Asymptotic rank bounds: a numerical census
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