MOSFiT: Modular Open-Source Fitter for Transients

TL;DR

MOSFiT is an open-source Python tool that automates fitting models to transient astronomical data, facilitating rapid, reproducible analysis and bridging the gap between observations and theoretical models in time-domain astronomy.

Contribution

It introduces MOSFiT, a modular, open-source software that streamlines the process of fitting models to transient data and enhances reproducibility and community sharing in time-domain astronomy.

Findings

Automates light curve fitting with Monte Carlo ensembles.

Provides statistically robust predictions for transient properties.

Enables integration with online transient catalogs for community access.

Abstract

Much of the progress made in time-domain astronomy is accomplished by relating observational multi-wavelength time series data to models derived from our understanding of physical laws. This goal is typically accomplished by dividing the task in two: collecting data (observing), and constructing models to represent that data (theorizing). Owing to the natural tendency for specialization, a disconnect can develop between the best available theories and the best available data, potentially delaying advances in our understanding new classes of transients. We introduce MOSFiT: the Modular Open-Source Fitter for Transients, a Python-based package that downloads transient datasets from open online catalogs (e.g., the Open Supernova Catalog), generates Monte Carlo ensembles of semi-analytical light curve fits to those datasets and their associated Bayesian parameter posteriors, and optionally delivers the fitting results back to those same catalogs to make them available to the rest of the community. MOSFiT is designed to help bridge the gap between observations and theory in time-domain astronomy; in addition to making the application of existing models and creation of new models as simple as possible, MOSFiT yields statistically robust predictions for transient characteristics, with a standard output format that includes all the setup information necessary to reproduce a given result. As large-scale surveys such as LSST discover entirely new classes of transients, tools such as MOSFiT will be critical for enabling rapid comparison of models against data in statistically consistent, reproducible, and scientifically beneficial ways.