Metadata-Version: 2.1
Name: nrpypn
Version: 2.0.0
Summary: Validated Post-Newtonian Expressions for Numerical Relativity
Home-page: https://github.com/nrpy/nrpypn
Author: Zachariah Etienne
License: BSD-2-Clause
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: sympy
Requires-Dist: black
Requires-Dist: nrpy

# NRPyPN: Validated Post-Newtonian Expressions for Numerical Relativity

## Author
Zachariah B. Etienne (https://etienneresearch.com)

## Special Thanks
Special thanks to Peter Diener and Roland Haas for reviewing
NRPyPN in preparation for its inclusion into the Einstein
Toolkit. Also special thanks to Antoni Ramos-Buades for sharing
the Mathematica notebooks that the paper
"Simple procedures to reduce eccentricity of binary black hole simulations"
Phys. Rev. D 99, 023003 (2019)
used, so that expressions in NRPyPN could be validated.

## Purpose

NRPyPN primarily focuses on implementation and validation of
post-Newtonian expressions, with the immediate goal of generating
high-PN-order tangential and radial momenta for binary black hole
initial data with minimal eccentricity. These momenta can be
directly injected into e.g., TwoPunctures to set up quasicircular
binary black hole initial data.

NRPyPN bases its approach on
"Simple procedures to reduce eccentricity of binary black hole simulations",
Ramos-Buades, Husa, and Pratten,
https://arxiv.org/abs/1810.00036,
Phys. Rev. D 99, 023003 (2019)

and

"Post-Newtonian Quasicircular Initial Orbits for Numerical Relativity",
Healy, Lousto, Nakano, and Zlochower,
https://arxiv.org/abs/1702.00872,
Class. Quant. Grav. 34 (2017) 14, 145011 


## Installation instructions

Prerequisites:

* Python 3.6+
* pip, the Python package manager, which should come with Python.

Python packages:

* SymPy 1.2+
* NRPy+ 2.0+

### Quick install from the command line (bash shell)

* First set up a virtual environment:

python3 -m venv nrpyvirtualenv
source nrpyvirtualenv/bin/activate
pip install nrpypn

* Then run the script

python3 nrpypn.quasicirc

The help message provides all the instructions needed.

## License:
BSD 2-Clause

Copyright (c) 2023, Zachariah Etienne
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

* Redistributions of source code must retain the above copyright notice, this
  list of conditions and the following disclaimer.

* Redistributions in binary form must reproduce the above copyright notice,
  this list of conditions and the following disclaimer in the documentation
  and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.


## Required Citation

1) Bibtex entry:

@misc{NRPyPN,
 author       = {Etienne, Zachariah B.},
 title        = {NRPyPN: Validated Post-Newtonian Expressions for Binary Black Hole Initial Data},
 month        = sep,
 year         = 2023,
 url          = {https://github.com/nrpy/nrpypn/}
}

## Suggested Citation

1) Bibtex entry:

@article{Habib:2020dba,
    author = "Habib, Sarah and Ramos-Buades, Antoni and Huerta, E.A. and Husa, Sascha and Haas, Roland and Etienne, Zachariah",
    title = "{Initial Data and Eccentricity Reduction Toolkit for Binary Black Hole Numerical Relativity Waveforms}",
    eprint = "2011.08878",
    archivePrefix = "arXiv",
    primaryClass = "gr-qc",
    month = "11",
    year = "2020"
}
