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V* CQ Lac , the SIMBAD biblio (38 results) | C.D.S. - SIMBAD4 rel 1.8 - 2024.04.23CEST19:03:15 |
Bibcode/DOI | Score |
in Title|Abstract| Keywords |
in a table | in teXt, Caption, ... | Nb occurence | Nb objects in ref |
Citations (from ADS) |
Title | First 3 Authors |
---|---|---|---|---|---|---|---|---|---|
1935AN....255..425M | 24 | 16 | 23 neue Veranderliche. | MORGENROTH O. | |||||
1936AN....260..393G | 194 | 6 | Benennung von veranderlichen Sternen. | GUTHNICK P. and PRAGER R. | |||||
1957SvA.....1..205A | 102 | 0 | Color excesses in 102 RR Lyrae stars. | ALANIA I.Ph. | |||||
1972MmSAI..43..319R | 33 | 0 | Studio sulle stelle variabili in due campi stellari nelle costellazioni delle Lacerta e delle Lira. | ROMANO G. and PERISSINOTTO M. | |||||
1978ATsir.979....7F | 7 | 0 | The supplement to the catalogue of RR Lyrae stars elements. | FIRMANYUK B.N. | |||||
1994AJ....108.1016L | 336 | 201 | The metallicities and kinematics of RR Lyrae variables. I. New observations of local stars. | LAYDEN A.C. | |||||
1996AJ....112.2110L | 216 | 181 | The absolute magnitude and kinematics of RR Lyrae stars via statistical parallax. | LAYDEN A.C., HANSON R.B., HAWLEY S.L., et al. | |||||
1996AJ....112.2769S | 106 | 31 | The Behlen Observatory variable star survey. IV. | SCHMIDT E.G. and SETH A. | |||||
1998AJ....116.1724M | 133 | 43 | A new analysis of RR Lyrae kinematics in the solar neighborhood. | MARTIN J.C. and MORRISON H.L. | |||||
2000AJ....119.2866B | 2011 | 171 | Kinematics of metal-poor stars in the Galaxy. II. Proper motions for a large nonkinematically selected sample. | BEERS T.C., CHIBA M., YOSHII Y., et al. | |||||
2001IBVS.5017....1A | 127 | 38 | Photoelectric minima of selected eclipsing binaries and maxima of pulsating stars. | AGERER F., DAHM M. and HUEBSCHER J. | |||||
2001AstL...27..108D | 266 | 12 | Absolute magnitudes and kinematic parameters of the subsystem of RR Lyrae variables. | DAMBIS A.K. and RASTORGUEV A.S. | |||||
2002A&A...390..173M | 179 | 1 | Identification of RR Lyrae stars in the Tycho-2 catalogue. | MENNESSIER M.O. and COLOME J. | |||||
2002AJ....123..965S | 67 | 13 | The intermediate-period cepheid strip stars. | SCHMIDT E.G. | |||||
2002ARep...46..460B | 176 | 4 | Subsystems of RR Lyrae variable stars in our Galaxy. | BORKOVA T.V. and MARSAKOV V.A. | |||||
2003IBVS.5485....1A | 147 | 17 | Photoelectric maxima of selected pulsating stars. | AGERER F. and HUEBSCHER J. | |||||
2004BAVSR..53....5A | O | 15 | 0 | Einige vernachlassigte Veranderliche mit grossen (B-R)-Werten. | ACHTERBERG H. | ||||
2005A&A...442..381M | 590 | 12 | Proper identification of RR Lyrae stars brighter than 12.5 mag. | MAINTZ G. | |||||
2005IBVS.5643....1H | 495 | 117 | Photoelectric minima of selected eclipsing binaries and maxima of pulsating stars. | HUEBSCHER J. | |||||
2005IBVS.5657....1H | 596 | 160 | Photoelectric minima of selected eclipsing binaries and maxima of pulsating stars. | HUBSCHER J., PASCHKE A. and WALTER F. | |||||
2006A&A...453..895W | 149 | 2 | [Fe/H] derived from the light curves of RR Lyrae stars in the Galactic halo. | WU C., QIU Y.L., DENG J.S., et al. | |||||
