A Particle System with Mean-Field Interaction: Large-Scale Limit of Stationary Distributions

Q1 Mathematics Stochastic Systems Pub Date : 2023-09-01 DOI:10.1287/stsy.2023.0108
Alexander L. Stolyar
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Abstract

We consider a system consisting of n particles, moving forward in jumps on the real line. System state is the empirical distribution of particle locations. Each particle “jumps forward” at some time points, with the instantaneous rate of jumps given by a decreasing function of the particle’s location quantile within the current state (empirical distribution). Previous work on this model established, under certain conditions, the convergence, as [Formula: see text], of the system random dynamics to that of a deterministic mean-field model (MFM), which is a solution to an integro-differential equation. Another line of previous work established the existence of MFMs that are traveling waves, as well as the attraction of MFM trajectories to traveling waves. The main results of this paper are: (a) We prove that, as [Formula: see text], the stationary distributions of (recentered) states concentrate on a (recentered) traveling wave; (b) we obtain a uniform across n moment bound on the stationary distributions of (recentered) states; and (c) we prove a convergence-to-MFM result, which is substantially more general than that in previous work. Results (b) and (c) serve as “ingredients” of the proof of (a), but also are of independent interest.
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具有平均场相互作用的粒子系统:平稳分布的大尺度极限
我们考虑一个由n个粒子组成的系统,它们在实线上跳跃前进。系统状态是粒子位置的经验分布。每个粒子在某些时间点“向前跳跃”,跳跃的瞬时速率由粒子在当前状态(经验分布)中的位置分位数的递减函数给出。先前对该模型的研究建立了在一定条件下,系统随机动力学收敛于确定性平均场模型(MFM)的收敛性[公式:见文],该模型是一个积分-微分方程的解。先前的另一项工作确定了行波的MFM的存在,以及MFM轨迹对行波的吸引力。本文的主要结果有:(a)我们证明了[公式:见文],(重向)态的平稳分布集中在(重向)行波上;(b)我们在(重中心)态的平稳分布上得到了一个跨n个矩界的均匀分布;(c)证明了一个收敛到mfm的结果,该结果比以前的工作具有更大的普遍性。结果(b)和(c)作为(a)证明的“成分”,但也具有独立的利益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Stochastic Systems
Stochastic Systems Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
3.70
自引率
0.00%
发文量
18
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