The majority of binary neutron star mergers are expected to result in a hypermassive remnant. These remnants emit gravitational waves that are highly informative as to neutron star composition, but are emitted at high (kHz) frequencies where the current-generation gravitational wave detectors are less sensitive. As a result, constraints on the nuclear equation of state from post-merger remnants was considered out-of-reach until the advent of next-generation detectors. 

I led an interdisciplinary team to develop a hierarchical Bayesian analysis called BayeStack. This analysis leverages empirical relations derived from numerical relativity alongside chirp mass measurements from the inspiral itself to statistically stack small amounts of information from each individually undetectable post-merger remnant across a large population of mergers. The BayeStack analysis was shown via simulations to be able to achieve meaningful constraints on the neutron star equation of state with current generation detector sensitivity.

This work is published in Physical Review D.

LISA, a spaceborne gravitational wave detector expected to launch in the 2030's, will have millions of sources all present in the detector simultaneously. One example of this is the Milky Way Foreground: the overlapping, stochastic hum from all of the individually-unresolvable white dwarf binaries in the Milky Way. This signal is expected to be so loud that it sits above the LISA noise curve, and will comprise a significant contribution to the overall noise present in LISA.

However, it is also an astrophysical gravitational-wave signal arising from the population of white dwarf binaries in our Galaxy. I am developing a hierarchical Bayesian analysis to infer the spatial distribution of this old stellar population from the stochastic foreground signal, allowing us to probe the early history of the Milky Way when LISA flies.

I am also leading several additional projects focused on LISA — most involving undergraduate researchers — that range from exploring the stochastic signals from white dwarf binaries in Milky Way satellites, to determining the angular resolution of anisotropic searches for stochastic gravitational wave signals with LISA, to enabling simultaneous inference of multiple stochastic signals in LISA.