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首页> 外文期刊>Computational Methods in Science and Technologygy >Parallel-Tempering Monte-Carlo Simulation with Feedback-Optimized Algorithm Applied to a Coil-to-Globule Transition of a Lattice Homopolymer
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Parallel-Tempering Monte-Carlo Simulation with Feedback-Optimized Algorithm Applied to a Coil-to-Globule Transition of a Lattice Homopolymer

机译:反馈优化算法的平行回火蒙特卡罗模拟应用于晶格均聚物的线圈到小球转变

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We present a study of the parallel tempering (replica exchange) Monte Carlo method, with special focus on the feedbackoptimized parallel tempering algorithm, used for generating an optimal set of simulation temperatures. This method is applied to a lattice simulation of a homopolymer chain undergoing a coil-to-globule transition upon cooling. We select the optimal number of replicas for different chain lengths, N = 25, 50 and 75, using replica's round-trip time in temperature space, in order to determine energy, specific heat, and squared end-to-end distance of the homopolymer chain for the selected temperatures. We also evaluate relative merits of this optimization method.
机译:我们对并行回火(副本交换)蒙特卡洛方法进行了研究,特别关注于反馈优化的并行回火算法,该算法用于生成一组最佳的仿真温度。该方法适用于均聚物链的晶格模拟,该均聚物链在冷却时会经历从线圈到球的过渡。我们使用温度空间中复制品的往返时间,选择不同链长(N = 25、50和75)的最佳复制品数量,以确定能量,比热和均聚物的端到端距离的平方选定温度的链。我们还评估了这种优化方法的相对优点。

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