
schattenMoment q (H.conditionalAverage hf z σ) ≤
Real.exp (-c G.size*Real.log σ.dimension+e G.size*h*Real.log G.size-H.cost)
noncomputable def cHat (s : ℕ) : ℝ := c s+1/(20*Real.sqrt (Real.log s))
noncomputable def eHat (s : ℕ) : ℝ := e s-1/(20*Real.sqrt (Real.log s))
end CoordinateSweeps
namespace CoordinateSweeps.Grid.Holes
open ScalarInduction YoungCorner
variable {A B : Grid} {r h q : ℕ} (H : (concat A B).Holes h)
theorem hook_auxiliary (hr : ScaleLarge r) (hA : A.Allowed r) (hB : B.Allowed r)
(hAB : A.b≤B.b) (hBA : B.b≤2*A.b) (hq : 1≤q)
(hS : MainSizeReady q (concat A B).size)
(z : ℝ) (hIA : MomentBound A q z) (hIB : MomentBound B q z)
(hf : H.Feasible) (σ : UnitaryIrrep H.stabilizer)
(p : ℕ) (hp : 0<p) (hpp : (p:ℝ)≤((concat A B).size:ℝ)^a)
(μ : YoungDiagram) (eB : H.FreeAt 0 ≃ Boxes μ)
(hσ : hasShape μ (Equiv.refl _) (σ.pullback (H.boxesChart μ eB)).asRepresentation)
(hhook : Hook μ p) :
schattenMoment q (H.conditionalAverage hf z σ) ≤
Real.exp (-cHat (concat A B).size*Real.log σ.dimension+
eHat (concat A B).size*h*Real.log (concat A B).size-H.cost+
((concat A B).size:ℝ)^((9:ℝ)/10)) := by
let G := concat A B
let L := Real.log G.size
let cStar := c0+(11/10:ℝ)/Real.sqrt L
let eStar := e0-(11/10:ℝ)/Real.sqrt L
have hG : G.Allowed r := (concat_allowed A B r).mpr ⟨hA,hB⟩
have hL : 0<L := (scale_coefficients hr G hG).1
have hLA := (scale_coefficients hr A hA).1
have hLB := (scale_coefficients hr B hB).1
have hlogs := balanced_logs hA hB hAB hBA
have hcsA : cStar≤c A.size ∧ e A.size≤eStar := improved_coefficients hL hLA hlogs.2.1
have hcsB : cStar≤c B.size ∧ e B.size≤eStar := improved_coefficients hL hLB hlogs.2.2.2
have hc : 0≤cStar := by
dsimp [cStar]
have hc0 : 0≤c0 := by norm_num [c0,a]
positivity
have hc2 : cStar≤2*c0 := hcsA.1.trans (scale_coefficients hr A hA).2.1
have hcq : cStar≤q := hc2.trans ((by norm_num [c0,a] : 2*c0≤1).trans (by exact_mod_cast hq))
have hR : ∀ y : B.Slot, ∀ τ : UnitaryIrrep (H.rowHoles y).stabilizer,
schattenMoment q ((H.rowHoles y).conditionalAverage (H.rowHoles y).feasible_of_disjoint z τ) ≤
Real.exp (-cStar*Real.log τ.dimension+eStar*H.rowCount y*Real.log A.size-(H.rowHoles y).cost) := by
intro y τ
apply (hIA _ _ _ τ).trans (Real.exp_le_exp.mpr ?_)
have hF := Real.log_nonneg (show (1:ℝ)≤τ.dimension by exact_mod_cast τ.positive)
have hc' := mul_le_mul_of_nonneg_right hcsA.1 hF
have he' := mul_le_mul_of_nonneg_right hcsA.2
(show 0≤(H.rowCount y:ℝ)*Real.log A.size by positivity)
nlinarith
have hC : ∀ x : A.Slot, ∀ τ : UnitaryIrrep (H.columnHoles x).stabilizer,
schattenMoment q ((H.columnHoles x).conditionalAverage (H.columnHoles x).feasible_of_disjoint z τ) ≤
Real.exp (-cStar*Real.log τ.dimension+eStar*H.columnCount x*Real.log B.size-(H.columnHoles x).cost) := by
