roseking's picture
Add lean source and binary files (part 47)
e5a97c6 verified
Raw History Blame Contribute Delete
21.3 kB
import Mathlib
import OAI.Combinatorics.MatchingCount.Graphs.RatWeight
namespace OAI
noncomputable section
namespace MatchingFPRAS.RealStage
open Finset
variable {n : ℕ}
lemma scalingTrace_invariant (hn : 2 ≤ n) (G : Fin n → Fin n → ℝ)
(hsym : ∀ i j, G i j=G j i) (hG : ∀ i j, i≠j → alpha ≤ G i j ∧ G i j ≤ 3)
(k : ℕ) : ScaleInvariant G (scalingTrace hn G k) ∧
∀ i, i.val<k → ∃ j, j≠i ∧ scalingTrace hn G k i*scalingTrace hn G k j=G i j := by
induction k with
| zero =>
constructor
· constructor
· intro i; norm_num [scalingTrace,alpha]
· intro i; simp [scalingTrace]
· intro i j h; have := (hG i j h).2; simp only [scalingTrace]; linarith
· intro i hi; omega
| succ k ih =>
by_cases hk : k<n
· let i : Fin n := ⟨k,hk⟩
have hinv := scaleUpdate_invariant hn G (scalingTrace hn G k) hsym (fun i j h => (hG i j h).1) ih.1 i
have htrace : scalingTrace hn G (k+1)=scaleUpdate hn G (scalingTrace hn G k) i := by
simp [scalingTrace,hk,i]
rw [htrace]
refine ⟨hinv,?_⟩
intro a ha
by_cases hak : a.val<k
· obtain ⟨j,hj,he⟩ := ih.2 a hak
refine ⟨j,hj,?_⟩
exact tight_persists G _ _ ih.1 hinv (scaleUpdate_le hn G _ ih.1 i) a j hj he
· have hai : a=i := Fin.ext (by dsimp [i]; omega)
subst a
exact scaleUpdate_tight hn G _ ih.1 i
· have htrace : scalingTrace hn G (k+1)=scalingTrace hn G k := by simp [scalingTrace,hk]
rw [htrace]
refine ⟨ih.1,?_⟩
intro i _
exact ih.2 i (by have := i.isLt; omega)
open Finset
theorem one_pass_scaling {n : ℕ} (hn : 2 ≤ n) (G : Fin n → Fin n → ℝ)
(hsym : ∀ i j, G i j=G j i) (hG : ∀ i j, i≠j → alpha ≤ G i j ∧ G i j ≤ 3) :
(∀ k i, scalingTrace hn G (k+1) i ≤ scalingTrace hn G k i) ∧
(∀ i, alpha/2 ≤ scalingTrace hn G n i ∧ scalingTrace hn G n i ≤ 2) ∧
(∀ i j, i≠j → G i j ≤ scalingTrace hn G n i * scalingTrace hn G n j) ∧
(∀ i, ∃ j, j≠i ∧ scalingTrace hn G n i * scalingTrace hn G n j=G i j) := by
have htrace := scalingTrace_invariant hn G hsym hG
refine ⟨?_,(htrace n).1.lower |> fun h => ?_⟩
· intro k i
by_cases hk : k<n
· change (if h : k<n then scaleUpdate hn G (scalingTrace hn G k) ⟨k,h⟩ else scalingTrace hn G k) i ≤ _
rw [dite_eq_left hk]
exact scaleUpdate_le hn G _ (htrace k).1 ⟨k,hk⟩ i
· simp [scalingTrace,hk]
· refine ⟨fun i => ⟨h i,(htrace n).1.upper i⟩,(htrace n).1.feasible,?_⟩
intro i
exact (htrace n).2 i i.isLt
def rowPeak {n : ℕ} (hn : 2 ≤ n) (g : Fin n → Fin n → ℝ) (i : Fin n) : ℝ :=
(univ.erase i).sup' (others_nonempty hn i) (g i)
def scaledHoleMatrix {n : ℕ} (g : Fin n → Fin n → ℝ) (v : Fin n → ℝ) (i j : Fin n) : ℝ :=
g i j/(v i*v j)
def BalancedRows {n : ℕ} (hn : 2 ≤ n) (g : Fin n → Fin n → ℝ) : Prop :=
∀ i, (1:ℝ)/4 ≤ rowPeak hn g i ∧ rowPeak hn g i ≤ 1
