This book employs sophisticated statistical and computational techniques, including machine learning, to characterize the spectra of electromagnetic counterparts to gravitational wave sources. Specifically, the author studies the explosions associated with neutron star collisions called kilonovae, developing the SPARK tool to infer rapid neutron capture (r-process) abundance patterns and offer insight into the production of heavy elements in the Universe. The innovative methods implemented by the author in SPARK are insightful for characterizing spectra from the first neutron star merger, GW170817, and will be essential for understanding the properties of the broader population of kilonova explosions. SPARK is thus poised to become a high impact, open-source tool, making this thesis essential reading for the astrophysics research community.
Nicholas Vieira
kilonovae origin of heaviest elements r-process Spectroscopic r-Process Abundance Retrieval for Kilonovae GW170817 neutron star merger multi-component ejecta spectra of kilonovae