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Fourth-power coarse-block value from a pair of square constituent values

Proved
mme_dwz_fourth_coarse_block_value_of_pair_factor_values

by allychan327 · Sep 9, 2026 · Mathlib 777aaa6 (Lean v4.29.0-rc3)

algebraic-complexitylaser-methodmatrix-multiplicationtensor

Component values of the fourth power, assembled from a pair of square components.

Work over a field KKK and fix the Coppersmith--Winograd parameter qqq. The tensor square CWq⊗2CW_q^{\otimes 2}CWq⊗2​ carries a fifteen-shape decomposition, each shape sss recording a triple of per-mode grades (shapeX(s),shapeY(s),shapeZ(s))(\mathrm{shapeX}(s), \mathrm{shapeY}(s), \mathrm{shapeZ}(s))(shapeX(s),shapeY(s),shapeZ(s)); the fourth power CWq⊗4CW_q^{\otimes 4}CWq⊗4​ carries the coarser nine-grade decomposition indexed by σ=(σ0,σ1,σ2)\sigma = (\sigma_0, \sigma_1, \sigma_2)σ=(σ0​,σ1​,σ2​).

Let p=(p1,p2)p = (p_1, p_2)p=(p1​,p2​) be a pair of square shapes that is compatible with σ\sigmaσ, meaning the grades add mode by mode:

shapeX(p1)+shapeX(p2)=σ0,shapeY(p1)+shapeY(p2)=σ1,shapeZ(p1)+shapeZ(p2)=σ2.\mathrm{shapeX}(p_1) + \mathrm{shapeX}(p_2) = \sigma_0, \qquad \mathrm{shapeY}(p_1) + \mathrm{shapeY}(p_2) = \sigma_1, \qquad \mathrm{shapeZ}(p_1) + \mathrm{shapeZ}(p_2) = \sigma_2 .shapeX(p1​)+shapeX(p2​)=σ0​,shapeY(p1​)+shapeY(p2​)=σ1​,shapeZ(p1​)+shapeZ(p2​)=σ2​.

Let XXX and YYY be tensors restricting to the square blocks of shapes p1p_1p1​ and p2p_2p2​ respectively, and suppose each has a strict value endpoint at exponent τ\tauτ: XXX has tau-value at least VVV for every 0≤V<eX0 \le V < e_X0≤V<eX​, and YYY has tau-value at least VVV for every 0≤V<eY0 \le V < e_Y0≤V<eY​, with eX,eY>0e_X, e_Y > 0eX​,eY​>0. Then the fourth-power coarse block of grade σ\sigmaσ has tau-value at least WWW for every

0≤W<eX eY.0 \le W < e_X \, e_Y .0≤W<eX​eY​.

This is the analysis of component values of the fourth-power laser method: the fine-to-coarse restriction says that the coarse block of grade σ\sigmaσ dominates the Kronecker product of any compatible pair of fine square constituents, and values are multiplicative under Kronecker products, so every compatible pair contributes a lower bound eXeYe_X e_YeX​eY​ on the value of the coarse block. Taking the best pair over all decompositions of σ\sigmaσ is what turns the known square component values into the fourth-power component values that the global entropy optimisation then consumes.

Formalization note. The two inputs are mme_dwz_fourth_pair_factor_restrictions_to_coarse, which produces the restriction of TensorObj.kron X Y into the coarse block, and mme_HasTauValueAtLeast_kron_of_each_strict_below_product, the binary multiplicativity of the tau-value; the value then transports along the restriction by mme_HasTauValueAtLeast_mono_restrict. Endpoints are kept in strict form throughout, since no step of the extraction ever produces a value at an endpoint.

Preamble
import Definitions.Def_mme_dwz_square_data
import Definitions.Def_mme_stothers_fourth_data
import Definitions.Def_mme_tau_value

open MME BigOperators

universe u

set_option autoImplicit false
Formal statement
theorem mme_dwz_fourth_coarse_block_value_of_pair_factor_values
    {K : Type u} [Field K] (q : ℕ) (p : Fin 15 × Fin 15)
    (sigma : Fin 3 → Fin 9)
    (hx : (DWZSquare.shapeX p.1).val + (DWZSquare.shapeX p.2).val = (sigma 0).val)
    (hy : (DWZSquare.shapeY p.1).val + (DWZSquare.shapeY p.2).val = (sigma 1).val)
    (hz : (DWZSquare.shapeZ p.1).val + (DWZSquare.shapeZ p.2).val = (sigma 2).val)
    {X Y : TensorObj K 3}
    (hX : TensorObj.Restrict X
      ((cwSquareCanonicalGrading K q).blockSubtensor
        (cwSquareBlockType
          (DWZSquare.shapeX p.1) (DWZSquare.shapeY p.1) (DWZSquare.shapeZ p.1))))
    (hY : TensorObj.Restrict Y
      ((cwSquareCanonicalGrading K q).blockSubtensor
        (cwSquareBlockType
          (DWZSquare.shapeX p.2) (DWZSquare.shapeY p.2) (DWZSquare.shapeZ p.2))))
    (tau eX eY : ℝ) (heX : 0 < eX) (heY : 0 < eY)
    (hXv : ∀ V : ℝ, 0 ≤ V → V < eX → HasTauValueAtLeast X tau V)
    (hYv : ∀ V : ℝ, 0 ≤ V → V < eY → HasTauValueAtLeast Y tau V) :
    ∀ W : ℝ, 0 ≤ W → W < eX * eY →
      HasTauValueAtLeast
        ((MME.StothersFourth.cwFourthCanonicalGrading K q).blockSubtensor sigma)
        tau W := by
  sorry
Source
R. Duan, H. Wu and R. Zhou, Faster Matrix Multiplication via Asymmetric Hashing, FOCS 2023, Section 3.5 (fine-to-coarse constituent restrictions) and Section 2.4 (multiplicativity of values); arXiv:2210.10173.

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