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三则为幸:锥形交叉优化的非绝热替代模型。

Smooth Things Come in Threes: A Diabatic Surrogate Model for Conical Intersection Optimization.

机构信息

Department of Chemistry-BMC, Uppsala University, P.O. Box 576, SE-75123 Uppsala, Sweden.

Uppsala Center for Computational Chemistry (UC3), Uppsala University, P.O. Box 576, SE-75123 Uppsala, Sweden.

出版信息

J Chem Theory Comput. 2023 Jun 13;19(11):3418-3427. doi: 10.1021/acs.jctc.3c00389. Epub 2023 May 16.

DOI:10.1021/acs.jctc.3c00389
PMID:37192531
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10269327/
Abstract

The optimization of conical intersection structures is complicated by the nondifferentiability of the adiabatic potential energy surfaces. In this work, we build a pseudodiabatic surrogate model, based on Gaussian process regression, formed by three smooth and differentiable surfaces that can adequately reproduce the adiabatic surfaces. Using this model with the restricted variance optimization method results in a notable decrease of the overall computational effort required to obtain minimum energy crossing points.

摘要

锥形交叉结构的优化受到非可微绝热势能面的复杂性的影响。在这项工作中,我们基于高斯过程回归构建了一个伪绝热替代模型,由三个平滑且可微的表面组成,可以充分再现绝热表面。使用这个模型和受限方差优化方法可以显著减少获得最小能量交叉点所需的总计算工作量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84dd/10269327/281d6a750979/ct3c00389_0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84dd/10269327/389e81979e51/ct3c00389_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84dd/10269327/18eaf8e2a4fd/ct3c00389_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84dd/10269327/17d57521dda2/ct3c00389_0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84dd/10269327/281d6a750979/ct3c00389_0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84dd/10269327/389e81979e51/ct3c00389_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84dd/10269327/18eaf8e2a4fd/ct3c00389_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84dd/10269327/17d57521dda2/ct3c00389_0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84dd/10269327/281d6a750979/ct3c00389_0010.jpg

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