Online Optimization of Total Acceptance in Hamiltonian Replica Exchange Simulations.
Online Optimization of Total Acceptance in Hamiltonian Replica Exchange Simulations.
复制标题
哈密顿副本交换模拟中总接受度的在线优化。
DOI：
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复制
发表时间：
2018
影响因子：
3.3
通讯作者：
Kari Gaalswyk
中科院分区：
文献类型：
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作者：
J. MacCallum;Mir Ishruna Muniyat;Kari Gaalswyk
副本交换是分子模拟中广泛使用的一种抽样策略。虽然存在各种方法来优化温度副本交换的参数，但对于如何优化更一般的哈密顿副本交换模拟的参数知之甚少。我们提出了一种基于随机梯度下降的温度和哈密顿副本交换模拟的总接受度在线优化算法。我们优化了总接受度，这是一个捕捉副本交换效率的启发式目标函数。我们的方法是通用的，并具有几个理想的性质，包括：(1)它对感兴趣的系统几乎没有假设，(2)优化在不需要预模拟的情况下在线进行，以及(3)最重要的是，它很容易推广到有多个控制参数(如温度、力常数等)的系统。来确定每个复制品的哈密顿量。我们在一个简单的谐振子系统上探索了该算法的一些一般性质，并在一个更复杂的数据引导的蛋白质折叠模拟中展示了它的有效性。
Replica exchange is a widely used sampling strategy in molecular simulation. While a variety of methods exist to optimize parameters for temperature replica exchange, less is known about how to optimize parameters for more general Hamiltonian replica exchange simulations. We present an algorithm for the online optimization of total acceptance for both temperature and Hamiltonian replica exchange simulations using stochastic gradient descent. We optimize the total acceptance, a heuristic objective function capturing the efficiency of replica exchange. Our approach is general and has several desirable properties, including: (1) it makes few assumptions about the system of interest, (2) optimization occurs online without the requirement of presimulation, and (3) most importantly, it readily generalizes to systems where there are multiple control parameters (e.g., temperatures, force constants, etc.) that determine the Hamiltonian of each replica. We explore some general properties of the algorithm on a simple harmonic oscillator system, and demonstrate its effectiveness on a more complex data-guided protein folding simulation.