Asymptotic rank bounds: a numerical census

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Authors: Kisun Lee
Cited by: 0

Abstract

We systematically compute improved asymptotic rank bounds for tensors. Using numerical implicitization, we implement the geometric framework of Kaski and Michałek across all computationally feasible cases. By detecting the absence of low-degree vanishing polynomials on secant varieties, we obtain new asymptotic rank bounds that improve upon the generic border rank bounds. The results provide numerical data supporting Strassen's asymptotic rank conjecture and clarify the computational barriers posed by current numerical methods.

Fields of Study & Subjects

Tensor decomposition and applications Polynomial and algebraic computation Complexity and Algorithms in Graphs

Publication details

Journal / source
arXiv (Cornell University)
Publication date
13 January 2026
Document type
Preprint