intro x τ
apply (hIB _ _ _ τ).trans (Real.exp_le_exp.mpr ?_)
have hF := Real.log_nonneg (show (1:ℝ)≤τ.dimension by exact_mod_cast τ.positive)
have hc' := mul_le_mul_of_nonneg_right hcsB.1 hF
have he' := mul_le_mul_of_nonneg_right hcsB.2
(show 0≤(H.columnCount x:ℝ)*Real.log B.size by positivity)
nlinarith
have hs1 : (1:ℝ)<G.size := (Real.log_pos_iff (by exact_mod_cast G.size_pos.le)).mp hL
have hpS : p≤G.size := by
have hx : (G.size:ℝ)^a≤G.size := by
simpa only [Real.rpow_one] using Real.rpow_le_rpow_of_exponent_le hs1.le (show a≤1 by norm_num [a])
exact_mod_cast hpp.trans hx
have hAS : A.size≤G.size := by dsimp [G]; rw [concat_size]; nlinarith [A.size_pos,B.size_pos]
have hBS : B.size≤G.size := by dsimp [G]; rw [concat_size]; nlinarith [A.size_pos,B.size_pos]
have ht := H.actual_hook_bound p hp hf z q (by omega) cStar eStar hc hcq G.size hpS hAS hBS σ hR hC μ eB hσ hhook
have hsizes := balanced_sizes hA hB hAB hBA
have hErr := hook_error_bound hs1 q A.size B.size p cStar hc hc2 hsizes.2.1 hsizes.2.2.2 hpp
have hroot : 2/e0≤Real.sqrt L := (Real.le_sqrt (by norm_num [e0,a]) hL.le).mpr
(hr.2.1.trans (G.log_size_lower_one hG))
have hgap := hook_strengthening hL hroot hc2
have hcompare := hook_comparison (F:=Real.log σ.dimension) (h:=(h:ℝ)) (E:=
(((2*q+1:ℕ):ℝ)*((A.size+B.size)*((2*p)*(2*p)):ℕ)+cStar*((A.size+B.size)*(41*p^2):ℕ))*Real.log (G.size+1:ℕ))
hL (Real.log_nonneg (by exact_mod_cast σ.positive)) (Nat.cast_nonneg _) hgap.1 hgap.2
have hlogsum : Real.log A.size+Real.log B.size=L := by
dsimp [L,G]
rw [concat_size,Nat.cast_mul,Real.log_mul (by exact_mod_cast A.size_pos.ne') (by exact_mod_cast B.size_pos.ne')]
rw [hlogsum] at ht
apply ht.trans (Real.exp_le_exp.mpr ?_)
have hES : _ ≤ (G.size:ℝ)^((9:ℝ)/10) := hErr.trans hS.hook
simp only [Nat.cast_add,Nat.cast_one,Nat.cast_mul] at hcompare hES ⊢
dsimp [cHat,eHat,c,e]
change _ ≤ -(c0+1/Real.sqrt L+1/(20*Real.sqrt L))*Real.log σ.dimension+
(e0-1/Real.sqrt L-1/(20*Real.sqrt L))*h*L-H.cost+(G.size:ℝ)^((9:ℝ)/10)
dsimp [cStar,eStar] at *
nlinarith
end CoordinateSweeps.Grid.Holes
namespace CoordinateSweeps.YoungCorner
lemma log_factorial_lower (k : ℕ) (hk : 0<k) :
(k:ℝ)*Real.log k-k ≤ Real.log (k.factorial:ℝ) := by
have hs := Stirling.le_log_factorial_stirling hk.ne'
have hk1 : (1:ℝ)≤k := by exact_mod_cast hk
have hl := Real.log_nonneg hk1
have hp : 0≤Real.log (2*Real.pi) := Real.log_nonneg (by linarith [Real.pi_gt_three])
linarith
lemma shape_finrank_pos (μ : YoungDiagram) :
0 < Module.finrank ℂ (shapeSubrep μ (Equiv.refl _)).toSubmodule := by
have : Nontrivial (shapeSubrep μ (Equiv.refl _)).toSubmodule :=
by
by_contra hn
have : Subsingleton (shapeSubrep μ (Equiv.refl _)).toSubmodule := not_nontrivial_iff_subsingleton.mp hn
