GWPopulation: Hardware agnostic population inference for compact binaries and beyond

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Talbot, Colm, Farah, Amanda, Galaudage, Shanika, Golomb, Jacob, Tong, Hui
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916405676343296
author Talbot, Colm
Farah, Amanda
Galaudage, Shanika
Golomb, Jacob
Tong, Hui
author_facet Talbot, Colm
Farah, Amanda
Galaudage, Shanika
Golomb, Jacob
Tong, Hui
contents Since the first direct detection of gravitational waves by the LIGO--Virgo collaboration in 2015, the size of the gravitational-wave transient catalog has grown to nearly 100 events, with more than as many observed during the ongoing fourth observing run. Extracting astrophysical/cosmological information from these observations is a hierarchical Bayesian inference problem. GWPopulation is designed to provide simple-to-use, robust, and extensible tools for hierarchical inference in gravitational-wave astronomy/cosmology. It has been widely adopted for gravitational-wave astronomy, including producing flagship results for the LIGO-Virgo-KAGRA collaborations. While designed to work with observations of compact binary coalescences, GWPopulation may be available to a wider range of hierarchical Bayesian inference problems.
format Preprint
id arxiv_https___arxiv_org_abs_2409_14143
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle GWPopulation: Hardware agnostic population inference for compact binaries and beyond
Talbot, Colm
Farah, Amanda
Galaudage, Shanika
Golomb, Jacob
Tong, Hui
Instrumentation and Methods for Astrophysics
General Relativity and Quantum Cosmology
Since the first direct detection of gravitational waves by the LIGO--Virgo collaboration in 2015, the size of the gravitational-wave transient catalog has grown to nearly 100 events, with more than as many observed during the ongoing fourth observing run. Extracting astrophysical/cosmological information from these observations is a hierarchical Bayesian inference problem. GWPopulation is designed to provide simple-to-use, robust, and extensible tools for hierarchical inference in gravitational-wave astronomy/cosmology. It has been widely adopted for gravitational-wave astronomy, including producing flagship results for the LIGO-Virgo-KAGRA collaborations. While designed to work with observations of compact binary coalescences, GWPopulation may be available to a wider range of hierarchical Bayesian inference problems.
title GWPopulation: Hardware agnostic population inference for compact binaries and beyond
topic Instrumentation and Methods for Astrophysics
General Relativity and Quantum Cosmology
url https://arxiv.org/abs/2409.14143