import Lean.Elab.Tactic.Omega import Mathlib.Algebra.BigOperators.Fin import Mathlib.Algebra.BigOperators.Intervals import Mathlib.Algebra.Order.BigOperators.Expect import Mathlib.Basic.Real.Basic import Mathlib.Tactic.Ring import OAI.Computability.BinPacking.Expanders.LazySmoothing import OAI.Computability.BinPacking.Expanders.SpectralCut namespace OAI noncomputable section namespace BinPackingGames.Foundations.PCP.PoweringMoment open scoped BigOperators def bit (p : Prop) : ℝ := by classical exact if p then 1 else 0 def hits {I Ω : Type*} [Fintype I] (E : I → Ω → Prop) (ω : Ω) : ℝ := ∑ i, bit (E i ω) def mean {Ω : Type*} [Fintype Ω] (f : Ω → ℝ) : ℝ := Finset.univ.expect f theorem bit_nonneg (p : Prop) : 0 ≤ bit p := by classical by_cases hp : p <;> simp [bit, hp] theorem bit_sq (p : Prop) : bit p ^ 2 = bit p := by classical by_cases hp : p <;> simp [bit, hp] theorem bit_mul (p q : Prop) : bit p * bit q = bit (p ∧ q) := by classical by_cases hp : p <;> by_cases hq : q <;> simp [bit, hp, hq] theorem bit_mono {p q : Prop} (hpq : p → q) : bit p ≤ bit q := by classical by_cases hp : p · simp [bit, hp, hpq hp] · have hz : bit p = 0 := by simp [bit, hp] rw [hz] exact bit_nonneg q theorem hits_nonneg {I Ω : Type*} [Fintype I] (E : I → Ω → Prop) (ω : Ω) : 0 ≤ hits E ω := Finset.sum_nonneg (fun i _ => bit_nonneg (E i ω)) theorem mean_nonneg {Ω : Type*} [Fintype Ω] (f : Ω → ℝ) (hf : ∀ ω, 0 ≤ f ω) : 0 ≤ mean f := Finset.expect_nonneg (fun ω _ => hf ω) theorem mean_hits {I Ω : Type*} [Fintype I] [Fintype Ω] (E : I → Ω → Prop) : mean (hits E) = ∑ i, mean (fun ω => bit (E i ω)) := by exact Finset.expect_sum_comm _ _ _ theorem second_moment_eq {I Ω : Type*} [Fintype I] [Fintype Ω] (E : I → Ω → Prop) : mean (fun ω => hits E ω ^ 2) = ∑ i, ∑ j, mean (fun ω => bit (E i ω ∧ E j ω)) := by simp only [hits, pow_two, Finset.sum_mul, Finset.mul_sum, bit_mul, mean, Finset.expect_sum_comm] exact Finset.sum_comm theorem mean_witness_sq_le {I Ω : Type*} [Fintype I] [Fintype Ω] (E W : I → Ω → Prop) (reject : Ω → Prop) (hWE : ∀ i ω, W i ω → E i ω) (hWR : ∀ i ω, W i ω → reject ω) : mean (hits W) ^ 2 ≤ mean (fun ω => bit (reject ω)) * mean (fun ω => hits E ω ^ 2) := by classical have hNH (ω : Ω) : hits W ω ≤ hits E ω := Finset.sum_le_sum (fun i _ => bit_mono (hWE i ω)) have hzero (ω : Ω) (hr : ¬ reject ω) : hits W ω = 0 := by apply Finset.sum_eq_zero intro i _ have hw : ¬ W i ω := fun h => hr (hWR i ω h) simp [bit, hw] have hsupport (ω : Ω) : bit (reject ω) * hits W ω = hits W ω := by by_cases hr : reject ω · simp [bit, hr] · rw [hzero ω hr] simp have hCS := Finset.expect_mul_sq_le_sq_mul_sq Finset.univ (fun ω => bit (reject ω)) (hits W) have hsquares : mean (fun ω => hits W ω ^ 2) ≤ mean (fun ω => hits E ω ^ 2) := by apply Finset.expect_le_expect intro ω _ simpa only [pow_two] using (mul_le_mul (hNH ω) (hNH ω) (hits_nonneg W ω) (hits_nonneg E ω)) calc _ ≤ mean (fun ω => bit (reject ω)) * mean (fun ω => hits W ω ^ 2) := by simpa only [mean, hsupport, bit_sq] using hCS _ ≤ _ := mul_le_mul_of_nonneg_left hsquares (mean_nonneg _ (fun ω => bit_nonneg (reject ω))) theorem rejection_lower_bound {I Ω : Type*} [Fintype I] [Fintype Ω] (E W : I → Ω → Prop) (reject : Ω → Prop) (hWE : ∀ i ω, W i ω → E i ω) (hWR : ∀ i ω, W i ω → reject ω) (a b : ℝ) (ha : 0 < a) (hb : 0 < b) (hfirst : a ≤ mean (hits W)) (hsecond : mean (fun ω => hits E ω ^ 2) ≤ b) : a ^ 2 / b ≤ mean (fun ω => bit (reject ω)) := by have hN : 0 ≤ mean (hits W) := mean_nonneg _ (hits_nonneg W) have hρ : 0 ≤ mean (fun ω => bit (reject ω)) := mean_nonneg _ (fun ω => bit_nonneg (reject ω)) have haSq : a ^ 2 ≤ mean (hits W) ^ 2 := by simpa only [pow_two] using mul_le_mul hfirst hfirst ha.le hN have hCS := mean_witness_sq_le E W reject hWE hWR apply (div_le_iff₀ hb).2 exact haSq.trans (hCS.trans (mul_le_mul_of_nonneg_left hsecond hρ)) end BinPackingGames.Foundations.PCP.PoweringMoment end section namespace BinPackingGames.Foundations.PCP.PoweringWalks variable {V D : Type*} def lazyRotate (G : PortGraph V D) : Edge V (Bool × D) → Edge V (Bool × D) | (v, (false, d)) => (v, (false, d)) | (v, (true, d)) => ((G.rot (v, d)).1, (true, (G.rot (v, d)).2)) theorem lazyRotate_involutive (G : PortGraph V D) : Function.Involutive (lazyRotate G) := by rintro ⟨v, b, d⟩ cases b with | false => rfl | true => exact congrArg (fun e : V × D => (e.1, (true, e.2))) (rot_rot G (v, d)) def lazyGraph (G : PortGraph V D) : PortGraph V (Bool × D) where rot := { toFun := lazyRotate G invFun := lazyRotate G left_inv := lazyRotate_involutive G right_inv := lazyRotate_involutive G } rot_involutive := lazyRotate_involutive G @[simp] theorem lazyGraph_rot_false (G : PortGraph V D) (v : V) (d : D) : (lazyGraph G).rot (v, (false, d)) = (v, (false, d)) := rfl @[simp] theorem lazyGraph_rot_true (G : PortGraph V D) (v : V) (d : D) : (lazyGraph G).rot (v, (true, d)) = ((G.rot (v, d)).1, (true, (G.rot (v, d)).2)) := rfl end BinPackingGames.Foundations.PCP.PoweringWalks namespace BinPackingGames.Foundations.PCP.PoweringLazy open PoweringWalks SpectralReturn variable {V D : Type*} theorem operator_binomialMean [Fintype D] (G : PortGraph V D) (n : Nat) (g : Nat → V → ℝ) (v : V) : averagingOperator G (fun w => LazySmoothing.binomialMean n (fun k => g k w)) v = LazySmoothing.binomialMean n (fun k => averagingOperator G (g k) v) := by unfold averagingOperator LazySmoothing.binomialMean exact Finset.expect_comm Finset.univ Finset.univ (fun d tape => g (LazySmoothing.bitCount tape) (G.rot (v, d)).1) theorem averagingOperator_lazy [Fintype D] [Nonempty D] (G : PortGraph V D) (f : V → ℝ) (v : V) : averagingOperator (lazyGraph G) f v = (f v + averagingOperator G f v) / 2 := by change mean (fun bd : Bool × D => f ((lazyGraph G).rot (v, bd)).1) = _ rw [mean_prod] change Finset.univ.expect (fun b : Bool => mean (fun d : D => f ((lazyGraph G).rot (v, (b, d))).1)) = _ rw [LazySmoothing.expect_bool] simp only [lazyGraph_rot_false, lazyGraph_rot_true] rw [mean_const] rfl theorem iterate_lazy_eq_binomialMean [Fintype D] [Nonempty D] (G : PortGraph V D) (n : Nat) (f : V → ℝ) : iterateOperator (lazyGraph G) n f = fun v => LazySmoothing.binomialMean n (fun k => iterateOperator G k f v) := by induction n with | zero => funext v simp [iterateOperator] | succ n ih => funext v change averagingOperator (lazyGraph G) (iterateOperator (lazyGraph G) n f) v = _ rw [ih, averagingOperator_lazy, operator_binomialMean, LazySmoothing.mean_succ] rfl theorem iterate_mem_Icc [Fintype D] [Nonempty D] (G : PortGraph V D) (f : V → ℝ) (hf : ∀ w, f w ∈ Set.Icc (0 : ℝ) 1) (n : Nat) (v : V) : iterateOperator G n f v ∈ Set.Icc (0 : ℝ) 1 := by induction n generalizing v with | zero => exact hf v | succ n ih => change mean (fun d : D => iterateOperator G n f (G.rot (v, d)).1) ∈ Set.Icc (0 : ℝ) 1 constructor · exact mean_nonnegative _ (fun d => (ih ((G.rot (v, d)).1)).1) · calc mean (fun d : D => iterateOperator G n f (G.rot (v, d)).1) ≤ mean (fun _ : D => (1 : ℝ)) := mean_mono (fun d => (ih ((G.rot (v, d)).1)).2) _ = 1 := mean_const _ theorem lazy_endpoint_modal_transfer [Fintype D] [Nonempty D] (G : PortGraph V D) (q M m : Nat) (hq : 1 ≤ q) (hM : 1 ≤ M) (hlo : (4 * q * M) ^ 2 - M ≤ m) (hhi : m ≤ (4 * q * M) ^ 2 + M) (f : V → ℝ) (hf : ∀ w, f w ∈ Set.Icc (0 : ℝ) 1) (v : V) (hmodal : 1 / (q : ℝ) ≤ iterateOperator (lazyGraph G) ((4 * q * M) ^ 2) f v) : 1 / (2 * (q : ℝ)) ≤ iterateOperator (lazyGraph G) m f v := by rw [iterate_lazy_eq_binomialMean] at hmodal ⊢ exact LazySmoothing.modal_transfer q M m hq hM hlo hhi (fun k => iterateOperator G k f v) (fun k => iterate_mem_Icc G f hf k v) hmodal end BinPackingGames.Foundations.PCP.PoweringLazy end namespace BinPackingGames.Foundations.PCP.PoweringReturn open PoweringWalks SpectralReturn open PoweringMoment (bit) variable {V D : Type*} def portConsEquiv (D : Type*) (n : Nat) : (D × (Fin n → D)) ≃ (Fin (n + 1) → D) where toFun z := Fin.cases z.1 z.2 invFun r := (r 0, fun j => r j.succ) left_inv z := by apply Prod.ext · rfl · funext j rfl right_inv r := by funext j exact Fin.cases rfl (fun _ => rfl) j theorem mean_word_cons_head [Fintype D] (n : Nat) (F : (Fin (n + 1) → D) → ℝ) : mean F = mean (fun d : D => mean (fun r : Fin n → D => F (Fin.cases d r))) := by calc mean F = mean (fun z : D × (Fin n → D) => F (Fin.cases z.1 z.2)) := (mean_equiv (portConsEquiv D n) F).symm _ = _ := mean_prod _ theorem mean_word_cons_tail [Fintype D] (n : Nat) (F : (Fin (n + 1) → D) → ℝ) : mean F = mean (fun r : Fin n → D => mean (fun d : D => F (Fin.cases d r))) := by calc mean F = mean (fun z : (Fin n → D) × D => F (Fin.cases z.2 z.1)) := (mean_equiv ((Equiv.prodComm (Fin n → D) D).trans (portConsEquiv D n)) F).symm _ = _ := mean_prod _ theorem iterateOperator_succ_right [Fintype D] (G : PortGraph V D) (n : Nat) (f : V → ℝ) : iterateOperator G n (averagingOperator G f) = iterateOperator G (n + 1) f := by induction n with | zero => rfl | succ n ih => exact congrArg (averagingOperator G) ih theorem mean_wordEnd [Fintype D] [Nonempty D] (G : PortGraph V D) : ∀ (n : Nat) (v : V) (f : V → ℝ), mean (fun r : Fin n → D => f (wordEnd G n v r)) = iterateOperator G n f v := by intro n induction n with | zero => intro v f change mean (fun _ : Fin 0 → D => f v) = f v exact mean_const _ | succ n ih => intro v f rw [mean_word_cons_head] change mean (fun d : D => mean (fun r : Fin n → D => f (wordEnd G n (next G v d) r))) = _ calc _ = mean (fun d : D => iterateOperator G n f (next G v d)) := by congr 1 funext d exact ih (next G v d) f _ = iterateOperator G (n + 1) f v := rfl theorem mean_pivot_endpoints [Fintype D] [Nonempty D] (G : PortGraph V D) : ∀ (n : Nat) (k : Fin (n + 1)) (e : Edge V D) (φ ψ : V → ℝ), mean (fun r : Fin n → D => φ (leftFromPivot G n k e.1 r) * ψ (rightFromPivot G n k e r)) = iterateOperator G k.val φ e.1 * iterateOperator G (n - k.val) ψ (next G e.1 e.2) := by intro n induction n with | zero => intro k e φ ψ have hk : k = 0 := Fin.eq_zero k subst k change mean (fun _ : Fin 0 → D => φ e.1 * ψ (next G e.1 e.2)) = φ e.1 * ψ (next G e.1 e.2) exact mean_const _ | succ n ih => intro k e φ ψ refine Fin.cases ?