Initial data for high-compactness black hole–neutron star binaries
Abstract
For highly compact neutron stars, constructing numerical initial data for black hole–neutron star binary evolutions is very difficult. We describe improvements to an earlier method that enable it to handle these more challenging cases. These improvements were found by invoking a general relaxation principle that may be helpful in improving robustness in other initial data solvers. We examine the case of a 6:1 mass ratio system in inspiral close to merger, where the star is governed by a polytropic Γ =2, an SLy, or an LS220 equation of state (EOS). In particular, we are able to obtain a solution with a realistic LS220 EOS for a star with compactness 0.26 and mass 1.98 M_⊙, which is representative of the highest reliably determined neutron star masses. For the SLy EOS, we can obtain solutions with a comparable compactness of 0.25, while for a family of polytropic equations of state, we obtain solutions with compactness up to 0.21, the largest compactness that is stable in this family. These compactness values are significantly higher than any previously published results.
Additional Information
© 2016 IOP Publishing Ltd. Received 22 January 2016. Accepted for publication 26 February 2016. Published 19 April 2016. K H would like to thank Geoffrey Lovelace, Curran Muhlberger, Harald Pfeiffer, and David Chernoff for useful discussions, and Andy Bohn for the use of computing resources. This work was supported in part by NSF Grants PHY-1306125 and AST-1333129 at Cornell University, and by a grant from the Sherman Fairchild Foundation. F F gratefully acknowledges support from the Vincent and Beatrice Tremaine Postdoctoral Fellowship and NSERC Canada. Support for this work was provided by NASA through Einstein Postdoctoral Fellowship grant number PF4-150122 awarded by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for NASA under contract NAS8-03060. This research was performed in part using the Zwicky computer system operated by the Caltech Center for Advanced Computing Research and funded by NSF MRI No. PHY-0960291 and the Sherman Fairchild Foundation.Attached Files
Submitted - 1409.7159
Files
Name | Size | Download all |
---|---|---|
md5:7b0f252598923b8a672eef36a7d5c6f1
|
216.1 kB | Download |
Additional details
- Eprint ID
- 86815
- DOI
- 10.1088/0264-9381/33/10/105009
- Resolver ID
- CaltechAUTHORS:20180605-163331410
- PHY-1306125
- NSF
- AST-1333129
- NSF
- Sherman Fairchild Foundation
- Vincent and Beatrice Tremaine Postdoctoral Fellowship
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- PF4-150122
- NASA Einstein Fellowship
- NAS8-03060
- NASA
- PHY-0960291
- NSF
- Created
-
2018-06-06Created from EPrint's datestamp field
- Updated
-
2022-07-12Created from EPrint's last_modified field