import Mathlib import OAI.Computability.MaxCut.PCP.RawInitialTables namespace OAI /-! Concrete bridges between graph cardinality and the length of the validated unary table encoding. These bounds supply the input-length and intermediate encoding estimates used by actual machine trace composition; they are not themselves a machine execution certificate. -/ namespace MaxCutGames.Foundations.PCP.GraphTableComplexity open MaxCutGames.Foundations.Complexity open Polynomial noncomputable def encodingPolynomial (q : Nat) : Polynomial Nat := X ^ 2 + C (2 * (q * q) + 1) * X + C 2 theorem encodingPolynomial_eval (q n : Nat) : (encodingPolynomial q).eval n = n ^ 2 + (2 * (q * q) + 1) * n + 2 := by simp [encodingPolynomial] theorem encodingPolynomial_mono (q : Nat) {n m : Nat} (hnm : n ≤ m) : (encodingPolynomial q).eval n ≤ (encodingPolynomial q).eval m := by rw [encodingPolynomial_eval, encodingPolynomial_eval] exact Nat.add_le_add_right (Nat.add_le_add (Nat.pow_le_pow_left hnm 2) (Nat.mul_le_mul_left _ hnm)) 2 theorem rowBound_le_polynomial (q vertices darts : Nat) : vertices + darts + 2 + darts * (vertices + darts + 2 * (q * q)) ≤ (encodingPolynomial q).eval (vertices + darts) := by have hd : darts ≤ vertices + darts := Nat.le_add_left darts vertices calc _ ≤ vertices + darts + 2 + (vertices + darts) * (vertices + darts + 2 * (q * q)) := Nat.add_le_add_left (Nat.mul_le_mul_right _ hd) _ _ = _ := by rw [encodingPolynomial_eval]; ring theorem generic_size_add_two_le_bits {q : Nat} (table : GenericGraphTables.Table q) : table.vertices + table.darts + 2 ≤ (GenericGraphTables.tableBits table).length := by simp only [GenericGraphTables.tableBits, GenericGraphTables.tableWords, encodeWords_append, List.length_append, encodeWords, encodeWord_length, List.length_nil] omega theorem generic_bits_le_polynomial {q : Nat} (table : GenericGraphTables.Table q) : (GenericGraphTables.tableBits table).length ≤ (encodingPolynomial q).eval (table.vertices + table.darts) := (GenericGraphTables.tableBits_length_le table).trans (rowBound_le_polynomial q table.vertices table.darts) theorem generic_bits_le_of_size_le {q N : Nat} (table : GenericGraphTables.Table q) (hsize : table.vertices + table.darts ≤ N) : (GenericGraphTables.tableBits table).length ≤ (encodingPolynomial q).eval N := (generic_bits_le_polynomial table).trans (encodingPolynomial_mono q hsize) theorem size_add_two_le_bits (table : GraphTables.Table) : table.vertices + table.darts + 2 ≤ (GraphTables.tableBits table).length := by simp only [GraphTables.tableBits, GraphTables.tableWords, encodeWords_append, List.length_append, encodeWords, encodeWord_length, List.length_nil] omega theorem bits_le_polynomial (table : GraphTables.Table) : (GraphTables.tableBits table).length ≤ (encodingPolynomial 64).eval (table.vertices + table.darts) := (GraphTables.tableBits_length_le table).trans (rowBound_le_polynomial 64 table.vertices table.darts) theorem bits_le_of_size_le {N : Nat} (table : GraphTables.Table) (hsize : table.vertices + table.darts ≤ N) : (GraphTables.tableBits table).length ≤ (encodingPolynomial 64).eval N := (bits_le_polynomial table).trans (encodingPolynomial_mono 64 hsize) end MaxCutGames.Foundations.PCP.GraphTableComplexity /-! The actual fixed-parameter graph transformation in one PCP amplification