Descending from infinity: convergence of tailed distributions.
Phys Rev E Stat Nonlin Soft Matter Phys
; 91(1): 012128, 2015 Jan.
Article
en En
| MEDLINE
| ID: mdl-25679591
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.
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01-internacional
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MEDLINE
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Modelos Teóricos
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En
Revista:
Phys Rev E Stat Nonlin Soft Matter Phys
Asunto de la revista:
BIOFISICA
/
FISIOLOGIA
Año:
2015
Tipo del documento:
Article
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Bélgica