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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 WFIRST.

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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 χ

^{2} 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 calculate
models in response to the

WFIRST Data
Analysis Challenges.

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MulensModel Microlensing Model Fitter

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