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arXiv 2510.26751physics.chem-ph
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分子轨道优化与神经网络辅助的配置相互作用计算:瑞利态

Orbital Optimization and Neural-Network-Assisted Configuration Interaction Calculations of Rydberg States

University of Iceland(冰岛大学);Max Planck Institute for the Science of Light(马克斯·普朗克光科学研究所)

Gianluca Levi, Max Kroesbergen, Louis Thirion, Yorick L. A. Schmerwitz, Elvar Ö. Jónsson, Pavlo Bilous, Philipp Hansmann, Hannes Jónsson

AI总结:

本文通过分子轨道优化和神经网络辅助配置相互作用方法,提高了对分子瑞利态的计算精度,验证了优化轨道对多体计算收敛性的重要性。

摘要:

分子轨道优化与神经网络辅助的配置相互作用计算:瑞利态

英文摘要:

Rydberg excited states of molecules pose a challenge for electronic structure calculations because of their highly diffuse electron distribution. Even large and elaborate atomic basis sets tend to underrepresent the long-range tail, overly confining the Rydberg state. An approach is presented here where the molecular orbitals are variationally optimized for the excited state using a plane wave basis set in a Hartree-Fock calculation, followed by a configuration interaction calculation. The use of excited state optimized orbitals greatly enhances the convergence of the many-body calculation, as illustrated by a full configuration interaction calculation of the $2s$ Rydberg state of H$_2$. A neural-network-based selective configuration interaction approach is then applied to calculations of $3s$ and $3p$ states of H$_2$O and NH$_3$. The obtained values of excitation energy are in close agreement with experimental measurements as well as previous many-body calculations where sufficiently diffuse atomic basis sets were used. Calculations using atomic basis sets lacking extra diffuse functions, such as aug-cc-pVTZ, give significantly higher estimates due to confinement of the Rydberg states.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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