J/A+A/648/A44ivo://CDS.VizieR/J/A+A/648/A44doi:10.26093/cds/vizier.36480044CDSMowlavi N.Rimoldini L.Evans D.W.Riello M.De Angeli F.Palaversa L.,Audard M.Eyer L.Garcia-Lario P.Gavras P.Holl B.,Jevardat de Fombelle G.Lecoeur-Taibi I.Nienartowicz K.2021-09-16T10:23:20Z2021-04-09T06:39:37ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.frsurveysvariable-starsphotometryPhotometric variability is an essential feature that sheds light on the intrinsic properties of celestial variable sources, the more so when photometry is available in various bands. In this respect, the all-sky Gaia mission is particularly attractive as it collects, among other quantities, epoch photometry measured quasi-simultaneously in three optical bands for sources ranging from a few magnitudes to fainter than magnitude twenty. The second data release (DR2) of the mission provides mean G, GBP and GRP photometry for 1.4 billion sources, but light curves and variability properties are available for only 0.5 million of them. Here, we provide a census of large-amplitude variables (LAVs) with amplitudes larger than 0.2mag in the G band for objects with mean brightnesses between 5.5 and 19mag. To achieve this, we rely on variability amplitude proxies in G, GBP and GRP computed from the uncertainties on the magnitudes published in DR2. We then apply successive filters to identify two subsets containing respectively sources with reliable mean GBP and GRP (for studies using colours) and sources having compatible amplitude proxies in G, GBP and GRP (for multi-band variability studies). The full catalogue gathers 23315874 LAV candidates, and the two subsets with increased levels of purity contain respectively 1148861 and 618966 sources. A multi-band variability analysis of the catalogue shows that different types of variable stars can be categorized according to their colour and blue-to-red amplitude ratios as determined from the G, GBP and GRP amplitude proxies. More specifically, four groups are globally identified. They mostly include long-period variables in a first group with amplitudes more than twice larger in the blue than in the red, hot compact variables in a second group with amplitudes smaller in the blue than in the red, classical instability strip pulsators in a third group with amplitudes larger in the blue than in the red by 50% to 80%, and other non-pulsating variables in a fourth group, mainly achromatic, but with still 10% of them having 20% to 50% larger amplitudes in the blue than in the red. The catalogue constitutes the first census of Gaia large amplitude variable (LAV) candidates, extracted from the public DR2 archive. The overview presented here illustrates the added-value of the mission for multi-band variability studies even at this stage when epoch photometry is not yet available for all sources.2021A&A...648A..44Mhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/648/A44CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toI/345 : Gaia DR2 (Gaia Collaboration, 2018)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/648/A44https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/648/A44http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/648/A44https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/648/A44https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/648/A44http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/648/A44GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/A+A/648/A44/tabled1 (Catalog of large amplitude variables from Gaia DR2)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/648/A44/tabled1?https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/648/A44/tabled1?