round. It preprocesses the input graph, checks all edges of each bounded walk using local endpoint labels, and applies the checked constant-query alphabet reduction. The bounded address list is explicit fixed data shared by every input graph. -/ noncomputable section namespace MaxCutGames.Foundations.PCP.AmplificationRound abbrev Label := QueryIncidence.Label 6 abbrev Addresses := PoweringLabels.PortWords Preprocessing.Port FinalConstants.walkLength abbrev PoweredAlphabet := PoweringLabels.PaddedLabel Preprocessing.Port FinalConstants.walkLength Label instance : Fintype PoweredAlphabet := Fintype.ofFinite _ instance : DecidableEq PoweredAlphabet := Classical.decEq _ variable {V E : Type*} [Fintype V] [Fintype E] [DecidableEq V] [DecidableEq E] [Nonempty E] abbrev PoweredDart (G : ConstraintGraph V E Label) := PoweringTest.Dart (Preprocessing.Vertex G) Preprocessing.Port (2 * FinalConstants.endpointLength) instance (G : ConstraintGraph V E Label) : DecidableEq (PoweredDart G) := Classical.decEq _ def selectors (addresses : List Addresses) (complete : ∀ w, w ∈ addresses) (G : ConstraintGraph V E Label) (v : Preprocessing.Vertex G) : PoweringLabels.AddressSelector (Preprocessing.portGraph G) FinalConstants.walkLength v := PoweringLabels.listSelector (Preprocessing.portGraph G) FinalConstants.walkLength v addresses complete def powered (addresses : List Addresses) (complete : ∀ w, w ∈ addresses) (G : ConstraintGraph V E Label) : ConstraintGraph (Preprocessing.Vertex G) (PoweredDart G) PoweredAlphabet := PoweringTest.poweredGraph (Preprocessing.portGraph G) (Preprocessing.graph G).accepts (2 * FinalConstants.endpointLength) (selectors addresses complete G) abbrev Vertex (G : ConstraintGraph V E Label) := QueryIncidence.Vertex (AlphabetGraph.Event (PoweredDart G) PoweredAlphabet) (AlphabetGraph.Address (Preprocessing.Vertex G) (PoweredDart G) PoweredAlphabet) abbrev Dart (G : ConstraintGraph V E Label) := QueryIncidence.Dart (AlphabetGraph.Event (PoweredDart G) PoweredAlphabet) 6 instance (G : ConstraintGraph V E Label) : Fintype (Vertex G) := by letI : Fintype (AlphabetGraph.Event (PoweredDart G) PoweredAlphabet) := inferInstance letI : Fintype (AlphabetGraph.Address (Preprocessing.Vertex G) (PoweredDart G) PoweredAlphabet) := inferInstance change Fintype (AlphabetGraph.Event (PoweredDart G) PoweredAlphabet ⊕ AlphabetGraph.Address (Preprocessing.Vertex G) (PoweredDart G) PoweredAlphabet) infer_instance instance (G : ConstraintGraph V E Label) : Fintype (Dart G) := by change Fintype ((AlphabetGraph.Event (PoweredDart G) PoweredAlphabet × Fin 6) × Bool) infer_instance instance (G : ConstraintGraph V E Label) : DecidableEq (Vertex G) := Classical.decEq _ def graph (addresses : List Addresses) (complete : ∀ w, w ∈ addresses) (G : ConstraintGraph V E Label) : ConstraintGraph (Vertex G) (Dart G) Label := AlphabetGraph.graph (powered addresses complete G) omit [Nonempty E] in theorem powered_completeness (addresses : List Addresses) (complete : ∀ w, w ∈ addresses) (G : ConstraintGraph V E Label) (satisfied : G.Satisfiable) : (powered addresses complete G).Satisfiable := by obtain ⟨assignment, hassignment⟩ := Preprocessing.completeness G satisfied refine ⟨PoweringOpinions.honestLabels (Preprocessing.portGraph G) FinalConstants.walkLength assignment, ?