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arXiv:2506.13242cs.SC

A non-commutative algorithm for multiplying 4x4 matrices using 48 non-complex multiplications

Jean-Guillaume Dumas, Clément Pernet, Alexandre Sedoglavic

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Abstract

The quest for non-commutative matrix multiplication algorithms over non-commutative rings in small dimensions has recently seen significant progress. Specifically, the number of scalar multiplications required to multiply two 4x4 matrices was reduced in \cite{Fawzi:2022aa} from 49 (using two recursion levels of Strassen's algorithm) to 47 in characteristic 2, and more recently to 48 in \cite{alphaevolve} over the complex numbers. We propose an algorithm requiring 48 multiplications that uses only rational coefficients, thereby removing the requirement for complex-number arithmetic, and making this algorithm valid over any ring except those of characteristic 2. We also produce a straight-line program of this algorithm reducing the number of additions and scalar multiplications, reaching a running time of $\frac{347}{32}n^{2+\log_4{3}}+o(n^{2+\log_4{3}})$ operations, as well as an alternative basis variant of it, leading to an algorithm running in $7n^{2+\log_4{3}} +o(n^{2+\log_4{3}})$ operations over any ring containing an inverse of 2. Similarly, the number of scalar multiplications required to multiply a 3x4 matrix by a 4x7 matrix was reduced from 66 in \cite{Smirnov:2021aa} to 63 in \cite{alphaevolve} by an algorithm over complex numbers. Using the same techniques, we propose an equivalent algorithm in 63 multiplications using only rational coefficients. In both cases the rational algorithm is obtained by identifying an isotropy that projects the previously known complex-valued decomposition onto the field of rational numbers.

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cs.SCSymbolic Computation

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    • No, your claim about matrix multiplication is false. Google's new algorithm can be applied recursively to 4x4 block matrices (over the field of complex numbers). This results in an asymptotically faster algorithm for nxn matrix multiplication than Strassen's. Earlier results on…

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