_ (fun j => ?_) k · change mean (fun r : Fin (n + 1) → D => φ e.1 * ψ (wordEnd G (n + 1) (next G e.1 e.2) r)) = φ e.1 * iterateOperator G (n + 1) ψ (next G e.1 e.2) rw [mean_mul_left, mean_wordEnd] · simp only [Fin.val_succ, Nat.add_sub_add_right] rw [mean_word_cons_tail] change mean (fun r : Fin n → D => mean (fun d : D => φ (next G (leftFromPivot G n j e.1 r) d) * ψ (rightFromPivot G n j e r))) = iterateOperator G (j.val + 1) φ e.1 * iterateOperator G (n - j.val) ψ (next G e.1 e.2) calc _ = mean (fun r : Fin n → D => averagingOperator G φ (leftFromPivot G n j e.1 r) * ψ (rightFromPivot G n j e r)) := by congr 1 funext r rw [mean_mul_right] rfl _ = iterateOperator G j.val (averagingOperator G φ) e.1 * iterateOperator G (n - j.val) ψ (next G e.1 e.2) := ih j e (averagingOperator G φ) ψ _ = _ := by rw [iterateOperator_succ_right] theorem mean_edge_endpoints [Fintype V] [Fintype D] [Nonempty D] (G : PortGraph V D) (n : Nat) (k : Fin (n + 1)) (φ ψ : Edge V D → V → ℝ) : mean (fun w : Walk V D (n + 1) => φ (edgeAt G n w k) w.1 * ψ (edgeAt G n w k) (endpoint G w)) = mean (fun e : Edge V D => iterateOperator G k.val (φ e) e.1 * iterateOperator G (n - k.val) (ψ e) (next G e.1 e.2)) := by let F : Edge V D × (Fin n → D) → ℝ := fun z => φ z.1 (leftFromPivot G n k z.1.1 z.2) * ψ z.1 (rightFromPivot G n k z.1 z.2) calc _ = mean (fun w => F (pivotEquiv G n k w)) := by congr 1 funext w dsimp [F] rw [leftFromPivot_actual, rightFromPivot_actual, pivotEquiv_fst] _ = mean F := mean_equiv (pivotEquiv G n k) F _ = mean (fun e : Edge V D => mean (fun r : Fin n → D => φ e (leftFromPivot G n k e.1 r) * ψ e (rightFromPivot G n k e r))) := mean_prod F _ = _ := by congr 1 funext e exact mean_pivot_endpoints G n k e (φ e) (ψ e) theorem bit_bool (b : Bool) : bit (b = true) = (if b then 1 else 0 : ℝ) := by cases b <;> simp [bit] theorem mean_edge_bit [Fintype D] (bad : V × D → Bool) (v : V) : mean (fun d : D => bit (bad (v, d) = true)) = edgeProfile bad v := by simp only [bit_bool, mean, edgeProfile] theorem mean_marked_bit [Fintype D] (G : PortGraph V D) (bad : V × D → Bool) (f : V → ℝ) (v : V) : mean (fun d : D => bit (bad (v, d) = true) * f (next G v d)) = markedStep G bad f v := by change mean (fun d : D => bit (bad (v, d) = true) * f (next G v d)) = mean (fun d : D => if bad (v, d) then f (next G v d) else 0) congr 1 funext d cases bad (v, d) <;> simp [bit] theorem edgeAt_zero (G : PortGraph V D) (n : Nat) (w : Walk V D (n + 1)) : edgeAt G n w 0 = (w.1, w.2 0) := by cases n <;> rfl theorem word_first_hit_mean [Fintype D] [Nonempty D] (G : PortGraph V D) (bad : V × D → Bool) (n : Nat) (v : V) : mean (fun p : Fin (n + 1) → D => bit (bad (edgeAt G n (v, p) 0) = true)) = edgeProfile bad v := by rw [mean_word_cons_head] simp_rw [edgeAt_zero] change mean (fun d : D => mean (fun _ : Fin n → D => bit (bad (v, d) = true))) = _ calc _ = mean (fun d : D => bit (bad (v, d) = true)) := by simp only [mean_const] _ = edgeProfile bad v := mean_edge_bit bad v theorem word_hit_mean [Fintype D] [Nonempty D] (G : PortGraph V D) (bad : V × D → Bool) : ∀ (n : Nat) (v : V) (k : Fin (n + 1)), mean (fun p : Fin (n + 1) → D => bit (bad (edgeAt G n (v, p) k) = true)) = iterateOperator G k.val (edgeProfile bad) v := by intro n induction n with | zero => intro v k have hk : k = 0 := Fin.eq_zero k subst k exact word_first_hit_mean G bad 0 v | succ n ih => intro v k refine Fin.cases ?_ (fun j => ?_) k · exact word_first_hit_mean G bad (n + 1) v · rw [mean_word_cons_head] change mean (fun d : D => mean (fun p : Fin (n + 1) → D => bit (bad (edgeAt G n (next G v d, p) j) = true))) = averagingOperator G (iterateOperator G j.val (edgeProfile bad)) v calc _ = mean (fun d : D => iterateOperator G j.val (edgeProfile bad) (next G v d)) := by congr 1 funext d exact ih (next G v d) j _ = _ := rfl theorem word_pair_hit_mean [Fintype D] [Nonempty D] (G : PortGraph V D) (bad : V × D → Bool) : ∀ (n : Nat) (v : V) (i j : Fin (n + 1)), i < j → mean (fun p : Fin (n + 1) → D => bit (bad (edgeAt G n (v, p) i) = true) * bit (bad (edgeAt G n (v, p) j) = true)) = iterateOperator G i.val (markedStep G bad (iterateOperator G (j.val - i.val - 1) (edgeProfile bad))) v := by intro n induction n with | zero => intro v i j hij have hi : i = 0 := Fin.eq_zero i have hj : j = 0 := Fin.eq_zero j subst i subst j exact ((lt_irrefl _) hij).elim | succ n ih => intro v i refine Fin.cases ?_ (fun a => ?_) i · intro j refine Fin.cases ?_ (fun b => ?_) j · intro hij exact ((lt_irrefl _) hij).elim · intro _hij simp only [Fin.val_zero, Fin.val_succ, Nat.sub_zero, Nat.add_sub_cancel] rw [mean_word_cons_head] change mean (fun d : D => mean (fun p : Fin (n + 1) → D => bit (bad (v, d) = true) * bit (bad (edgeAt G n (next G v d, p) b) = true))) = markedStep G bad (iterateOperator G b.val (edgeProfile bad)) v calc _ = mean (fun d : D => bit (bad (v, d) = true) * iterateOperator G b.val (edgeProfile bad) (next G v d)) := by congr 1 funext d rw [mean_mul_left, word_hit_mean] _ = _ := mean_marked_bit G bad _ v · intro j refine Fin.cases ?_ (fun b => ?_) j · intro hij exact (Nat.not_lt_zero _ hij).elim · intro hij have hab : a < b := Nat.lt_of_succ_lt_succ hij simp only [Fin.val_succ, Nat.add_sub_add_right] rw [mean_word_cons_head] change mean (fun d : D => mean (fun p : Fin (n + 1) → D => bit (bad (edgeAt G n (next G v d, p) a) = true) * bit (bad (edgeAt G n (next G v d, p) b) = true))) = averagingOperator G (iterateOperator G a.val (markedStep G bad (iterateOperator G (b.val - a.val - 1) (edgeProfile bad)))) v calc _ = mean (fun d : D => iterateOperator G a.val (markedStep G bad (iterateOperator G (b.val - a.val - 1) (edgeProfile bad))) (next G v d)) := by congr 1 funext d exact ih (next G v d) a b hab _ = _ := rfl theorem hit_mean [Fintype V] [Fintype D] [Nonempty V] [Nonempty D] (G : PortGraph V D) (bad : V × D → Bool) (n : Nat) (k : Fin (n + 1)) : mean (fun w : Walk V D (n + 1) => bit (bad (edgeAt G n w k) = true)) = edgeDensity bad := by calc _ = mean (fun v : V => mean (fun p : Fin (n + 1) → D => bit (bad (edgeAt G n (v, p) k) = true))) := mean_prod (A := V) (B := Fin (n + 1) → D) (fun w => bit (bad (edgeAt G n w k) = true)) _ = mean (iterateOperator G k.val (edgeProfile bad)) := by congr 1 funext v exact word_hit_mean G bad n v k _ = mean (edgeProfile bad) := mean_iterate G k.val _ _ = _ := rfl theorem pair_hit_mean [Fintype V] [Fintype D] [Nonempty V] [Nonempty D] (G : PortGraph V D) (bad : V × D → Bool) (n : Nat) (i j : Fin (n + 1)) (hij : i < j) : mean (fun w : Walk V D (n + 1) => bit (bad (edgeAt G n w i) = true) * bit (bad (edgeAt G n w j) = true)) = returnMass G bad (j.val - i.val - 1) := by calc _ = mean (fun v : V => mean (fun p : Fin (n + 1) → D => bit (bad (edgeAt G n (v, p) i) = true) * bit (bad (edgeAt G n (v, p) j) = true))) := mean_prod (A := V) (B := Fin (n + 1) → D) (fun w => bit (bad (edgeAt G n w i) = true) * bit (bad (edgeAt G n w j) = true)) _ = mean (iterateOperator G i.val (markedStep G bad (iterateOperator G (j.val - i.val - 1) (edgeProfile bad)))) := by congr 1 funext v exact word_pair_hit_mean G bad n v i j hij _ = mean (markedStep G bad (iterateOperator G (j.val - i.val - 1) (edgeProfile bad))) := mean_iterate G i.val _ _ = _ := rfl theorem pair_event_mean [Fintype V] [Fintype D] [Nonempty V] [Nonempty D] (G : PortGraph V D) (bad : V × D → Bool) (n : Nat) (i j : Fin (n + 1)) (hij : i < j) : mean (fun w : Walk V D (n + 1) => bit (bad (edgeAt G n w i) = true ∧ bad (edgeAt G n w j) = true)) = returnMass G bad (j.val - i.val - 1) := by simpa only [PoweringMoment.bit_mul] using pair_hit_mean G bad n i j hij end BinPackingGames.Foundations.PCP.PoweringReturn namespace BinPackingGames.Foundations.PCP.PoweringWitness open PoweringWalks SpectralReturn PoweringReturn PoweringLazy open PoweringMoment (bit) variable {V D : Type*} theorem iterate_mul_const [Fintype D] (G : PortGraph V D) (n : Nat) (c : ℝ) (h : V → ℝ) : iterateOperator G n (fun x => c * h x) = fun x => c * iterateOperator G n h x := by induction n with | zero => rfl | succ n ih => change averagingOperator G (iterateOperator G n (fun x => c * h x)) = fun x => c * averagingOperator G (iterateOperator G n h) x rw [ih] funext v exact mean_mul_left c (fun d => iterateOperator G n h (G.rot (v, d)).1) noncomputable def endpointWitness (G : PortGraph V D) (bad : Edge V D → Bool) (φ ψ : Edge V D → V → ℝ) (n : Nat) (k : Fin (n + 1)) (w : Walk V D (n + 1)) : ℝ := bit (bad (edgeAt G n w k) = true) * φ (edgeAt G n w k) w.1 * ψ (edgeAt G n w k) (endpoint G w) noncomputable def vertexWitness (G : PortGraph V D) (bad : Edge V D → Bool) (f : V → V → ℝ) (n : Nat) (k : Fin (n + 1)) : Walk V D (n + 1) → ℝ := endpointWitness G bad (fun e => f e.1) (fun e => f (next G e.1 e.2)) n k theorem endpoint_lower_bound [Fintype V] [Fintype D] [Nonempty D] (G : PortGraph V D) (n : Nat) (k : Fin (n + 1)) (bad : Edge V D → Bool) (φ ψ : Edge V D → V → ℝ) (a : ℝ) (ha : 0 ≤ a) (hL : ∀ e, bad e = true → a ≤ iterateOperator G k.val (φ e) e.1) (hR : ∀ e, bad e = true → a ≤ iterateOperator G (n - k.val) (ψ e) (next G e.1 e.2)) : edgeDensity bad * a ^ 2 ≤ mean (endpointWitness G bad φ ψ n k) := by have hfactor : mean (endpointWitness G bad φ ψ n k) = mean (fun e : Edge V D => (bit (bad e = true) * iterateOperator G k.val (φ e) e.1) * iterateOperator G (n - k.val) (ψ e) (next G e.1 e.2)) := by unfold endpointWitness rw [mean_edge_endpoints G n k (fun e x => bit (bad e = true) * φ e x) ψ] simp_rw [iterate_mul_const] have hbitMean : mean (fun e : Edge V D => bit (bad e = true)) = edgeDensity bad := by calc _ = mean (fun v : V => mean (fun d : D => bit (bad (v, d) = true))) := mean_prod (A := V) (B := D) (fun e => bit (bad e = true)) _ = edgeDensity bad := by simp only [mean_edge_bit, edgeDensity] calc edgeDensity bad * a ^ 2 = mean (fun e : Edge V D => bit (bad e = true) * a ^ 2) := by rw [mean_mul_right, hbitMean] _ ≤ mean (fun e : Edge V D => (bit (bad e = true) * iterateOperator G k.val (φ e) e.1) * iterateOperator G (n - k.val) (ψ e) (next G e.1 e.2)) := by apply mean_mono intro e cases hb : bad e with | false => simp [bit] | true => have hprod := mul_le_mul (hL e hb) (hR e hb) ha (ha.trans (hL e hb)) simpa [bit, hb, pow_two] using hprod _ = mean (endpointWitness G bad φ ψ n k) := hfactor.symm theorem lazy_middle_witness_mean [Fintype V] [Fintype D] [Nonempty D] (G : PortGraph V D) (q M : Nat) (hq : 1 ≤ q) (hM : 1 ≤ M) (k : Fin (2 * (4 * q * M) ^ 2 + 1)) (hlo : (4 * q * M) ^ 2 - M ≤ k.val) (hhi : k.val ≤ (4 * q * M) ^ 2 + M) (bad : Edge V (Bool × D) → Bool) (f : V → V → ℝ) (hf : ∀ u w, f u w ∈ Set.Icc (0 : ℝ) 1) (hmodal : ∀ u, 1 / (q : ℝ) ≤ iterateOperator (lazyGraph G) ((4 * q * M) ^ 2) (f u) u) : edgeDensity bad / (4 * (q : ℝ) ^ 2) ≤ mean (vertexWitness (lazyGraph G) bad f (2 * (4 * q * M) ^ 2) k) := by have hk : k.val ≤ 2 * (4 * q * M) ^ 2 := Nat.le_of_lt_succ k.isLt have hslo : (4 * q * M) ^ 2 - M ≤ 2 * (4 * q * M) ^ 2 - k.val := by omega have hshi : 2 * (4 * q * M) ^ 2 - k.val ≤ (4 * q * M) ^ 2 + M := by omega have ha : (0 : ℝ) ≤ 1 / (2 * (q : ℝ)) := by positivity have hbound := endpoint_lower_bound (lazyGraph G) (2 * (4 * q * M) ^ 2) k bad (fun e => f e.1) (fun e => f (next (lazyGraph G) e.1 e.2)) (1 / (2 * (q : ℝ))) ha (by intro e _ exact lazy_endpoint_modal_transfer G q M k.val hq hM hlo hhi (f e.1) (hf e.1) e.1 (hmodal e.1)) (by intro e _ exact lazy_endpoint_modal_transfer G q M (2 * (4 * q * M) ^ 2 - k.val) hq hM hslo hshi (f (next (lazyGraph G) e.1 e.2)) (hf (next (lazyGraph G) e.1 e.2)) (next (lazyGraph G) e.1 e.2) (hmodal (next (lazyGraph G) e.1 e.2))) have hscale : edgeDensity bad * (1 / (2 * (q : ℝ))) ^ 2 = edgeDensity bad / (4 * (q : ℝ) ^ 2) := by ring simpa only [vertexWitness, hscale] using hbound end BinPackingGames.Foundations.PCP.PoweringWitness namespace BinPackingGames.Foundations.PCP.PoweringMomentBound open scoped BigOperators open PoweringWalks SpectralReturn PoweringReturn open PoweringMoment (bit hits) theorem symmetric_gap_matrix_sum (ε : ℝ) (r : Nat → ℝ) : ∀ (m : Nat) (f : Fin m → Fin m → ℝ), (∀ i j, f i j = f j i) → (∀ i, f i i = ε) → (∀ i j, i.val < j.val → f i j = r (j.val - i.val - 1)) → (∑ i, ∑ j, f i j) = (m : ℝ) * ε + 2 * ∑ j ∈ Finset.range m, ∑ gap ∈ Finset.range j, r gap := by intro m induction m with | zero => intro f _hSym _hDiag _hUpper; simp | succ m ih => intro f hSym hDiag hUpper have hOld : (∑ i : Fin m, ∑ j : Fin m, f i.castSucc j.castSucc) = (m : ℝ) * ε + 2 * ∑ j ∈ Finset.range m, ∑ gap ∈ Finset.range j, r gap := by apply ih (fun i j => f i.castSucc j.castSucc) · intro i j; exact hSym i.castSucc j.castSucc · intro i; exact hDiag i.castSucc · intro