_⟩ apply PoweringTest.perfect_completeness (Preprocessing.portGraph G) (Preprocessing.graph G).accepts (2 * FinalConstants.endpointLength) (selectors addresses complete G) assignment intro e exact hassignment e omit [Nonempty E] in theorem completeness (addresses : List Addresses) (complete : ∀ w, w ∈ addresses) (G : ConstraintGraph V E Label) (satisfied : G.Satisfiable) : (graph addresses complete G).Satisfiable := AlphabetGraph.perfect_completeness _ (powered_completeness addresses complete G satisfied) end MaxCutGames.Foundations.PCP.AmplificationRound end /-! # The actual first moment of an endpoint-opinion witness The pivot factorization is applied to actual finite walks. Its two endpoint operator bounds are obtained from the proved lazy-graph mixture and smoothing theorem. No witness-event probability law is assumed. -/ namespace MaxCutGames.Foundations.PCP.PoweringWitness open PoweringWalks SpectralReturn PoweringReturn PoweringLazy open PoweringMoment (bit) variable {V D : Type*} /-- A constant scalar passes through every iterate of the actual graph mean. -/ 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) /-- The actual pivot dart is marked and both endpoint opinions pass their tests. For indicator opinions this is the indicator of their conjunction. -/ 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) /-- Vertex-indexed opinions are tested at the two endpoints of the pivot dart. -/ 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 /-- Pointwise bounds on the two genuine earlier-length graph iterates give the witness first moment. The hypotheses are only needed on marked darts. -/ 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 /-- The two endpoint-opinion tests each retain probability at least `1/(2q)` at every middle pivot. The walk has `2N+1` edges, with `N=(4qM)^2`, so the prefix and suffix lengths are exactly `k` and `2N-k`. The only modal input is the actual centered lazy iterate at each vertex. It will be supplied by the finite modal-opinion decoder, not by a witness law. -/ 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 MaxCutGames.Foundations.PCP.PoweringWitness /-! The second moment of the actual marked-edge count in a consecutive walk window. Pair events are reduced to the checked spectral return operator. -/ namespace MaxCutGames.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 /-- All moment terms come from actual walk events; the only analytic input is the stated spectral contraction certificate of the given graph. -/ 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 MaxCutGames.Foundations.PCP.PoweringMomentBound /-! # The scalar bound for all positive error densities The first lemma bounds a ratio using only a nonnegative coefficient bounded by a positive cutoff. The second applies it to a positive natural count and the first- and second-moment expressions in the powering argument. -/ namespace MaxCutGames.Foundations.PCP.PoweringNumeric /-- A bounded nonnegative coefficient gives the required ratio bound both below and above the cutoff `1/t`. -/ theorem min_density_ratio (ε C k t : ℝ) (hε : 0 < ε) (hC : 0 < C) (hk : 0 ≤ k) (ht : 0 < t) (hkt : k ≤ t) : min ε (1 / t) / (C + 1) ≤ ε / (C + k * ε) := by have hx : 0 ≤ min ε (1 / t) := le_min hε.le (one_div_nonneg.mpr ht.le) have hxt : min