apply bot_ne_top (α := Subrepresentation (shapeSubrep μ (Equiv.refl _)).toRepresentation)
exact Subrepresentation.toSubmodule_injective (Subsingleton.elim _ _)
exact Module.finrank_pos
/-- The translated removed diagram has the entropy required in the large-k
branch, using the checked factorial/rank-count lower bound. -/
lemma removed_dimension_entropy (μ : YoungDiagram) (p s : ℕ)
(hs : 0<s) (hM : Fintype.card (Boxes μ) ≤ s)
(hfloor : (s:ℝ)^a ≤ p+1) (hL : 800 ≤ Real.log s)
(hk : (s:ℝ)^(1-a/2) ≤ Fintype.card (Boxes (removedPart μ p))) :
(a/4)*(Fintype.card (Boxes (removedPart μ p)):ℝ)*Real.log s ≤
Real.log (Module.finrank ℂ (shapeSubrep (removedPart μ p) (Equiv.refl _)).toSubmodule) := by
let k := Fintype.card (Boxes (removedPart μ p))
let D := Module.finrank ℂ (shapeSubrep (removedPart μ p) (Equiv.refl _)).toSubmodule
let L := 2*(Fintype.card (Boxes μ)/(p+1))
have hs0 : (0:ℝ)<s := by exact_mod_cast hs
have hk0 : 0<k := by
have hh : (0:ℝ)<k := (Real.rpow_pos_of_pos hs0 _).trans_le hk
exact_mod_cast hh
have hD0 : 0<D := shape_finrank_pos _
have hLp : 0<L := by
obtain ⟨x⟩ := Fintype.card_pos_iff.mp hk0
exact Nat.zero_le (x.val.1+x.val.2) |>.trans_lt (removedPart_rank_lt μ p x)
have hL0 : (0:ℝ)<L := by exact_mod_cast hLp
have hc := shape_dimension_entropy (removedPart μ p)
(shapeSubrep (removedPart μ p) (Equiv.refl _)).toRepresentation
(shapeSubrep_hasShape _ _) L (removedPart_rank_lt μ p)
have hc' : (k.factorial:ℝ) ≤ (L:ℝ)^k*D := by exact_mod_cast hc
have hlog := Real.log_le_log (by exact_mod_cast Nat.factorial_pos k : (0:ℝ)<k.factorial) hc'
rw [Real.log_mul (by positivity : (L:ℝ)^k≠0) (by exact_mod_cast hD0.ne'),Real.log_pow] at hlog
have hfac := log_factorial_lower k hk0
have hLp' : (L:ℝ)*(p+1) ≤ 2*s := by
have hh := Nat.div_mul_le_self (Fintype.card (Boxes μ)) (p+1)
have hh' : (Fintype.card (Boxes μ)/(p+1))*(p+1) ≤ s := hh.trans hM
dsimp [L]
exact_mod_cast (show 2*(Fintype.card (Boxes μ)/(p+1))*(p+1)≤2*s by nlinarith [hh'])
have hLupper : (L:ℝ) ≤ 2*(s:ℝ)^(1-a) := by
have hh := mul_le_mul_of_nonneg_left hfloor hL0.le
have hhs : (L:ℝ)*(s:ℝ)^a ≤ 2*s := hh.trans hLp'
apply (mul_le_mul_iff_left₀ (Real.rpow_pos_of_pos hs0 a)).mp
calc
_ ≤ 2*(s:ℝ) := hhs
_ = 2*(s:ℝ)^(1-a)*(s:ℝ)^a := by rw [mul_assoc,←Real.rpow_add hs0]; norm_num
have hLogL : Real.log L ≤ Real.log 2+(1-a)*Real.log s := by
have hh := Real.log_le_log hL0 hLupper
rw [Real.log_mul (by norm_num : (2:ℝ)≠0) (Real.rpow_pos_of_pos hs0 _).ne',Real.log_rpow hs0] at hh
exact hh
have hLogk : (1-a/2)*Real.log s ≤ Real.log k := by
have hh := Real.log_le_log (Real.rpow_pos_of_pos hs0 (1-a/2)) hk
simpa only [Real.log_rpow hs0] using hh
have hl2 : Real.log 2≤1 := by
have hh := Real.log_le_sub_one_of_pos (by norm_num : (0:ℝ)<2)
linarith
have hkR : (0:ℝ)≤k := Nat.cast_nonneg _