theorem one_pass_restores_balance {n : ℕ} (hn : 2 ≤ n) (g G : Fin n → Fin n → ℝ)
(hGsym : ∀ i j, G i j=G j i)
(hG : ∀ i j, i≠j → alpha ≤ G i j ∧ G i j ≤ 3)
(hpre : ∀ i, (1:ℝ)/8 ≤ rowPeak hn g i)
(haccuracy : ∀ i j, i≠j → g i j ≤ G i j ∧ G i j ≤ g i j+2*alpha) :
(∀ i, (1:ℝ)/16 ≤ scalingTrace hn G n i) ∧
BalancedRows hn (scaledHoleMatrix g (scalingTrace hn G n)) := by
let v := scalingTrace hn G n
have hv := (scalingTrace_invariant hn G hGsym hG n).1
have hlow (i : Fin n) : (1:ℝ)/16 ≤ v i := by
obtain ⟨j,hj,heq⟩ := Finset.exists_mem_eq_sup' (others_nonempty hn i) (g i)
have hji := (mem_erase.mp hj).1
change rowPeak hn g i=g i j at heq
have hgij : (1:ℝ)/8 ≤ g i j := by rw [← heq]; exact hpre i
have hGi := (haccuracy i j hji.symm).1
have hfeas := hv.feasible i j hji.symm
have hup := mul_le_mul_of_nonneg_left (hv.upper j) (hv.pos i).le
dsimp [v]
linarith
refine ⟨hlow,?_⟩
intro i
constructor
· obtain ⟨j,hji,heq⟩ := (one_pass_scaling hn G hGsym hG).2.2.2 i
have hprod : (1:ℝ)/256 ≤ v i*v j := by
calc
(1:ℝ)/256 = ((1:ℝ)/16)*((1:ℝ)/16) := by norm_num
_ ≤ v i*v j := mul_le_mul (hlow i) (hlow j) (by norm_num) (hv.pos i).le
have hacc := (haccuracy i j hji.symm).2
have hg : (1:ℝ)/4 ≤ scaledHoleMatrix g v i j := by
apply (le_div_iff₀ (mul_pos (hv.pos i) (hv.pos j))).mpr
change v i*v j=G i j at heq
norm_num [alpha] at hacc
nlinarith
apply hg.trans
exact Finset.le_sup' (scaledHoleMatrix g v i) (mem_erase.mpr ⟨hji,mem_univ _⟩)
· apply Finset.sup'_le
intro j hj
have hji := (mem_erase.mp hj).1
apply (div_le_one (mul_pos (hv.pos i) (hv.pos j))).mpr
exact ((haccuracy i j hji.symm).1).trans (hv.feasible i j hji.symm)
def sigma (D K : ℕ) (epsilon : ℝ) : ℝ := min (alpha/(100*D)) (epsilon/(1000*K))
def ratioEstimate (abar dbar : ℝ) : ℝ := if 0<abar then dbar/abar else 1
def upperEstimate (D : ℕ) (dbar zbar : ℝ) : ℝ :=
if 0<dbar then max alpha (min 3 ((D:ℝ)*zbar/dbar+alpha)) else 1
lemma sigma_nonneg (D K : ℕ) (epsilon : ℝ) (he : 0 ≤ epsilon) : 0 ≤ sigma D K epsilon := by
unfold sigma alpha; positivity
lemma sigma_small (D K : ℕ) (hD : 1 ≤ D) (epsilon : ℝ) : sigma D K epsilon ≤ (1:ℝ)/10000000 := by
have hDr : (1:ℝ) ≤ D := by exact_mod_cast hD
apply (min_le_left _ _).trans
apply (div_le_iff₀ (by positivity : 0 < (100:ℝ)*D)).mpr
norm_num [alpha]
linarith
lemma sigma_times_D (D K : ℕ) (hD : 1 ≤ D) (epsilon : ℝ) : (D:ℝ)*sigma D K epsilon ≤ alpha/100 := by
have hDr : (1:ℝ) ≤ D := by exact_mod_cast hD
have hs : sigma D K epsilon ≤ alpha/(100*D) := min_le_left _ _
have hm := (le_div_iff₀ (by positivity : 0 < (100:ℝ)*D)).mp hs
norm_num [alpha] at hm ⊢
nlinarith only [hm]
lemma sigma_relative (D K : ℕ) (epsilon : ℝ) : 10*sigma D K epsilon ≤ epsilon/(100*K) := by