i j hij; exact hUpper i.castSucc j.castSucc hij have hLast : (∑ i : Fin m, f i.castSucc (Fin.last m)) = ∑ gap ∈ Finset.range m, r gap := by calc _ = ∑ i : Fin m, r (m - 1 - i.val) := by apply Finset.sum_congr rfl intro i _ rw [hUpper i.castSucc (Fin.last m) i.isLt] simp only [Fin.val_last, Fin.val_castSucc] congr 1 omega _ = ∑ i ∈ Finset.range m, r (m - 1 - i) := Fin.sum_univ_eq_sum_range (fun i => r (m - 1 - i)) m _ = _ := Finset.sum_range_reflect r m have hLastRow : (∑ j : Fin m, f (Fin.last m) j.castSucc) = ∑ gap ∈ Finset.range m, r gap := by calc _ = ∑ j : Fin m, f j.castSucc (Fin.last m) := by apply Finset.sum_congr rfl intro j _ exact hSym (Fin.last m) j.castSucc _ = _ := hLast calc (∑ i, ∑ j, f i j) = (∑ i : Fin m, ∑ j : Fin m, f i.castSucc j.castSucc) + (∑ i : Fin m, f i.castSucc (Fin.last m)) + (∑ j : Fin m, f (Fin.last m) j.castSucc) + f (Fin.last m) (Fin.last m) := by simp only [Fin.sum_univ_castSucc, Finset.sum_add_distrib] ring _ = (m : ℝ) * ε + 2 * (∑ j ∈ Finset.range m, ∑ gap ∈ Finset.range j, r gap) + (∑ gap ∈ Finset.range m, r gap) + (∑ gap ∈ Finset.range m, r gap) + ε := by rw [hOld, hLast, hLastRow, hDiag] _ = ((m + 1 : Nat) : ℝ) * ε + 2 * ∑ j ∈ Finset.range (m + 1), ∑ gap ∈ Finset.range j, r gap := by rw [Finset.sum_range_succ] simp only [Nat.cast_add, Nat.cast_one] ring def windowIndex (n start m : Nat) (h : start + m ≤ n + 1) (i : Fin m) : Fin (n + 1) := ⟨start + i.val, (Nat.add_lt_add_left i.isLt start).trans_le h⟩ variable {V D : Type*} [Fintype V] [Fintype D] [Nonempty V] [Nonempty D] def windowEvent (G : PortGraph V D) (bad : V × D → Bool) (n start m : Nat) (h : start + m ≤ n + 1) (i : Fin m) (w : Walk V D (n + 1)) : Prop := bad (edgeAt G n w (windowIndex n start m h i)) = true theorem window_second_moment_eq (G : PortGraph V D) (bad : V × D → Bool) (n start m : Nat) (h : start + m ≤ n + 1) : mean (fun w => hits (windowEvent G bad n start m h) w ^ 2) = (m : ℝ) * edgeDensity bad + 2 * ∑ j ∈ Finset.range m, ∑ gap ∈ Finset.range j, returnMass G bad gap := by rw [show mean (fun w => hits (windowEvent G bad n start m h) w ^ 2) = ∑ i, ∑ j, mean (fun w => bit (windowEvent G bad n start m h i w ∧ windowEvent G bad n start m h j w)) from PoweringMoment.second_moment_eq (windowEvent G bad n start m h)] apply symmetric_gap_matrix_sum · intro i j congr 1 funext w simp only [and_comm] · intro i simp only [and_self] exact hit_mean G bad n (windowIndex n start m h i) · intro i j hij have hwin : windowIndex n start m h i < windowIndex n start m h j := Nat.add_lt_add_left hij start have hp := pair_event_mean G bad n (windowIndex n start m h i) (windowIndex n start m h j) hwin simpa only [windowEvent, windowIndex, Nat.add_sub_add_left] using hp theorem window_second_moment_le (G : PortGraph V D) (lambda : ℝ) (certificate : SpectralCertificate G lambda) (bad : V × D → Bool) (reversal : ∀ e, bad (G.rot e) = bad e) (n start m : Nat) (h : start + m ≤ n + 1) : mean (fun w => hits (windowEvent G bad n start m h) w ^ 2) ≤ (m : ℝ) * edgeDensity bad * (1 + 2 / (1 - lambda) + ((m : ℝ) - 1) * edgeDensity bad) := by rw [window_second_moment_eq] exact secondMoment_return_envelope G lambda certificate bad reversal m end BinPackingGames.Foundations.PCP.PoweringMomentBound end OAI