have hh1 := mul_le_mul_of_nonneg_left hLogL hkR
have hh2 := mul_le_mul_of_nonneg_left hLogk hkR
have hh3 : (a/4)*Real.log s ≥ Real.log 2+1 := by norm_num [a] at *; linarith
have hh4 := mul_le_mul_of_nonneg_left hh3 hkR
change (a/4)*(k:ℝ)*Real.log s ≤ Real.log D
nlinarith
end CoordinateSweeps.YoungCorner
namespace CoordinateSweeps.Grid.Holes
open YoungCorner ScalarInduction
variable {G : Grid} {h : ℕ} (H : G.Holes h)
lemma exists_initial_shape (σ : UnitaryIrrep H.stabilizer) :
∃ (μ : YoungDiagram) (eB : H.FreeAt 0 ≃ Boxes μ),
hasShape μ (Equiv.refl _) (σ.pullback (H.boxesChart μ eB)).asRepresentation := by
let τ := (σ.pullback H.stabilizerFreeEquiv.symm).asRepresentation
obtain ⟨p,hp⟩ := exists_partitionShape τ
refine ⟨diagramOfPartition p,partitionFilling p,?_⟩
have hh : hasShape (V:=Fin σ.dimension → ℂ) (diagramOfPartition p)
((partitionFilling p).symm.trans (partitionFilling p))
(τ.comp (partitionFilling p).symm.permCongrHom) :=
(hasShape_reparam (diagramOfPartition p) (partitionFilling p).symm (partitionFilling p) τ).mpr hp
change hasShape (V:=Fin σ.dimension → ℂ) (diagramOfPartition p) (Equiv.refl _)
(τ.comp (partitionFilling p).symm.permCongrHom)
simpa only [Equiv.symm_trans_self] using hh
lemma augmented_boxesChart (μ : YoungDiagram) (p : ℕ) (eB : H.FreeAt 0 ≃ Boxes μ)
(x : H.Placement (k := Fintype.card (Boxes (removedPart μ p))))
(ω₀ : {ω : G.Choices // H.Compatible ω}) :
(H.augmented x ω₀).boxesChart (hookPart μ p) (H.augmentedRetainedEquiv μ p eB x ω₀).symm=
H.augmentedRetainedChart μ p eB x ω₀ := by
rfl
lemma retained_log_dimension (μ : YoungDiagram) (p : ℕ) (eB : H.FreeAt 0 ≃ Boxes μ)
(σ : UnitaryIrrep H.stabilizer)
(ρ : UnitaryIrrep (H.placementChart (H.removedPlacement μ p eB)).stabilizer)
(hd : σ.dimension≤(Fintype.card (Boxes μ))^(Fintype.card (Boxes (removedPart μ p)))*ρ.dimension) :
Real.log σ.dimension≤Real.log ρ.dimension+
Fintype.card (Boxes (removedPart μ p))*Real.log G.size := by
have hM : Fintype.card (Boxes μ)≤G.size := by
rw [←Fintype.card_congr eB,H.card_freeAt]
exact Nat.sub_le _ _
have hh := hd.trans (Nat.mul_le_mul_right _ (Nat.pow_le_pow_left hM _))
have hhR : (σ.dimension:ℝ)≤(G.size:ℝ)^(Fintype.card (Boxes (removedPart μ p)))*ρ.dimension := by exact_mod_cast hh
have hlog := Real.log_le_log (by exact_mod_cast σ.positive : (0:ℝ)<σ.dimension) hhR
have hs0 : (0:ℝ)<G.size := by exact_mod_cast G.size_pos
rw [Real.log_mul (by positivity : (G.size:ℝ)^(Fintype.card (Boxes (removedPart μ p)))≠0)
(by exact_mod_cast ρ.positive.ne'),Real.log_pow] at hlog
linarith
end CoordinateSweeps.Grid.Holes
namespace CoordinateSweeps.Grid.Holes
open YoungCorner ScalarInduction
variable {A B : Grid} {r h q : ℕ} (H : (concat A B).Holes h)
/-- Large-dimension branch of the exact main: actual retained constituent,
