{ "id": "2202.04906", "version": "v1", "published": "2022-02-10T08:58:48.000Z", "updated": "2022-02-10T08:58:48.000Z", "title": "Number of distinct sites visited by a resetting random walker", "authors": [ "Marco Biroli", "Francesco Mori", "Satya N. Majumdar" ], "comment": "41 pages, 8 figs", "categories": [ "cond-mat.stat-mech", "math-ph", "math.MP", "math.PR" ], "abstract": "We investigate the number $V_p(n)$ of distinct sites visited by an $n$-step resetting random walker on a $d$-dimensional hypercubic lattice with resetting probability $p$. In the case $p=0$, we recover the well-known result that the average number of distinct sites grows for large $n$ as $\\langle V_0(n)\\rangle\\sim n^{d/2}$ for $d<2$ and as $\\langle V_0(n)\\rangle\\sim n$ for $d>2$. For $p>0$, we show that $\\langle V_p(n)\\rangle$ grows extremely slowly as $\\sim \\left[\\log(n)\\right]^d$. We observe that the recurrence-transience transition at $d=2$ for standard random walks (without resetting) disappears in the presence of resetting. In the limit $p\\to 0$, we compute the exact crossover scaling function between the two regimes. In the one-dimensional case, we derive analytically the full distribution of $V_p(n)$ in the limit of large $n$. Moreover, for a one-dimensional random walker, we introduce a new observable, which we call imbalance, that measures how much the visited region is symmetric around the starting position. We analytically compute the full distribution of the imbalance both for $p=0$ and for $p>0$. Our theoretical results are verified by extensive numerical simulations.", "revisions": [ { "version": "v1", "updated": "2022-02-10T08:58:48.000Z" } ], "analyses": { "keywords": [ "full distribution", "one-dimensional random walker", "dimensional hypercubic lattice", "standard random walks", "exact crossover scaling function" ], "note": { "typesetting": "TeX", "pages": 41, "language": "en", "license": "arXiv", "status": "editable" } } }