English

Inner Rank and Lower Bounds for Matrix Multiplication

Computational Complexity 2019-05-15 v2 Data Structures and Algorithms

Abstract

We develop a notion of {\em inner rank} as a tool for obtaining lower bounds on the rank of matrix multiplication tensors. We use it to give a short proof that the border rank (and therefore rank) of the tensor associated with n×nn\times n matrix multiplication over an arbitrary field is at least 2n2n+12n^2-n+1. While inner rank does not provide improvements to currently known lower bounds, we argue that this notion merits further study.

Keywords

Cite

@article{arxiv.1706.04225,
  title  = {Inner Rank and Lower Bounds for Matrix Multiplication},
  author = {Joel Friedman},
  journal= {arXiv preprint arXiv:1706.04225},
  year   = {2019}
}

Comments

Errors in many of the results (starting with those of Section 4) due to an "exchange of indices."

R2 v1 2026-06-22T20:17:57.551Z