have h : sigma D K epsilon ≤ epsilon/(1000*K) := min_le_right _ _
calc
_ ≤ 10*(epsilon/(1000*K)) := mul_le_mul_of_nonneg_left h (by norm_num)
_ = _ := by ring
lemma ratio_error (s a d abar dbar : ℝ) (hs : 0 ≤ s) (hs1 : s ≤ (1:ℝ)/100)
(ha : (1:ℝ)/2 ≤ a) (hR : (1:ℝ)/2 ≤ d/a ∧ d/a ≤ 1)
(haerr : |abar-a| ≤ s) (hderr : |dbar-d| ≤ s) :
|ratioEstimate abar dbar/(d/a)-1| ≤ 10*s := by
have hab := abs_le.mp haerr
have hdb := abs_le.mp hderr
have hap : 0 < a := by linarith
have habp : 0 < abar := by linarith
have hRp : 0 < d/a := by linarith [hR.1]
have hden : (1:ℝ)/5 ≤ (d/a)*abar := by
have hbar : (1:ℝ)/2-s ≤ abar := by linarith
have hm := mul_le_mul hR.1 hbar (by linarith : 0 ≤ (1:ℝ)/2-s) hRp.le
nlinarith
have hnum : |dbar-(d/a)*abar| ≤ 2*s := by
have hid : dbar-(d/a)*abar=(dbar-d)+(d/a)*(a-abar) := by
have hm : (d/a)*a=d := div_mul_cancel₀ d hap.ne'
nlinarith
rw [hid]
calc
_ ≤ |dbar-d|+|(d/a)*(a-abar)| := abs_add_le _ _
_ = |dbar-d|+(d/a)*|abar-a| := by rw [abs_mul,abs_of_pos hRp,abs_sub_comm a abar]
_ ≤ s+(d/a)*s := add_le_add hderr (mul_le_mul_of_nonneg_left haerr hRp.le)
_ ≤ 2*s := by nlinarith [mul_le_mul_of_nonneg_right hR.2 hs]
have hid : ratioEstimate abar dbar/(d/a)-1=(dbar-(d/a)*abar)/((d/a)*abar) := by
simp only [ratioEstimate, ite_eq_left habp]
have hdne : d ≠ 0 := by intro hh; simp [hh] at hRp
field_simp [hap.ne', habp.ne', hdne]
rw [hid,abs_div,abs_of_pos (mul_pos hRp habp)]
apply (div_le_iff₀ (mul_pos hRp habp)).mpr
nlinarith [mul_le_mul_of_nonneg_right hden (show 0 ≤ 10*s by positivity)]
lemma upper_error (D : ℕ) (hD : 1 ≤ D) (s d z dbar zbar : ℝ)
(hs : 0 ≤ s) (hs1 : s ≤ (1:ℝ)/100)
(hDs : (D:ℝ)*s ≤ alpha/100) (hd : (1:ℝ)/4 ≤ d)
(hg : 0 ≤ (D:ℝ)*z/d ∧ (D:ℝ)*z/d ≤ 2)
(hderr : |dbar-d| ≤ s) (hzerr : |zbar-z| ≤ s) :
alpha ≤ upperEstimate D dbar zbar ∧ upperEstimate D dbar zbar ≤ 3 ∧
(D:ℝ)*z/d ≤ upperEstimate D dbar zbar ∧
upperEstimate D dbar zbar ≤ (D:ℝ)*z/d+2*alpha := by
have hDr : (1:ℝ) ≤ D := by exact_mod_cast hD
have hdp : 0 < d := by linarith
have hdb := abs_le.mp hderr
have hbar : (1:ℝ)/5 ≤ dbar := by linarith
have hbarp : 0 < dbar := by linarith
let g := (D:ℝ)*z/d
have hg0 : 0 ≤ g := hg.1
have hg2 : g ≤ 2 := hg.2
have hnum : |(D:ℝ)*(zbar-z)+g*(d-dbar)| ≤ ((D:ℝ)+2)*s := by
calc
_ ≤ |(D:ℝ)*(zbar-z)|+|g*(d-dbar)| := abs_add_le _ _
_ = (D:ℝ)*|zbar-z|+g*|dbar-d| := by
rw [abs_mul, abs_mul, abs_of_nonneg (Nat.cast_nonneg D), abs_of_nonneg hg0,
abs_sub_comm d dbar]
_ ≤ (D:ℝ)*s+g*s := add_le_add (mul_le_mul_of_nonneg_left hzerr (Nat.cast_nonneg D))
(mul_le_mul_of_nonneg_left hderr hg0)
_ ≤ ((D:ℝ)+2)*s := by nlinarith [mul_le_mul_of_nonneg_right hg2 hs]
have hid : (D:ℝ)*zbar/dbar-g=((D:ℝ)*(zbar-z)+g*(d-dbar))/dbar := by
dsimp [g]
field_simp [hdp.ne', hbarp.ne']
ring
