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Dynamical reweighting: Improved estimates of dynamical properties from simulations at multiple temperatures

机译:动态重加权:在多个温度下通过仿真改进的动力学特性估计

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摘要

Dynamical averages based on functionals of dynamical trajectories, such as time-correlation functions, play an important role in determining kinetic or transport properties of matter. At temperatures of interest, the expectations of these quantities are often dominated by contributions from rare events, making the precise calculation of these quantities by molecular dynamics simulation difficult. Here, we present a reweighting method for combining simulations from multiple temperatures (or from simulated or parallel tempering simulations) to compute an optimal estimate of the dynamical properties at the temperature of interest without the need to invoke an approximate kinetic model (such as the Arrhenius law). Continuous and differentiable estimates of these expectations at any temperature in the sampled range can also be computed, along with an assessment of the associated statistical uncertainty. For rare events, aggregating data from multiple temperatures can produce an estimate with the desired precision at greatly reduced computational cost compared with simulations conducted at a single temperature. Here, we describe use of the method for the canonical (NVT) ensemble using four common models of dynamics (canonical distribution of Hamiltonian trajectories, Andersen thermostatting, Langevin, and overdamped Langevin or Brownian dynamics), but it can be applied to any thermodynamic ensemble provided the ratio of path probabilities at different temperatures can be computed. To illustrate the method, we compute a time-correlation function for solvated terminally-blocked alanine peptide across a range of temperatures using trajectories harvested using a modified parallel tempering protocol. © 2011 American Institute of Physics Article Outline INTRODUCTION THEORY Dynamical expectations Dynamical reweighting Models of dynamics in the canonical ensemble Canonical distribution of Hamiltonian trajectories Andersen thermostat Langevin dynamics Overdamped Langevin (Brownian) dynamics Modified parallel tempering protocol CORRELATION FUNCTIONS OF A SOLVATED TERMINALLY-BLOCKED ALANINE PEPTIDE DISCUSSION
机译:基于动力学轨迹功能(例如时间相关函数)的动力学平均值在确定物质的动力学或传输性质方面起着重要作用。在感兴趣的温度下,对这些数量的期望通常受罕见事件的影响,这使得通过分子动力学模拟精确计算这些数量变得困难。在这里,我们提出了一种重加权方法,用于组合多个温度下的模拟(或模拟或并行回火模拟),以计算在所需温度下的动力学特性的最佳估计,而无需调用近似动力学模型(例如Arrhenius)法)。还可以计算出在采样范围内任何温度下这些期望值的连续且可区分的估计,以及相关统计不确定性的评估。对于罕见事件,与在单个温度下进行的仿真相比,来自多个温度的数据汇总可以以所需的精度生成估计值,而计算成本却大大降低。在这里,我们使用四种常见的动力学模型(哈密顿轨线的经典分布,安徒生恒温,朗格文和过度阻尼的朗文或布朗动力学)描述了该方法用于规范(NVT)集成的方法,但是它可以应用于任何热力学集成只要可以计算出不同温度下的路径概率之比。为了说明该方法,我们使用修改后的平行回火协议收集的轨迹,计算了一定温度范围内溶剂化的末端封闭的丙氨酸肽的时间相关函数。 ©2011美国物理研究所文章大纲简介导言动态期望动态重加权哈密顿轨线经典分布中的动力学动态模型安徒生恒温器Langevin动力学过度阻尼的Langevin(Brownian)动力学修改后的平行回火协议讨论

著录项

  • 来源
    《Journal of Chemical Physics》 |2011年第24期|p.1-14|共14页
  • 作者单位

    California Institute of Quantitative Biosciences (QB3), University of California, Berkeley, 260J Stanley Hall, Berkeley, California 94720, USA;

    IBM Almaden Research Center, San Jose, California 95120, USA;

    DFG Research Center Matheon, FU Berlin, Arnimallee 6, 14195 Berlin, Germany;

    DFG Research Center Matheon, FU Berlin, Arnimallee 6, 14195 Berlin, Germany|IWR, University of Heidelberg, INF 368, 69120 Heidelberg, Germany;

    Department of Chemical Engineering, University of Virginia, Virginia 22904, USA;

    Department of Chemistry, Stanford University, Stanford, California 94305, USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Brownian motion; molecular dynamics method; reaction kinetics theory; tempering;

    机译:布朗运动;分子动力学方法;反应动力学理论;回火;

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