ε (1 / t) * t ≤ 1 := (le_div_iff₀ ht).mp (min_le_right ε (1 / t)) have hkx : k * min ε (1 / t) ≤ 1 := by calc k * min ε (1 / t) ≤ t * min ε (1 / t) := mul_le_mul_of_nonneg_right hkt hx _ ≤ 1 := by simpa only [mul_comm] using hxt have hC1 : 0 < C + 1 := by positivity have hden : 0 < C + k * ε := add_pos_of_pos_of_nonneg hC (mul_nonneg hk hε.le) apply (div_le_div_iff₀ hC1 hden).2 calc min ε (1 / t) * (C + k * ε) = C * min ε (1 / t) + ε * (k * min ε (1 / t)) := by ring _ ≤ C * ε + ε * 1 := add_le_add (mul_le_mul_of_nonneg_left (min_le_left ε (1 / t)) hC.le) (mul_le_mul_of_nonneg_left hkx hε.le) _ = ε * (C + 1) := by ring /-- A positive natural count supplies `0 ≤ m - 1`. After cancelling the positive mass `m*ε`, the ratio of moments dominates a constant times `min ε (1/t)`. No sign condition on `α` is needed for its fourth power. -/ theorem count_moment_ratio_lower (α ε C t : ℝ) (m : ℕ) (hm : 0 < m) (hε : 0 < ε) (hC : 0 < C) (ht : 0 < t) (hmt : (m : ℝ) - 1 ≤ t) : (α ^ 4 * (m : ℝ) / (C + 1)) * min ε (1 / t) ≤ (α ^ 2 * (m : ℝ) * ε) ^ 2 / ((m : ℝ) * ε * (C + ((m : ℝ) - 1) * ε)) := by have hm0 : (0 : ℝ) < (m : ℝ) := Nat.cast_pos.mpr hm have hm1 : (1 : ℝ) ≤ (m : ℝ) := by exact_mod_cast (Nat.succ_le_iff.mpr hm) have hk : 0 ≤ (m : ℝ) - 1 := sub_nonneg.mpr hm1 have hden : 0 < C + ((m : ℝ) - 1) * ε := add_pos_of_pos_of_nonneg hC (mul_nonneg hk hε.le) have hαm : 0 ≤ α ^ 4 * (m : ℝ) := by positivity have hratio := min_density_ratio ε C ((m : ℝ) - 1) t hε hC hk ht hmt calc (α ^ 4 * (m : ℝ) / (C + 1)) * min ε (1 / t) = (α ^ 4 * (m : ℝ)) * (min ε (1 / t) / (C + 1)) := by ring _ ≤ (α ^ 4 * (m : ℝ)) * (ε / (C + ((m : ℝ) - 1) * ε)) := mul_le_mul_of_nonneg_left hratio hαm _ = (α ^ 2 * (m : ℝ) * ε) ^ 2 / ((m : ℝ) * ε * (C + ((m : ℝ) - 1) * ε)) := by field_simp [ne_of_gt hm0, ne_of_gt hε, ne_of_gt hden] end MaxCutGames.Foundations.PCP.PoweringNumeric /-! The actual graph-powering soundness bound. Modal endpoint opinions give the first moment, spectral return gives the second moment, and an actual checked path constraint turns each witness into rejection. -/ noncomputable section namespace MaxCutGames.Foundations.PCP.PoweringSoundness open scoped BigOperators open PoweringWalks PoweringLabels PoweringOpinions PoweringTest open SpectralReturn PoweringWitness PoweringMomentBound open PoweringMoment (bit hits) variable {V D A : Type*} def center (q M : Nat) : Nat := (4 * q * M) ^ 2 theorem le_center (q M : Nat) (hq : 1 ≤ q) (hM : 1 ≤ M) : M ≤ center q M := by have hfour : 1 ≤ 4 * q := by omega have hx : M ≤ 4 * q * M := by simpa only [Nat.one_mul] using Nat.mul_le_mul_right M hfour have hone : 1 ≤ 4 * q * M := hM.trans hx have hsquare : 4 * q * M ≤ (4 * q * M) * (4 * q * M) := by simpa only [Nat.mul_one] using Nat.mul_le_mul_left (4 * q * M) hone exact hx.trans (by simpa only [center, pow_two] using hsquare) def gain (q M : Nat) (lambda : ℝ) : ℝ := (1 / (2 * (q : ℝ))) ^ 4 * ((2 * M + 1 : Nat) : ℝ) / ((1 + 2 / (1 - lambda)) + 1) variable [Fintype V] [Fintype D] [Nonempty V] [Nonempty D] [Fintype A] [Nonempty A] def decodedError (G : PortGraph V D) (accepts : Edge V D → A → A → Bool) (n N : Nat) (selectors : ∀ v, AddressSelector G (n + 1) v) (labels : V → PaddedLabel D (n + 1) A) (fallback : A) : ℝ := edgeDensity (decodedBad G accepts (decoded G (n + 1) N selectors