椭圆扩散和相互作用粒子系统欧拉方案的 L2-Wasserstein 收缩

IF 1.1 2区 数学 Q3 STATISTICS & PROBABILITY Stochastic Processes and their Applications Pub Date : 2024-10-18 DOI:10.1016/j.spa.2024.104504
Linshan Liu , Mateusz B. Majka , Pierre Monmarché
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引用次数: 0

摘要

在漂移的无穷收缩性条件和足够高的扩散性要求下,我们证明了离散化扩散过程过渡核的 L2-Wasserstein 收缩。这扩展了最近的一些结果,这些结果在漂移的类似假设下,显示了 L1-Wasserstein 收缩,或 p>1 的 Lp-Wasserstein 边界,但这并不是真正的收缩。我们解释了显示真正的 L2-Wasserstein 收缩对于获得扩散的欧拉方案过渡核的局部波恩卡列不等式是如何至关重要的。此外,我们还讨论了我们的收缩结果的其他后果,如 KL-发散和总变异的集中不等式和收敛率。我们还研究了相互作用扩散离散的相应 L2-Wasserstein 收缩。作为一个特殊的应用,这使我们能够分析粒子系统的行为,这些粒子系统可以用来近似最近在均值场优化文献中研究的一类麦肯-弗拉索夫 SDEs。
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L2-Wasserstein contraction for Euler schemes of elliptic diffusions and interacting particle systems
We show L2-Wasserstein contraction for the transition kernel of a discretised diffusion process, under a contractivity at infinity condition on the drift and a sufficiently high diffusivity requirement. This extends recent results that, under similar assumptions on the drift but without the diffusivity restrictions, showed L1-Wasserstein contraction, or Lp-Wasserstein bounds for p>1 that were, however, not true contractions. We explain how showing a true L2-Wasserstein contraction is crucial for obtaining a local Poincaré inequality for the transition kernel of the Euler scheme of a diffusion. Moreover, we discuss other consequences of our contraction results, such as concentration inequalities and convergence rates in KL-divergence and total variation. We also study corresponding L2-Wasserstein contraction for discretisations of interacting diffusions. As a particular application, this allows us to analyse the behaviour of particle systems that can be used to approximate a class of McKean-Vlasov SDEs that were recently studied in the mean-field optimisation literature.
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来源期刊
Stochastic Processes and their Applications
Stochastic Processes and their Applications 数学-统计学与概率论
CiteScore
2.90
自引率
7.10%
发文量
180
审稿时长
23.6 weeks
期刊介绍: Stochastic Processes and their Applications publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests. Characterization, structural properties, inference and control of stochastic processes are covered. The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines. All papers are refereed.
期刊最新文献
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