Improvements to the construction of binary black hole initial data
Abstract
Construction of binary black hole initial data is a prerequisite for numerical evolutions of binary black holes. This paper reports improvements to the binary black hole initial data solver in the spectral Einstein code, to allow robust construction of initial data for mass-ratio above 10:1, and for dimensionless black hole spins above 0.9, while improving efficiency for lower mass-ratios and spins. We implement a more flexible domain decomposition, adaptive mesh refinement and an updated method for choosing free parameters. We also introduce a new method to control and eliminate residual linear momentum in initial data for precessing systems, and demonstrate that it eliminates gravitational mode mixing during the evolution. Finally, the new code is applied to construct initial data for hyperbolic scattering and for binaries with very small separation.
Additional Information
© 2015 IOP Publishing Ltd. Received 4 June 2015, revised 12 October 2015. Accepted for publication 27 October 2015. Published 3 December 2015. We thank Geoffrey Lovelace, Larry Kidder and Mark Scheel for helpful discussions. Calculations were performed with the SpEC-code [31]. We gratefully acknowledge support from NSERC of Canada, from the Canada Research Chairs Program, and from the Canadian Institute for Advanced Research. FF gratefully acknowledges support from the Vincent and Beatrice Tremaine Postdoctoral fellowship at CITA. Support for this work was provided by NASA through Einstein Postdoctoral Fellowship grant numbered PF4-150122. We further gratefully acknowledge support from the Sherman Fairchild Foundation; from NSF Grants PHY-1306125 and AST-1333129 at Cornell; and from NSF Grants No. PHY-1440083 and AST-1333520 at Caltech. Calculations were performed at the Gravity cluster and the GPC supercomputer at the SciNet HPC Consortium [71]; SciNet is funded by: the Canada Foundation for Innovation (CFI) under the auspices of Compute Canada; the Government of Ontario; Ontario Research Fund (ORF)—Research Excellence; and the University of Toronto. Further calculations were performed on the Briarée cluster from Sherbrooke University, managed by Calcul Québec and Compute Canada. The operation of this supercomputer is funded by the Canada Foundation for Innovation (CFI), Ministère de l'Économie, de l'Innovation et des Exportations du Québec (MEIE), RMGA and the Fonds de recherche du Québec—Nature et Technologies (FRQ-NT).Attached Files
Submitted - 1506.01689v1.pdf
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Additional details
- Eprint ID
- 63448
- DOI
- 10.1088/0264-9381/32/24/245010
- Resolver ID
- CaltechAUTHORS:20160107-105510379
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- Canada Research Chairs program
- Canadian Institute for Advanced Research (CIAR)
- PF4-150122
- NASA Einstein Postdoctoral Fellowship
- Sherman Fairchild Foundation
- PHY-1306125
- NSF
- AST-1333129
- NSF
- PHY-1440083
- NSF
- AST-1333520
- NSF
- Canada Foundation for Innovation (CFI)
- Government of Ontario
- Ontario Research Fund-Research Excellence
- Compute Canada
- University of Toronto
- Ministére de l'Économie, de l'Innovation et des Exportations du Quebec (MEIE)
- RMGA
- Fonds de recherche du Québe-Nature et technologies (FRQ-NT)
- Created
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2016-01-07Created from EPrint's datestamp field
- Updated
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2022-07-12Created from EPrint's last_modified field