WoU-MMA: Multimessenger Parameter Estimation for Binary Neutron Star Mergers

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This award supports research in relativity and relativistic astrophysics and it addresses the priority areas of NSF's "Windows on the Universe" Big Idea. The detection of gravitational waves and photons from a binary neutron star merger by NSF-funded LIGO and partner observatories in August 2017 ushered in the era of multimessenger astronomy. Since then LIGO has detected a few more binary neutron star systems and many more are expected in the future. These discoveries are starting to revolutionize our understanding of, among others, high energy astrophysics phenomena, such as short gamma-ray bursts, the properties of matter under extreme conditions, and the origin of heavy elements, such as gold and platinum. However, to make fundamental progress observations need to be complemented by theoretical understanding. This project aims to build a pipeline for the joint analysis of the different messengers in multimessenger observations of neutron star mergers. To this aim, data analysis techniques and large-scale supercomputer simulations of neutron star mergers will be combined. The project will constitute the bulk of the PhD thesis of one graduate student at Penn State, who will acquire skills in high demand in the academic and industry job markets. Numerical methods developed for these simulations could also find applications in other STEM fields. Numerical simulations of neutron star and black hole spacetimes will also be used to create an immersive and interactive virtual reality exploratorium for compact objects to be used for classroom teaching and outreach.The most common multimessenger observations of neutron star mergers are expected to combine gravitational waves and UV/optical/infrared photons generated as radioactive byproducts of the nucleosynthesis process decay. This is the so-called kilonova. This project will deliver improved gravitational wave and kilonova models based on first-principle simulations and use them in the context of a joint Bayesian parameter estimation pipeline. Many-orbit high-resolution inspiral and merger simulations will be performed in full general-relativity using newly developed high-order numerical techniques based on the entropy viscosity method to deliver convergent gravitational wave strain data extending down to the post Newtonian regime and up to the kilohertz regime, where current models start to fail. The numerical relativity data will be used to construct new frequency domain phenomenological waveform models suited for Bayesian parameter estimation. Long-term merger and post-merger simulations with microphysics and subgrid turbulence models will be performed to predict the quality and quantity of the outflows that ultimately power the kilonovae as a function of the binary parameters, such as the total mass, the tidal deformability, and, in particular, the binary mass ratio. The numerical data will be combined with a semi-analytic kilonova model calibrated against full radiative transfer calculations to construct a model of the kilonova emission as a function of the binary parameters. Kilonova and new gravitational wave models will finally be combined to perform joint parameter estimation analysis of neutron star merger events.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.