actual augmented paths, induced placement-cycle estimate, and absorbed entropy. -/
theorem conditional_large_main (hr : ScaleLarge r) (hA : A.Allowed r) (hB : B.Allowed r)
(hAB : A.b≤B.b) (hBA : B.b≤2*A.b) (hq : 1≤q)
(hS : MainSizeReady q (concat A B).size)
(z : ℝ) (hz : 0≤z) (hz' : z<1)
(hlo : ∀ j g, (1/2:ℝ)*FiniteLaw.uniform _ g≤lineLaw ((concat A B).bits j) z hz hz'.le g)
(hhi : ∀ j g, lineLaw ((concat A B).bits j) z hz hz'.le g≤2*FiniteLaw.uniform _ g)
(hIA : MomentBound A q z) (hIB : MomentBound B q z)
(hf : H.Feasible) (σ : UnitaryIrrep H.stabilizer)
(hF : ((concat A B).size:ℝ)^(1-a/4)≤Real.log σ.dimension) :
schattenMoment q (H.conditionalAverage hf z σ)≤
Real.exp (-c (concat A B).size*Real.log σ.dimension+
e (concat A B).size*h*Real.log (concat A B).size-H.cost) := by
let G := concat A B
let p := ⌊(G.size:ℝ)^a⌋₊
let L := Real.log G.size
obtain ⟨μ,eB,hσ⟩ := H.exists_initial_shape σ
obtain ⟨ρ,hρ,hm,hd⟩ := H.exists_retained_irrep μ p eB σ hσ
let k := Fintype.card (Boxes (removedPart μ p))
let D := Module.finrank ℂ (shapeSubrep (removedPart μ p) (Equiv.refl _)).toSubmodule
have hG : G.Allowed r := (concat_allowed A B r).mpr ⟨hA,hB⟩
have hcoeff := scale_coefficients hr G hG
have hL : 0<L := hcoeff.1
have hs : (1:ℝ)<G.size := (Real.log_pos_iff (by exact_mod_cast G.size_pos.le)).mp hL
have hs0 : (0:ℝ)<G.size := by exact_mod_cast G.size_pos
have hp : 0<p := by
change 1≤⌊(G.size:ℝ)^a⌋₊
apply (Nat.one_le_floor_iff _).mpr
exact Real.one_le_rpow hs.le (by norm_num [a])
have hpp : (p:ℝ)≤(G.size:ℝ)^a := Nat.floor_le (Real.rpow_nonneg hs0.le _)
have hfloor : (G.size:ℝ)^a≤p+1 := (Nat.lt_floor_add_one _).le
let budget := -cHat G.size*Real.log ρ.dimension+eHat G.size*(h+k)*L+(G.size:ℝ)^((9:ℝ)/10)
have hT : ∀ (x : H.Placement (k:=k)) (ω₀ : {ω : G.Choices // H.Compatible ω}),
schattenMoment q ((H.augmented x ω₀).conditionalAverage (H.augmented_feasible x ω₀) z
(H.augmentedIrrep (H.removedPlacement μ p eB) x ω₀ ρ))≤Real.exp (budget-(H.augmented x ω₀).cost) := by
intro x ω₀
have hsH := H.augmented_hasShape μ p eB ρ hρ x ω₀
rw [←H.augmented_boxesChart] at hsH
have hh := (H.augmented x ω₀).hook_auxiliary hr hA hB hAB hBA hq hS z hIA hIB
(H.augmented_feasible x ω₀) (H.augmentedIrrep (H.removedPlacement μ p eB) x ω₀ ρ)
p hp hpp (hookPart μ p) (H.augmentedRetainedEquiv μ p eB x ω₀).symm hsH (hookPart_property μ p)
apply hh.trans_eq
congr 1
change -cHat (concat A B).size*Real.log ρ.dimension+
eHat (concat A B).size*((h+k:ℕ):ℝ)*Real.log (concat A B).size-
(H.augmented x ω₀).cost+((concat A B).size:ℝ)^((9:ℝ)/10)=budget-(H.augmented x ω₀).cost
dsimp [budget,L,k,G]
push_cast
ring
have hind := H.actual_induced_endgame hf (H.removedPlacement μ p eB) ρ σ hz hz' hlo hhi q (by omega) budget hT
