Metadata-Version: 1.1
Name: precession
Version: 1.0.3
Summary: Dynamics of precessing black-hole binaries
Home-page: https://github.com/dgerosa/precession/
Author: Davide Gerosa
Author-email: d.gerosa@damtp.cam.ac.uk
License: CC by 4.0
Description: precession
        ==========
        
        **Author** Davide Gerosa
        
        **email** dgerosa@caltech.edu
        
        **Copyright** Copyright (C) 2016 Davide Gerosa
        
        **Licence** CC BY 4.0
        
        **Version** 1.0.3
        
        DYNAMICS OF SPINNING BLACK-HOLE BINARIES WITH PYTHON
        ====================================================
        
        ``precession`` is an 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 formulae 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.
        
        This code is released to the community under the `Creative Commons
        Attribution International
        license <http://creativecommons.org/licenses/by/4.0>`__. 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.*
           D. Gerosa, M. Kesden. PRD 93 (2016)
           `124066 <http://journals.aps.org/prd/abstract/10.1103/PhysRevD.93.124066>`__.
           `arXiv:1605.01067 <https://arxiv.org/abs/1605.01067>`__
        
        ``precession`` is an open-source code distributed under git
        version-control system on
        
        -  `github.com/dgerosa/precession <https://github.com/dgerosa/precession>`__
        
        API documentation can be generated automatically in html format from the
        code docstrings using ``pdoc``, and is uplodad to a dedicated branch of
        the git repository
        
        -  `dgerosa.github.io/precession <https://dgerosa.github.io/precession>`__
        
        Further information and scientific results are available at:
        
        -  `www.tapir.caltech.edu/~dgerosa/precession <http://www.tapir.caltech.edu/~dgerosa/precession>`__
        -  `www.davidegerosa.com/precession <http://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 <https://pypi.python.org/pypi/precession>`__:
        
        ::
        
            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``. A detailed description of the functionalies of the
        code is provided in the scientific paper
        `arXiv:1605.01067 <https://arxiv.org/abs/1605.01067>`__, where examples
        are also presented.
        
        RESULTS
        -------
        
        ``precession`` has been used in the following published papers:
        
        -  Gerosa and Sesana. MNRAS 446 (2015) 38-55.
           `arXiv:1405.2072 <https://arxiv.org/abs/1405.2072>`__
        -  Kesden et al. PRL 114 (2015) 081103.
           `arXiv:1411.0674 <https://arxiv.org/abs/1411.0674>`__
        -  Gerosa et al. MNRAS 451 (2015) 3941-3954.
           `arXiv:1503.06807 <https://arxiv.org/abs/1503.06807>`__
        -  Gerosa et al. PRD 92 (2015) 064016.
           `arXiv:1506.03492 <https://arxiv.org/abs/1506.03492>`__
        -  Gerosa et al. PRL 115 (2015) 141102.
           `arXiv:1506.09116 <https://arxiv.org/abs/1506.09116>`__
        -  Trifiro' et al. PRD 93 (2016) 044071.
           `arXiv:1507.05587 <https://arxiv.org/abs/1507.05587>`__
        -  Gerosa and Kesden. PRD 93 (2016) 124066.
           `arXiv:1605.01067 <https://arxiv.org/abs/1605.01067>`__
        -  Gerosa and Moore. PRL 117 (2016) 011101.
           `arXiv:1606.04226 <https://arxiv.org/abs/1606.04226>`__
        -  Rodriguez et al. APJL 832 (2016) L2
           `arXiv:1609.05916 <https://arxiv.org/abs/1609.05916>`__
        -  Gerosa et al. CQG 34 (2017) 6, 064004
           `arXiv:1612.05263 <https://arxiv.org/abs/1612.05263>`__
        -  Gerosa and Berti. PRD 95 (2017) 124046.
           `arXiv:1703.06223 <https://arxiv.org/abs/1703.06223>`__
        -  Zhao et al. PRD 96 (2017) 024007.
           `arXiv:1705.02369 <https://arxiv.org/abs/1705.02369>`__
        -  Wysocki et al. PRD 97 (2018) 043014
           `arXiv:1709.01943 <https://arxiv.org/abs/1709.01943>`__
        -  Gerosa J.Phys.Conf.Ser. 957 (2018) 012014.
           `arXiv:1711.1003 <https://arxiv.org/abs/1711.1003>`__
        -  Rodriguez et al. PRL 120 (2018) 151101.
           `arXiv:1712.0493 <https://arxiv.org/abs/1712.0493>`__
        -  Gerosa et al. PRD 97 (2018) 104049.
           `arXiv:1802.04276 <https://arxiv.org/abs/1802.04276>`__
        -  Gerosa et al. PRD 98 (2018) 084036.
           `arXiv:1808.02491 <https://arxiv.org/abs/1808.02491>`__
        -  Varma et al. `arXiv:1809.09125 <https://arxiv.org/abs/1809.09125>`__
        -  Tso et al. `arXiv:1807.00075 <https://arxiv.org/abs/1807.00075>`__
        
        RELEASES
        --------
        
        |DOI|
        
        *v1.0.0* Stable version released together with the first arxiv
        submission of `arXiv:1605.01067 <https://arxiv.org/abs/1605.01067>`__.
        
        *v1.0.2* Clarifications on typos in Eq. (36) and (37) of
        `arXiv:1605.01067 <https://arxiv.org/abs/1605.01067>`__. See
        help(precession) for more information.
        
        *v1.0.3* Python 3 now supported (hurray!). By default, ``finalspin`` now
        returns more updated result by Hofmann, Barausse and Rezzolla 2016.
        
        CREDITS
        -------
        
        The code is developed and maintained by `Davide
        Gerosa <www.davidegerosa.com>`__. Please, report bugs to
        
        ::
        
            dgerosa@caltech.edu
        
        I am happy to help you out!
        
        **Thanks**: M. Kesden, U. Sperhake, E. Berti, R. O'Shaughnessy, A.
        Sesana, D. Trifiro', A. Klein, J. Vosmera and X. Zhao.
        
        .. |DOI| image:: https://zenodo.org/badge/46057982.svg
           :target: https://zenodo.org/badge/latestdoi/46057982
        
Keywords: black hole spin inspiral precession post-Newtonian
Platform: UNKNOWN
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Software Development :: Libraries :: Python Modules