labels fallback)) def poweredRejection (G : PortGraph V D) (accepts : Edge V D → A → A → Bool) (n : Nat) (selectors : ∀ v, AddressSelector G (n + 1) v) (labels : V → PaddedLabel D (n + 1) A) : ℝ := mean (fun d : Dart V D n => bit ((poweredGraph G accepts n selectors).edgeSatisfied labels d = false)) omit [Fintype V] [Nonempty V] in omit [Nonempty D] in theorem witness_bit_eq (G : PortGraph V D) (accepts : Edge V D → A → A → Bool) (n N : Nat) (selectors : ∀ v, AddressSelector G (n + 1) v) (labels : V → PaddedLabel D (n + 1) A) (fallback : A) (w : Walk V D (n + 1)) (k : Fin (n + 1)) : bit (witness G accepts n selectors labels fallback (decoded G (n + 1) N selectors labels fallback) w k) = vertexWitness G (decodedBad G accepts (decoded G (n + 1) N selectors labels fallback)) (matchFn G (n + 1) N selectors labels fallback) n k w := by simp only [witness, vertexWitness, endpointWitness, matchFn, PoweringMoment.bit_mul, next, and_assoc] omit [Nonempty V] in theorem modal_witness_mean (G : PortGraph V D) (M : Nat) (hM : 1 ≤ M) (accepts : Edge V (Bool × D) → A → A → Bool) (selectors : ∀ v, AddressSelector (lazyGraph G) (2 * center (Fintype.card A) M + 1) v) (labels : V → PaddedLabel (Bool × D) (2 * center (Fintype.card A) M + 1) A) (fallback : A) (k : Fin (2 * center (Fintype.card A) M + 1)) (hlo : center (Fintype.card A) M - M ≤ k.val) (hhi : k.val ≤ center (Fintype.card A) M + M) : decodedError (lazyGraph G) accepts (2 * center (Fintype.card A) M) (center (Fintype.card A) M) selectors labels fallback / (4 * (Fintype.card A : ℝ) ^ 2) ≤ mean (fun w => bit (witness (lazyGraph G) accepts (2 * center (Fintype.card A) M) selectors labels fallback (decoded (lazyGraph G) (2 * center (Fintype.card A) M + 1) (center (Fintype.card A) M) selectors labels fallback) w k)) := by have h := lazy_middle_witness_mean G (Fintype.card A) M Fintype.card_pos hM k hlo hhi (decodedBad (lazyGraph G) accepts (decoded (lazyGraph G) (2 * center (Fintype.card A) M + 1) (center (Fintype.card A) M) selectors labels fallback)) (matchFn (lazyGraph G) (2 * center (Fintype.card A) M + 1) (center (Fintype.card A) M) selectors labels fallback) (matchFn_mem_Icc (lazyGraph G) (2 * center (Fintype.card A) M + 1) (center (Fintype.card A) M) selectors labels fallback) (decoded_modal_baseline (lazyGraph G) (2 * center (Fintype.card A) M + 1) (center (Fintype.card A) M) selectors labels fallback) simp_rw [witness_bit_eq] convert h using 1 <;> rfl /-- Positive decoded error forces rejection of the actual powered graph. The cap and amplification coefficient are explicit constants. -/ theorem rejection_lower_bound (G : PortGraph V D) (lambda : ℝ) (certificate : SpectralCertificate (lazyGraph G) lambda) (accepts : Edge V (Bool × D) → A → A → Bool) (reverse_accepts : ∀ e a b, accepts ((lazyGraph G).rot e) b a = accepts e a b) (M : Nat) (hM : 1 ≤ M) (selectors : ∀ v, AddressSelector (lazyGraph G) (2 * center (Fintype.card A) M + 1) v) (labels : V → PaddedLabel (Bool × D) (2 * center (Fintype.card A) M + 1) A) (fallback : A) (hε : 0 < decodedError (lazyGraph G) accepts (2 * center (Fintype.card A) M) (center (Fintype.card A) M) selectors labels fallback) : gain (Fintype.card A) M lambda * min (decodedError (lazyGraph G) accepts (2 * center (Fintype.card A) M) (center (Fintype.card A) M) selectors