A Caltech Library Service

Surrogate models for precessing binary black hole simulations with unequal masses

Varma, Vijay and Field, Scott E. and Scheel, Mark A. and Blackman, Jonathan and Gerosa, Davide and Stein, Leo C. and Kidder, Lawrence E. and Pfeiffer, Harald P. (2019) Surrogate models for precessing binary black hole simulations with unequal masses. Physical Review Research, 1 (3). Art. No. 033015. ISSN 2643-1564.

[img] PDF - Published Version
See Usage Policy.

[img] PDF - Submitted Version
See Usage Policy.


Use this Persistent URL to link to this item:


Only numerical relativity simulations can capture the full complexities of binary black hole mergers. These simulations, however, are prohibitively expensive for direct data analysis applications such as parameter estimation. We present two fast and accurate surrogate models for the outputs of these simulations: the first model, NRSur7dq4, predicts the gravitational waveform and the second model, NRSur7dq4Remnant, predicts the properties of the remnant black hole. These models extend previous seven-dimensional, noneccentric precessing models to higher mass ratios and have been trained against 1528 simulations with mass ratios q≤4 and spin magnitudes χ_1,χ_2≤0.8, with generic spin directions. The waveform model, NRSur7dq4, which begins about 20 orbits before merger, includes all ℓ≤4 spin-weighted spherical harmonic modes, as well as the precession frame dynamics and spin evolution of the black holes. The final black hole model, NRSur7dq4Remnant, models the mass, spin, and recoil kick velocity of the remnant black hole. In their training parameter range, both models are shown to be more accurate than existing models by at least an order of magnitude, with errors comparable to the estimated errors in the numerical relativity simulations. We also show that the surrogate models work well even when extrapolated outside their training parameter space range, up to mass ratios q=6.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Varma, Vijay0000-0002-9994-1761
Blackman, Jonathan0000-0002-7113-0289
Gerosa, Davide0000-0002-0933-3579
Stein, Leo C.0000-0001-7559-9597
Kidder, Lawrence E.0000-0001-5392-7342
Pfeiffer, Harald P.0000-0001-9288-519X
Additional Information:© 2019 Published by the American Physical Society. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Received 25 July 2019; published 10 October 2019. We thank Dan Hemberger, Kevin Barkett, Marissa Walker, Matt Giesler, Nils Deppe, Francois Hebert, Maria Okounkova, and Geoffrey Lovelace for helping carry out the new SpEC simulations used in this work. V.V. and M.S. are supported by the Sherman Fairchild Foundation and NSF Grants No. PHY–170212 and No. PHY–1708213 at Caltech. L.E.K. acknowledges support from the Sherman Fairchild Foundation and NSF Grant No. PHY-1606654 at Cornell. S.E.F is partially supported by NSF Grant No. PHY-1806665. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant No. ACI-1548562. This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (Awards No. OCI-0725070 and No. ACI-1238993) and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications. Simulations were performed on NSF/NCSA Blue Waters under allocation NSF PRAC–1713694; on the Wheeler cluster at Caltech, which is supported by the Sherman Fairchild Foundation and by Caltech; and on XSEDE resources Bridges at the Pittsburgh Supercomputing Center, Comet at the San Diego Supercomputer Center, and Stampede and Stampede2 at the Texas Advanced Computing Center, through Allocation No. TGPHY990007N. Computations for building the model were performed on Wheeler.
Funding AgencyGrant Number
Sherman Fairchild FoundationUNSPECIFIED
State of IllinoisUNSPECIFIED
Issue or Number:3
Record Number:CaltechAUTHORS:20191010-090915013
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:99207
Deposited By: Tony Diaz
Deposited On:10 Oct 2019 16:26
Last Modified:09 Mar 2020 13:18

Repository Staff Only: item control page