Collisions of neutron stars and black holes are very rare events, but the enormous energies they release in gravitational waves, infrared radiation, X-rays, and gamma-rays make them potentially detectable even when very far away. Their gravitational wave and electromagnetic signals contain information about the properties and unknown physics of the colliding objects, but to extract this information, astronomers need theoretical models to which they can compare. For this project, computer simulations will be carried out of systems with a black hole and neutron star orbiting each other and eventually merging. Simulations will also explore the debris commonly produced by black hole-neutron star and neutron star-neutron star mergers: radioactive gas ejected into the surrounding space and hot, magnetized nuclear matter swirling around a black hole. Carrying out these simulations will involve training both graduate and undergraduate students on techniques of computer modeling in relativistic astrophysics. The resulting gravitational wave and nuclear debris data will be made available to all astronomers working to detect and characterize these events.
This research fills some of the most interesting remaining gaps in the modeling of inspiral, disk, and outflow phases of black hole-neutron star binary mergers using simulations with the Spectral Einstein Code (SpEC), a high-accuracy numerical relativity code that now includes magnetohydrodynamics, nuclear microphysics, and neutrino cooling. Simulations of long inspirals are used to test and improve algorithms for detecting and identifying the gravitational wave signals from such sources. Improvements to SpEC's treatment of flows near black hole horizons enable higher-accuracy accretion disk simulations, and these are used to study the disk dynamics, gamma ray burst, energy extraction, and late-time (tenths of a second) behavior. The project studies outflows for a wide range of binary parameters. The evolution of ejecta far from the post-merger black hole is tracked with smoothed-particle hydrodynamics and nuclear reaction network codes using SpEC data as input, enabling predictions of fallback, kilonova brightness, and nucleosynthesis.
