Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published November 15, 2019 | Submitted + Published
Journal Article Open

Numerical binary black hole collisions in dynamical Chern-Simons gravity

Abstract

We produce the first numerical relativity binary black hole gravitational waveforms in a higher-curvature theory beyond general relativity. In particular, we study head-on collisions of binary black holes in order-reduced dynamical Chern-Simons gravity. This is a precursor to producing beyond-general-relativity waveforms for inspiraling binary black hole systems that are useful for gravitational wave detection. Head-on collisions are interesting in their own right, however, as they cleanly probe the quasinormal mode spectrum of the final black hole. We thus compute the leading-order dynamical Chern-Simons modifications to the complex frequencies of the postmerger gravitational radiation. We consider equal-mass systems, with equal spins oriented along the axis of collision, resulting in remnant black holes with spin. We find modifications to the complex frequencies of the quasinormal mode spectrum that behave as a power law with the spin of the remnant, and that are not degenerate with the frequencies associated with a Kerr black hole of any mass and spin. We discuss these results in the context of testing general relativity with gravitational wave observations.

Additional Information

© 2019 American Physical Society. Received 20 June 2019; published 13 November 2019. This work was supported in part by the Sherman Fairchild Foundation, and NSF Grants No. PHY-1708212 and No. PHY-1708213 at Caltech and No. PHY-1606654 at Cornell. Computations were performed using the Spectral Einstein Code [21]. All computations were performed on the Wheeler cluster at Caltech, which is supported by the Sherman Fairchild Foundation and by Caltech.

Attached Files

Published - PhysRevD.100.104026.pdf

Submitted - 1906.08789.pdf

Files

1906.08789.pdf
Files (2.5 MB)
Name Size Download all
md5:f823f0aa69a64554cbaa2538ab3cd74d
1.2 MB Preview Download
md5:c7ddd52e8513bcaba048e8f8b8eda84a
1.3 MB Preview Download

Additional details

Created:
August 19, 2023
Modified:
October 18, 2023