PyFstat: a Python package for continuous gravitational-wave data analysis
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.
Keywords
Cite
@article{arxiv.2101.10915,
title = {PyFstat: a Python package for continuous gravitational-wave data analysis},
author = {David Keitel and Rodrigo Tenorio and Gregory Ashton and Reinhard Prix},
journal= {arXiv preprint arXiv:2101.10915},
year = {2021}
}
Comments
4 pages, updated to match published version. Software repository: https://github.com/PyFstat/PyFstat/