Asymptotic tensor rank of graph tensors: beyond matrix multiplication

被引:0
|
作者
Matthias Christandl
Péter Vrana
Jeroen Zuiddam
机构
[1] University of Copenhagen,Department of Mathematical Sciences
[2] Budapest University of Technology and Economics,Department of Geometry
[3] Centrum Wiskunde & Informatica Science Park 123,undefined
来源
computational complexity | 2019年 / 28卷
关键词
tensor rank; graph tensors; subrank; Dicke tensors; algebraic complexity; matrix multiplication; 05D40; 05C99; 68Q17; 68Q12; 15A69; 81P45;
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学科分类号
摘要
We present an upper bound on the exponent of the asymptotic behaviour of the tensor rank of a family of tensors defined by the complete graph on k vertices. For k≥4\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${k \geq 4}$$\end{document}, we show that the exponent per edge is at most 0.77, outperforming the best known upper bound on the exponent per edge for matrix multiplication (k = 3), which is approximately 0.79. We raise the question whether for some k the exponent per edge can be below 2/3, i.e. can outperform matrix multiplication even if the matrix multiplication exponent equals 2. In order to obtain our results, we generalize to higher-order tensors a result by Strassen on the asymptotic subrank of tight tensors and a result by Coppersmith and Winograd on the asymptotic rank of matrix multiplication. Our results have applications in entanglement theory and communication complexity.
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页码:57 / 111
页数:54
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