have hraw : |(D:ℝ)*zbar/dbar-g| ≤ alpha := by
rw [hid, abs_div, abs_of_pos hbarp]
apply (div_le_iff₀ hbarp).mpr
have hsm : s ≤ (D:ℝ)*s := by nlinarith [mul_le_mul_of_nonneg_right hDr hs]
have ha : 0 < alpha := by norm_num [alpha]
have hm := mul_le_mul_of_nonneg_left hbar ha.le
norm_num [alpha] at hDs hm ⊢
nlinarith only [hDs, hm, hnum, hsm]
have hbounds := abs_le.mp hraw
unfold upperEstimate
rw [ite_eq_left hbarp]
refine ⟨le_max_left _ _, ?_, ?_, ?_⟩
· apply max_le
· norm_num [alpha]
· exact min_le_left _ _
· apply le_max_of_le_right
exact le_min (by linarith) (by linarith)
· apply max_le
· have ha : 0 ≤ alpha := by norm_num [alpha]
linarith
· exact (min_le_right _ _).trans (by linarith)
theorem successful_stage_estimates (D K : ℕ) (hD : 1 ≤ D) (_hK : 1 ≤ K)
(epsilon : ℝ) (he : 0<epsilon) (he1 : epsilon<1)
(a d z abar dbar zbar : ℝ) (ha : (1:ℝ)/2 ≤ a) (hd : (1:ℝ)/4 ≤ d)
(hR : (1:ℝ)/2 ≤ d/a ∧ d/a ≤ 1)
(hg : 0 ≤ (D:ℝ)*z/d ∧ (D:ℝ)*z/d ≤ 2)
(haerr : |abar-a| ≤ sigma D K epsilon)
(hderr : |dbar-d| ≤ sigma D K epsilon)
(hzerr : |zbar-z| ≤ sigma D K epsilon) :
0<abar ∧ 0<dbar ∧
|ratioEstimate abar dbar/(d/a)-1| ≤ 10*sigma D K epsilon ∧
10*sigma D K epsilon ≤ epsilon/(100*K) ∧
alpha ≤ upperEstimate D dbar zbar ∧ upperEstimate D dbar zbar ≤ 3 ∧
(D:ℝ)*z/d ≤ upperEstimate D dbar zbar ∧
upperEstimate D dbar zbar ≤ (D:ℝ)*z/d+2*alpha := by
have hs := sigma_nonneg D K epsilon he.le
have hs1 : sigma D K epsilon ≤ (1:ℝ)/100 :=
(sigma_small D K hD epsilon).trans (by norm_num)
have hab := abs_le.mp haerr
have hdb := abs_le.mp hderr
refine ⟨by linarith, by linarith, ?_, sigma_relative D K epsilon, ?_⟩
· exact ratio_error _ _ _ _ _ hs hs1 ha hR haerr hderr
· exact upper_error D hD _ _ _ _ _ hs hs1 (sigma_times_D D K hD epsilon) hd hg hderr hzerr
end MatchingFPRAS.RealStage
end
namespace MatchingFPRAS.Enlargement
open MatchingFPRAS.Switching MatchingFPRAS.Subdivision MatchingFPRAS.RealGeometry
open MatchingFPRAS.Hierarchy MatchingFPRAS.Transport MatchingFPRAS.StageAnalysis Finset
open scoped Classical
variable {V : Type*} [Fintype V] [LinearOrder V]
def pairEdge (i j : V) (hij : i≠j) : LogicalEdge V :=
⟨(min i j,max i j),min_lt_max.mpr hij⟩
omit [Fintype V] in
lemma pairEdge_swap (i j : V) (hij : i≠j) : pairEdge i j hij=pairEdge j i hij.symm := by
apply Subtype.ext
simp [pairEdge,min_comm,max_comm]
omit [Fintype V] in
lemma pairEdge_holes (i j : V) (hij : i≠j) :
({source (pairEdge i j hij),target (pairEdge i j hij)} : Finset V)={i,j} := by
rcases le_total i j with h|h
· simp [pairEdge,source,target,min_eq_left h,max_eq_right h]
· simp [pairEdge,source,target,min_eq_right h,max_eq_left h,Finset.pair_comm]
noncomputable def probeMatrix (z : LogicalEdge V → ℝ) (i j : V) : ℝ :=
if hij : i=j then 0 else z (pairEdge i j hij)
