Summary

A new software package called MulensModel has been developed to calculate and fit gravitational microlensing light curves. The package provides a framework for calculating microlensing model magnification curves and goodness-of-fit statistics for microlensing events with single and binary lenses as well as a variety of higher-order effects: extended sources with limb-darkening, annual microlensing parallax, and satellite microlensing parallax. The software is easily adaptable to analyze the planned microlensing survey with the Roman Space Telescope.

Generating the Microlensing Models and Comparing to Photometric Data

MulensModel produces light curves and compares them to models. It uses three Python types: Model, Mulensdata and Event. A set of parameters stored in the ModelParameters class specifies Model. The photometric dataset (epochs, photometric measurements and their uncertainties) are stored in MulensData. Finally, the Event class combines the Mulensdata with an instance of Model. The main method used is to calculate the χ² statistic. The magnification is calculated and the flux from surrounding stars in a crowded region is taken into account. The annual microlensing parallax and the satellite microlensing parallax may be taken into account here as well. The lenses can be single lenses or binary lenses. In the future, the MulensModel can be used to fit simulated Roman Space Telescope light curves, like the ones in WFIRST Data Analysis Challenge.

MulensModel Microlensing Model Fitter

MulensModel is available at https://github.com/rpolenski/MulensModel/ and it is described in model details in Poleski & Yee (2018).