THE BERLIN EXOPLANET SEARCH TELESCOPE II CATALOG OF VARIABLE STARS. II. CHARACTERIZATION OF THE CoRoT SRc02 FIELD

Klagyivik, P.; Csizmadia, Sz.; Pasternacki, T.; Cabrera, J.; Chini, R.; Eigmüller, Philipp; Erikson, A.; Fruth, T.; Kabáth, P.; Lemke, R.; Murphy, M.; Rauer, H.; Titz-Weider, R.

doi:10.3847/0004-6256/151/5/110

Cited by 6 publications

(5 citation statements)

References 31 publications

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“…step were included. We note that the typical precision of our light curves is comparable to that of recent studies for the search of exoplanets from space (Nascimbeni et al 2012) or from the ground (Klagyivik et al 2016).…”

Section: Light Curves Productionsupporting

confidence: 84%

TheGaiaspectrophotometric standard stars survey – III. Short-term variability monitoring

Marinoni¹,

Pancino²,

Altavilla³

et al. 2016

Mon. Not. R. Astron. Soc.

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We present the results of the short-term constancy monitoring of candidate Gaia Spectrophotometric Standard Stars (SPSS). We obtained time series of typically 1.24 hour -with sampling periods from 1-3 min to a few hours, depending on the case -to monitor the constancy of our candidate SPSS down to 10 mmag, as required for the calibration of Gaia photometric data. We monitored 162 out of a total of 212 SPSS candidates. The observing campaign started in 2006 and finished in 2015, using 143 observing nights on nine different instruments covering both hemispheres. Using differential photometry techniques, we built light curves with a typical precision of 4 mmag, depending on the data quality. As a result of our constancy assessment, 150 SPSS candidates were validated against short term variability, and only 12 were rejected because of variability including some widely used flux standards such as BD+174708, SA 105-448, 1740346, and HD 37725.

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Section: Light Curves Productionsupporting

confidence: 84%

TheGaiaspectrophotometric standard stars survey – III. Short-term variability monitoring

Marinoni¹,

Pancino²,

Altavilla³

et al. 2016

Mon. Not. R. Astron. Soc.

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“…The need for visual inspection of candidate variables is common for all types of variability search (e.g. Bernard et al 2010;Cusano et al 2013;Abbas et al 2014;Ramsay et al 2014;Klagyivik et al 2016;Pawlak et al 2016). The underlying problem is that corrupted measurements cannot be reliably identified in all cases.…”

Section: Discussionmentioning

confidence: 99%

Variability search in M 31 using principal component analysis and the Hubble Source Catalogue

Moretti

Hatzidimitriou

Karampelas

et al. 2018

Monthly Notices of the Royal Astronomical Society

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Principal Component Analysis (PCA) is being extensively used in Astronomy but not yet exhaustively exploited for variability search. The aim of this work is to investigate the effectiveness of using the PCA as a method to search for variable stars in large photometric data sets. We apply PCA to variability indices computed for light curves of 18152 stars in three fields in M 31 extracted from the Hubble Source Catalogue. The projection of the data into the principal components is used as a stellar variability detection and classification tool, capable of distinguishing between RR Lyrae stars, long period variables (LPVs) and non-variables. This projection recovered more than 90% of the known variables and revealed 38 previously unknown variable stars (about 30% more), all LPVs except for one object of uncertain variability type. We conclude that this methodology can indeed successfully identify candidate variable stars.

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“…It is always applied when one aims to produce a clean list of variable stars (e.g. Pawlak et al 2016;Klagyivik et al 2016;Salinas et al 2018;Jayasinghe et al 2018) rather than a (more extensive, but contaminated) list of candidate variables (e.g. Oelkers et al 2018;Heinze et al 2018).…”

Section: An Overview Of Variability Detection Techniquesmentioning

confidence: 99%

The Hubble Catalog of Variables (HCV)

Bonanos

Yang

Sokolovsky

et al. 2019

A&A

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Aims. Over its lifetime and despite not being a survey telescope, the Hubble Space Telescope (HST) has obtained multi-epoch observations by multiple, diverse observing programs, providing the opportunity for a comprehensive variability search aiming to uncover new variables. We have therefore undertaken the task of creating a catalog of variable sources based on archival HST photometry. In particular, we have used version 3 of the Hubble Source Catalog (HSC), which relies on publicly available images obtained with the WFPC2, ACS, and WFC3 instruments on board the HST. Methods. We adopted magnitude-dependent thresholding in median absolute deviation (a robust measure of light curve scatter) combined with sophisticated preprocessing techniques and visual quality control to identify and validate variable sources observed by Hubble with the same instrument and filter combination five or more times. Results. The Hubble Catalog of Variables (HCV) includes 84,428 candidate variable sources (out of 3.7 million HSC sources that were searched for variability) with V ≤ 27 mag; for 11,115 of them the variability is detected in more than one filter. The data points in the light curves of the variables in the HCV catalog range from five to 120 points (typically having less than ten points); the time baseline ranges from under a day to over 15 years; while ∼8% of all variables have amplitudes in excess of 1 mag. Visual inspection performed on a subset of the candidate variables suggests that at least 80 % of the candidate variables that passed our automated quality control are true variable sources rather than spurious detections resulting from blending, residual cosmic rays, and calibration errors.Conclusions. The HCV is the first, homogeneous catalog of variable sources created from the highly diverse, archival HST data and currently is the deepest catalog of variables available. The catalog includes variable stars in our Galaxy and nearby galaxies, as well as transients and variable active galactic nuclei. We expect that the catalog will be a valuable resource for the community. Possible uses include searches for new variable objects of a particular type for population analysis, detection of unique objects worthy of follow-up studies, identification of sources observed at other wavelengths, and photometric characterization of candidate progenitors of supernovae and other transients in nearby galaxies. The catalog is available to the community from the ESA Hubble Science Archive (eHST) at the European Space Astronomy Centre (ESAC) and the Mikulski Archive for Space Telescopes (MAST) at Space Telescope Science Institute (STScI).

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THE BERLIN EXOPLANET SEARCH TELESCOPE II CATALOG OF VARIABLE STARS. II. CHARACTERIZATION OF THE CoRoT SRc02 FIELD

Cited by 6 publications

References 31 publications

TheGaiaspectrophotometric standard stars survey – III. Short-term variability monitoring

TheGaiaspectrophotometric standard stars survey – III. Short-term variability monitoring

Variability search in M 31 using principal component analysis and the Hubble Source Catalogue

The Hubble Catalog of Variables (HCV)

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