omit [Fintype V] in
lemma probeMatrix_off (z : LogicalEdge V → ℝ) (i j : V) (hij : i≠j) :
probeMatrix z i j=z (pairEdge i j hij) := dite_eq_right hij
omit [Fintype V] in
lemma probeMatrix_symm (z : LogicalEdge V → ℝ) (i j : V) : probeMatrix z i j=probeMatrix z j i := by
by_cases hij : i=j
· subst j; rfl
· rw [probeMatrix_off _ _ _ hij,probeMatrix_off _ _ _ (Ne.symm hij),pairEdge_swap]
noncomputable def estimateMatrix (D : ℕ) (dbar : ℝ) (zbar : LogicalEdge V → ℝ) (i j : V) : ℝ :=
RealStage.upperEstimate D dbar (probeMatrix zbar i j)
omit [Fintype V] in
lemma estimateMatrix_symm (D : ℕ) (dbar : ℝ) (zbar : LogicalEdge V → ℝ) (i j : V) :
estimateMatrix D dbar zbar i j=estimateMatrix D dbar zbar j i := by
rw [estimateMatrix,estimateMatrix,probeMatrix_symm]
lemma rowMax_cooling_lower (hn : 2 ≤ Fintype.card V) (w w₁ : V → V → ℝ)
(hw : ∀ x y,0 ≤ w x y) (hz : 0 < partition w ∅)
(hr : ∀ i,(1:ℝ)/4 ≤ rowMax hn w i)
(hc : ∀ R,partition w R/2 ≤ partition w₁ R ∧ partition w₁ R ≤ partition w R) (i : V) :
(1:ℝ)/8 ≤ rowMax hn w₁ i := by
obtain ⟨j,hji,hj⟩ := rowMax_attained hn w i
have h := (holeRatio_cooling w w₁ hw hz hc {i,j}).1
have hu := holeRatio_le_rowMax hn w₁ i j hji.symm
rw [hj] at h
linarith [hr i]
variable [Nontrivial V]
noncomputable local instance (w : V → V → ℝ) (K : ℕ) : DecidableEq (SourceLabel w K) := Classical.decEq _
noncomputable local instance (w : V → V → ℝ) (K : ℕ) : Fintype (BagEdge (sourceBags w K)) := Fintype.ofFinite _
noncomputable def meanA (w : V → V → ℝ) (K : ℕ) : ℝ :=
∑ q : SourceMarked w K,sourceLaw w K (sourceD (V:=V) K) q*observableA w K q
noncomputable def meanD (w w₁ : V → V → ℝ) (K : ℕ) : ℝ :=
∑ q : SourceMarked w K,sourceLaw w K (sourceD (V:=V) K) q*observableD w w₁ K q
noncomputable def meanProbe (w w₁ : V → V → ℝ) (K : ℕ) (e : LogicalEdge (V)) : ℝ :=
∑ q : SourceMarked w K,sourceLaw w K (sourceD (V:=V) K) q*observableProbe w w₁ K e q
variable {n : ℕ} [Nontrivial (Fin n)]
noncomputable local instance (w : Fin n → Fin n → ℝ) (K : ℕ) : DecidableEq (SourceLabel w K) := Classical.decEq _
noncomputable local instance (w : Fin n → Fin n → ℝ) (K : ℕ) : Fintype (BagEdge (sourceBags w K)) := Fintype.ofFinite _
omit [Nontrivial (Fin n)] in
lemma rowPeak_holeMatrix (hn : 2 ≤ n) (w : Fin n → Fin n → ℝ) (i : Fin n) :
RealStage.rowPeak hn (fun i j => Switching.holeRatio w {i,j}) i=
rowMax (by simpa using hn) w i := rfl
structure StageData (n K T : ℕ) where
hn : 2 ≤ n
w : Fin n → Fin n → ℝ
next : Fin n → Fin n → ℝ
positive : ∀ i j,0 < w i j
next_positive : ∀ i j,0 < next i j
partition_positive : 0 < partition w ∅
lower : ∀ i,(1:ℝ)/4 ≤ rowMax (by simpa using hn) w i
upper : ∀ i,rowMax (by simpa using hn) w i ≤ 1
cool_lower : ∀ i j,i≠j → (1+1/(n:ℝ))⁻¹*w i j ≤ next i j
