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This thesis presents new approaches to evolutions of binary black hole systems in numerical relativity. We analyze and compare evolutions from various physically motivated initial data sets, in particular presenting the first evolutions of Thin Sandwich data generated by the Meudon group. For the first time two different quasi-circular orbit initial data sequences are compared through fully 3d numerical evolutions: Puncture data and Thin Sandwich data (TSD) based on a helical killing vector ansatz. The two different sets are compared in terms of the physical quantities that can be measured from the numerical data, and in terms of their evolutionary behavior. The evolutions demonstrate that for the latter, "Meudon" datasets, the black holes do in fact orbit for a longer amount of time before they merge, in comparison with Puncture data from the same separation. This indicates they are potentially better estimates of quasi-circular orbit parameters. The merger times resulting from the numerical simulations are consistent with independent Post-Newtonian estimates that the final plunge phase of a black hole inspiral should take 60% of an orbit.
A task-based parallel elliptic solver for numerical relativity with discontinuous Galerkin methods
(2022)
Elliptic partial differential equations are ubiquitous in physics. In numerical relativity---the study of computational solutions to the Einstein field equations of general relativity---elliptic equations govern the initial data that seed every simulation of merging black holes and neutron stars. In the quest to produce detailed numerical simulations of these most cataclysmic astrophysical events in our Universe, numerical relativists resort to the vast computing power offered by current and future supercomputers. To leverage these computational resources, numerical codes for the time evolution of general-relativistic initial value problems are being developed with a renewed focus on parallelization and computational efficiency. Their capability to solve elliptic problems for accurate initial data must keep pace with the increasing detail of the simulations, but elliptic problems are traditionally hard to parallelize effectively.
In this thesis, I develop new numerical methods to solve elliptic partial differential equations on computing clusters, with a focus on initial data for orbiting black holes and neutron stars. I develop a discontinuous Galerkin scheme for a wide range of elliptic equations, and a stack of task-based parallel algorithms for their iterative solution. The resulting multigrid-Schwarz preconditioned Newton-Krylov elliptic solver proves capable of parallelizing over 200 million degrees of freedom to at least a few thousand cores, and already solves initial data for a black hole binary about ten times faster than the numerical relativity code SpEC. I also demonstrate the applicability of the new elliptic solver across physical disciplines, simulating the thermal noise in thin mirror coatings of interferometric gravitational-wave detectors to unprecedented accuracy. The elliptic solver is implemented in the new open-source SpECTRE numerical relativity code, and set up to support simulations of astrophysical scenarios for the emerging era of gravitational-wave and multimessenger astronomy.