Record statistics for random walks and Levy flights with resetting

被引:25
|
作者
Majumdar, Satya N. [1 ]
Mounaix, Philippe [2 ]
Sabhapandit, Sanjib [3 ]
Schehr, Gregory [4 ]
机构
[1] Univ Paris Saclay, Univ Paris Sud, CNRS, LPTMS, F-91405 Orsay, France
[2] Ecole Polytechniquc, IP Paris, CNRS, CPHT, F-91128 Palaiscau, France
[3] Raman Res Inst, Bangalore 560080, Karnataka, India
[4] Sorbonne Univ, Lab Phys Theor & Hautes Energies, CNRS, UMR 7589, 4 Pl Jussieu, F-75252 Paris 05, France
关键词
record statistics; resetting dynamics; random walks; extreme statistics; WEATHER RECORDS; BREAKING;
D O I
10.1088/1751-8121/ac3fc1
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We compute exactly the mean number of records < R-N > for a time-series of size N whose entries represent the positions of a discrete time random walker on the line with resetting. At each time step, the walker jumps by a length eta drawn independently from a symmetric and continuous distribution f (eta) with probability 1 - r (with 0 <= r < 1) and with the complementary probability r it resets to its starting point x = 0. This is an exactly solvable example of a weakly correlated time-series that interpolates between a strongly correlated random walk series (for r = 0) and an uncorrelated time-series (for (1 - r) << 1). Remarkably, we found that for every fixed r is an element of [0, 1 [ and any N, the mean number of records < R-N > is completely universal, i.e. independent of the jump distribution f (eta). In particular, for large N, we show that < R-N > grows very slowly with increasing N as < R-N > approximate to (1/root r) ln N for 0 < r < 1. We also computed the exact universal crossover scaling functions for < R-N > in the two limits r -> 0 and r -> 1. Our analytical predictions are in excellent agreement with numerical simulations.
引用
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页数:20
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