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arXiv 2007.12956math.PR
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具有平均场相互作用和噪声消失的大偏差标度下随机流的渐近行为

Asymptotic Behavior of Stochastic Currents under Large Deviation Scaling with Mean Field Interaction and Vanishing Noise

Amarjit Budhiraja, Michael Conroy

摘要:

研究了具有平均场相互作用的扩散粒子系统的大偏差行为,通过一组随机微分方程来描述,其中每个粒子由一个消失的独立布朗噪声驱动.当粒子数接近无穷大且噪声强度接近零时,描述渐近行为的一个重要对象是Flandoli等人(2005)意义上的与相互作用粒子系统相关的随机流。在同时存在大粒子和小噪声的情况下,我们建立了粒子系统及其随机流的路径经验测度的联合大偏差原理(LDP)。我们的工作扩展了Orrieri(2018)的最新结果,其中扩散系数被认为是恒等式,以设置状态依赖和可能退化的噪声,平均场相互作用影响漂移和扩散系数,并允许在LDP中随机电流空间上建立更强的拓扑结构。证明技术与Orrieri(2018)不同,依赖于随机控制、弱收敛理论和布朗运动的拉普拉斯泛函的表示公式。

英文摘要:

We study the large deviation behavior of a system of diffusing particles with a mean field interaction, described through a collection of stochastic differential equations, in which each particle is driven by a vanishing independent Brownian noise. An important object in the description of the asymptotic behavior, as the number of particles approach infinity and the noise intensity approaches zero, is the stochastic current associated with the interacting particle system in the sense of Flandoli et al. (2005). We establish a joint large deviation principle (LDP) for the path empirical measure for the particle system and the associated stochastic currents in the simultaneous large particle and small noise limit. Our work extends recent results of Orrieri (2018), in which the diffusion coefficient is taken to be identity, to a setting of a state dependent and possibly degenerate noise with the mean field interaction influencing both the drift and diffusion coefficients, and allows for a stronger topology on the space of stochastic currents in the LDP. Proof techniques differ from Orrieri (2018) and rely on methods from stochastic control, theory of weak convergence, and representation formulas for Laplace functionals of Brownian motions.

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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