Ref: ASTROimport-954

Hipparcos Variable Star Detection and Classification Efficiency

Dubath, P. ; Lecoeur-Taïbi, I. ; Rimoldini, L. ; Süveges, M. ; Blomme, J. ; López, M. ; Sarro, L. M. ; De Ridder, J. ; Cuypers, J. ; Guy, L. ; Nienartowicz, K. ; Jan, A. ; Beck, M. ; Mowlavi, N. ; De Cat, P. ; Lebzelter, T. ; Eyer, L.

published in Astrostatistics and Data Mining, pp. 117 (2012)

Abstract: A complete periodic star extraction and classification scheme is set up and tested with the Hipparcos catalog. The efficiency of each step is derived by comparing the results with prior knowledge coming from the catalog or from the literature. A combination of two variability criteria is applied in the first step to select 17,006 variability candidates from a complete sample of 115,152 stars. Our candidate sample turns out to include 10,406 known variables (i.e., 90% of the total of 11,597) and 6,600 contaminating constant stars. A random forest classification is used in the second step to extract 1,881 (82%) of the known periodic objects while removing entirely constant stars from the sample and limiting the contamination of nonperiodic variables to 152 stars (7.5%). The confusion introduced by these 152 nonperiodic variables is evaluated in the third step using the results of the Hipparcos periodic star classification presented in a previous study [Dubath et al. (Mon Not R Astron Soc May:651, 2011)].

DOI: 10.1007/978-1-4614-3323-1_11
Links: link

The record appears in these collections:
Royal Observatory of Belgium > Astronomy & Astrophysics
Science Articles > Non-refereed Articles

 Record created 2016-07-01, last modified 2016-07-01