{
  "id": "1510.02431",
  "version": "v1",
  "published": "2015-10-08T18:20:33.000Z",
  "updated": "2015-10-08T18:20:33.000Z",
  "title": "Large deviations for Markov processes with resetting",
  "authors": [
    "Janusz M. Meylahn",
    "Sanjib Sabhapandit",
    "Hugo Touchette"
  ],
  "comment": "7 pages, 3 figures",
  "categories": [
    "cond-mat.stat-mech"
  ],
  "abstract": "Markov processes restarted or reset at random times to a fixed state or region in space have been actively studied recently in connection with random searches, foraging, and population dynamics. Here we study the large deviations of time-additive functions or observables of Markov processes with resetting. By deriving a renewal formula linking generating functions with and without resetting we are able to obtain the rate function of such observables, characterizing the likelihood of their fluctuations in the long-time limit. We consider as an illustration the large deviations of the area of the Ornstein-Uhlenbeck process with resetting. Other applications involving, diffusions, random walks, and jump processes with resetting or catastrophes are discussed.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2015-10-08T18:20:33.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "markov processes",
      "large deviations",
      "renewal formula linking generating functions",
      "random searches",
      "rate function"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 7,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}