Implementation of a Causal Spectral Decomposition Representation for the Neutron Star Equation of State for Gravitational Wave Parameter Estimation

On August 17, 2017 LIGO observed a binary neutron star merger 130 million lightyears away by detecting ripples in the fabric of spacetime called gravitational waves. Information about the neutron star equation of state (EOS), an equation relating the state variables of a system, is encoded in these waves. Currently the neutron star EOS is highly unconstrained. However, constraining this equation through gravitational wave measurements may provide us unprecedented knowledge about a naturally occurring source of nuclear matter at densities unachievable in a laboratory. Theoretical physicists use knowledge of microscopic and thermodynamic properties of nuclear matter in order to invent potential candidate EOSs that are consistent with current neutron star observations. Prior to LIGO’s monumental discovery, NS observations and EOS constraints came exclusively via optical telescopes. However, we can extract NS EOS information from gravitational waves as well. In this project, I incorporated an EOS model with physical conditions such as causality and thermodynamic stability built in. I have developed software that will be incorporated into LIGO’s parameter estimation algorithms to measure the neutron star EOS from future gravitational wave observations using this model.