openAI-math-dataset / lean /OAI /NumberTheory /TwoPoint /Circuits /CircuitPolynomialAlgebra.lean
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Add lean source and binary files (part 117)
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import OAI.NumberTheory.TwoPoint.Circuits.CircuitPolynomialMean
import Mathlib.Data.Finset.SymmDiff
namespace OAI
/-! Algebra of the low-degree functions used in the circuit approximation.
Multiplication adds degrees, including after Boolean multilinearization. -/
namespace TwoPointCorrelations
open Finset
open scoped Classical symmDiff
variable {n : ℕ}
lemma walsh_mul (S T : Finset (Fin n)) (x : BooleanCube n) :
walsh S x * walsh T x = walsh (S ∆ T) x := by
have hd : Disjoint (S ∆ T) (S ∩ T) := by
rw [disjoint_left]
intro i hi hi'
simp only [mem_symmDiff, mem_inter] at hi hi'
tauto
have hu : (S ∆ T) ∪ (S ∩ T) = S ∪ T := by
ext i
simp only [mem_union, mem_symmDiff, mem_inter]
tauto
have he : walsh (S ∪ T) x * walsh (S ∩ T) x = walsh S x * walsh T x :=
prod_union_inter
have hh : walsh (S ∪ T) x = walsh (S ∆ T) x * walsh (S ∩ T) x := by
simpa only [walsh, hu] using
(prod_union hd : (∏ i ∈ (S ∆ T) ∪ (S ∩ T), booleanSign (x i)) = _)
rw [hh, mul_assoc, walsh_mul_self, mul_one] at he
exact he.symm
lemma WalshDegreeLE.of_walsh (S : Finset (Fin n)) {t : ℕ} (hS : S.card ≤ t) :
WalshDegreeLE (walsh S) t := by
refine ⟨fun T => if T = S then 1 else 0, ?_⟩
intro x
simp [hS]
lemma WalshDegreeLE.const (c : ℝ) (t : ℕ) :
WalshDegreeLE (fun _ : BooleanCube n => c) t := by
refine ⟨fun S => if S = ∅ then c else 0, ?_⟩
intro x
simp
lemma WalshDegreeLE.smul {F : BooleanCube n → ℝ} {t : ℕ}
(hF : WalshDegreeLE F t) (c : ℝ) : WalshDegreeLE (fun x => c * F x) t := by
obtain ⟨a, ha⟩ := hF
refine ⟨fun S => c * a S, ?_⟩
intro x
dsimp only
rw [ha, mul_sum]
apply sum_congr rfl
intro S _
ring
lemma WalshDegreeLE.sub {F G : BooleanCube n → ℝ} {t : ℕ}
(hF : WalshDegreeLE F t) (hG : WalshDegreeLE G t) :
WalshDegreeLE (fun x => F x - G x) t := by
obtain ⟨a, ha⟩ := hF
obtain ⟨b, hb⟩ := hG
refine ⟨fun S => a S - b S, ?_⟩
intro x
dsimp only
rw [ha, hb, ← sum_sub_distrib]
apply sum_congr rfl
intro S _
ring
lemma WalshDegreeLE.sum {ι : Type*} (I : Finset ι) (F : ι → BooleanCube n → ℝ)
{t : ℕ} (hF : ∀ i ∈ I, WalshDegreeLE (F i) t) :
WalshDegreeLE (fun x => ∑ i ∈ I, F i x) t := by
choose a ha using fun i : I => hF i i.property
refine ⟨fun S => ∑ i : I, a i S, ?_⟩
intro x
dsimp only
rw [← sum_coe_sort I]
simp_rw [ha]
rw [sum_comm]
apply sum_congr rfl
intro S _
exact (sum_mul _ _ _).symm
lemma WalshDegreeLE.mul {F G : BooleanCube n → ℝ} {p q : ℕ}
(hF : WalshDegreeLE F p) (hG : WalshDegreeLE G q) :
WalshDegreeLE (fun x => F x * G x) (p + q) := by
obtain ⟨a, ha⟩ := hF
obtain ⟨b, hb⟩ := hG
let A := (univ : Finset (Finset (Fin n))).filter (fun S => S.card ≤ p)
let B := (univ : Finset (Finset (Fin n))).filter (fun S => S.card ≤ q)
have heq : (fun x => F x * G x) = fun x =>
∑ S ∈ A, ∑ T ∈ B, (a S * b T) * walsh (S ∆ T) x := by
funext x
rw [ha, hb, sum_mul]
apply sum_congr rfl
intro S _
rw [mul_sum]
apply sum_congr rfl
intro T _
rw [← walsh_mul]
ring
rw [heq]
apply WalshDegreeLE.sum A
intro S hS
apply WalshDegreeLE.sum B
intro T hT
apply WalshDegreeLE.smul
apply WalshDegreeLE.of_walsh
calc
(S ∆ T).card ≤ (S ∪ T).card := card_le_card symmDiff_subset_union
_ ≤ S.card + T.card := card_union_le S T
_ ≤ p + q := add_le_add (mem_filter.mp hS).2 (mem_filter.mp hT).2
end TwoPointCorrelations
end OAI