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PreprintCC BY-NC-ND 4.0HAL

Cutoff beyond non-negative curvature

Abstract

We study how a relaxed gradient estimate is enough to prove cutoff for several new families of Markov processes, within the varentropy framework of [Sal25a].

In particular, we show how certain regularization estimates from hypocoercivity theory allow one to prove cutoff for kinetic dynamics. Moreover, we prove cutoff for some families of diffusions with non-convex potentials and for mean-field dynamics, as well as for biased random walks on the symmetric group, giving a simple proof of a far-reaching extension of a result of [NY24].

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BibTeX
@misc{fathi2026cutoff,
  title = {{Cutoff beyond non-negative curvature}},
  author = {Max Fathi and Arnaud Guillin and Cyril Labbé and Justin Salez},
  howpublished = {HAL},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.26019},
  eprint = {2610.26019},
  archivePrefix = {arXiv},
  url = {https://hal.science/hal-05803728v1},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - UNPB
TI  - Cutoff beyond non-negative curvature
AU  - Max Fathi
AU  - Arnaud Guillin
AU  - Cyril Labbé
AU  - Justin Salez
PY  - 2026
DA  - 2026/10/16
PB  - HAL
DO  - 10.48550/arxiv.2610.26019
UR  - https://hal.science/hal-05803728v1
AB  - We study how a relaxed gradient estimate is enough to prove cutoff for several new families of Markov processes, within the varentropy framework of [Sal25a].  In particular, we show how certain regularization estimates from hypocoercivity theory allow one to prove cutoff for kinetic dynamics. Moreover, we prove cutoff for some families of diffusions with non-convex potentials and for mean-field dynamics, as well as for biased random walks on the symmetric group, giving a simple proof of a far-reaching extension of a result of [NY24].
ER  -