import Mathlib import OAI.Probability.Contingency.GreedyTable namespace OAI /-! Direct Cases. -/ noncomputable section open scoped BigOperators open scoped BigOperators namespace Contingency noncomputable section variable {m n : ℕ} (r : Fin m → ℕ) (c : Fin n → ℕ) def DirectCase (_c : Fin n → ℕ) : Prop := m=0 ∨ n=0 ∨ (∑ i,r i)=0 ∨ m=1 ∨ n=1 theorem table_subsingleton_of_direct (h : DirectCase r c) : Subsingleton (Tables r c) := by constructor intro X Y apply Subtype.ext funext i j rcases h with hm | hn | hN | hm | hn · exact Fin.elim0 (hm ▸ i) · exact Fin.elim0 (hn ▸ j) · have hi : r i=0 := by have hh := Finset.single_le_sum (fun i _ => Nat.zero_le (r i)) (Finset.mem_univ i) omega have hx := Finset.single_le_sum (fun j _ => Nat.zero_le (X.val i j)) (Finset.mem_univ j) have hy := Finset.single_le_sum (fun j _ => Nat.zero_le (Y.val i j)) (Finset.mem_univ j) rw [X.property.1 i,hi] at hx rw [Y.property.1 i,hi] at hy omega · subst m have hx := X.property.2 j have hy := Y.property.2 j simp only [Fin.sum_univ_one] at hx hy have hi : i=0 := Fin.eq_zero i simp only [hi,hx,hy] · subst n have hx := X.property.1 i have hy := Y.property.1 i simp only [Fin.sum_univ_one] at hx hy have hj : j=0 := Fin.eq_zero j simp only [hj,hx,hy] namespace Law variable {α : Type*} [Fintype α] [Nonempty α] [Subsingleton α] theorem uniform_subsingleton (x : α) : uniform α=pure x := by classical apply Law.ext funext a have hcard : Fintype.card α=1 := by rw [← Nat.card_eq_fintype_card]; exact Nat.card_unique simp [uniform,pure,hcard,Subsingleton.elim a x] end Law local instance directCasesTablesFintype : Fintype (Tables r c) := Fintype.ofFinite _ def arbitraryDraw (hrc : (∑ i,r i)=∑ j,c j) (k : ℕ) : DyadicLaw (Tables r c) := by classical by_cases h : DirectCase r c · exact DyadicLaw.pure (greedyTable r c hrc) 0 · have hm : 0 < m := by by_contra hh; exact h (Or.inl (by omega)) have hn : 0 < n := by by_contra hh; exact h (Or.inr (Or.inl (by omega))) exact PaddedGraph.canonicalDraw r c hm hn hrc k theorem arbitraryDraw_bits (hrc : (∑ i,r i)=∑ j,c j) (k : ℕ) : (arbitraryDraw r c hrc k).bits≤Schedule.R (Parameters.dim m n) (Parameters.bits m n (∑ i,r i)) k := by classical unfold arbitraryDraw split_ifs · exact Nat.zero_le _ · exact (PaddedGraph.canonicalDraw_bits _ _ _ _ _ _).le theorem arbitraryDraw_tv (hrc : (∑ i,r i)=∑ j,c j) (k : ℕ) (hk : 1≤k) : letI := tables_nonempty r c hrc (arbitraryDraw r c hrc k).toLaw.tv (Law.uniform (Tables r c))≤(2:ℝ)^(-(k:ℤ)) := by classical let := tables_nonempty r c hrc unfold arbitraryDraw split_ifs with h · have huni : Law.uniform (Tables r c)=Law.pure (greedyTable r c hrc) := by let := table_subsingleton_of_direct r c h exact Law.uniform_subsingleton _ rw [DyadicLaw.toLaw_pure,huni,Law.tv_self] positivity · exact PaddedGraph.canonicalDraw_tv _ _ _ _ _ _ hk end end Contingency open scoped BigOperators namespace Contingency.IntegerTabulation def step {s : ℕ} (A : Fin s → Fin s → ℕ) (v : Fin s → ℕ) (j : Fin s) : ℕ := ∑ i,v i*A i j def propagate {s : ℕ} (A : Fin s → Fin s → ℕ) (v : Fin s → ℕ) : ℕ → (Fin s → ℕ) | 0 => v | t+1 => step A (propagate A v t) def propagationOps (s : ℕ) : ℕ → ℕ | 0 => 0 | t+1 => propagationOps s t+2*s*s theorem propagationOps_eq (s t : ℕ) : propagationOps s t=2*t*s^2 := by induction t with | zero => simp [propagationOps] | succ t ih => rw [propagationOps,ih]; ring theorem step_total {s : ℕ} (A : Fin s → Fin s → ℕ) (v : Fin s → ℕ) (Q : ℕ) (hA : ∀ i,∑ j,A i j=2^Q) : (∑ j,step A v j)=(∑ i,v i)*2^Q := by unfold step rw [Finset.sum_comm] simp_rw [← Finset.mul_sum,hA] rw [Finset.sum_mul] theorem propagate_total {s : ℕ} (A : Fin s → Fin s → ℕ) (v : Fin s → ℕ) (Q R : ℕ) (hA : ∀ i,∑ j,A i j=2^Q) (hv : ∑ i,v i=2^R) (t : ℕ) : (∑ i,propagate A v t i)=2^(R+t*Q) := by induction t with | zero => simpa [propagate] using hv | succ t ih => rw [propagate,step_total _ _ Q hA,ih,← pow_add]; congr 1; ring theorem propagate_entry_bound {s : ℕ} (A : Fin s → Fin s → ℕ) (v : Fin s → ℕ) (Q R : ℕ) (hA : ∀ i,∑ j,A i j=2^Q) (hv : ∑ i,v i=2^R) (t : ℕ) (i : Fin s) : propagate A v t i≤2^(R+t*Q) := by rw [← propagate_total A v Q R hA hv t] exact Finset.single_le_sum (fun _ _ => Nat.zero_le _) (Finset.mem_univ i) theorem partial_step_bound {s : ℕ} (A : Fin s → Fin s → ℕ) (v : Fin s → ℕ) (Q R : ℕ) (hA : ∀ i,∑ j,A i j=2^Q) (hv : ∑ i,v i=2^R) (t : ℕ) (j : Fin s) (I : Finset (Fin s)) : (∑ i∈I,propagate A v t i*A i j)≤2^(R+(t+1)*Q) := by apply (Finset.sum_le_sum_of_subset_of_nonneg (Finset.subset_univ I) (fun _ _ _ => Nat.zero_le _)).trans exact propagate_entry_bound A v Q R hA hv (t+1) j theorem propagate_walk {s : ℕ} (q : Fin s → DyadicLaw (Fin s)) (Q : ℕ) (hq : ∀ i,(q i).bits=Q) (i₀ : Fin s) (t : ℕ) : propagate (fun i j => (q i).count j) (fun i => if i=i₀ then 1 else 0) t= (DyadicLaw.walk q Q hq i₀ t).count := by induction t with | zero => rfl | succ t ih => funext j simp only [propagate,step,DyadicLaw.walk,DyadicLaw.bind,ih] def stoppedVector {s : ℕ} (R φ : ℕ) (a : Fin s → ℕ) (z₀ : Fin s) : ℕ → (Fin s → ℕ) | 0 => fun z => if z=z₀ then 1 else 0 | j+1 => fun z => a z*2^(R*j)+φ*stoppedVector R φ a z₀ j z theorem stoppedVector_eq {s : ℕ} (R φ : ℕ) (a : Fin s → ℕ) (z₀ : Fin s) (J : ℕ) (z : Fin s) : stoppedVector R φ a z₀ J z=stoppedNumerator R φ a z₀ z J := by induction J with | zero => rfl | succ J ih => simp only [stoppedVector,stoppedNumerator,ih] theorem stoppedVector_total {s : ℕ} (R φ : ℕ) (a : Fin s → ℕ) (z₀ : Fin s) (ht : (∑ z,a z)+φ=2^R) (J : ℕ) : (∑ z,stoppedVector R φ a z₀ J z)=2^(R*J) := by simp_rw [stoppedVector_eq] exact stoppedNumerator_total R φ a z₀ ht J theorem stoppedVector_bound {s : ℕ} (R φ : ℕ) (a : Fin s → ℕ) (z₀ : Fin s) (ht : (∑ z,a z)+φ=2^R) (J : ℕ) (z : Fin s) : stoppedVector R φ a z₀ J z≤2^(R*J) := by rw [← stoppedVector_total R φ a z₀ ht J] exact Finset.single_le_sum (fun _ _ => Nat.zero_le _) (Finset.mem_univ z) end Contingency.IntegerTabulation open scoped BigOperators namespace Contingency.PaddedGraph noncomputable section variable {m n : ℕ} (U L : ℕ) (r : Fin m → ℕ) (c : Fin n → ℕ) def graphArray (X : GraphState U r c) : Bool×Cell m n → Fin (U+1) := fun w => ⟨(if w.1 then (graphUnderlying U r c X).x w.2 else (graphUnderlying U r c X).q w.2).toNat,by have h := (graph_feasible U r c X).1 w.2 cases w.1 <;> simp only [Bool.false_eq_true,ite_false,ite_true] <;> omega⟩ theorem graphArray_injective : Function.Injective (graphArray U r c) := by intro X Y h apply graphUnderlying_injective U r c have hx : (graphUnderlying U r c X).x=(graphUnderlying U r c Y).x := by funext w have hh := congrArg Fin.val (congrFun h (true,w)) dsimp [graphArray] at hh have hX := ((graph_feasible U r c X).1 w).1 have hY := ((graph_feasible U r c Y).1 w).1 omega have hq : (graphUnderlying U r c X).q=(graphUnderlying U r c Y).q := by funext w have hh := congrArg Fin.val (congrFun h (false,w)) dsimp [graphArray] at hh have hX := ((graph_feasible U r c X).1 w).2.2.1 have hY := ((graph_feasible U r c Y).1 w).2.2.1 omega exact congrArg₂ State.mk hx hq theorem graph_card_array : Nat.card (GraphState U r c)≤(U+1)^(2*(m*n)) := by rw [Nat.card_eq_fintype_card] simpa [Cell] using Fintype.card_le_of_injective (graphArray U r c) (graphArray_injective U r c) theorem graph_card_dyadic (d b C : ℕ) (hmn : m*n≤d) (hU : U≤C) (hCb : C+1≤2^b) : Nat.card (GraphState U r c)≤2^(2*d*b) := by calc _ ≤ (U+1)^(2*(m*n)) := graph_card_array U r c _ ≤ (C+1)^(2*(m*n)) := Nat.pow_le_pow_left (by omega) _ _ ≤ (C+1)^(2*d) := Nat.pow_le_pow_right (by omega) (by omega) _ ≤ (2^b)^(2*d) := Nat.pow_le_pow_left hCb _ _ = _ := by rw [← pow_mul]; congr 1; ring def completionArray (C : ℕ) (hC : ∀ i,paddedRow U L r c i≤C) (X : GraphState U r c) (A : Completion U L r c (graphUnderlying U r c X)) : Cell m n → Fin (C+1) := fun w => ⟨(A.val w).toNat,by have hlo := A.property.1 w have hhi := (completion_cell_le U L r c _ (graph_feasible U r c X) A w).trans (hC w.1) omega⟩ theorem completion_card_cap (C : ℕ) (hC : ∀ i,paddedRow U L r c i≤C) (X : GraphState U r c) : Nat.card (Completion U L r c (graphUnderlying U r c X))≤(C+1)^(m*n) := by let : Fintype (Completion U L r c (graphUnderlying U r c X)) := Fintype.ofFinite _ have hinj : Function.Injective (completionArray U L r c C hC X) := by intro A B h apply Subtype.ext funext w have hh := congrArg Fin.val (congrFun h w) dsimp [completionArray] at hh have ha := A.property.1 w have hb := B.property.1 w omega rw [Nat.card_eq_fintype_card] simpa [Cell] using