2006AJ....132.1202K | 15 | D | 1185 | 88 | Analysis of RR Lyrae stars in the northern sky variability survey. | KINEMUCHI K., SMITH H.A., WOZNIAK P.R., et al. | |||
2006MNRAS.368.1757W | 617 | 72 | A catalogue of RR Lyrae stars from the Northern Sky Variability Survey. | WILS P., LLOYD C. and BERNHARD K. | |||||
2006IBVS.5686....1L | 59 | 4 | The GEOS RR Lyr survey. | LE BORGNE J.F., KLOTZ A. and BOER M. | |||||
2006IBVS.5731....1H | 818 | 148 | Photoelectric minima of selected eclipsing binaries and maxima of pulsating stars. | HUBSCHER J., PASCHKE A. and WALTER F. | |||||
2009AJ....138..466H | 15 | D | 1 | 4126 | 116 | Automated variable star classification using the Northern Sky Variability Survey. | HOFFMAN D.I., HARRISON T.E. and McNAMARA B.J. | ||
2010IBVS.5941....1H | 15 | D | 1 | 458 | 27 | BAV-results of observations - photoelectric minima of selected eclipsing binaries and maxima of pulsating stars. | HUBSCHER J., LEHMANN P.B., MONNINGER G., et al. | ||
2013MNRAS.435.3206D | 16 | D | 1 | 429 | 79 | RR Lyrae variables: visual and infrared luminosities, intrinsic colours and kinematics. | DAMBIS A.K., BERDNIKOV L.N., KNIAZEV A.Y., et al. | ||
2014MNRAS.441..715G | 16 | D | 1 | 13079 | 14 | A mid-infrared study of RR Lyrae stars with the Wide-field Infrared Survey Explorer all-sky data release. | GAVRILCHENKO T., KLEIN C.R., BLOOM J.S., et al. | ||
2017A&A...605A..79G | 16 | D | 1 | 735 | 92 | Gaia Data Release 1. Testing parallaxes with local Cepheids and RR Lyrae stars. | GAIA COLLABORATION, CLEMENTINI G., EYER L., et al. | ||
2018ARep...62...50M | 16 | D | 1 | 416 | 12 | Relationship between the elemental abundances and the kinematics of Galactic-field RR Lyrae stars. | MARSAKOV V.A., GOZHA M.L. and KOVAL V.V. | ||
2018AJ....156..241H | 16 | D | 1 | 311114 | 199 | A first catalog of variable stars measured by the Asteroid Terrestrial-impact Last Alert System (ATLAS). | HEINZE A.N., TONRY J.L., DENNEAU L., et al. | ||
2018MNRAS.481.1195M | 16 | D | 1 | 404 | 118 | RR Lyrae stars as standard candles in the Gaia Data Release 2 Era. | MURAVEVA T., DELGADO H.E., CLEMENTINI G., et al. | ||
2019A&A...622A..60C | 17 | D | 1 | 150347 | 194 | Gaia Data Release 2. Specific characterisation and validation of all-sky Cepheids and RR Lyrae stars. | CLEMENTINI G., RIPEPI V., MOLINARO R., et al. | ||
2020MNRAS.492.2161Z | 17 | D | 1 | 482 | ~ | Local RR Lyrae stars: native and alien. | ZINN R., CHEN X., LAYDEN A.C., et al. | ||
2020MNRAS.492.3408P | 17 | D | 1 | 327 | 20 | Evidence for Galactic disc RR Lyrae stars in the solar neighbourhood. | PRUDIL Z., DEKANY I., GREBEL E.K., et al. | ||
2021MNRAS.502.4074M | 17 | D | 1 | 858 | ~ | Kinematics and multiband period-luminosity-metallicity relation of RR Lyrae stars via statistical parallax. | MUHIE T.D., DAMBIS A.K., BERDNIKOV L.N., et al. | ||
2022ApJS..261...33D | 18 | D | 1 | 104673 | 3 | Photometric Metallicity Prediction of Fundamental-mode RR Lyrae Stars in the Gaia Optical and Ks Infrared Wave Bands by Deep Learning. | DEKANY I. and GREBEL E.K. |