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sfit_minimizer

sfit_minimizer is a gradient-type minimization algorithm known to work particularly well for point lens microlensing light curves. This algorithm generalizes Simpson's idea that a 1-D function is well described by it first derivative (which can easily be solved exactly) to several dimensions, i.e., the function is well described by a tangent plane.

Detailed documentation: https://jenniferyee.github.io/sfit_minimizer/

Latest release: 1.0.2

Acknowledgements

If you are using sfit_minimizer for scientific research: please cite Yee & Gould 2025

Examples

Please see the "examples" folder.

How to install?

Clone this repository.

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Minimization routine based on the algorithm A. Gould wrote in Fortran for minimizing chi2.

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