Fintype.card_le_of_injective _ hinj theorem completion_card_dyadic (d b C : ℕ) (hmn : m*n≤d) (hC : ∀ i,paddedRow U L r c i≤C) (hCb : C+1≤2^b) (X : GraphState U r c) : Nat.card (Completion U L r c (graphUnderlying U r c X))≤2^(d*b) := by calc _ ≤ (C+1)^(m*n) := completion_card_cap U L r c C hC X _ ≤ (C+1)^d := Nat.pow_le_pow_right (by omega) hmn _ ≤ (2^b)^d := Nat.pow_le_pow_left hCb _ _ = _ := by rw [← pow_mul]; congr 1; ring end end Contingency.PaddedGraph namespace Contingency.BinaryArithmetic open PosNum def succCost : PosNum → ℕ | .one => 1 | .bit0 _ => 1 | .bit1 a => succCost a+1 theorem succCost_le (a : PosNum) : succCost a≤a.natSize := by induction a <;> simp_all [succCost,PosNum.natSize] theorem succ_size_le (a : PosNum) : a.succ.natSize≤a.natSize+1 := by induction a <;> simp_all [PosNum.succ,PosNum.natSize] theorem add_size_le (a b : PosNum) : (a+b).natSize≤a.natSize+b.natSize := by induction a generalizing b with | one => change (PosNum.succ b).natSize≤1+b.natSize simpa [Nat.add_comm] using succ_size_le b | bit0 a ih => cases b with | one => exact (succ_size_le a.bit0) | bit0 b => change (a+b).natSize+1≤(a.natSize+1)+(b.natSize+1); have := ih b; omega | bit1 b => change (a+b).natSize+1≤(a.natSize+1)+(b.natSize+1); have := ih b; omega | bit1 a ih => cases b with | one => exact (succ_size_le a.bit1) | bit0 b => change (a+b).natSize+1≤(a.natSize+1)+(b.natSize+1); have := ih b; omega | bit1 b => change (a+b).succ.natSize+1≤(a.natSize+1)+(b.natSize+1) have := succ_size_le (a+b) have := ih b omega def addCost : PosNum → PosNum → ℕ | .one,b => succCost b+1 | a,.one => succCost a+1 | .bit0 a,.bit0 b => addCost a b+1 | .bit1 a,.bit1 b => addCost a b+succCost (a+b)+2 | .bit0 a,.bit1 b => addCost a b+1 | .bit1 a,.bit0 b => addCost a b+1 theorem addCost_le (a b : PosNum) : addCost a b≤(a.natSize+b.natSize+1)^2 := by induction a generalizing b with | one => have := succCost_le b simp only [addCost,PosNum.natSize] nlinarith | bit0 a ih => cases b with | one => have := succCost_le a.bit0; simp only [addCost,PosNum.natSize,Nat.succ_eq_add_one] at *; nlinarith | bit0 b => have := ih b; simp only [addCost,PosNum.natSize,Nat.succ_eq_add_one]; nlinarith [Nat.zero_le a.natSize,Nat.zero_le b.natSize] | bit1 b => have := ih b; simp only [addCost,PosNum.natSize,Nat.succ_eq_add_one]; nlinarith [Nat.zero_le a.natSize,Nat.zero_le b.natSize] | bit1 a ih => cases b with | one => have := succCost_le a.bit1; simp only [addCost,PosNum.natSize,Nat.succ_eq_add_one] at *; nlinarith | bit0 b => have := ih b; simp only [addCost,PosNum.natSize,Nat.succ_eq_add_one]; nlinarith [Nat.zero_le a.natSize,Nat.zero_le b.natSize] | bit1 b => have h := ih b have hs := (succCost_le (a+b)).trans (add_size_le a b) simp only [addCost,PosNum.natSize,Nat.succ_eq_add_one] nlinarith def mulCost (a : PosNum) : PosNum → ℕ | .one => a.natSize+1 | .bit0 b => mulCost a b+1 | .bit1 b => mulCost a b+addCost ((a*b).bit0) a+2 theorem mul_size_le (a b : PosNum) : (a*b).natSize≤a.natSize+b.natSize := by have ha : (a:ℕ)<2^a.natSize := by rw [PosNum.natSize_to_nat]; exact Nat.size_le.mp le_rfl have hb : (b:ℕ)<2^b.natSize := by rw [PosNum.natSize_to_nat]; exact Nat.size_le.mp le_rfl rw [PosNum.natSize_to_nat,PosNum.mul_to_nat,Nat.size_le,pow_add] exact Nat.mul_lt_mul_of_lt_of_le ha hb.le (by positivity) theorem mulCost_le (a b : PosNum) : mulCost a b≤4*(a.natSize+b.natSize+1)^3 := by induction b with | one => simp only [mulCost,PosNum.natSize]; nlinarith [Nat.zero_le (a.natSize^3)] | bit0 b ih => simp only [mulCost,PosNum.natSize,Nat.succ_eq_add_one]; nlinarith [Nat.zero_le a.natSize,Nat.zero_le b.natSize,Nat.zero_le (a.natSize*b.natSize)] | bit1 b ih => have ha := addCost_le ((a*b).bit0) a have hs := mul_size_le a b simp only [PosNum.natSize] at ha have hh : ((a*b).natSize+1+a.natSize+1)^2≤(2*(a.natSize+b.natSize+1))^2 := by apply Nat.pow_le_pow_left omega have ha' := ha.trans hh simp only [mulCost,PosNum.natSize,Nat.succ_eq_add_one] nlinarith theorem add_certificate (a b : PosNum) : ((a+b:PosNum):ℕ)=(a:ℕ)+(b:ℕ) ∧ addCost a b≤(a.natSize+b.natSize+1)^2 := ⟨PosNum.add_to_nat a b,addCost_le a b⟩ theorem mul_certificate (a b : PosNum) : ((a*b:PosNum):ℕ)=(a:ℕ)*(b:ℕ) ∧ mulCost a b≤4*(a.natSize+b.natSize+1)^3 := ⟨PosNum.mul_to_nat a b,mulCost_le a b⟩ end Contingency.BinaryArithmetic open scoped BigOperators namespace Contingency.BinaryArithmetic def numAddCost : Num → Num → ℕ | .zero, b => b.natSize+1 | a, .zero => a.natSize+1 | .pos a, .pos b => addCost a b+1 def numMulCost : Num → Num → ℕ | .zero, _ => 1 | _, .zero => 1 | .pos a, .pos b => mulCost a b+1 theorem numAddCost_le (a b : Num) : numAddCost a b≤(a.natSize+b.natSize+2)^2 := by cases a with | zero => simp only [numAddCost,Num.natSize,zero_add]; nlinarith [Nat.zero_le b.natSize] | pos a => cases b with | zero => simp only [numAddCost,Num.natSize,add_zero]; nlinarith [Nat.zero_le a.natSize] | pos b => have h := addCost_le a b simp only [numAddCost,Num.natSize] nlinarith [Nat.zero_le a.natSize,Nat.zero_le b.natSize] theorem numMulCost_le (a b : Num) : numMulCost a b≤5*(a.natSize+b.natSize+2)^3 := by cases a with | zero => have h := Nat.one_le_pow 3 (b.natSize+2) (by omega) have hh : 1≤5*(b.natSize+2)^3 := by omega simpa only [numMulCost,Num.natSize,zero_add] using hh | pos a => cases b with | zero => change 1≤5*(a.natSize+2)^3 have h := Nat.one_le_pow 3 (a.natSize+2) (by omega) omega | pos b => have h := mulCost_le a b simp only [numMulCost,Num.natSize] nlinarith [Nat.zero_le ((a.natSize+b.natSize)^2),Nat.zero_le ((a.natSize+b.natSize)^3),Nat.zero_le a.natSize,Nat.zero_le b.natSize] theorem numSize_le_of_lt (a : Num) (L : ℕ) (h : (a:ℕ)<2^L) : a.natSize≤L := by cases a with | zero => exact Nat.zero_le _ | pos a => change a.natSize≤L rw [PosNum.natSize_to_nat,Nat.size_le] exact h def binaryDot : List (Num×Num) → Num×ℕ | [] => (.zero,1) | (a,b)::xs => let t := binaryDot xs let p := a*b (p+t.1,t.2+numMulCost a b+numAddCost p t.1+3) def dotValue (xs : List (Num×Num)) : ℕ := (xs.map (fun ab => (ab.1:ℕ)*(ab.2:ℕ))).sum theorem binaryDot_value (xs : List (Num×Num)) : ((binaryDot xs).1:ℕ)=dotValue xs := by induction xs with | nil => rfl | cons ab xs ih => rcases ab with ⟨a,b⟩ simp only [binaryDot,Num.add_to_nat,Num.mul_to_nat,dotValue,List.map_cons,List.sum_cons] at * rw [ih] theorem binaryDot_cost (xs : List (Num×Num)) (L : ℕ) (hx : ∀ ab∈xs,ab.1.natSize≤L ∧ ab.2.natSize≤L) (hv : dotValue xs<2^L) : (binaryDot xs).2≤1+xs.length*(10*(2*L+2)^3) := by induction xs with | nil => simp [binaryDot] | cons ab xs ih => rcases ab with ⟨a,b⟩ have hv' : (a:ℕ)*(b:ℕ)+dotValue xs<2^L := hv have hp : (a:ℕ)*(b:ℕ)<2^L := (Nat.le_add_right _ _).trans_lt hv' have ht : dotValue xs<2^L := (Nat.le_add_left _ _).trans_lt hv' have hab := hx (a,b) (by simp) dsimp only at hab have hc := ih (fun ab h => hx ab (by simp [h])) ht have hs := numSize_le_of_lt (a*b) L (by simpa only [Num.mul_to_nat] using hp) have hst := numSize_le_of_lt (binaryDot xs).1 L (by simpa only [binaryDot_value] using ht) have hm := (numMulCost_le a b).trans (Nat.mul_le_mul_left 5 (Nat.pow_le_pow_left (by omega : a.natSize+b.natSize+2≤2*L+2) 3)) have ha := (numAddCost_le (a*b) (binaryDot xs).1).trans (Nat.pow_le_pow_left (by omega : (a*b).natSize+(binaryDot xs).1.natSize+2≤2*L+2) 2) have he : (2*L+2)^2≤(2*L+2)^3 := Nat.pow_le_pow_right (by omega) (by omega) have hu : 1≤(2*L+2)^3 := Nat.one_le_pow _ _ (by omega) simp only [binaryDot,List.length_cons] nlinarith only [hc,hm,ha,he,hu] def binaryColumn {s : ℕ} (A : Fin s → Fin s → Num) (v : Fin s → Num) (j : Fin s) : Num×ℕ := binaryDot (List.ofFn (fun i => (v i,A i j))) theorem binaryColumn_value {s : ℕ} (A : Fin s → Fin s → Num) (v : Fin s → Num) (j : Fin s) : ((binaryColumn A v j).1:ℕ)=IntegerTabulation.step (fun i j => (A i j:ℕ)) (fun i => (v i:ℕ)) j := by rw [binaryColumn,binaryDot_value] simp [dotValue,IntegerTabulation.step,List.map_ofFn,List.sum_ofFn] def binaryPropagate {s : ℕ} (A : Fin s → Fin s → Num) (v : Fin s → Num) : ℕ → (Fin s → Num) | 0 => v | t+1 => let previous := binaryPropagate A v t fun j => (binaryColumn A previous j).1 theorem binaryPropagate_value {s : ℕ} (A : Fin s → Fin s → Num) (v : Fin s → Num) (t : ℕ) : (fun i => (binaryPropagate A v t i:ℕ))= IntegerTabulation.propagate (fun i j => (A i j:ℕ)) (fun i => (v i:ℕ)) t := by induction t with | zero => rfl | succ t ih => funext j simp only [binaryPropagate,binaryColumn_value,IntegerTabulation.propagate,ih] end