{
  "id": "2102.07069",
  "version": "v1",
  "published": "2021-02-14T04:46:28.000Z",
  "updated": "2021-02-14T04:46:28.000Z",
  "title": "Convergence Rates in Strong Ergodicity by Hitting Times and $L^2$-exponential Convergence Rates",
  "authors": [
    "Yong-Hua Mao",
    "Tao Wang"
  ],
  "categories": [
    "math.PR"
  ],
  "abstract": "The computable convergence rates in strong ergodicity for Markov processes are obtained by using uniformly bounded moments of hitting times and the convergence rates in $L^2$-exponential ergodicity. We reveal a phenomenon for a class of Markov processes which are strongly ergodic that the two convergence rates in both strong ergodicity and exponential ergodicity are identical. These processes vary from Markov chains, diffusions to SDEs driven by symmetric stable processes.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2021-02-14T04:46:28.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "60J25",
      "47A75"
    ],
    "keywords": [
      "strong ergodicity",
      "exponential convergence rates",
      "hitting times",
      "markov processes",
      "exponential ergodicity"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}