Transition from the annealed to the quenched asymptotics for a random walk on random obstacles
Abstract
In this work we study a natural transition mechanism describing the passage from a quenched (almost sure) regime to an annealed (in average) one, for a symmetric simple random walk on random obstacles on sites having an identical and independent law. The transition mechanism we study was first proposed in the context of sums of identical independent random exponents by Ben Arous, Bogachev and Molchanov in [Probab. Theory Related Fields 132 (2005) 579--612]. Let be the survival probability at time of the random walk, starting from site , and let be some increasing function of time. We show that the empirical average of over a box of side has different asymptotic behaviors depending on . T here are constants such that if , with , a law of large numbers is satisfied and the empirical survival probability decreases like the annealed one; if , with , also a central limit theorem is satisfied. If , the averaged survival probability decreases like the quenched survival probability. If and we obtain an intermediate regime. Furthermore, when the dimension it is possible to describe the fluctuations of the averaged survival probability when with : it is shown that they are infinitely divisible laws with a L\'{e}vy spectral function which explodes when as stable laws of characteristic exponent . These results show that the quenched and annealed survival probabilities correspond to a low- and high-temperature behavior of a mean-field type phase transition mechanism.
Keywords
Cite
@article{arxiv.math/0501107,
title = {Transition from the annealed to the quenched asymptotics for a random walk on random obstacles},
author = {Gérard Ben Arous and Stanislav Molchanov and Alejandro F. Ramírez},
journal= {arXiv preprint arXiv:math/0501107},
year = {2016}
}
Comments
Published at http://dx.doi.org/10.1214/009117905000000404 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org)