{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pyflosic-python-based-fermi-lowdin-orbital","title":"PyFLOSIC: Python-based Fermi-Löwdin orbital self-interaction correction","arxiv_id":"1905.02631","date":"2019-05-07","proceeding":null,"authors":["Sebastian Schwalbe","Lenz Fiedler","Jakob Kraus","Jens Kortus","Kai Trepte","Susi Lehtola"],"abstract":"We present PyFLOSIC, an open-source, general-purpose Python implementation of the Fermi-L\\\"owdin orbital self-interaction correction (FLO-SIC), which is based on the Python simulation of chemistry frame-work (PySCF) electronic structure and quantum chemistry code. Thanks to PySCF, PyFLOSIC can be used with any kind of Gaussian-type basis set, various kinds of radial and angular quadrature grids, and all exchange-correlation functionals within the local density approximation (LDA), generalized-gradient approximation (GGA), and meta-GGA provided in the Libxc and XCFun libraries. A central aspect of FLO-SIC are Fermi-orbital descriptors, which are used to estimate the self-interaction correction. Importantly, they can be initialized automatically within PyFLOSIC and optimized with an interface to the atomic simulation environment, a Python library which provides a variety of powerful gradient-based algorithms for geometry optimization. Although PyFLOSIC has already facilitated applications of FLO-SIC to chemical studies, it offers an excellent starting point for further developments in FLO-SIC approaches, thanks to its use of a high-level programming language and pronounced modularity.","url_abs":"https://arxiv.org/abs/1905.02631v3","url_pdf":"https://arxiv.org/pdf/1905.02631v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"pyflosic-python-based-fermi-lowdin-orbital","repo_url":"https://github.com/pyflosic/pyflosic","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"pyflosic-python-based-fermi-lowdin-orbital","repo_url":"https://gitlab.com/opensic/pyflosic2","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}