Core package to analyze gravitational-wave data, find signals, and study their parameters. This package was used in the first direct detection of gravitational waves (GW150914), and is used in the ongoing analysis of LIGO/Virgo data.

Learn how to use PyCBC to analyze gravitational-wave data and do parameter inference.

A python package for Bayesian inference of gravitational-wave data

Repository for the PyCBC Inference workshop in Portsmouth, UK, 14 May - 16 May 2019.

Fourth Open Gravitational-wave Catalog of Compact Binary Mergers (4-OGC). Using the data from LIGO and Virgo from 2015-2020, a comprehensive catalog including 94 detected mergers (90 BBH, 2 BNS, 2 NSBH) and sub-threshold candidates throughout O1, O2, O3a, and O3b..

Investigating the noise residuals around the gravitational wave event GW150914

First Open Gravitational-wave Catalog of Compact Binary Mergers from Advanced LIGO's first observing run.

Configuration files for the PyCBC-based online and offline searches.

Measuring the viewing angle of GW170817 with electromagnetic and gravitational waves

Data Release associated with the PyCBC Inference paper. This includes posterior samples for GW150914, LVT151012, and GW151226 along with configuration files and run scripts,

Interactive Web Apps to Explore Gravitational Waves

Supplementary materials for our GW-GRB search of the first observing run of advanced LIGO.

Scripts to reproduce the right hand plot shown in Figure 4 of https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.116.061102

Results from the common equation of state constraint analysis of GW170817

Associated data release to the search for mergers of stellar-mass and sub-solar mass black holes

Matched filtering with pyCBC, Click -->

Data Release of posterior samples from PyCBC Inference analysis of the binary black-hole signals GW170104, GW170608 and GW170814 in Advanced LIGO-Virgo's second observing run. This repository also includes configuration files and run scripts to run the analyses.

Parameter estimates for the eccentricity of GW170817 and GW190425

The Apple Silicon Gravitational-Wave Cluster project utilizes the power of Apple Silicon M2 processors to construct a high-performance cluster tailored for gravitational-wave astronomy.