旋转适应的外部承包的多引用配置交互方法基于选择的参考配置的交互方法
Yinxuan Song1, Wei Huang1, Chungen Liu1
1School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, People's Republic of China.
The journal of physical chemistry. A
|January 25, 2024
概括
对于大型系统,选择的配置交互 (sCI) 方法得到了改进. 使用配置状态函数和先进算法的新方法提高了量子化学计算中的动态相关性效率和准确性.
科学领域:
- 量子化学 是一个量子化学.
- 计算化学计算化学
背景情况:
- 选择配置交互 (sCI) 是对完整配置交互的近似,对大型活动空间有价值.
- 动态相关性对于超出大型活动空间的定量结果至关重要.
- 使用sCI引用的外部承包的多引用配置交互 (EC-MRCI) 是有希望的,但也有缺点.
研究的目的:
- 为了解决之前的sCI-EC-MRCI方法中的旋转污染和低效率.
- 为大型量子系统开发一种更有效,更准确的计算方法.
主要方法:
- 使用了配置状态函数 (CSF) 基础,而不是斯莱特决定因素.
- 介绍了一种混合算法,它结合了用于配置空间管理的树结构和用于矩阵元素计算的图形单元组方法 (GUGA).
- 开发了一种旋转适应的方法版本.
主要成果:
- 以旋转调整的CSF为基础的方法实现了6.0的加快速度,相比纳烯的斯莱特决定性版本.
- 改进的sCI-EC-MRCI方法为双核铜 (II) 化合物和Ln (III) /An (III) 复合物提供了定量准确的结果.
- 证明了将超越sCI的动态相关性纳入大型活动空间和基础集的能力.
结论:
- 新的基于CSF的sCI-EC-MRCI方法显著提高了效率,并减少了旋转污染.
- 这种方法可以准确地处理具有大型活性空间和基础集的复杂系统中的动态相关性.
- 开发的计算策略对于在量子化学中挑战化学系统是有效的.
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