Pearson Walk with Shrinking Steps in Two Dimensions
Journal Article

Published: Thursday, January 14, 2010
Citation: Journal of Statistical Mechanics: Theory and Experiment, Pages P01006
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Authors (2 total): C. A. Serino, S. Redner


We study the shrinking Pearson random walk in two dimensions and greater, in which the direction of the Nth step is random and its length equals lambda^{N-1}, with lambda<1. As lambda increases past a critical value lambda_c, the endpoint distribution in two dimensions, P(r), changes from having a global maximum away from the origin to being peaked at the origin. The probability distribution for a single coordinate, P(x), undergoes a similar transition, but exhibits multiple maxima on a fine length scale for lambda close to lambda_c. We numerically determine P(r) and P(x) by applying a known algorithm that accurately inverts the exact Bessel function product form of the Fourier transform for the probability distributions.