bajes-mma: Joint Bayesian Inference Framework for Multi-Messenger Astronomy with Binary Neutron Star Coalescences

The coincident observation of three events GW170817, GRB170817A, and AT2017gfo---a gravitational-wave signal with associated electromagnetic counterpart observed via a short gamma-ray burst, kilonova, and successive long-term afterglow emission---marked the onset of multi-messenger astronomy using gravitational and electromagnetic waves. The consequent analyses of these transient events provided a treasure trove of data shedding light onto the dense matter regime, cosmological measurements, and the accuracy of general relativity itself. In expectation of further multi-messenger events during upcoming observing runs by the LIGO, Virgo, and KAGRA observatories we developed a data analysis pipeline to jointly examine the observational data associated with a multi-messenger event. The pipeline is built on the Bayesian inference framework bajes and leverages its strength to incorporate any data channel, i.e. for binary neutron star mergers the gravitational waves signal and associated electromagnetic transients---including klionovae, short gamma-ray bursts, and synchrotron from the fast-tail of the ejecta. Using this pipeline we analyzed the events associated to GW170817 simultaneously to improve the parameter constraints of prior studies.