title: Descending from infinity: convergence of tailed distributions.
abstract: We investigate the relaxation of long-tailed distributions under stochastic dynamics that do not support such tails. Linear relaxation is found to be a borderline case in which long tails are exponentially suppressed in time but not eliminated. Relaxation stronger than linear suppresses long tails immediately, but may lead to strong transient peaks in the probability distribution. We also find that a δ-function initial distribution under stronger than linear decay displays not one but two different regimes of diffusive spreading.
authors: Hasselt University, B-3500 Hasselt, Belgium.
authors: Christian
authors: C
authors: Van den Broeck
authors: Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore 560012, India.
authors: Upendra
authors: U
authors: Harbola
authors: IFISC (Instituto de Física Interdisciplinar y Sistemas Complejos), Universitat de les Illes Balears-CSIC, Palma de Mallorca 07122, Spain.
authors: Raul
authors: R
authors: Toral
authors: Department of Chemistry and Biochemistry and BioCircuits Institute, University of California San Diego, La Jolla, California 92093-0340, USA.
authors: Katja
authors: K
authors: Lindenberg
mesh_terms: D004058:Diffusion; D008962:Models, Theoretical; D011336:Probability; D013269:Stochastic Processes