2015
Ref: ASTROimport-858

The variability analysis of the Gaia data

Eyer, L. ; Evans, D. W. ; Mowlavi, N. ; Lanzafame, A. ; Cuypers, J. ; De Ridder, J. ; Sarro, L. ; Clementini, G. ; Guy, L. ; Holl, B. ; Ordonez, D. ; Nienartowicz, K. ; Lecoeur-Taïbi, I. ; Charnas, J. ; Jévardat de Fombelle, G. ; Rimoldini, L. ; Süveges, M.


published in IAU General Assembly, 22, pp. 2257301 (2015)

Abstract: The ESA Gaia spacecraft acts as a unique and exceptional time-domain survey for more than one billion sources. Most known variability phenomena in the Universe will be detected by Gaia. Although the Gaia sampling is quite sparse, i.e. a source will be observed on average 70 times over Gaia’s 5 year mission, the detection performance for periodic signals will be high, due to the irregular sampling.The scientific return for variable phenomena will be enormous. This is mainly due to Gaia's combined measurements of the white light G magnitude time series, together with astrometry, spectro-photometry in the blue and red, and spectroscopy (the latter for sources brighter than magnitude 16).We present the organisation and general overview of the variability processing and analysis within the Gaia Data Processing and Analysis Consortium (DPAC), whose goal is to systematically detect variability, classify the variable objects, derive characteristic parameters for specific variability classes, and give global descriptions of variable phenomena.At the beginning of 2015, the variability processing of the 28-day Ecliptic Pole Scanning Law data was performed on nearly 789,000 sources. We will present some results and highlights of this data set. The results comprise various global statistics describing the variability, examples of processing, sets of light curves, and a comparison with the validation data set obtained from cross-matches with known variables in the literature (e.g. OGLE survey).

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