随机微分方程在离散化下的Smoluchowski-Kramers逼近
Smoluchowski-Kramers Approximation for Stochastic Differential Equations under Discretization
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摘要: 文研究了由粒子在力场中的运动所描述的动力系统在时间离散化下的Smoluchowski-Kramers逼近。我们证明了当使用漂移项隐-Euler-Maruyama格式进行离散化时, Smoluchowski-Kramers逼近成立, 并得到了收敛速度。特别地, 离散化系统的解在均方意义下收敛于一阶方程的解, 且它不依赖于质量μ和步长h趋于0的阶数。Abstract: This paper studies the Smoluchowski–Kramers approximation for a discrete-time dynamical system modeled as the motion of a particle in a force field. We show that the approximation holds for the drift-implicit Euler–Maruyama discretization and derive its convergence rate. In particular, the solution of the discretized system converges to the solution of the first-order limit equation in the mean-square sense, and this convergence is independent of the order in which the mass parameter μ and the step size h tend to zero.