{"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/pyfstat-a-python-package-for-continuous","title":"PyFstat: a Python package for continuous gravitational-wave data analysis","arxiv_id":"2101.10915","date":"2021-01-26","proceeding":null,"authors":["David Keitel","Rodrigo Tenorio","Gregory Ashton","Reinhard Prix"],"abstract":"Gravitational waves in the sensitivity band of ground-based detectors can be emitted by a number of astrophysical sources, including not only binary coalescences, but also individual spinning neutron stars. The most promising signals from such sources, although not yet detected, are long-lasting, quasi-monochromatic Continuous Waves (CWs). The PyFstat package provides tools to perform a range of CW data-analysis tasks. It revolves around the F-statistic, a matched-filter detection statistic for CW signals that has been one of the standard methods for LIGO-Virgo CW searches for two decades. PyFstat is built on top of established routines in LALSuite but through its more modern Python interface it enables a flexible approach to designing new search strategies. Hence, it serves a dual function of (i) making LALSuite CW functionality more easily accessible through a Python interface, thus facilitating the new user experience and, for developers, the exploratory implementation of novel methods; and (ii) providing a set of production-ready search classes for use cases not yet covered by LALSuite itself, most notably for MCMC-based followup of promising candidates from wide-parameter-space searches.","url_abs":"https://arxiv.org/abs/2101.10915v2","url_pdf":"https://arxiv.org/pdf/2101.10915v2.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":"pyfstat-a-python-package-for-continuous","repo_url":"https://github.com/pyfstat/pyfstat","is_official":1,"mentioned_in_paper":1,"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}