http://www.cnr.it/ontology/cnr/individuo/prodotto/ID64931
Self similar solutions in one-dimensional kinetic models: a probabilistic view (Articolo in rivista)
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- Self similar solutions in one-dimensional kinetic models: a probabilistic view (Articolo in rivista) (literal)
- Anno
- 2010-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1214/11-AAP818 (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Federico Bassetti; Lucia Ladelli (literal)
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- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Università degli Studi di Pavia;
Politecnico di Milano (literal)
- Titolo
- Self similar solutions in one-dimensional kinetic models: a probabilistic view (literal)
- Abstract
- This paper deals with a class of Boltzmann equations on the real line, extensions of the well-known Kac caricature. A distinguishing feature of the corresponding equations is that the therein collision gain operators are defined by $N$-linear smoothing transformations. This kind of problems have been studied, from an essentially analytic viewpoint, in a recent paper by Bobylev, Gamba and Cercignani. Instead, the present work rests exclusively on probabilistic methods, based on techniques pertaining to the classical central limit problem and to the so-called fixed-point equations for probability distributions. An advantage of resorting to methods from the probability theory is that the same results - relative to self-similar solutions - as those obtained by Bobylev, Gamba and Cercignani, are here deduced under weaker conditions. In particular, it is shown how convergence to self--similar solution depends on the belonging of the initial datum to the domain of attraction of a specific stable distribution. Moreover, some results on the speed of convergence are given in terms of Kantorovich-Wasserstein and Zolotarev distances between probability measures. (literal)
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