SIMBAD references

2018MNRAS.478.1272H - Mon. Not. R. Astron. Soc., 478, 1272-1280 (2018/July-3)

The fidelity of Kepler eclipsing binary parameters inferred by the neural network.

HOLANDA N. and DA SILVA J.R.P.

Abstract (from CDS):

This work aims to test the fidelity and efficiency of obtaining automatic orbital elements of eclipsing binary systems, from light curves using neural network models. We selected a random sample with 78 systems, from over 1400 detached eclipsing binaries obtained from the Kepler Eclipsing Binaries Catalog, processed using the neural network approach. The orbital parameters of the sample systems were measured applying the traditional method of light-curve adjustment with uncertainties calculated by the bootstrap method, employing the JKTEBOP code. These estimated parameters were compared with those obtained by the neural network approach for the same systems. The results reveal a good agreement between techniques for the sum of the fractional radii and moderate agreement for e cosω and e sinω, but orbital inclination is clearly underestimated in neural network tests.

Abstract Copyright: © 2018 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society

Journal keyword(s): binaries: eclipsing - stars: fundamental parameters - stars: low-mass

Status in Simbad:  being processed

Simbad objects: 100

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2019.11.20-07:03:22

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