Geometric Rank of Tensors and Subrank of Matrix Multiplication

Electronic Colloquium on Computational Complexity (ECCC)(2023)

引用 18|浏览19
暂无评分
摘要
Motivated by problems in algebraic complexity theory (e.g., matrix multiplica-tion) and extremal combinatorics (e.g., the cap set problem and the sunflower problem), we introduce the geometric rank as a new tool in the study of tensors and hypergraphs. We prove that the geometric rank is an upper bound on the subrank of tensors and the independence number of hypergraphs. We prove that the geometric rank is smaller than the slice rank of Tao, and relate geometric rank to the analytic rank of Gowers and Wolf in an asymptotic fashion. As a first application, we use geometric rank to prove a tight upper bound on the (border) subrank of the matrix multiplication tensors, matching Strassen's well-known lower bound from 1987.
更多
查看译文
关键词
algebraic complexity theory, combinatorics, matrix multiplication, tensors, subrank, analytic rank, slice rank, hypergraphs, independence number
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要