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arXiv 2501.09323math.PR
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图上具有对数线性交互的马尔可夫链的扩散极限

A diffusion limit for Markov chains with log-linear interaction on a graph

Anatolii Puhalskii, Vadim Shcherbakov

AI总结:

本文研究了图上具有对数线性交互的多元连续时间马尔可夫链,证明其时间缩放与归一化版本在值域扩展时收敛于原点反射的交互 Ornstein-Uhlenbeck 过程系统,借鉴排队论与鞅方法揭示了与 heavy traffic limits 的联系。

摘要:

本文为一个多元连续时间马尔可夫链建立了扩散极限,其分量由有限图的顶点索引。这些分量在一个共同的有限非负整数集中取值,并基于图的对数线性交互进行演化。我们证明,如果分量的共同值集合扩展至所有非负整数集合,则该马尔可夫链的时间缩放与归一化版本收敛于在原点反射的交互 Ornstein-Uhlenbeck 过程系统。该极限类似于排队论中的 heavy traffic limits(且我们的模型可自然解释为排队模型)。我们的证明借鉴了排队论的发展并依赖于鞅方法。

英文摘要:

In this paper we establish a diffusion limit for a multivariate continuous time Markov chain whose components are indexed by vertices of a finite graph. The components take values in a common finite set of non-negative integers and evolve subject to a graph based log-linear interaction. We show that if the set of common values of the components expands to the set of all non-negative integers, then a time-scaled and normalised version of the Markov chain converges to a system of interacting Ornstein-Uhlenbeck processes reflected at the origin. This limit is akin to heavy traffic limits in queueing (and our model can be naturally interpreted as a queueing model). Our proof draws on developments in queueing theory and relies on martingale methods.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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