have hMoment0 := H.conditionalMoment_nonneg hf z σ q
have hD0 : 0<D := shape_finrank_pos _
have hD0R : (0:ℝ)<D := by exact_mod_cast hD0
have hDT : (D:ℝ)*schattenMoment q (H.conditionalAverage hf z σ)≤Real.exp (budget-H.cost+Real.log 4*k*G.b) :=
(mul_le_mul_of_nonneg_right (by exact_mod_cast hm) hMoment0).trans hind
have ht : schattenMoment q (H.conditionalAverage hf z σ)≤
Real.exp (budget-H.cost+Real.log 4*k*G.b-Real.log D) := by
rw [Real.exp_sub,Real.exp_log hD0R]
exact (le_div_iff₀ hD0R).mpr (by simpa only [mul_comm] using hDT)
have hD := H.retained_log_dimension μ p eB σ ρ hd
have hM : Fintype.card (Boxes μ)≤G.size := by
rw [←Fintype.card_congr eB,H.card_freeAt]
exact Nat.sub_le _ _
have h800 : 800≤Real.log G.size := by
have hh := hr.2.1.trans (G.log_size_lower_one hG)
norm_num [e0,a] at hh
linarith
have hEnt : (G.size:ℝ)^(1-a/2)≤k → (a/4)*(k:ℝ)*L≤Real.log D := by
intro hh
exact removed_dimension_entropy μ p G.size G.size_pos hM hfloor h800 hh
have hcost := removed_cost_bound hs (Nat.cast_nonneg k) (Nat.cast_nonneg G.b) hcoeff.2.2.2 hF
(Real.log_nonneg (by exact_mod_cast hD0 : (1:ℝ)≤D)) hS hEnt
have hscalar := removed_endgame L (Real.log σ.dimension) (Real.log ρ.dimension) (Real.log D)
k h G.b H.cost G.size ((G.size:ℝ)^((9:ℝ)/10)) hL
(Real.log_nonneg (by exact_mod_cast σ.positive)) (Nat.cast_nonneg _) (Nat.cast_nonneg _) hD
(Real.sqrt_pos.mpr hL) hcost
apply ht.trans (Real.exp_le_exp.mpr ?_)
simpa only [budget,cHat,eHat,c,e,L] using hscalar
end CoordinateSweeps.Grid.Holes
namespace CoordinateSweeps
open Filter
lemma eventually_scaleLarge : ∀ᶠ r : ℕ in atTop, ScaleLarge r := by
obtain ⟨r₀,hr₀⟩ := exists_scaleLarge
filter_upwards [eventually_ge_atTop r₀] with r hr
have hh : (r₀:ℝ)*Real.log 2 ≤ (r:ℝ)*Real.log 2 :=
mul_le_mul_of_nonneg_right (by exact_mod_cast hr) (Real.log_nonneg (by norm_num))
exact ⟨hr₀.1.trans hr,hr₀.2.1.trans hh,hr₀.2.2.trans hh⟩
lemma exists_main_scale : ∃ r : ℕ, ScaleLarge r ∧ SparseScalar.ScaleReady r ∧
∀ G : Grid, G.Allowed r → ScalarInduction.MainSizeReady SparseScalar.q G.size := by
obtain ⟨S,hS⟩ := eventually_atTop.mp (ScalarInduction.eventually_mainSizeReady SparseScalar.q)
have hp : Tendsto (fun r : ℕ => (2:ℝ)^r) atTop atTop :=
tendsto_pow_atTop_atTop_of_one_lt (by norm_num)
have hall : ∀ᶠ r : ℕ in atTop, ScaleLarge r ∧ SparseScalar.ScaleReady r ∧ S≤(2:ℝ)^r := by
filter_upwards [eventually_scaleLarge,SparseScalar.eventually_scaleReady,
hp.eventually (eventually_ge_atTop S)] with r h1 h2 h3
exact ⟨h1,h2,h3⟩
obtain ⟨r,hr,hs,ht⟩ := hall.exists
exact ⟨r,hr,hs,fun G hG => hS G.size (ht.trans (G.pow_r_le_size hG))⟩
/-- Strong induction on the literal ordered coordinate count; every child is
an actual conditioned row/column grid, not a surrogate representation law. -/
