Inferring physical properties of stellar collapse by third-generation gravitational-wave detectors

Galactic core-collapse supernovae are among the possible sources of gravitational waves. We investigate the ability of gravitational-wave detectors to extract the properties of the collapsing progenitor from the gravitational waves radiated. We use simulations of supernovae that explore a variety of progenitor core rotation rates and nuclear equations of state and use principal component analysis of the simulation catalog to determine the dominant features of the waveforms and create a map between the measured properties of the waveform and the physical properties of the progenitor, namely the ratio of the progenitor’s core rotational kinetic energy to potential energy ($\beta$) and the post bounce oscillation frequency (f-peak). We use Bayesian parameter inference and the map to calculate posteriors for the physical properties given a gravitational-wave observation. For a supernovae at the distance of the galactic center with $\beta=0.02$ our method can estimate $\beta$ with a $90\%$ credible interval of 0.004 for Advanced LIGO, and 0.0008 for Cosmic Explorer. We demonstrate that if $\beta>0.02$ for a source within the Milky Way observed by Cosmic Explorer, our method can also extract f-peak to a precision of within 5Hz allowing us to constrain the nuclear equation of state.