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Communication: Predicting virial coefficients and alchemical transformations by extrapolating Mayer-sampling Monte Carlo simulations

机译:交流:通过外推Mayer采样蒙特卡洛模拟来预测病毒系数和炼金术转化

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摘要

Virial coefficients are predicted over a large range of both temperatures and model parameter values (i.e., alchemical transformation) from an individual Mayer-sampling Monte Carlo simulation by statistical mechanical extrapolation with minimal increase in computational cost. With this extrapolation method, a Mayer-sampling Monte Carlo simulation of the SPC/E (extended simple point charge) water model quantitatively predicted the second virial coefficient as a continuous function spanning over four orders of magnitude in value and over three orders of magnitude in temperature with less than a 2% deviation. In addition, the same simulation predicted the second virial coefficient if the site charges were scaled by a constant factor, from an increase of 40% down to zero charge. This method is also shown to perform well for the third virial coefficient and the exponential parameter for a Lennard-Jones fluid.
机译:通过统计机械外推法从单个Mayer采样蒙特卡洛模拟中预测温度和模型参数值(即,化学转化)的很大范围内的病毒系数,而计算成本的增加最小。使用这种外推方法,对SPC / E(扩展的单点电荷)水模型进行Mayer采样的蒙特卡洛模拟,定量地预测了第二维里系数作为连续函数,其值跨度超过四个数量级,而跨度超过三个数量级。温度偏差小于2%。此外,如果站点电荷按恒定因子缩放(从40%降低到零电荷),则相同的模拟预测第二维里系数。对于第三维里系数和Lennard-Jones流体的指数参数,该方法也显示出良好的性能。

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