Rapid analysis of binary lens gravitational microlensing light curves

Details Rapid analysis of binary lens gravitational microlensing light curves Rapid analysis of binary lens gravitational microlensing light curves

Sep 2003

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003mnras.344..651v&link_type=abstract

Monthly Notice of the Royal Astronomical Society, Volume 344, Issue 2, pp. 651-656.

Astronomy and Astrophysics

Astronomy

Gravitational Lensing, Binaries: General

Scientific paper

A new algorithm for the autonomous fitting of light curves of gravitational microlensing by binary lenses is presented here. The algorithm relies on the combination of artificial neural networks with a conventional amoeba (downhill simplex) method to achieve a success rate of 68 per cent using strict success criteria, in an average fitting time of 48 s per light curve when applied to 400 simulated light curves. The current algorithm fits a simple seven-parameter model to generated test curves and requires complete light curves to function, but serves as proof of concept for future work.

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