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Published May 21, 2015 | Submitted
Journal Article Open

Improved methods for simulating nearly extremal binary black holes

Abstract

Astrophysical black holes could be nearly extremal (that is, rotating nearly as fast as possible); therefore, nearly extremal black holes could be among the binaries that current and future gravitational-wave observatories will detect. Predicting the gravitational waves emitted by merging black holes requires numerical-relativity simulations, but these simulations are especially challenging when one or both holes have mass m and spin S exceeding the Bowen–York limit of S/m^2 = 0.93. We present improved methods that enable us to simulate merging, nearly extremal black holes (i.e., black holes with S/m^2 > 0.93) more robustly and more efficiently. We use these methods to simulate an unequal-mass, precessing binary black hole (BBH) coalescence, where the larger black hole has S/m^2 = 0.99. We also use these methods to simulate a non-precessing BBH coalescence, where both black holes have S/m^2 = 0.994, nearly reaching the Novikov–Thorne upper bound for holes spun up by thin accretion disks. We demonstrate numerical convergence and estimate the numerical errors of the waveforms; we compare numerical waveforms from our simulations with post-Newtonian and effective-one-body waveforms; we compare the evolution of the black hole masses and spins with analytic predictions; and we explore the effect of increasing spin magnitude on the orbital dynamics (the so-called 'orbital hangup' effect).

Additional Information

© 2015 IOP Publishing Ltd. Received 4 December 2014; revised 23 February 2015; Accepted for publication 25 March 2015; Published 28 April 2015. We are grateful to Eric Poisson, Nicolas Yunes, and Katerina Chatziioannou for detailed discussions about perturbative expressions for tidal torquing and about the problems inherent in comparing numerical and post-Newtonian expressions for near-field quantities. We thank Alessandra Buonanno and Sebastiano Bernuzzi for helpful discussions. Simulations used in this work were computed with SpEC [47]. This work was supported in part by the Sherman Fairchild Foundation; NSF grants PHY-1440083 and AST-1333520 at Caltech, NSF grants PHY-1306125 and AST-1333129 at Cornell, and NSF grant PHY-1307489 at California State University Fullerton; a 2013–2014 California State University Fullerton Junior Faculty Research Grant. Computations were performed on the Zwicky cluster at Caltech, which is supported by the Sherman Fairchild Foundation and by NSF award PHY-0960291; on the NSF XSEDE network under grant TG-PHY990007N; on the Orca cluster supported by NSF award NSF-1429873, the Research Corporation for Science Advancement, and by California State University Fullerton; and on the GPC supercomputer at the SciNet HPC Consortium [105]. SciNet is funded by: the Canada Foundation for Innovation under the auspices of Compute Canada; the Government of Ontario; Ontario Research Fund–Research Excellence; and the University of Toronto.

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