precession: Dynamics of spinning black-hole binaries with python
Physical Review D
American Physical Society (APS)
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Gerosa, D., & Kesden, M. (2016). precession: Dynamics of spinning black-hole binaries with python. Physical Review D, 93 (124066) https://doi.org/10.1103/physrevd.93.124066
This is the author accepted manuscript. The final version is available from the American Physical Society via http://dx.doi.org/10.1103/PhysRevD.93.124066
We present the numerical code precession, a new open-source python module to study the dynamics of precessing black-hole binaries in the post-Newtonian regime. The code provides a comprehensive toolbox to (i) study the evolution of the black-hole spins along their precession cycles, (ii) perform gravitational-wave-driven binary inspirals using both orbit-averaged and precession-averaged integrations, and (iii) predict the properties of the merger remnant through fitting formulas obtained from numerical-relativity simulations. precession is a ready-to-use tool to add the black-hole spin dynamics to larger-scale numerical studies such as gravitational-wave parameter estimation codes, population synthesis models to predict gravitational-wave event rates, galaxy merger trees and cosmological simulations of structure formation. precession provides fast and reliable integration methods to propagate statistical samples of black-hole binaries from/to large separations where they form to/from small separations where they become detectable, thus linking gravitational-wave observations of spinning black-hole binaries to their astrophysical formation history. The code is also a useful tool to compute initial parameters for numerical-relativity simulations targeting specific precessing systems. precession can be installed from the python Package Index, and it is freely distributed under version control on github, where further documentation is provided.
D. G. is supported by the UK STFC and the Isaac Newton Studentship of the University of Cambridge. Partial support is also acknowledged from the Royal Astronomical Society, Darwin College of the University of Cambridge, the Cambridge Philosophical Society, the H2020 ERC Consolidator Grant No. MaGRaTh–646597, the H2020-MSCA-RISE-2015 Grant No. StronGrHEP-690904, the STFC Consolidator Grant No. ST/L000636/1, the SDSC Comet and TACC Stampede clusters through NSF-XSEDE Award No. PHY-090003, the Cambridge High Performance Computing Service Supercomputer Darwin using Strategic Research Infrastructure Funding from the HEFCE and the STFC, and DiRAC’s Cosmos Shared Memory system through BIS Grant No. ST/J005673/1 and STFC Grants No. ST/H008586/1 and No. ST/K00333X/1. M. K. is supported by Alfred P. Sloan Foundation Grant No. FG-2015-65299 and NSF Grant No. PHY-1607031.
External DOI: https://doi.org/10.1103/physrevd.93.124066
This record's URL: https://www.repository.cam.ac.uk/handle/1810/256617
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