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/648/A44/tabled1?GETtext/xml+votable180.050000true44.9990047425070.2304990195750.0055555555555555560/0-11 6/https://cdsarc.cds.unistra.fr/viz-bin/moc/J/A+A/648/A44?format=asciidefaultJ/A+A/648/A44/tabled1Catalog of large amplitude variables from Gaia DR2recnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintGaiaDR2GaiaDR2 source ID (source_id)meta.id;meta.maindatasetB[0/1] In in dataset B? (dataset_B) (1)meta.codeintdatasetC[0/1] In in dataset C? (dataset_C) (1)meta.codeintGLONGaiaDR2 Galactic longitude (l_deg)degpos.galactic.lonindexedGLATGaiaDR2 Galactic latitude (b_deg)degpos.galactic.latindexedPlx? GaiaDR2 absolute stellar parallax (parallax_mas)maspos.parallaxdoublenullablee_Plx? GaiaDR2 Standard error of parallax (parallax_error_mas)masstat.error;pos.parallaxfloatnullableo_Gmag? GaiaDR2 number of observations contributing to G photometry (phot_g_n_obs)meta.numberintnullableFGGaiaDR2 G-band mean flux (phot_g_mean_flux)phot.flux.density;em.optdoublee_FGGaiaDR2 Error on G-band mean flux (phot_g_mean_flux_error)stat.errordoubleGmagGaiaDR2 G-band mean magnitude (Vega) (phot_g_mean_mag)magphot.mag;em.optdoubleo_BPmag? GaiaDR2 Number of observations contributing to BP photometry (phot_bp_n_obs)meta.numberintnullableFBP? GaiaDR2 mean flux in the integrated BP band (phot_bp_mean_flux)phot.flux.density;em.opt.Bdoublenullablee_FBP? GaiaDR2 error on the integrated BP mean flux (phot_bp_mean_flux_error)stat.errordoublenullableBPmag? GaiaDR2 integrated BP mean magnitude (Vega) (phot_bp_mean_mag)magphot.mag;em.opt.Bdoublenullableo_RPmag? GaiaDR2 number of observations contributing to RP photometry (phot_rp_n_obs)meta.numberintnullableFRP? GaiaDR2 mean flux in the integrated RP band (phot_rp_mean_flux)phot.flux.density;em.opt.Rdoublenullablee_FRP? GaiaDR2 error on the integrated RP mean flux (phot_rp_mean_flux_error)stat.errordoublenullableRPmag? GaiaDR2 integrated RP mean magnitude (Vega) (phot_rp_mean_mag)magphot.mag;em.opt.RdoublenullableE(BR/RP)? GaiaDR2 BP/RP excess factor (phot_bp_rp_excess_factor)arith.factorfloatnullableNE(BR/RP)? Normalized GaiaDR2 BP/RP excess factor (phot_bp_rp_excess_factor_normalized)arith.factorfloatnullablef_NE(BR/RP)[0/1] Is BP/RP flux excess reliable ? (isGoodBpRpExcessFactorNormalized)meta.codeintLPV[0/1] Is LPV candidate in GaiaDR2? (DR2_LPV)meta.codeintRRL-SOS[0/1] Is RR Lyrae candidate in GaiaDR2 (sos table)? (DR2_RRL_SOS)meta.codeintRRL-Cl[0/1] Is RR Lyrae candidate in GaiaDR2 (classif table)? (DR2_RRL_Classif)meta.codeintCep-SOS[0/1] Is Cepheid candidate in GaiaDR2 (sos table)? (DR2_Cep_SOS)meta.codeintCep-Cl[0/1] Is Cepheid candidate in GaiaDR2 (classif table)? (DR2_Cep_Classif)meta.codeintdSctSXPhe[0/1] Is delta Scuti & SXPHE candidate in GaiaDR2? (DR2_dSct_SXPhe)meta.codeintRotMod[0/1] Is rotation modulation candidate in GaiaDR2? (DR2_RotMod)meta.codeintSTS[0/1] Is short time-scale candidate in GaiaDR2? (DR2_STS)meta.codeintAmpGAmplitude proxy in G (amplProxyG)src.var.amplitudedoubleAmpBP? Amplitude proxy in BP (amplProxyBP)src.var.amplitudedoublenullableAmpRP? Amplitude proxy in RP (amplProxyRP)src.var.amplitudedoublenullableAmpBP+RP? Amplitude proxy in BP+RP, Eq. (C10) (amplProxyBPplusRPwithoutCov)src.var.amplitudedoublenullableGroup1[0/1] Is in Group 1 (for Dataset C only)? (Group_1) (2)meta.codeintGroup2[0/1] Is in Group 2 (for Dataset C only)? (Group_2) (2)meta.codeintGroup3[0/1] Is in Group 3 (for Dataset C only)? (Group_3) (2)meta.codeintGroup4[0/1] Is in Group 4 (for Dataset C only)? (Group_4) (2)meta.codeintGroup4a[0/1] Is in Group 4a (for Dataset C only)? (Group_4a) (2)meta.codeint_RA.icrsRight ascension (ICRS) (computed by VizieR, not part of the original data. The format may include more digits than the original data because of internal accuracy requirements in VizieR and across other CDS services)degpos.eq.ranullableindexed_DE.icrsDeclination (ICRS) (computed by VizieR, not part of the original data. The format may include more digits than the original data because of internal accuracy requirements in VizieR and across other CDS services)degpos.eq.decnullableindexed