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通过将皮里斯自然轨道泛函与扩展随机相位近似相结合的激发态

Excited States by Coupling Piris Natural Orbital Functionals with the Extended Random-Phase Approximation.

作者信息

Lew-Yee Juan Felipe Huan, Bonfil-Rivera Iván Alejandro, Piris Mario, M Del Campo Jorge

机构信息

Departamento de Física y Química Teórica, Facultad de Química, Universidad Nacional Autónoma de México, México City C.P. 04510, Mexico.

Donostia International Physics Center (DIPC), 20018 Donostia, Spain.

出版信息

J Chem Theory Comput. 2024 Mar 12;20(5):2140-2151. doi: 10.1021/acs.jctc.3c01194. Epub 2024 Feb 14.

Abstract

In this work, we explore the use of Piris natural orbital functionals (PNOFs) to calculate excited-state energies by coupling their reconstructed second-order reduced density matrix with the extended random-phase approximation (ERPA). We have named the general method PNOF-ERPA, and specific approaches are referred to as PNOF-ERPA0, PNOF-ERPA1, and PNOF-ERPA2, according to the way the excitation operator is built. The implementation has been tested in the first excited states of H, HeH, LiH, Li, and N showing good results compared to the configuration interaction (CI) method. As expected, an increase in accuracy is observed on going from ERPA0 to ERPA1 and ERPA2. We also studied the effect of electron correlation included by PNOF5, PNOF7, and the recently proposed global NOF (GNOF) on the predicted excited states. PNOF5 appears to be good and may even provide better results in very small systems, but including more electron correlation becomes important as the system size increases, where GNOF achieves better results. Overall, the extension of PNOF to excited states has been successful, making it a promising method for further applications.

摘要

在这项工作中,我们探索了使用皮里斯自然轨道泛函(PNOFs)通过将其重构的二阶约化密度矩阵与扩展随机相位近似(ERPA)耦合来计算激发态能量。我们将这种通用方法命名为PNOF-ERPA,根据激发算符的构建方式,具体方法分别称为PNOF-ERPA0、PNOF-ERPA1和PNOF-ERPA2。该实现方法已在H、HeH、LiH、Li和N的第一激发态上进行了测试,与组态相互作用(CI)方法相比显示出良好的结果。正如预期的那样,从ERPA0到ERPA1和ERPA2,精度有所提高。我们还研究了PNOF5、PNOF7以及最近提出的全局自然轨道泛函(GNOF)所包含的电子关联对预测激发态的影响。PNOF5似乎表现良好,甚至在非常小的体系中可能会提供更好的结果,但随着体系尺寸的增加,包含更多的电子关联变得很重要,此时GNOF能取得更好的结果。总体而言,PNOF到激发态的扩展是成功的,使其成为一种有前景的可进一步应用的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32ea/10938499/98cb1c827fb3/ct3c01194_0001.jpg

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