Self similar solutions in one-dimensional kinetic models: a probabilistic view

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.