Systematic simulations and analysis of transition states using committor functions

IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

Abstract

Data about the transition states of rare transitions between long-lived states are needed to simulate physical and chemical processes; however, existing computational approaches often gather little information about these states. A machine-learning technique resolves this challenge by exploiting the century-old theory of committor functions.

Abstract Image

使用委托函数对过渡状态进行系统模拟和分析。
模拟物理和化学过程需要有关长寿命状态之间罕见转换的过渡状态的数据;然而,现有的计算方法往往收集不到有关这些状态的信息。一种机器学习技术利用具有百年历史的承诺函数理论解决了这一难题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
11.70
自引率
0.00%
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0
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