cool_upper : ∀ i j,i≠j → next i j ≤ w i j
cap : ∀ i j,i≠j → edgeActivity w i j ≤ (4:ℝ)^K
stages : 1 ≤ T
epsilon : ℝ
epsilon_positive : 0 < epsilon
epsilon_lt_one : epsilon < 1
variable {K T : ℕ}
structure EmpiricalData (c : StageData n K T) where
abar : ℝ
dbar : ℝ
zbar : LogicalEdge (Fin n) → ℝ
errorA : |abar-meanA c.w K| ≤ RealStage.sigma (sourceD (V:=Fin n) K) T c.epsilon
errorD : |dbar-meanD c.w c.next K| ≤ RealStage.sigma (sourceD (V:=Fin n) K) T c.epsilon
errorProbe : ∀ e,|zbar e-meanProbe c.w c.next K e| ≤ RealStage.sigma (sourceD (V:=Fin n) K) T c.epsilon
omit [Nontrivial (Fin n)] in
lemma StageData.cooling (c : StageData n K T) (R : Finset (Fin n)) :
partition c.w R/2 ≤ partition c.next R ∧ partition c.next R ≤ partition c.w R := by
apply partition_cooling (by simpa using c.hn) c.w c.next (fun i j => (c.positive i j).le)
· simpa using c.cool_lower
· exact c.cool_upper
lemma StageData.mean_bounds (c : StageData n K T) :
(1:ℝ)/2 ≤ meanA c.w K ∧ (1:ℝ)/4 ≤ meanD c.w c.next K ∧
meanD c.w c.next K/meanA c.w K=partition c.next ∅/partition c.w ∅ ∧
(1:ℝ)/2 ≤ meanD c.w c.next K/meanA c.w K ∧ meanD c.w c.next K/meanA c.w K ≤ 1 ∧
(∀ e,(sourceD (V:=Fin n) K:ℝ)*meanProbe c.w c.next K e/meanD c.w c.next K=
Switching.holeRatio c.next {source e,target e}) := by
have h := source_observable_means (V:=Fin n) (by simpa using c.hn) c.w c.next c.positive c.partition_positive
c.lower c.upper (by simpa using c.cool_lower) c.cool_upper K c.cap
unfold meanA meanD meanProbe
exact h.2.2
omit [Nontrivial (Fin n)] in
lemma StageData.hole_upper (c : StageData n K T) (i j : Fin n) (hij : i≠j) :
Switching.holeRatio c.next {i,j} ≤ 2 := by
have h := (holeRatio_cooling c.w c.next (fun i j => (c.positive i j).le)
c.partition_positive c.cooling {i,j}).2
have hr := (holeRatio_le_rowMax (by simpa using c.hn) c.w i j hij).trans (c.upper i)
linarith
theorem actual_stage_statistics (c : StageData n K T) (b : EmpiricalData c) (i j : Fin n) (hij : i≠j) :
let G := estimateMatrix (sourceD (V:=Fin n) K) b.dbar b.zbar
0 < b.abar ∧ 0 < b.dbar ∧
|RealStage.ratioEstimate b.abar b.dbar/(partition c.next ∅/partition c.w ∅)-1| ≤ c.epsilon/(100*T) ∧
RealStage.alpha ≤ G i j ∧ G i j ≤ 3 ∧
Switching.holeRatio c.next {i,j} ≤ G i j ∧
G i j ≤ Switching.holeRatio c.next {i,j}+2*RealStage.alpha := by
dsimp only
have hm := c.mean_bounds
have hem := hm.2.2.2.2.2 (pairEdge i j hij)
rw [pairEdge_holes] at hem
have hg0 := holeRatio_nonneg c.next (fun x y => (c.next_positive x y).le) {i,j}
have h := RealStage.successful_stage_estimates (sourceD (V:=Fin n) K) T (sourceD_one K)
c.stages c.epsilon c.epsilon_positive c.epsilon_lt_one
(meanA c.w K) (meanD c.w c.next K) (meanProbe c.w c.next K (pairEdge i j hij))
