precession 0.0.0.50

Dynamics of precessing black-hole binaries

precession

Author Davide Gerosa

email [e-mail]

Copyright Copyright (C) 2016 Davide Gerosa

Licence CC BY 4.0

Version 0.0.0.49

DYNAMICS OF SPINNING BLACK-HOLE BINARIES WITH PYTHON

precession is an open-source Python module to study the post-Newtonian dynamics of precessing black-hole binaries. The code provides a self-consistent framework to (i) study the evolution of the black-hole spins along their precession cycles, (ii) perform gravitational-wave driven binary inspirals using both standard integrations and innovative multi-timescale methods, and (iii) predict the properties of the black-hole remnant using fitting formulae to numerical relativity simulations. Flexibility, ease-of-use and numerical efficiency make precession the ideal tool to insert black-hole spin dynamics in larger-scale numerical studies such as gravitational-wave parameter-estimation codes, populations 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 promising tool to compute post-Newtonian injections to numerical relativity simulations targeting the spin precession dynamics.

This code is released to the community under the Creative Commons Attribution International license. Essentially, you may use precession as you like but must make reference to our work. When using precession in any published work, please cite the paper describing its implementation:

• Precession. Dynamics of spinning black-hole binaries with Python. Davide Gerosa. Submitted to… arXiv:…

precession is an open-source code distributed under git version-control system on

• github.com/dgerosa/precession

API documentation can be generated automatically in html format from the code docstrings using pdoc, and is is uplodad to a dedicated branch of the git repository

• dgerosa.github.io/precession

Further information and scientific results on the results are available at:

• www.damtp.cam.ac.uk/user/dg438/precession

• www.davidegerosa.com/precession

INSTALLATION

precession works in python 2.x and has been tested on 2.7.10. It can be installed through pip:

pip install precession

Prerequisites are numpy, scipy and parmap, which can be all installed through pip. Information on all code functions are available through Pyhton’s built-in help system

import precession
help(precession.function)

Several tests and tutorial are available in the submodule precession.test.

CREDITS

The code is developed and maintained by Davide Gerosa. Please, report bugs to

[e-mail]

I’m happy to help you out!

Thanks: E. Berti, M. Kesden, U. Sperhake, R. O’Shaughnessy, D. Trifiro’, A. Klein, J. Vosmera and X. Zhao.