English

Large deviations, moderate deviations, and the KLS conjecture

Probability 2020-03-26 v1 Functional Analysis

Abstract

Having its origin in theoretical computer science, the Kannan-Lov\'asz-Simonovits (KLS) conjecture is one of the major open problems in asymptotic convex geometry and high-dimensional probability theory today. In this work, we establish a new connection between this conjecture and the study of large and moderate deviations for isotropic log-concave random vectors, thereby providing a novel possibility to tackle the conjecture. We then study the moderate deviations for the Euclidean norm of random orthogonally projected random vectors in an pn\ell_p^n-ball. This leads to a number of interesting observations: (A) the 1n\ell_1^n-ball is critical for the new approach; (B) for p2p\geq 2 the rate function in the moderate deviations principle undergoes a phase transition, depending on whether the scaling is below the square-root of the subspace dimensions or comparable; (C) for 1p<21\leq p<2 and comparable subspace dimensions, the rate function again displays a phase transition depending on its growth relative to np/2n^{p/2}.

Keywords

Cite

@article{arxiv.2003.11442,
  title  = {Large deviations, moderate deviations, and the KLS conjecture},
  author = {David Alonso-Gutiérrez and Joscha Prochno and Christoph Thaele},
  journal= {arXiv preprint arXiv:2003.11442},
  year   = {2020}
}

Comments

22 pages

R2 v1 2026-06-23T14:26:56.778Z