GBasis: A Python library for evaluating functions, functionals, and integrals expressed with Gaussian basis functions

Python(编程语言) 高斯分布 计算 计算机科学 基函数 理论计算机科学 基础(线性代数) 计算科学 算法 程序设计语言 物理 数学 量子力学 几何学
作者
Taewon David Kim,Leila Pujal,Michelle Richer,Maximilian van Zyl,Marco Martínez González,Alireza Tehrani,Valerii Chuiko,Gabriela Sánchez‐Díaz,Wesley Sanchez,William Adams,Xiaomin Huang,Braden Kelly,Esteban Vöhringer‐Martinez,Toon Verstraelen,Farnaz Heidar‐Zadeh,Paul W. Ayers
出处
期刊:Journal of Chemical Physics [American Institute of Physics]
卷期号:161 (4) 被引量:5
标识
DOI:10.1063/5.0216776
摘要

GBasis is a free and open-source Python library for molecular property computations based on Gaussian basis functions in quantum chemistry. Specifically, GBasis allows one to evaluate functions expanded in Gaussian basis functions (including molecular orbitals, electron density, and reduced density matrices) and to compute functionals of Gaussian basis functions (overlap integrals, one-electron integrals, and two-electron integrals). Unique features of GBasis include supporting evaluation and analytical integration of arbitrary-order derivatives of the density (matrices), computation of a broad range of (screened) Coulomb interactions, and evaluation of overlap integrals of arbitrary numbers of Gaussians in arbitrarily high dimensions. For circumstances where the flexibility of GBasis is less important than high performance, a seamless Python interface to the Libcint C package is provided. GBasis is designed to be easy to use, maintain, and extend following many standards of sustainable software development, including code-quality assurance through continuous integration protocols, extensive testing, comprehensive documentation, up-to-date package management, and continuous delivery. This article marks the official release of the GBasis library, outlining its features, examples, and development.

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