${\tt bajes}$: Bayesian inference of multimessenger astrophysical data, methods and application to gravitational-waves

Understand

We present ${\tt bajes}$, a parallel and lightweight framework for Bayesian inference of multimessenger transients.

• ${\tt bajes}$ is a Python modular package with minimal dependencies on external libraries adaptable to the majority of the Bayesian models and to various sampling methods.
• We describe the general workflow and the parameter estimation pipeline for compact-binary-coalescence gravitational-wave transients.
• The latter is validated against injections of binary black hole and binary neutron star waveforms, including confidence interval tests that demonstrates the inference is well-calibrated.