马尔科夫蒙特卡洛
动力学蒙特卡罗方法
蒙特卡罗方法
统计物理学
混合蒙特卡罗
蒙特卡罗分子模拟
动态蒙特卡罗方法
计算机科学
统计物理中的蒙特卡罗方法
平行回火
比例(比率)
马尔可夫链
马尔可夫过程
数学优化
算法
数学
物理
统计
机器学习
量子力学
出处
期刊:Physical Review E
[American Physical Society]
日期:2011-03-31
卷期号:83 (3): 037701-037701
被引量:63
标识
DOI:10.1103/physreve.83.037701
摘要
We rigorously establish a physical time scale for a general class of kinetic Monte Carlo algorithms for the simulation of continuous-time Markov chains. This class of algorithms encompasses rejection-free (or BKL) and rejection (or "standard") algorithms. For rejection algorithms, it was formerly considered that the availability of a physical time scale (instead of Monte Carlo steps) was empirical, at best. Use of Monte Carlo steps as a time unit now becomes completely unnecessary.
科研通智能强力驱动
Strongly Powered by AbleSci AI