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[求助]
求问 分子模拟中 提高温度是否就能实现增强抽样呢?
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http://wenku.baidu.com/link?url= ... OWPEiaMSpcSOGRSvStm 最近在看上面这篇文章,想对 分子模拟中的 增强抽样方法有一个基本的了解 ———————————————— 想问一个问题 提高温度是不是就能达到增强抽样的目的了呢? 比如原来的温度是T1 现在把温度变成更高的温度T2,在这个温度下,就能达到增强抽样了? 怎么理解呢? |
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lsloneil
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是的,升温可以增强抽样。因为温度对应于分子的平均动能,当势能面上有一个很深的势阱的时候在里面的粒子由于动能不够高是很难跳出这个势阱的,这样的话你的采样基本就在势阱里面采样而无法在势能面的其他位置采样,升高温度就可以使粒子跳出势阱。升温来增加抽样的经典方法是Replica Exchange MD (REMD). Enhanced Sampling是分子模拟中当前非常热门的课题。你可以看看本版EPI ChemiAndy写的这篇关于自由能计算的文章:http://muchong.com/bbs/viewthread.php?tid=3672663 里面谈到的Umbrella Sampling, WHAM等都是常用的方法。 |
3楼2014-04-07 02:00:43
lsloneil
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leukos: 金币+45, ★★★★★最佳答案, 再次感谢~~思路清晰了不少呢 2014-04-08 12:48:00
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leukos: 金币+45, ★★★★★最佳答案, 再次感谢~~思路清晰了不少呢 2014-04-08 12:48:00
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见下,我在latex里用英文敲的,你凑合着看吧。 \section{First Question} I think your answer with regard to the probability distribution of potential energy is correct. There is indeed an expression in term of ensemble average for this probability distribution, which is given below. For a system with N particles, the potential energy is where Then the probability distribution of potential energy P(U) can be written as For most systems, there is no analytical way of calculating P(U), but one could just sample P(U) in simulations, which can be done very easily. In general the P(U) obtained from sampling is not perfectly Gaussian, but one could fit it to Gaussian. \section{Second Question} From the figure you showed, one could see that the mean value of potential energy increases as temperature increases. Also, the width of the potential energy distribution (i.e. fluctuations) also increases as temperature increases. This is a natural result from thermodynamics and statistical mechanics. First, the derivative of mean potential energy with respect to temperature is just the heat capacity (here it means the non-ideal part of the heat capacity). Apparently the heat capacity is greater than zero (because of the convexity of free energy function), so the mean potential energy increases with temperature. On the other hand, one could easily find the relation between fluctuation of energy (the width of potential energy distribution) and temperature in a standard stat mech textbook. So the fluctuation increases as temperature increases. So, to answer your question, I would say that in canonical (NVT) ensemble, molecules would always prefer configurations that minimizes free energy. Since free energy comprises parts both from energy and entropy, molecules have to choose configurations that find a balance between energy and entropy (i.e. minimize energy but also maximize entropy). \section{Last Question} The last question is much easier to answer. Suppose to get sufficient statistics, you need to sample at least 100 ps in the region of stable configuration. However, since you're using REMD, you spend 50 ps of your 100 ps exploring other parts of the phase space, then you have to spend more time totally in order to obtain as good statistics as your previous simulations for your stable configuration. |
6楼2014-04-08 10:36:30
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