LibppRPA: An Open-Source Library for Particle-Particle Random Phase Approximation

Fuente: arXiv
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Main Authors: Yu, Jincheng, Li, Jiachen, Zhang, Chaoqun, Zhu, Tianyu, Yang, Weitao
Format: Preprint
Published: 2025
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author Yu, Jincheng
Li, Jiachen
Zhang, Chaoqun
Zhu, Tianyu
Yang, Weitao
author_facet Yu, Jincheng
Li, Jiachen
Zhang, Chaoqun
Zhu, Tianyu
Yang, Weitao
contents The accurate description of electron correlation and excitation energies remains a fundamental challenge in quantum chemistry. The particle-particle random phase approximation (ppRPA) has emerged as a promising method for capturing a broad range of excited-state properties. However, the implementation of ppRPA has been largely limited to in-house software, restricting its accessibility and usability. In this work, we present LibppRPA, an open-source and lightweight Python library designed for efficient and flexible ppRPA calculations of (1) electronic excitation energy and its associated analytical gradients and (2) the ground state correlation energy, and its associated analytical gradients. LibppRPA enables seamless integration with existing quantum chemistry packages, such as PySCF, by utilizing occupation numbers, molecular orbital coefficients, and three-center electron repulsion integrals. We implement both direct diagonalization and the iterative Davidson algorithm for solving the ppRPA equations, as well as active-space approximations, allowing users to balance accuracy and computational efficiency. We demonstrate the performance of LibppRPA through benchmark calculations on singlet-triplet gaps, double excitations, charge-transfer excitations, and valence/Rydberg excitations, showcasing its reliability across diverse molecular systems. The library provides a robust platform for studying electronic excitations and offers new opportunities for future developments in electronic structure theory.
format Preprint
id arxiv_https___arxiv_org_abs_2512_12515
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle LibppRPA: An Open-Source Library for Particle-Particle Random Phase Approximation
Yu, Jincheng
Li, Jiachen
Zhang, Chaoqun
Zhu, Tianyu
Yang, Weitao
Chemical Physics
The accurate description of electron correlation and excitation energies remains a fundamental challenge in quantum chemistry. The particle-particle random phase approximation (ppRPA) has emerged as a promising method for capturing a broad range of excited-state properties. However, the implementation of ppRPA has been largely limited to in-house software, restricting its accessibility and usability. In this work, we present LibppRPA, an open-source and lightweight Python library designed for efficient and flexible ppRPA calculations of (1) electronic excitation energy and its associated analytical gradients and (2) the ground state correlation energy, and its associated analytical gradients. LibppRPA enables seamless integration with existing quantum chemistry packages, such as PySCF, by utilizing occupation numbers, molecular orbital coefficients, and three-center electron repulsion integrals. We implement both direct diagonalization and the iterative Davidson algorithm for solving the ppRPA equations, as well as active-space approximations, allowing users to balance accuracy and computational efficiency. We demonstrate the performance of LibppRPA through benchmark calculations on singlet-triplet gaps, double excitations, charge-transfer excitations, and valence/Rydberg excitations, showcasing its reliability across diverse molecular systems. The library provides a robust platform for studying electronic excitations and offers new opportunities for future developments in electronic structure theory.
title LibppRPA: An Open-Source Library for Particle-Particle Random Phase Approximation
topic Chemical Physics
url https://arxiv.org/abs/2512.12515