JCE-GW
Bilby (Bayesian Inference Library) is an open-source Python package designed to perform Bayesian parameter estimation and model selection for gravitational-wave (GW) signals. It offers a flexible, modular, and user-friendly framework that allows researchers to analyze...
JCE-GW
B-pop is a modular, Python-based software package designed to generate realistic populations of binary compact objects—such as binary neutron stars (BNS), neutron star–black hole binaries (NSBH), and binary black holes (BBH)—for use in gravitational-wave (GW)...
JCE-GW
GWFish is a flexible, open-source software package designed to perform Fisher matrix–based forecasts for gravitational-wave (GW) detector networks. Its primary purpose is to evaluate the expected performance of current and future GW observatories in estimating source...
JCE-GW
AResGW is a machine-learning-based pipeline designed for offline real-time gravitational wave (GW) detection, especially optimized for binary black hole (BBH) mergers in the 7–50 M☉ range (individual component masses) with non-aligned spins, using real LIGO data. Core...
JCE-GW
GRANITE (GRAvitational-wave parameter iNference Integration Tool Environment) is a pipeline designed to perform rapid and reliable parameter estimation (PE) for gravitational-wave (GW) events, particularly in the context of low-latency multi-messenger astronomy. It...
