Multi-messenger astronomy in the era of gravitational wave detections

Abstract

From the first detection of gravitational waves, to the discovery of the optical counterpart to a binary neutron star merger, gravitational-wave multi-messenger astronomy has been a powerful driving force in the development of new large-scale optical sky surveys, techniques, and methods, seeking to exploit the powerful synergies this new way of looking at the Universe has unlocked. This thesis is a compilation of original work from across time-domain astronomy – with a common thread of applying statistical methods to large datasets to extract new conclusions. Chapters 3 and 6 fuse deep learning and databases to build high-performance, uncertainty-aware source classification algorithms for large-scale optical sky surveys, breaking new ground in integrating contextual information directly into deep-learned classifiers. Chapter 4 constructs a Bayesian inference pipeline for homogeneous reprocessing of over 20 years of high-resolution spectra of the principal continuous-wave source and cornerstone LMXB, Sco X-1 – delivering the most precise ephemerides for the system thus far to enable high-sensitivity searches for gravitational waves. Chapter 5 presents a search for short- timescale variability in supernova light curves, with the aim of providing novel constraints on the structuring and density of the circumstellar medium in these systems. Although null results were obtained, the data constrain the amplitude of and rate of occurrence of previously-observed fluctuations, and allow us to develop the techniques necessary to extend this study to a larger sample in future