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基于搜索基元逃逸通道构建的马氏态模型的准确性。

Accuracy of a Markov state model generated by searching for basin escape pathways.

机构信息

Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh 208016, India.

出版信息

J Chem Phys. 2013 Feb 28;138(8):084103. doi: 10.1063/1.4792439.

Abstract

Markov state models (MSMs) are employed extensively in literature with the kinetic Monte Carlo (KMC) method for studying state-to-state dynamics in a wide range of material systems. A MSM contains a list of atomic processes and their rate constants for different states of the system. In many situations, only few of the possible atomic processes are included in the MSM. The use of an incomplete MSM with the KMC method can lead to an error in the dynamics. In this work, we develop an error measure to assess the accuracy of a MSM generated using dynamical basin escape pathway searches. We show that the error associated with an incomplete MSM depends on the rate constants missing from the MSM. A procedure to estimate the missing rate constants is developed. We demonstrate our approach using some examples.

摘要

马尔可夫状态模型 (MSMs) 与动力学蒙特卡罗 (KMC) 方法一起在文献中被广泛应用,用于研究各种材料系统中的状态到状态动力学。MSM 包含一个原子过程列表及其系统不同状态的速率常数。在许多情况下,MSM 中只包含少数几种可能的原子过程。使用 KMC 方法的不完整 MSM 可能会导致动力学错误。在这项工作中,我们开发了一种误差度量方法来评估使用动力学基态逃逸途径搜索生成的 MSM 的准确性。我们表明,与不完整 MSM 相关的误差取决于 MSM 中缺失的速率常数。开发了一种估计缺失速率常数的程序。我们使用一些示例演示了我们的方法。

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