布朗动力学
朗之万方程
统计物理学
布朗运动
模拟退火
朗之万动力
地铁列车时刻表
退火(玻璃)
应用数学
数学
物理
数学优化
计算机科学
热力学
统计
操作系统
作者
Martin Chak,Nikolas Kantas,Grigorios A. Pavliotis
摘要
In this paper, we consider the generalised (higher order) Langevin equation for the purpose of simulated annealing and optimisation of nonconvex functions. Our approach modifies the underdamped Langevin equation by replacing the Brownian noise with an appropriate Ornstein-Uhlenbeck process to account for memory in the system. Under reasonable conditions on the loss function and the annealing schedule, we establish convergence of the continuous time dynamics to a global minimum. In addition, we investigate the performance numerically and show better performance and higher exploration of the state space compared to the underdamped and overdamped Langevin dynamics with the same annealing schedule.
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