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关于非平稳广义朗之万方程。

On the non-stationary generalized Langevin equation.

机构信息

Physikalisches Institut, Albert-Ludwigs-Universität, 79104 Freiburg, Germany.

Institut für Materialphysik im Weltraum, Deutsches Zentrum für Luft- und Raumfahrt (DLR), 51170 Köln, Germany.

出版信息

J Chem Phys. 2017 Dec 7;147(21):214110. doi: 10.1063/1.5006980.

Abstract

In molecular dynamics simulations and single molecule experiments, observables are usually measured along dynamic trajectories and then averaged over an ensemble ("bundle") of trajectories. Under stationary conditions, the time-evolution of such averages is described by the generalized Langevin equation. By contrast, if the dynamics is not stationary, it is not a priori clear which form the equation of motion for an averaged observable has. We employ the formalism of time-dependent projection operator techniques to derive the equation of motion for a non-equilibrium trajectory-averaged observable as well as for its non-stationary auto-correlation function. The equation is similar in structure to the generalized Langevin equation but exhibits a time-dependent memory kernel as well as a fluctuating force that implicitly depends on the initial conditions of the process. We also derive a relation between this memory kernel and the autocorrelation function of the fluctuating force that has a structure similar to a fluctuation-dissipation relation. In addition, we show how the choice of the projection operator allows us to relate the Taylor expansion of the memory kernel to data that are accessible in MD simulations and experiments, thus allowing us to construct the equation of motion. As a numerical example, the procedure is applied to Brownian motion initialized in non-equilibrium conditions and is shown to be consistent with direct measurements from simulations.

摘要

在分子动力学模拟和单分子实验中,通常沿着动态轨迹测量可观测值,然后在轨迹的“束”上对其进行平均。在静态条件下,这种平均值的时间演化由广义朗之万方程描述。相比之下,如果动力学不是静态的,则平均可观测值的运动方程的形式并不清楚。我们采用时变投影算子技术的形式来推导非平衡轨迹平均可观测值及其非平稳自相关函数的运动方程。该方程的结构与广义朗之万方程相似,但具有时变记忆核以及隐式依赖于过程初始条件的随机力。我们还推导出了这个记忆核与随机力的自相关函数之间的关系,其结构类似于涨落耗散关系。此外,我们展示了如何选择投影算子,以便将记忆核的泰勒展开与 MD 模拟和实验中可获得的数据相关联,从而允许我们构建运动方程。作为一个数值例子,该程序应用于非平衡条件下初始化的布朗运动,并与从模拟中的直接测量结果一致。

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