Initialization of Binary Neutron Star Orbits Using External Potential Relaxation Scheme
POSTER
Abstract
Simulating neutron-star binary mergers is important for probing our knowledge of fundamental physics. Investigation into the equation of state of cold, dense nuclear matter, gaining insight into r-process nucleosynthesis during kilonovae, and gravitational-wave signal interpretation are among the many research pursuits that benefit from the numerical study of compact-star binaries with computational fluid dynamics codes. Merger simulations require accurate initial conditions in regard to the shapes of each star in orbit to correctly model the inspiral phase. In this work we demonstrate two different methods for preparing initial conditions of binary neutron-star systems for Newtonian smoothed particle hydrodynamics simulations. The first method simply assigns particle velocities based on spin, angular momentum, and separation of the stars. The binary is then evolved without the inclusion of gravitational-wave emission, i.e. at a fixed orbital distance, until the stars have relaxed to the physically correct shapes. The second method relaxes the stars within an external potential which emulates the forces experienced by the stars in a frame that is corotating with the binary. The forces deform each star to the configuration they should have given a particular spin and separation to the binary partner. We explore and compare the two different schemes e.g. in terms of their accuracy and computational efficiency. Future work will involve the application of the methods to compact-star binaries with solid components in the crust or core and their impact on the inspiral phase.
*The presented work was supported by the Advanced Simulation and Computing program (NNSA/DOE) and the Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200145ER. The research used resources provided by the LANL Institutional Computing Program and the LANL Darwin testbed. This work is authorized for unlimited release under LA-UR-22-29526
Presenters
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Michael Falato
- Los Alamos National Laboratory