J/A+A/563/A45ivo://CDS.VizieR/J/A+A/563/A45doi:10.26093/cds/vizier.35630045CDSSarro L.M.Bouy H.Bertin E.Moraux E.Bouvier J.Cuillandre J.-C.,Barrado D.Solano E.2017-06-28T06:58:14Z2014-03-05T07:47:34ZCDS support team

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

cds-question@unistra.fropen-star-clustersproper-motionsphotometryWith the advent of deep wide surveys, large photometric and astrometric catalogues of literally all nearby clusters and associations have been produced. The unprecedented accuracy and sensitivity of these data sets and their broad spatial, temporal and wavelength coverage make obsolete the classical membership selection methods that were based on a handful of colours and luminosities. We present a new technique designed to take full advantage of the high dimensionality (photometric, astrometric, temporal) of such a survey to derive self-consistent and robust membership probabilities of the Pleiades cluster. We aim at developing a methodology to infer membership probabilities to the Pleiades cluster from the DANCe multidimensional astro-photometric data set in a consistent way throughout the entire derivation. The determination of the membership probabilities has to be applicable to censored data and must incorporate the measurement uncertainties into the inference procedure. We use Bayes-theorem and a curvilinear forward model for the likelihood of the measurements of cluster members in the colour-magnitude space, to infer posterior membership probabilities. The distribution of the cluster members proper motions and the distribution of contaminants in the full multidimensional astro-photometric space is modelled with a mixture-of-Gaussians likelihood. We analyse several representation spaces composed of the proper motions plus a subset of the available magnitudes and colour indices. We select two prominent representation spaces composed of variables selected using feature relevance determination techniques based in Random Forests, and analyse the resulting samples of high probability candidates. We consistently find lists of high probability (p>0.9975) candidates with ~1000 sources, 4 to 5 times more than obtained in the most recent astro-photometric studies of the cluster. Multidimensional data sets require statistically sound multivariate analysis techniques to fully exploit their scientific information content. Proper motions in particular are, as expected, critical for the correct separation of contaminants. The methodology presented here is ready for application in data sets that include more dimensions, such as radial and/or rotational velocities, spectral indices, and variability.2014A&A...563A..45Shttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/563/A45CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toI/258 : Pleiades positions and proper motions (Wang+, 1996)J/A+A/320/74 : Radial velocities of Pleiades members (Mermilliod+ 1997)J/A+A/329/101 : Masses of Pleiades members (Raboud+ 1998)J/A+A/332/575 : Pleiades member list (Belikov+ 1998)J/MNRAS/380/712 : ZYJHK photometry in Pleiades (Lodieu+, 2007)J/MNRAS/422/1495 : UKIDSS Galactic Clusters Survey Pleiades membershttps://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/563/A45https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/563/A45http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/563/A45https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/563/A45https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/563/A45http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/563/A45GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/A+A/563/A45/catalog (Positions, proper motions, photometry and membership probabilities of sources in the Pleiades region of the sky)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/563/A45/catalog?https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/563/A45/catalog?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/563/A45/catalog?GETtext/xml+votable180.050000true56.1166872224.346814170.0055555555555555563/7 5/89-91 94-95 101 103 109 209 212 288 290 296 6/319 355 369-371 374-375 403 409 411 445 447 832-833 845 852-853 856 1064 1066-1067 1158 1164 1166 1188 1192-11947.952274030004205e-20 1.7798557115773645e-19https://cdsarc.cds.unistra.fr/viz-bin/moc/J/A+A/563/A45?format=asciiOpticaldefaultJ/A+A/563/A45/catalogPositions, proper motions, photometry and membership probabilities of sources in the Pleiades region of the skyDANCeDANCe identifier (Dynamical Analysis of Nearby ClustErs)meta.id;meta.mainintprimaryRAJ2000Right ascension (J2000.0)degpos.eq.ra;meta.mainindexedDEJ2000Declination (J2000.0)degpos.eq.dec;meta.mainindexedpmRAProper motion in RA axis (accuracy 0.3mas/yr)mas/yrpos.pm;pos.eq.rafloatpmDEProper motion in DE axis (accuracy 0.3mas/yr)mas/yrpos.pm;pos.eq.decfloatumag? u magnitudemagphot.mag;em.opt.Ufloatnullablegmag? g magnitudemagphot.mag;em.opt.Bfloatnullablermag? r magnitudemagphot.mag;em.opt.Rfloatnullableimag? i magnitudemagphot.mag;em.opt.IfloatnullableJmag? J magnitudemagphot.mag;em.IR.JfloatnullableHmag? H magnitudemagphot.mag;em.IR.HfloatnullableKmag? K magnitudemagphot.mag;em.IR.KfloatnullableYmag? Y magnitudemagphot.mag;em.IR.Jfloatnullablezmag? z magnitudemagphot.mag;em.opt.IfloatnullablepAMa[0/1] Membership probability AM, p_in_=0.9545 (1)stat.probabilityfloatpAMb[0/1] Membership probability AM, p_in_=0.975 (1)stat.probabilityfloatpAMc[0/1] Membership probability AM, p_in_=0.9975 (1)stat.probabilityfloatpRF2a[0/1] Membership probability RF2, p_in_=0.9545 (1)stat.probabilityfloatpRF2b[0/1] Membership probability RF2, p_in_=0.975 (1)stat.probabilityfloatpRF2c[0/1] Membership probability RF2, p_in_=0.9975 (1)stat.probabilityfloatpRF3a[0/1] Membership probability RF3, p_in_=0.9545 (1)stat.probabilityfloatpRF3b[0/1] Membership probability RF3, p_in_=0.975 (1)stat.probabilityfloatpRF3c[0/1] Membership probability RF3, p_in_=0.9975 (1)stat.probabilityfloat