Fast matrix multiplication is one of the most fundamental problems in algorithm research. The exponent of the optimal time complexity of matrix multiplication is usually denoted by $\omega$. This paper discusses new ideas for improving the laser method for fast matrix multiplication. We observe that the analysis of higher powers of the Coppersmith-Winograd tensor [Coppersmith & Winograd 1990] incurs a "combination loss", and we partially compensate for it using an asymmetric version of CW's hashing method. By analyzing the eighth power of the CW tensor, we give a new bound of $\omega<2.371866$, which improves the previous best bound of $\omega<2.372860$ [Alman & Vassilevska Williams 2020]. Our result breaks the lower bound of $2.3725$ in [Ambainis, Filmus & Le Gall 2015] because of the new method for analyzing component (constituent) tensors.
翻译:快速矩阵乘法是算法研究中最基本的问题之一。矩阵乘法优化的最优时间复杂度通常用$\omega$表示。本文讨论了改进快速矩阵乘法的新方法。我们观察到分析Coppersmith-Winograd 张量 [Coppersmith& Winograd 1990]的高次幂会带来“组合损失”,因此我们使用CW哈希方法的不对称版本进行部分控制。通过分析 CW 张量的八次幂,我们给出了一个新界限 $\omega<2.371866$,这比先前的最佳界限 $\omega<2.372860$ [Alman & Vassilevska Williams 2020] 更优。由于分析组成张量的新方法,我们的结果打破了[Ambainis,Filmus和Le Gall 2015]的$2.3725$下限。