labels fallback) (1 / ((2 * center (Fintype.card A) M + 1 : Nat) : ℝ)) ≤ poweredRejection (lazyGraph G) accepts (2 * center (Fintype.card A) M) selectors labels := by let q := Fintype.card A let N := center q M let n := 2 * N let m := 2 * M + 1 let start := N - M let L := lazyGraph G let assignment := decoded L (n + 1) N selectors labels fallback let bad := decodedBad L accepts assignment let ε := edgeDensity bad let α : ℝ := 1 / (2 * (q : ℝ)) let C : ℝ := 1 + 2 / (1 - lambda) have hNM : M ≤ N := le_center q M Fintype.card_pos hM have hw : start + m ≤ n + 1 := by dsimp [start, m, n]; omega let E := windowEvent L bad n start m hw let W : Fin m → Walk V (Bool × D) (n + 1) → Prop := fun i w => witness L accepts n selectors labels fallback assignment w (windowIndex n start m hw i) let R : Walk V (Bool × D) (n + 1) → Prop := fun w => pathAccepts L accepts n selectors w (labels w.1) (labels (endpoint L w)) = false have hWE : ∀ i w, W i w → E i w := by intro i w h exact h.1 have hWR : ∀ i w, W i w → R w := by intro i w h exact witness_implies_path_rejection L accepts n selectors labels fallback assignment w (windowIndex n start m hw i) h have hpoint (i : Fin m) : ε / (4 * (q : ℝ) ^ 2) ≤ mean (fun w => bit (W i w)) := by have hlo : N - M ≤ (windowIndex n start m hw i).val := by dsimp [windowIndex, start] omega have hhi : (windowIndex n start m hw i).val ≤ N + M := by have hi := i.isLt dsimp [windowIndex, start] dsimp [m] at hi omega exact modal_witness_mean G M hM accepts selectors labels fallback (windowIndex n start m hw i) hlo hhi have hfirst : α ^ 2 * (m : ℝ) * ε ≤ mean (hits W) := by change α ^ 2 * (m : ℝ) * ε ≤ PoweringMoment.mean (hits W) rw [PoweringMoment.mean_hits] calc _ = ∑ _i : Fin m, ε / (4 * (q : ℝ) ^ 2) := by simp only [Finset.sum_const, Finset.card_univ, Fintype.card_fin, nsmul_eq_mul] dsimp [α] ring _ ≤ _ := Finset.sum_le_sum (fun i _ => hpoint i) have hsecond : mean (fun w => hits E w ^ 2) ≤ (m : ℝ) * ε * (C + ((m : ℝ) - 1) * ε) := window_second_moment_le L lambda certificate bad (decodedBad_rot L accepts reverse_accepts assignment) n start m hw have hε' : 0 < ε := hε have hm : 0 < m := by dsimp [m]; omega have hmReal : (0 : ℝ) < m := Nat.cast_pos.mpr hm have hqReal : (0 : ℝ) < q := Nat.cast_pos.mpr Fintype.card_pos have hden : 0 < 1 - lambda := sub_pos.mpr certificate.lt_one have hC : 0 < C := by dsimp [C]; positivity have hmOne : (1 : ℝ) ≤ m := by exact_mod_cast hm have hα : 0 < α := by dsimp [α]; positivity have ha : 0 < α ^ 2 * (m : ℝ) * ε := by positivity have hb : 0 < (m : ℝ) * ε * (C + ((m : ℝ) - 1) * ε) := by have hdiff : 0 ≤ (m : ℝ) - 1 := sub_nonneg.mpr hmOne positivity have hCS := PoweringMoment.rejection_lower_bound E W R hWE hWR (α ^ 2 * (m : ℝ) * ε) ((m : ℝ) * ε * (C + ((m : ℝ) - 1) * ε)) ha hb hfirst hsecond have ht : (0 : ℝ) < ((n + 1 : Nat) : ℝ) := Nat.cast_pos.mpr (Nat.succ_pos n) have hmn : m ≤ n + 1 := by dsimp [m, n]; omega have hmt : (m : ℝ) - 1 ≤ ((n + 1 : Nat) : ℝ) := by have hmnReal : (m : ℝ) ≤ ((n + 1 : Nat) : ℝ) := by exact_mod_cast hmn linarith have hratio := PoweringNumeric.count_moment_ratio_lower α ε C ((n + 1 : Nat) : ℝ) m hm hε' hC ht hmt change (α ^ 4 * (m : ℝ) / (C + 1)) * min ε (1 / ((n + 1 : Nat) : ℝ)) ≤ _ change _ ≤ mean (fun d : Dart V (Bool × D) n => bit ((poweredGraph L accepts n