The biggest software project I’ve been involved with is MOSFiT: the Modular Open Source Fitter for Transients. This code allows users to construct and fit semi-analytic light curve models to transient data, and is optimised for use with the Open Supernova Catalog

MOSFiT is available on Github, can easily be installed in Python using pip or conda, and is fully documented.

The paper describing the code is here, and the first results are presented in this paper.

Kilonova models

I recently developed the ‘bns’ model in MOSFiT to predict the observable kilonova signatures of neutron star mergers directly from the binary properties that can be measured in their gravitational wave signal.

I have produced an example population of UV-optical-NIR multicolour light curves for 555 models with different chirp masses, mass ratios, viewing angles, disk wind efficiencies and GRB shocks.

These models are available here, please feel free to use them and cite this paper!

Python scripts

My personal Github page also contains a few Python scripts that I’ve written and use a lot in my research. These are provided free for anyone who might find them useful!

  • Superbol: Construct a bolometric light curve from multicolour photometric time-series data
  • Photometry Sans Frustration (PSF): Carry out point-spread function fitting photometry using a quick and convenient wrapper for Iraf’s daophot
  • Simple scripts to reduce FITS images using astropy tasks

If you use Superbol, please cite Nicholl, M. 2018, RNAAS

Light curve of the GW170817 kilonova fit with the MOSFiT BNS model