Bit rank and Walsh bounds for global vector-slot pairings
Lax342547.SlotWalsh · concepts/Lax342547/SlotWalsh.lean · lax-342547
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Lemma
Each of N bit coordinates carries the same cross-slot coefficient matrix. The resulting bilinear bit matrix has rank N times its rank, so a nonzero cross pattern has correlation at most 2^(-N/2).
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| 1 | import Lax342547.BilinearWalsh |
| 2 | |
| 3 | /-! |
| 4 | --- |
| 5 | title: Bit rank and Walsh bounds for global vector-slot pairings |
| 6 | type: lemma |
| 7 | --- |
| 8 | Each of N bit coordinates carries the same cross-slot coefficient |
| 9 | matrix. The resulting bilinear bit matrix has rank N times its rank, |
| 10 | so a nonzero cross pattern has correlation at most 2^(-N/2). |
| 11 | -/ |
| 12 | |
| 13 | namespace Lax342547.SlotWalsh |
| 14 | |
| 15 | open Lax342547.MomentSpace |
| 16 | |
| 17 | def bitMatrix {I J : Type} (C : Matrix I J Binary) (N : ℕ) : |
| 18 | Matrix (Fin N × I) (Fin N × J) Binary := |
| 19 | fun x y => if x.1 = y.1 then C x.2 y.2 else 0 |
| 20 | |
| 21 | axiom bit_evaluation {I J : Type} [Fintype I] [Fintype J] |
| 22 | (C : Matrix I J Binary) (N : ℕ) (x : Fin N × I → Binary) (y : Fin N × J → Binary) : |
| 23 | dotProduct x ((bitMatrix C N).mulVec y) = ∑ i, ∑ j, C i j * ∑ a, x (a, i) * y (a, j) |
| 24 | |
| 25 | axiom bit_rank {I J : Type} [Fintype J] |
| 26 | (C : Matrix I J Binary) (N : ℕ) : (bitMatrix C N).rank = N * C.rank |
| 27 | |
| 28 | axiom nonzero_pattern_bound {I J : Type} [Fintype I] [Fintype J] |
| 29 | [DecidableEq I] [DecidableEq J] (C : Matrix I J Binary) (hC : C ≠ 0) (N : ℕ) |
| 30 | (f : (Fin N × I → Binary) → ℝ) (g : (Fin N × J → Binary) → ℝ) |
| 31 | (hf : ∀ x, |f x| ≤ 1) (hg : ∀ y, |g y| ≤ 1) : |
| 32 | |BilinearWalsh.average (bitMatrix C N) f g| ≤ 1 / Real.sqrt ((2 : ℝ) ^ N) |
| 33 | |
| 34 | end Lax342547.SlotWalsh |
| 35 |
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