Research output
PyQInt: A Teaching-Oriented Hartree–Fock Implementation in Python
Abstract
PyQInt is a modular Python package for learning and prototyping quantum chemistry methods, with a particular focus on the Hartree-Fock formalism (Roothaan, 1951) using Gaussian-type orbitals (Pople et al., 1995).Designed to prioritize educational transparency, PyQInt exposes all computational building blocks-integrals, matrices, Hamiltonians, SCF procedures, and gradients-through a clean, inspectable API.Users can evaluate molecular integrals (Taketa et al., 1966), perform self-consistent field calculations with direct inversion of iterative subspace (DIIS) (Pulay, 1980), construct and localize orbitals, compute crystal orbital Hamilton population (COHP) coefficients (Dronskowski & Bloechl, 1993), and optimize molecular geometries.PyQInt is especially well suited for students and researchers who want to interact with and understand the underlying steps of electronic structure theory, offering full access to intermediate data structures and algorithmic pathways.While numerical efficiency is not the primary goal, PyQInt connects to a C++ backend for integral evaluation, enabling practical computations on small molecules.The package is fully documented and tested, and is ideal for use in courses, tutorials, or prototyping new electronic structure ideas.
Abstract from OpenAlex , checked 2026-06-29.
Citation
Filot, I.A.W. PyQInt: A Teaching-Oriented Hartree–Fock Implementation in Python. JOSE 2025, 8 (94), 286. 10.21105/jose.00286
Metric Source
Citation markers are read from Scopus when configured, with public DOI metadata as fallback, and cached locally. They can differ from Pure counts shown on institutional portals. Checked 2026-07-09 via OpenAlex.