论文标题
在算法上以恒定体积和变化的细胞进行蒙特卡洛模拟
On the algorithm to perform Monte Carlo simulations in cells with constant volume and variable shape
论文作者
论文摘要
在晶体的模拟中，与液体或气体不同，研究系统的性质不仅取决于模拟电池的体积，而且还取决于其形状。在这种情况下，希望在模拟过程中随时更改盒子的形状，因为它可能在几何形状最适合研究系统的时间之前不知道。在这项工作中，我们根据在恒定压力集合中观察到的恒定体积匹配的模拟中观察到的特定几何参数的分布来得出此任务的算法。对所提出的算法进行了硬核椭圆系统的测试，该系统根据粒子的非球性参数而形成不同类型的晶格。结果表明，算法的性能严重取决于采样几何参数的范围。如果范围狭窄，采样方法的影响很小。如果范围很大，则采样不足会导致相关分布函数的显着扭曲，因此，自由能的估计值中的错误。
In simulations of crystals, unlike liquids or gases, it may happen that the properties of the studied system depend not only on the volume of the simulation cell but also on its shape. For such cases it is desirable to change the shape of the box on the fly in the course of the simulation as it may not be known ahead of time which geometry fits the studied system best. In this work we derive an algorithm for this task based on the condition that the distribution of specific geometrical parameter observed in simulations at a constant volume matches that observed in the constant-pressure ensemble. The proposed algorithm is tested for the system of hard-core ellipses which makes lattices of different types depending on the asphericity parameter of the particle. It is shown that the performance of the algorithm critically depends on the range of the sampled geometrical parameter. If the range is narrow, the impact of the sampling method is minimal. If the range is large, inadequate sampling can lead to significant distortions of the relevant distribution functions and, as a consequence, errors in the estimates of free energy.