selectors).edgeSatisfied labels d = false)) rw [rejection_mean_eq_path_mean] exact hratio.trans hCS end MaxCutGames.Foundations.PCP.PoweringSoundness end namespace MaxCutGames.Foundations.PCP.PoweringGap open PoweringWalks PoweringLabels PoweringOpinions PoweringTest open SpectralReturn PoweringSoundness PoweringCounting variable {V D A : Type*} theorem gain_nonneg (q M : Nat) (lambda : ℝ) (hlambda : lambda < 1) : 0 ≤ gain q M lambda := by have hden : 0 < 1 - lambda := sub_pos.mpr hlambda unfold gain positivity variable [Fintype V] [Fintype D] [Nonempty V] [Nonempty D] [Fintype A] [Nonempty A] theorem uniform_count_gap (G : PortGraph V D) (lambda : ℝ) (certificate : SpectralCertificate (lazyGraph G) lambda) (accepts : Edge V (Bool × D) → A → A → Bool) (reverse_accepts : ∀ e a b, accepts ((lazyGraph G).rot e) b a = accepts e a b) (M : Nat) (hM : 1 ≤ M) (selectors : ∀ v, AddressSelector (lazyGraph G) (2 * center (Fintype.card A) M + 1) v) (epsilon : ℝ) (hepsilon : 0 ≤ epsilon) (hgap : ∀ assignment : V → A, epsilon * (Fintype.card (Edge V (Bool × D)) : ℝ) ≤ ((baseGraph (lazyGraph G) accepts reverse_accepts).rejectionCount assignment : ℝ)) (labels : V → PaddedLabel (Bool × D) (2 * center (Fintype.card A) M + 1) A) : (gain (Fintype.card A) M lambda * min epsilon (1 / ((2 * center (Fintype.card A) M + 1 : Nat) : ℝ))) * (Fintype.card (Dart V (Bool × D) (2 * center (Fintype.card A) M)) : ℝ) ≤ ((poweredGraph (lazyGraph G) accepts (2 * center (Fintype.card A) M) selectors).rejectionCount labels : ℝ) := by classical let L := lazyGraph G let N := center (Fintype.card A) M let n := 2 * N let H := poweredGraph L accepts n selectors change (gain (Fintype.card A) M lambda * min epsilon (1 / ((n + 1 : Nat) : ℝ))) * (Fintype.card (Dart V (Bool × D) n) : ℝ) ≤ (H.rejectionCount labels : ℝ) rcases eq_or_lt_of_le hepsilon with hzero | hpositive · rw [← hzero] have hcap : (0 : ℝ) ≤ 1 / ((n + 1 : Nat) : ℝ) := by positivity rw [min_eq_left hcap, mul_zero, zero_mul] exact Nat.cast_nonneg _ · let fallback : A := Classical.choice (inferInstance : Nonempty A) let assignment := decoded L (n + 1) N selectors labels fallback have hdecoded : epsilon ≤ decodedError L accepts n N selectors labels fallback := by change epsilon ≤ edgeDensity (decodedBad L accepts assignment) exact base_count_lower_to_density L accepts reverse_accepts assignment Fintype.card_pos epsilon (hgap assignment) have herror : 0 < decodedError L accepts n N selectors labels fallback := hpositive.trans_le hdecoded have hsound := PoweringSoundness.rejection_lower_bound G lambda certificate accepts reverse_accepts M hM selectors labels fallback herror have hgain : 0 ≤ gain (Fintype.card A) M lambda := gain_nonneg (Fintype.card A) M lambda certificate.lt_one have hmin : min epsilon (1 / ((n + 1 : Nat) : ℝ)) ≤ min (decodedError L accepts n N selectors labels fallback) (1 / ((n + 1 : Nat) : ℝ)) := min_le_min hdecoded (le_refl _) have hlower : gain (Fintype.card A) M lambda * min epsilon (1 / ((n + 1 : Nat) : ℝ)) ≤ poweredRejection L accepts n selectors labels := (mul_le_mul_of_nonneg_left hmin hgain).trans hsound exact (constraint_rejection_lower_iff H labels Fintype.card_pos (gain (Fintype.card A) M lambda * min epsilon (1 / ((n + 1 : Nat) : ℝ)))).mp hlower end MaxCutGames.Foundations.PCP.PoweringGap /-! # The fixed