English

Estimates for the quantized tensor train ranks for the power functions

Numerical Analysis 2025-01-20 v1 Numerical Analysis

Abstract

In this work we provide theoretical estimates for the ranks of the power functions f(k)=kαf(k) = k^{-\alpha}, α>1\alpha>1 in the quantized tensor train (QTT) format for k=1,2,3,,2dk = 1, 2, 3, \ldots, 2^{d}. Such functions and their several generalizations (e.~g. f(k)=kαeλk,λ>0f(k) = k^{-\alpha} \cdot e^{-\lambda k}, \lambda > 0) play an important role in studies of the asymptotic solutions of the aggregation-fragmentation kinetic equations. In order to support the constructed theory we verify the values of QTT-ranks of these functions in practice with the use of the TTSVD procedure and show an agreement between the numerical and analytical results.

Keywords

Cite

@article{arxiv.2404.12230,
  title  = {Estimates for the quantized tensor train ranks for the power functions},
  author = {Sergey A. Matveev and Matvey Smirnov},
  journal= {arXiv preprint arXiv:2404.12230},
  year   = {2025}
}

Comments

6 pages, 1 figure, 20 references

R2 v1 2026-06-28T15:58:48.638Z