arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2401.16617math.PR
收藏

双重均值反射倒向随机微分方程的混沌传播

Propagation of chaos for doubly mean reflected BSDEs

Hanwu Li, Ning Ning

AI总结:

本文针对双重均值反射倒向随机微分方程,提出两类带平均场Skorokhod问题的相互作用粒子系统进行近似,首次建立其混沌传播结果,并得到不同场景下的收敛速度。

摘要:

本文建立了双重均值反射倒向随机微分方程(MRBSDEs)的混沌传播(POC)。MRBSDEs与典型的反射倒向随机微分方程(RBSDEs)的区别在于,其约束并非作用于解的路径,而是作用于解的分布。这一独特性质自MRBSDEs提出以来就受到了广泛关注。本文并未直接研究这类方程,而是聚焦于通过相互作用粒子系统(IPS)对其进行近似。我们提出了两类带平均场Skorokhod问题的IPS,刻画了以平均场方式反射的IPS的动力学特性。当IPS的维度趋于无穷时,会出现混沌传播现象,表明系统收敛到一个粒子相互独立的极限,其中每个粒子都求解该MRBSDE。除了建立首个双重MRBSDEs的混沌传播结果外,我们还在不同场景下得到了不同的收敛速度。

英文摘要:

In this paper, we establish propagation of chaos (POC) for doubly mean reflected backward stochastic differential equations (MRBSDEs). MRBSDEs differentiate the typical RBSDEs in that the constraint is not on the paths of the solution but on its law. This unique property has garnered significant attention since the inception of MRBSDEs. Rather than directly investigating these equations, we focus on approximating them by interacting particle systems (IPS). We propose two sets of IPS having mean-field Skorokhod problems, capturing the dynamics of IPS reflected in a mean-field way. As the dimension of the IPS tends to infinity, the POC phenomenon emerges, indicating that the system converges to a limit with independent particles, where each solves the MRBSDE. Beyond establishing the first POC result for doubly MRBSDEs, we achieve distinct convergence speeds under different scenarios.

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。

↑