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首页> 外文期刊>The journal of physical chemistry, A. Molecules, spectroscopy, kinetics, environment, & general theory >A Simple “Boxed Molecular Kinetics” Approach To Accelerate Rare Events in the Stochastic Kinetic Master Equation
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A Simple “Boxed Molecular Kinetics” Approach To Accelerate Rare Events in the Stochastic Kinetic Master Equation

机译：一种简单的“盒装分子动力学”方法，以加速随机动力学总体方程中的罕见事件

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摘要

The chemical master equation is a powerful theoretical tool for analyzing the kinetics of complex multiwell potential energy surfaces in a wide range of different domains of chemical kinetics spanning combustion, atmospheric chemistry, gas-surface chemistry, solution phase chemistry, and biochemistry. There are two well-established methodologies for solving the chemical master equation: a stochastic “kinetic Monte Carlo” approach and a matrix-based approach. In principle, the results yielded by both approaches are identical; the decision of which approach is better suited to a particular study depends on the details of the specific system under investigation. In this Article, we present a rigorous method for accelerating stochastic approaches by several orders of magnitude, along with a method for unbiasing the accelerated results to recover the “true” value. The approach we take in this paper is inspired by the so-called “boxed molecular dynamics” (BXD) method, which has previously only been applied to accelerate rare events in molecular dynamics simulations. Here we extend BXD to design a simple algorithmic strategy for accelerating rare events in stochastic kinetic simulations. Tests on a number of systems show that the results obtained using the BXD rare event strategy are in good agreement with unbiased results. To carry out these tests, we have implemented a kinetic Monte Carlo approach in MESMER, which is a cross-platform, open-source, and freely available master equation solver.
机译：化学总体方程是一种强大的理论工具，用于分析复杂多阱势能表面的动力学在跨越燃烧，大气化学，气体表面化学，溶液相化学和生物化学的各种不同领域中的各种不同领域。解决化学总体方程有两种良好的方法：一种随机的“动力学蒙特卡罗”方法和基于矩阵的方法。原则上，两种方法产生的结果是相同的;哪种方法更适合特定研究的决定取决于调查的特定系统的细节。在本文中，我们提出了一种严格的方法，用于通过几个数量级加速随机方法，以及用于取消释放加速结果以恢复“真实”值的方法。我们采用本文的方法是由所谓的“盒装分子动力学”（BXD）方法的启发，该方法仅应用于加速分子动力学模拟中的罕见事件。在这里，我们扩展了BXD来设计一种简单的算法策略，用于加速随机动力学模拟中的罕见事件。对许多系统的测试表明，使用BXD罕见事件策略获得的结果与无偏见的结果一致。为了执行这些测试，我们在MESMER中实施了动力学蒙特卡罗方法，它是跨平台，开源和自由可用的主级求解器。

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