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Acceleration of Monte Carlo simulations through spatial updating in the grand canonical ensemble

机译:大正则合集中通过空间更新来加速蒙特卡洛模拟

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摘要

A new grand canonical Monte Carlo algorithm for continuum fluid models is proposed.The method is based on a generalization of sequential Monte Carlo algorithms for lattice gas systems.The elementary moves,particle insertions and removals,are constructed by analogy with those of a lattice gas.The updating is implemented by selecting points in space(spatial updating)either at random or in a definitive order(sequential).The type of move,insertion or removal,is deduced based on the local environment of the selected points.Results on two-dimensional square-well fluids indicate that the sequential version of the proposed algorithm converges faster than standard grand canonical algorithms for continuum fluids.Due to the nature of the updating,additional reduction of simulation time may be achieved by parallel implementation through domain decomposition.
机译:提出了一种新的连续流体模型的大经典蒙特卡罗算法。该方法是基于对格架气体系统的顺序蒙特卡罗算法的推广。通过与格架气体的类比构造基本运动,粒子插入和去除更新是通过随机选择空间中的点(空间更新)或以确定的顺序(顺序)来实现的。移动,插入或移除的类型是根据所选点的局部环境推导出的。两个结果维方井流体表明,与连续流体的标准大规范算法相比,该算法的顺序版本收敛速度更快。由于更新的性质,可以通过域分解并行实现来实现仿真时间的额外减少。

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