{
  "abstract": "We study convergence in relative entropy of the bouncy particle sampler with Gaussian velocity refreshment, for a target $e^{-U}$ on $\\mathbb R^d$ with $U$ $m$-strongly convex and $L$-smooth, and condition number $κ=L/m$. For initial laws with bounded density relative to equilibrium, we show that the relative entropy decays exponentially up to an arbitrary additive error $δ$, with a rate that depends only logarithmically on the density bound and on $δ$. From a Gaussian cold start and with a suitably chosen refreshment rate, the relative entropy falls below $δ$ after time $\\widetilde O(\\sqrt{d/m})$. Combined with exact simulation by windowed thinning, this gives an expected gradient-query complexity of $\\widetilde O(d\\sqrtκ)$, improving the $\\widetilde O(d^2\\sqrtκ)$ bound based on $L^2$ hypocoercivity.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.25354",
  "author_total": 2,
  "authors": [
    {
      "name": "Jianfeng Lu"
    },
    {
      "name": "Yinchen Luo"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1y94bk5qs2027.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.25354",
  "fulltext_url": null,
  "id": "1y94bk5qs2027",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.25354",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "math.PR"
    ],
    [
      "openalex",
      "2613|Markov Chains and Monte Carlo Methods"
    ]
  ],
  "openalex": "W7223055419",
  "pdf_url": "https://arxiv.org/pdf/2610.25354",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-18",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/1y94bk5qs2027.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:30:57Z",
      "native_id": "2610.25354",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.25354"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.PR",
      "subfield": "probability"
    }
  ],
  "title": "Entropy hypocoercivity and query complexity for the bouncy particle sampler",
  "title_text": "Entropy hypocoercivity and query complexity for the bouncy particle sampler",
  "type": "preprint",
  "updated_at": "2026-10-30T12:33:44Z",
  "url": "https://research.draconitic.com/paper/1y94bk5qs2027",
  "venue": "arXiv",
  "versions": []
}