Slowdown estimates and central limit theorem for random walks in random environment

By A. Sznitman. 2000

130 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Management Science and Operations Research, Mathematical Physics

View Paper: https://www.semanticscholar.org/paper/e0abf55a31b72aee79877efcf86751eca784c831

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In Computer Vision and Pattern Recognition

In Management Science and Operations Research

In Mathematical Physics

Citations in the corpus

On a general many-dimensional excited random walk (2010, background): “In this section we will prove Theorems 1.1 and 1.2.”
A central limit theorem for biased random walks on Galton–Watson trees (2006, background): “[ 22, Theorem 4.1 ],[24, Theorem 3.5.24]) is the following: Corollary 4 There exists a constant 2 such that, under the annealed measure GW, the process f(jXbntcj nvt)= p 2ngt 0 converges in distribution to a”
On multidimensional branching random walks in random environment (2005, background): “Also, in higher dimensions, Sznitman obtains estimates for hitting times of hyperplanes [25, 26].”
On the Anisotropic Walk on the Supercritical Percolation Cluster (2003, background): “1 of Sznitman [26], once we know that E[τ 2 1 ] < ∞ .”
On new examples of ballistic random walks in random environment (2003, background): “3) such as a ballistic law of large numbers, a central limit theorem and various large deviation controls were later proved in [22, 19].”
Random Walks in Random Environment (2009, background): “16 are a weak form of estimates contained in [71].”
Positively and negatively excited random walks on integers, with branching processes (2008, background): “2, no. 2, 93–143 [SZ99] A.-S. Sznitman and M.P.W. Zerner (1999).”
Large deviations for random walks on Galton–Watson trees: averaging and uncertainty (2002, background): “Striking partial results were obtained by Sznitman and Zerner [19, 21, 16, 17 ] in the more difficult setting of multidimensional RWRE.”
A law of large numbers for random walks in random mixing environments (2002, methodology): “Our goal in this paper is to present a technique, based on an appropriate coupling, for extending some of the results of [18], [15] to the case where P is not a product measure.”