b.abar b.dbar (b.zbar (pairEdge i j hij)) hm.1 hm.2.1
⟨hm.2.2.2.1,hm.2.2.2.2.1⟩
⟨by rw [hem]; exact hg0,by rw [hem]; exact c.hole_upper i j hij⟩
b.errorA b.errorD (b.errorProbe _)
refine ⟨h.1,h.2.1,?_,?_⟩
· have he := h.2.2.1.trans h.2.2.2.1
rwa [hm.2.2.1] at he
· simpa only [estimateMatrix,probeMatrix_off _ _ _ hij,hem] using h.2.2.2.2
theorem actual_successful_stage (c : StageData n K T) (b : EmpiricalData c) :
let G := estimateMatrix (sourceD (V:=Fin n) K) b.dbar b.zbar
let v := RealStage.scalingTrace c.hn G n
(∀ i,(1:ℝ)/16 ≤ v i ∧ v i ≤ 2) ∧
(∀ i,(1:ℝ)/4 ≤ rowMax (by simpa using c.hn) (fun x y => c.next x y*v x*v y) i ∧
rowMax (by simpa using c.hn) (fun x y => c.next x y*v x*v y) i ≤ 1) ∧
|RealStage.ratioEstimate b.abar b.dbar/(partition c.next ∅/partition c.w ∅)-1| ≤ c.epsilon/(100*T) := by
dsimp only
let G := estimateMatrix (sourceD (V:=Fin n) K) b.dbar b.zbar
let g := fun i j => Switching.holeRatio c.next {i,j}
have hest := actual_stage_statistics c b
have hGs := estimateMatrix_symm (sourceD (V:=Fin n) K) b.dbar b.zbar
have hGb : ∀ i j,i≠j → RealStage.alpha ≤ G i j ∧ G i j ≤ 3 := by
intro i j hij
exact ⟨(hest i j hij).2.2.2.1,(hest i j hij).2.2.2.2.1⟩
have hGa : ∀ i j,i≠j → g i j ≤ G i j ∧ G i j ≤ g i j+2*RealStage.alpha := by
intro i j hij
exact (hest i j hij).2.2.2.2.2
have hpre : ∀ i,(1:ℝ)/8 ≤ RealStage.rowPeak c.hn g i := by
intro i
rw [show g=(fun i j => Switching.holeRatio c.next {i,j}) from rfl,rowPeak_holeMatrix]
exact rowMax_cooling_lower (by simpa using c.hn) c.w c.next (fun x y => (c.positive x y).le)
c.partition_positive c.lower c.cooling i
have hb := RealStage.one_pass_restores_balance c.hn g G hGs hGb hpre hGa
let v := RealStage.scalingTrace c.hn G n
have hv := (RealStage.scalingTrace_invariant c.hn G hGs hGb n).1
have heq (i j : Fin n) (hij : i≠j) :
Switching.holeRatio (fun x y => c.next x y*v x*v y) {i,j}=RealStage.scaledHoleMatrix g v i j := by
rw [holeRatio_vertex_scaling c.next v (fun x => hv.pos x),Finset.prod_pair hij]
rfl
have hb' (i : Fin n) : (1:ℝ)/4 ≤ rowMax (by simpa using c.hn) (fun x y => c.next x y*v x*v y) i ∧
rowMax (by simpa using c.hn) (fun x y => c.next x y*v x*v y) i ≤ 1 := by
have he : rowMax (by simpa using c.hn) (fun x y => c.next x y*v x*v y) i=
RealStage.rowPeak c.hn (RealStage.scaledHoleMatrix g v) i := by
unfold rowMax RealStage.rowPeak
apply Finset.sup'_congr _ rfl
intro j hj
exact heq i j (Finset.mem_erase.mp hj).1.symm
rw [he]
exact hb.2 i
refine ⟨fun i => ⟨hb.1 i,hv.upper i⟩,hb',?_⟩
let i : Fin n := ⟨0,by have := c.hn; omega⟩
let j : Fin n := ⟨1,by have := c.hn; omega⟩
have hij : i≠j := by intro h; have := Fin.val_eq_of_eq h; dsimp [i,j] at this; omega
exact (hest i j hij).2.2.1
end MatchingFPRAS.Enlargement
end OAI