theorem all_grid_moment {r : ℕ} (hr : ScaleLarge r) (hrS : SparseScalar.ScaleReady r)
(hS : ∀ G : Grid, G.Allowed r → ScalarInduction.MainSizeReady SparseScalar.q G.size)
{zStar : ℝ} (hζ : SparsePerturb r zStar) {z : ℝ} (hz : z∈Set.Icc 0 zStar) :
∀ G : Grid, G.Allowed r → MomentBound G SparseScalar.q z := by
have hzB : z≤baseZeta r := hz.2.trans hζ.2.1
have hz1 : z<1 := lt_of_le_of_lt (hzB.trans (baseZeta_le_half r)) (by norm_num)
have hq : 1≤SparseScalar.q := by norm_num [SparseScalar.q]
have aux : ∀ n : ℕ, ∀ G : Grid, G.b=n → G.Allowed r → MomentBound G SparseScalar.q z := by
intro n
induction n using Nat.strong_induction_on with
| h n ih =>
intro G hb hG h H hf σ
have hnonneg := H.conditionalMoment_nonneg hf z σ SparseScalar.q
by_cases hone : G.b=1
· exact moment_le_exp_of_logMoment_le hnonneg
(Grid.conditional_main_b_one hr G hone hG H hf hz.1 hzB σ hq)
by_cases hdim : σ.dimension=1
· exact moment_le_exp_of_logMoment_le hnonneg
(H.conditional_dimension_one hr hG hf hz.1 hz1 σ hdim SparseScalar.q)
by_cases haut : (1+c G.size)*Real.log σ.dimension ≤ e G.size*h*Real.log G.size-H.cost
· exact moment_le_exp_of_logMoment_le hnonneg
(H.conditional_automatic hf hz.1 hz1 σ SparseScalar.q haut)
by_cases hF : Real.log σ.dimension < (G.size:ℝ)^(1-a/4)
· exact H.conditional_sparse_main hr hrS hG (hS G hG) hf hζ hz σ hdim haut hF
have hlarge : (G.size:ℝ)^(1-a/4)≤Real.log σ.dimension := le_of_not_gt hF
have hb2 : 2≤G.b := by have hh:=G.positive; omega
obtain ⟨A,B,hAB,hA,hB,hab,hba⟩ := G.exists_half_concat hb2
have hallowed : A.Allowed r ∧ B.Allowed r :=
(Grid.concat_allowed A B r).mp (by simpa only [hAB] using hG)
have hIA : MomentBound A SparseScalar.q z := ih A.b (by omega) A rfl hallowed.1
have hIB : MomentBound B SparseScalar.q z := ih B.b (by omega) B rfl hallowed.2
subst G
exact H.conditional_large_main hr hallowed.1 hallowed.2 hab hba hq
(hS _ hG) z hz.1 hz1
(fun j g => (lineLaw_base_bounds (hG j).2 hz.1 hzB g).1)
(fun j g => (lineLaw_base_bounds (hG j).2 hz.1 hzB g).2)
hIA hIB hf σ hlarge
exact fun G hG => aux G.b G rfl hG
/-- Manuscript03 thm:conditional / ac:main, with c₀=e₀=a/100,
a=1/100, natural logarithms, unnormalized integer Schatten moments,
all feasible disjoint paths (including none and all), and log(0)=−∞. -/
theorem conditional_main : ConditionalMain := by
obtain ⟨r,hr,hrS,hS⟩ := exists_main_scale
obtain ⟨zStar,hζ⟩ := exists_sparsePerturb r
have hq : 1≤SparseScalar.q := by norm_num [SparseScalar.q]
refine ⟨r,SparseScalar.q,zStar,hr.1,hq,hζ.1,hζ.2.1.trans (baseZeta_le_half r),?_⟩
intro G hG h H hf z hz σ
exact logMoment_le_of_moment_le_exp (H.conditionalMoment_nonneg hf z σ SparseScalar.q)
(all_grid_moment hr hrS hS hζ hz G hG h H hf σ)
end CoordinateSweeps
end OAI