4 research outputs found
A Method For Eclipsing Component Identification In Large Photometric Datasets
We describe an automated method for assigning the most likely physical
parameters to the components of an eclipsing binary (EB), using only its
photometric light curve and combined color. In traditional methods (e.g. WD and
EBOP) one attempts to optimize a multi-parameter model over many iterations, so
as to minimize the chi-squared value. We suggest an alternative method, where
one selects pairs of coeval stars from a set of theoretical stellar models, and
compares their simulated light curves and combined colors with the
observations. This approach greatly reduces the EB parameter-space over which
one needs to search, and allows one to determine the components' masses, radii
and absolute magnitudes, without spectroscopic data. We have implemented this
method in an automated program using published theoretical isochrones and
limb-darkening coefficients. Since it is easy to automate, this method lends
itself to systematic analyses of datasets consisting of photometric time series
of large numbers of stars, such as those produced by OGLE, MACHO, TrES, HAT,
and many others surveys.Comment: 6 pages, 5 figures. To appear in the conference proceedings of "Close
Binaries in the 21st Century: New Opportunities and Challenges", Syros,
Greece, 27-30 June, 200