驻点过程的最优输运:公制结构、梯度流和比熵的凸性

IF 1.7 2区 数学 Q1 MATHEMATICS
Matthias Erbar , Martin Huesmann , Jonas Jalowy , Bastian Müller
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引用次数: 0

摘要

我们建立了平稳随机测度的最优运输理论,重点研究了平稳随机测度的平稳点过程,并构造了平稳随机测度集合上的一组距离。这就引出了一个自然的概念,即两个平稳随机测量之间沿着一条最短的曲线进行插值。在驻点过程的设置中,我们利用这种输运距离给出了具有平稳分布的无限粒子系统演化的几何解释。也就是说,我们将无限多个布朗运动的演化描述为特定相对熵的梯度流,即泊松点过程。此外,我们建立了特定相对熵沿最优插值点过程的位移凸性,并建立了HWI不等式的平稳模拟,将特定熵、传输距离和特定相对Fisher信息联系起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal transport of stationary point processes: Metric structure, gradient flow and convexity of the specific entropy
We develop a theory of optimal transport for stationary random measures with a focus on stationary point processes and construct a family of distances on the set of stationary random measures. These induce a natural notion of interpolation between two stationary random measures along a shortest curve connecting them. In the setting of stationary point processes we leverage this transport distance to give a geometric interpretation for the evolution of infinite particle systems with stationary distribution. Namely, we characterise the evolution of infinitely many Brownian motions as the gradient flow of the specific relative entropy w.r.t. the Poisson point process. Further, we establish displacement convexity of the specific relative entropy along optimal interpolations of point processes and establish a stationary analogue of the HWI inequality, relating specific entropy, transport distance, and a specific relative Fisher information.
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来源期刊
CiteScore
3.20
自引率
5.90%
发文量
271
审稿时长
7.5 months
期刊介绍: The Journal of Functional Analysis presents original research papers in all scientific disciplines in which modern functional analysis plays a basic role. Articles by scientists in a variety of interdisciplinary areas are published. Research Areas Include: • Significant applications of functional analysis, including those to other areas of mathematics • New developments in functional analysis • Contributions to important problems in and challenges to functional analysis
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