Contingency.BinaryArithmetic open scoped BigOperators namespace Contingency.BinaryArithmetic variable {s : ℕ} (A : Fin s → Fin s → Num) (v : Fin s → Num) (Q R : ℕ) (hA : ∀ i,∑ j,(A i j:ℕ)=2^Q) (hv : ∑ i,(v i:ℕ)=2^R) theorem denominator_size (x B : ℕ) (hx : x≤2^B) : x<2^(B+1) := by exact hx.trans_lt (Nat.pow_lt_pow_right (by norm_num) (Nat.lt_succ_self B)) include hA hv in theorem binaryColumn_cost (t : ℕ) (j : Fin s) : (binaryColumn A (binaryPropagate A v t) j).2≤ 1+s*(10*(2*(R+(t+1)*Q+1)+2)^3) := by let L := R+(t+1)*Q+1 have hval := binaryPropagate_value A v t have hvec (i : Fin s) : (binaryPropagate A v t i:ℕ)≤2^(R+t*Q) := by rw [show (binaryPropagate A v t i:ℕ)= IntegerTabulation.propagate (fun i j => (A i j:ℕ)) (fun i => (v i:ℕ)) t i from congrFun hval i] exact IntegerTabulation.propagate_entry_bound _ _ Q R hA hv t i have hentry (i l : Fin s) : (A i l:ℕ)≤2^Q := by rw [← hA i] exact Finset.single_le_sum (fun l _ => Nat.zero_le (A i l:ℕ)) (Finset.mem_univ l) have hi : Q≤R+(t+1)*Q := by nlinarith only [Nat.zero_le R,Nat.zero_le (t*Q)] unfold binaryColumn have hh := binaryDot_cost (List.ofFn (fun i => (binaryPropagate A v t i,A i j))) L rw [List.length_ofFn] at hh apply hh · intro ab hab rcases List.mem_ofFn.mp hab with ⟨i,rfl⟩ constructor · apply numSize_le_of_lt change (binaryPropagate A v t i:ℕ)<2^(R+(t+1)*Q+1) apply denominator_size exact (hvec i).trans (Nat.pow_le_pow_right (by norm_num) (by gcongr; omega)) · apply numSize_le_of_lt change (A i j:ℕ)<2^(R+(t+1)*Q+1) exact denominator_size _ _ ((hentry i j).trans (Nat.pow_le_pow_right (by norm_num) hi)) · change _<2^(R+(t+1)*Q+1) apply denominator_size rw [← binaryDot_value] change ((binaryColumn A (binaryPropagate A v t) j).1:ℕ)≤_ rw [binaryColumn_value,hval] exact IntegerTabulation.propagate_entry_bound _ _ Q R hA hv (t+1) j def binaryPropagationCost : ℕ → ℕ | 0 => 0 | t+1 => binaryPropagationCost t+∑ j,(binaryColumn A (binaryPropagate A v t) j).2 include hA hv in theorem binaryPropagationCost_le_aux (T : ℕ) (t : ℕ) (ht : t≤T) : binaryPropagationCost A v t≤t*s*(1+s*(10*(2*(R+T*Q+1)+2)^3)) := by induction t with | zero => simp [binaryPropagationCost] | succ t ih => have hi := ih (by omega) have hcol (j : Fin s) := binaryColumn_cost A v Q R hA hv t j have hb : R+(t+1)*Q+1≤R+T*Q+1 := by gcongr have hm : (∑ j,(binaryColumn A (binaryPropagate A v t) j).2)≤ s*(1+s*(10*(2*(R+T*Q+1)+2)^3)) := by calc _ ≤ ∑ _ : Fin s,(1+s*(10*(2*(R+T*Q+1)+2)^3)) := by apply Finset.sum_le_sum intro j _ exact (hcol j).trans (by gcongr) _ = _ := by simp rw [binaryPropagationCost] nlinarith only [hi,hm] include hA hv in theorem binaryPropagationCost_le (T : ℕ) : binaryPropagationCost A v T≤T*s*(1+s*(10*(2*(R+T*Q+1)+2)^3)) := binaryPropagationCost_le_aux A v Q R hA hv T T le_rfl end Contingency.BinaryArithmetic end end OAI