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有偏梯度平方下降鞍点查找方法。

Biased gradient squared descent saddle point finding method.

机构信息

Department of Chemistry and the Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas 78712-0165, USA.

Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, USA.

出版信息

J Chem Phys. 2014 May 21;140(19):194102. doi: 10.1063/1.4875477.

Abstract

The harmonic approximation to transition state theory simplifies the problem of calculating a chemical reaction rate to identifying relevant low energy saddle points in a chemical system. Here, we present a saddle point finding method which does not require knowledge of specific product states. In the method, the potential energy landscape is transformed into the square of the gradient, which converts all critical points of the original potential energy surface into global minima. A biasing term is added to the gradient squared landscape to stabilize the low energy saddle points near a minimum of interest, and destabilize other critical points. We demonstrate that this method is competitive with the dimer min-mode following method in terms of the number of force evaluations required to find a set of low-energy saddle points around a reactant minimum.

摘要

过渡态理论的谐波近似将计算化学反应速率的问题简化为确定化学系统中相关的低能鞍点。在这里,我们提出了一种不需要特定产物状态知识的鞍点查找方法。在该方法中,将势能面变换为梯度的平方,这将原始势能表面上的所有临界点转换为全局最小值。在梯度平方景观中添加一个偏置项,以稳定感兴趣的最小附近的低能鞍点,并使其他临界点失稳。我们证明,就找到一组围绕反应物最小的低能鞍点所需的力评估数量而言,该方法与二聚体 min-mode following 方法具有竞争力。

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