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PRECESSION: Dynamics of spinning black-hole binaries with python

dc.creatorGerosa, Davide
dc.creatorKesden, Michael
dc.date.accessioned2016-06-04
dc.date.accessioned2018-11-24T23:19:02Z
dc.date.available2016-07-05T12:04:32Z
dc.date.available2018-11-24T23:19:02Z
dc.date.issued2016-06-27
dc.identifierhttps://www.repository.cam.ac.uk/handle/1810/256617
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/123456789/3394
dc.description.abstractWe 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.
dc.languageen
dc.publisherAmerican Physical Society
dc.publisherPhysical Review D
dc.titlePRECESSION: Dynamics of spinning black-hole binaries with python
dc.typeArticle


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