constants in the actual powering estimate The six-bit alphabet has 64 letters. The middle window, endpoint length, spectral parameter and composition loss in the checked powering theorem give exactly the constants used in the final amplification round. Large natural constants remain symbolic in these calculations. -/ namespace MaxCutGames.Foundations.PCP.PoweringFinalConstants abbrev Alphabet := Fin 6 → Bool @[simp] theorem card_alphabet : Fintype.card Alphabet = 64 := by norm_num [Alphabet, Fintype.card_fun] theorem card_alphabet_eq_final : Fintype.card Alphabet = FinalConstants.alphabet := by exact card_alphabet /-- The actual six-bit alphabet gives the endpoint length fixed for the round. -/ theorem center_eq : PoweringSoundness.center (Fintype.card Alphabet) FinalConstants.windowHalf = FinalConstants.endpointLength := by rw [card_alphabet] rfl /-- Prefix, pivot and suffix together have the fixed odd walk length. -/ theorem walkLength_eq : 2 * PoweringSoundness.center (Fintype.card Alphabet) FinalConstants.windowHalf + 1 = FinalConstants.walkLength := by rw [center_eq] rfl /-- The spectral denominator is exactly 66 at the fixed return parameter. -/ theorem spectral_denominator_eq : (1 + 2 / (1 - (31 / 32 : ℝ))) + 1 = 66 := by norm_num /-- Dividing the actual powering coefficient by the composition loss gives the round coefficient exactly. The large window parameter is not evaluated. -/ theorem gain_eq : PoweringSoundness.gain 64 FinalConstants.windowHalf (31 / 32) / 12288 = FinalConstants.gain := by change (1 / (2 * (FinalConstants.alphabet : ℝ))) ^ 4 * (FinalConstants.windowSize : ℝ) / ((1 + 2 / (1 - (31 / 32 : ℝ))) + 1) / (FinalConstants.compositionLoss : ℝ) = (FinalConstants.windowSize : ℝ) / (FinalConstants.denominator : ℝ) rw [spectral_denominator_eq] have hden : (FinalConstants.denominator : ℝ) = 16 * (FinalConstants.alphabet : ℝ) ^ 4 * 66 * (FinalConstants.compositionLoss : ℝ) := by simp only [FinalConstants.denominator, Nat.cast_mul, Nat.cast_pow, Nat.cast_ofNat] rw [hden] simp only [div_eq_mul_inv, mul_inv_rev] ring theorem gain_card_eq : PoweringSoundness.gain (Fintype.card Alphabet) FinalConstants.windowHalf (31 / 32) / 12288 = FinalConstants.gain := by rw [card_alphabet] exact gain_eq /-- Both the coefficient and cap in the actual estimate match the fixed round constants, for every real error parameter. -/ theorem scaled_bound_eq (ε : ℝ) : (PoweringSoundness.gain (Fintype.card Alphabet) FinalConstants.windowHalf (31 / 32) * min ε (1 / ((2 * PoweringSoundness.center (Fintype.card Alphabet) FinalConstants.windowHalf + 1 : Nat) : ℝ))) / 12288 = FinalConstants.gain * min ε FinalConstants.cap := by rw [walkLength_eq] rw [mul_div_right_comm, gain_card_eq] rfl /-- The composed powering and alphabet-reduction coefficient yields the fixed doubling bound after the checked preprocessing loss. -/ theorem composed_scaled_gap (ε : ℝ) (hε : 0 ≤ ε) : min (2 * ε) FinalConstants.cap ≤ (PoweringSoundness.gain (Fintype.card Alphabet) FinalConstants.windowHalf (31 / 32) * min (ε / (Preprocessing.sizeFactor : ℝ)) (1 / ((2 * PoweringSoundness.center (Fintype.card Alphabet) FinalConstants.windowHalf + 1 : Nat) : ℝ))) / 12288 := by rw [scaled_bound_eq] exact FinalConstants.composed_gap ε hε end MaxCutGames.Foundations.PCP.PoweringFinalConstants end OAI