Please contact divya.singh@berkeley.edu or tianqi.zhao@berkeley.edu for zoom links.

As the sensitivity of gravitational-wave detector networks increases, high-fidelity signal recovery from the most prominent events becomes possible. The strongest signals present both opportunities and challenges for inferring the properties of their sources. Focusing on the problem of inferring neutron star equations of state in neutron star mergers, I will discuss how systematic errors from waveform modeling have the potential to dominate the inference of matter properties in future observations. If it is properly addressed, however, subdominant effects added to the waveform model may then be revealed, providing novel opportunities to learn about neutron star matter beyond the equation of state. I will outline a data-driven approach to interpreting gravitational-wave observations with phenomenological signal corrections, including some first results from my group at CSUF. I’ll also discuss methods of connecting measured waveform corrections to the energetics of the source system. Finally, I will relate these uncertainty quantification methods to goals for interferometer commissioning and instrumental design, demonstrating how next-generation sensitivities will translate into improved scientific potential.