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arXiv 1701.09115math.PRmath-phmath.MP
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随机对偶与正交多项式

Stochastic Duality and Orthogonal Polynomials

Chiara Franceschini, Cristian Giardinà

摘要:

对于一系列马氏过程,我们证明了对偶函数由正交多项式给出的随机对偶关系。这意味着关于原始过程(其演化正交多项式的变量)的期望可以通过关于对偶过程(其演化多项式的指数)的期望来研究。这组过程包括相互作用的粒子系统,如排它过程,包含过程和独立的随机游动,以及相互作用的扩散和再分配模型的Kipnis-Marchioro-Presutti型。对偶函数由离散变量和连续变量的经典正交多项式给出,且正交关系中的测度与过程平稳测度一致.

英文摘要:

For a series of Markov processes we prove stochastic duality relations with duality functions given by orthogonal polynomials. This means that expectations with respect to the original process (which evolves the variable of the orthogonal polynomial) can be studied via expectations with respect to the dual process (which evolves the index of the polynomial). The set of processes include interacting particle systems, such as the exclusion process, the inclusion process and independent random walkers, as well as interacting diffusions and redistribution models of Kipnis-Marchioro-Presutti type. Duality functions are given in terms of classical orthogonal polynomials, both of discrete and continuous variable, and the measure in the orthogonality relation coincides with the process stationary measure.

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