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README.md

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[**Detailed documentation: https://rpoleski.github.io/MulensModel/**](https://rpoleski.github.io/MulensModel/)
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[Latest release: 2.22.0](https://github.com/rpoleski/MulensModel/releases/latest) and we're working on further developing the code.
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[Latest release: 2.23.0](https://github.com/rpoleski/MulensModel/releases/latest) and we're working on further developing the code.
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MulensModel can generate a microlensing light curve for a given set of microlensing parameters, fit that light curve to some data, and return a chi2 value. That chi2 (and its gradient in some cases) can then be input into an arbitrary likelihood function to find the best-fit parameters.
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Currently, MulensModel supports:
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* Lens Systems: point lens or binary lens. Shear and convergence allowed for both point and binary lenses.
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* Source Stars: single source or binary source.
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* Effects: finite source (1-parameter), parallax (satellite & annual), binary lens orbital motion, **xallarap effect (new)**, different parametrizations of microlensing models.
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* Effects: finite source (1-parameter), parallax (satellite & annual), binary lens orbital motion, xallarap effect (**new - with both sources luminous**), different parametrizations of microlensing models.
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Need more? Open [an issue](https://github.com/rpoleski/MulensModel/issues), start [a discussion](https://github.com/rpoleski/MulensModel/discussions), or send us an e-mail.
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![PyPI - Downloads](https://img.shields.io/pypi/dm/MulensModel)
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![example workflow](https://github.com/rpoleski/MulensModel/actions/workflows/python-app.yml/badge.svg)
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file revised Apr 2024
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file revised May 2024

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