Eclipsing variables: Catalogue and classification

Avvakumova, E. A.; Malkov, O. Yu.; Kniazev, A. Y.

doi:10.1002/asna.201311942

Cited by 87 publications

(72 citation statements)

References 30 publications

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“…A large catalogue of Es (viz. 7179 LCs) has been compiled by Malkov and Avvakumova (2013) along with update on some previous catalogues (Malkov et al 2006;Avvakumova et al 2013). However, in the present paper we decided to focus on the LCs of Es of Miller et al (2010), as we are interested in the classification of binary stars in our Galaxy associated with the spiral arms.…”

Section: Introductionmentioning

confidence: 99%

Unsupervised classification of eclipsing binary light curves throughk-medoids clustering

Modak

Chattopadhyay

2019

Journal of Applied Statistics

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An automatic unsupervised classification of 1318 light curves of variable stars, including eclipsing binaries along with some possible pulsating stars, has been performed using k-medoids clustering method. This separates the stars according to their geometrical configuration in a more scientific way compared to the subjective traditional classification scheme. The light curves in the Galaxy, subjectively grouped in four categories (EA, EB, EW, PUL) in Miller et al. (2010), have been found to consist of two optimum groups containing primarily eclipsing binaries corresponding to bright, massive systems and fainter, less massive systems. Our technique has been assessed in terms of clustering accuracy measure the Average Silhouette Width, which shows the resulting clustering pattern is quite good.

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Section: Introductionmentioning

confidence: 99%

Unsupervised classification of eclipsing binary light curves throughk-medoids clustering

Modak

Chattopadhyay

2019

Journal of Applied Statistics

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“…There is also a star with age 3 Myr that did not meet the lower limit of GB membership criterion even within error bars. After checking the literature for this star we have found that it is an Algol type eclipsing binary (Avvakumova et al 2013), which means it would throw off RAVE measurements yielding such an unpredictable and possibly incorrect age. This star's age was calculated as ≈ 3 Myr and is the only star below the age limit as seen in Fig.…”

Section: Calculating Ages Of Gb Starsmentioning

confidence: 99%

Gould Belt members in X-ray RAVE: cross-matching RAVE stars with 3XMM point sources

Coşkunoğlu

Plevne

Özkan

2019

Astrophys Space Sci

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In this paper the results of matching the RAdial Velocity Experiment (RAVE), a spectroscopic Southern hemisphere survey (9 < I DEN IS < 12), and XMM-Newton Serendipitous Source Catalogue (3XMM) are presented. The latest data releases of RAVE and XMM were matched and a X-ray RAVE catalogue of 1071 stars was obtained. Then the catalogue was checked for possible Gould Belt (GB) members. We obtained a subsample of 10 stars that meet the GB membership criteria. This subsample and GB member candidates were tested photometrically and kinematically. Among the members there are two BY Dra type variables, an NGC2451 open cluster member, a high proper motion star. The rest are regular main sequence stars. The members have very low velocity dispersions which lead us to think that the members belong in a single structure. We also found out that a kinematical GB membership test might be possible to derive given a large enough GB member sample as they fit in a narrow interval in space velocity diagrams.

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“…Two of these stars with low (NUV − V ) 0 are actually RR Lyrae stars: SW Ret is an RRd (Szczgiel & Fabrycky 2007) and v1643 Sgr is an RRc (Dvorak 2004). The more recent catalog of Avvakumova et al (2013) continues to identify v1643 Sgr as a contact binary. The mean (FUV − NUV) 0 of 16 RRc variables is +2.59 ± 0.14.…”

Section: Appendix B Contact Binariesmentioning

confidence: 99%

THE IDENTIFICATION OF RR LYRAE AND δ SCUTTI STARS FROM VARIABLEGALAXY EVOLUTION EXPLORERULTRAVIOLET SOURCES

Kinman¹,

Brown²

2014

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We identify the RR Lyrae and δ Scuti stars in three catalogs of Galaxy Evolution Explorer (GALEX) variable sources. The NUV amplitude of RR Lyrae stars is about twice that in V, so we find a larger percentage of low-amplitude variables than catalogs such as Abbas et al. Interestingly, the (NUV − V ) 0 color is sensitive to metallicity and can be used to distinguish between variables of the same period but differing [Fe/H]. This color is also more sensitive to T eff than optical colors and can be used to identify the red edge of the instability gap. We find 8 δ Scuti stars, 17 RRc stars, 1 RRd star, and 84 RRab stars in the GALEX variable catalogs of Welsh et al. and Wheatley et al. We also classify 6 δ Scuti stars, 5 RRc stars, and 18 RRab stars among the 55 variable GALEX sources identified as "stars" or RR Lyrae stars in the catalog of Gezari et al. We provide ephemerides and light curves for the 26 variables that were not previously known.

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Eclipsing variables: Catalogue and classification

Cited by 87 publications

References 30 publications

Unsupervised classification of eclipsing binary light curves throughk-medoids clustering

Unsupervised classification of eclipsing binary light curves throughk-medoids clustering

Gould Belt members in X-ray RAVE: cross-matching RAVE stars with 3XMM point sources

THE IDENTIFICATION OF RR LYRAE AND δ SCUTTI STARS FROM VARIABLEGALAXY EVOLUTION EXPLORERULTRAVIOLET SOURCES

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