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TomWagg/README.md

Hello there!

I'm Tom Wagg, an astrophysics PhD student at the University of Washington. I love all sorts of astrophysics, particularly anything involving binaries and massive stars, and I'm very enthusiastic to share all of the code I use in my research on GitHub!

I'm currently working on creating self-consistent population synthesis and galactic dynamics simulations (with cogsworth!) to use for better constraining binary stellar evolution with positions and kinematics. I'm broadly interested in massive stars though and have previously worked on asteroseismology, stellar flares and galactic gravitational wave sources (with LISA). In the past I've also explored taken a foray into making predictions for NEO follow-up during LSST and constraining the planetary radius valley.

I've contributed to several astrophysics codes. I've released a python package called LEGWORK with Katie Breivik to make everyone's life easier when working with stellar-origin binaries in LISA and doing the legwork for you. I also use and enjoy helping with the development of the rapid binary population synthesis codes COSMIC and COMPAS, as well as the Gala galactic dynamics code.

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  1. cogsworth cogsworth Public

    A Python package for performing self-consistent population synthesis and galactic dynamics simulations

    Python 16 3

  2. TeamLEGWORK/LEGWORK TeamLEGWORK/LEGWORK Public

    Package for making predictions about stellar-origin sources in space-based gravitational wave detectors

    Python 43 9

  3. software-citation-station software-citation-station Public

    A website for making citing software used in your research quick and easy

    TeX 24 2

  4. COSMIC-PopSynth/COSMIC COSMIC-PopSynth/COSMIC Public

    COSMIC (Compact Object Synthesis and Monte Carlo Investigation Code)

    Fortran 48 59

  5. TeamCOMPAS/COMPAS TeamCOMPAS/COMPAS Public

    COMPAS rapid binary population synthesis code

    Jupyter Notebook 64 66

  6. detecting-DCOs-in-LISA detecting-DCOs-in-LISA Public

    Predictions for LISA detectable BH and NS binaries - Wagg et al. (2022)

    Jupyter Notebook 6 1