gwBOB 1.0.1

A Backwards-One-Body Gravitational Waveform Package

gwBOB

The Backwards-One-Body Gravitational Waveform Package

Getting Started

Please see more detailed documentation here!\

What is the Backwards One Body Model?

The Backwards One Body (BOB) model is an analytical and physically motivated approach to modeling gravitational waveforms from black hole binary mergers, as described in arXiv:1810.00040. The BOB model is based on the physical insight that, during the late stages of binary evolution, the spacetime dynamics of the binary system closely resemble a linear perturbation of the final, stationary black hole remnant.

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Features

• Analytical accuracy: Closed form expressions for the amplitude and frequency evolution.
• Minimally Calibrated: Requires minimal calibration to numerical relativity (NR)
• Test all BOB flavors Easily generate and switch between different "flavors" of BOB depending on your research problem.
• Easy initialization Easy initialization using SXS, CCE, or raw NR data.
• Beyond Kerr waveforms Compare NR data to BOB waveforms generated with custom QNMs.
• Easy comparisons: Easy comparisons to waveforms from the public SXS and CCE catalog, as well as raw NR data.
• Well Documented and Actively Developed

Generate plots like these with just a few lines of code!

Requirements

• (Windows users should use WSL)
• kuibit
• sxs
• qnmfits
• scri
• jax (install the GPU compatible version if possible)
• sympy
• numpy
• scipy
• matplotlib

Install via pip

pip install gwBOB

Citing this Code

If you use this code please cite

@article{mcwilliams2019analytical,
  title={Analytical black-hole binary merger waveforms},
  author={McWilliams, Sean T},
  journal={Physical review letters},
  volume={122},
  number={19},
  pages={191102},
  year={2019},
  publisher={APS}
}

BOB paper to be added.

JOSS paper to be added.

Contributing

Contributions are always welcome! If you find an issue, or have any questions on how to use the code, please raise an issue on this repo. If you want to contribute directly to the code, please fork the code and create a pull request!