J/A+A/682/A92ivo://CDS.VizieR/J/A+A/682/A92doi:10.26093/cds/vizier.36820092CDSHerz P.Samland M.Bailer-Jones C.A.L.2024-11-29T20:00:55Z2024-02-07T09:28:28ZCDS support team

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

cds-question@unistra.frmultiple-starsexoplanetsinfrared-photometryDirect imaging searches for exoplanets around stars detect many spurious candidates that are in fact background field stars. To help distinguish these from genuine companions, multi-epoch astrometry can be used to identify a common proper motion with the host star. Although this is frequently done, many approaches lack an appropriate model for the motions of the background population, or do not use a statistical framework to properly quantify the results. Here we use Gaia astrometry combined with 2MASS photometry to model the parallax and proper motion distributions of field stars around exoplanet host stars as a function of candidate magnitude. We develop a likelihood-based method that compares the positions of a candidate at multiple epochs with the positions expected under both this field star model and a co-moving companion model. Our method propagates the covariances in the Gaia astrometry and the candidate positions. True companions are assumed to have long periods compared to the observational baseline, so we currently neglect orbital motion. We apply our method to a sample of 23 host stars with 263 candidates identified in the B-Star Exoplanet Abundance Study (BEAST) survey on VLT/SPHERE. We identify seven candidates in which the odds ratio favours the co-moving companion model by a factor of 100 or more. Most of these detections are based on only two or three epochs separated by less than three years, so further epochs should be obtained to reassess the companion probabilities. Our method is publicly available as an open-source python package from https://github.com/herzphi/compass to use with any data.2024A&A...682A..92Hhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/682/A92CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicehttps://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/682/A92https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/682/A92http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/682/A92https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/682/A92https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/682/A92http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/682/A92GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/A+A/682/A92/table1 (Candidates with logarithmic odds ratio greater than zero under the parallax and proper motion model)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/682/A92/table1?https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/682/A92/table1?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/682/A92/table1?GETtext/xml+votable180.050000true188.3007797-52.08284360.0055555555555555566/38023 41534 41606 41815 41917 42428 42549 42658 42674 42778 43011 43062 43067 43101 43117 43138 43153 43183 43192 43279 43365 43383 43397 43538 441017.952274030004205e-20 1.0188844282367877e-19https://cdsarc.cds.unistra.fr/viz-bin/moc/J/A+A/682/A92?format=asciiInfrareddefaultJ/A+A/682/A92/table1Candidates with logarithmic odds ratio greater than zero under the parallax and proper motion modelSimbadSimbad column added by the CDSmeta.ref.urlcharrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintSeqSequential numbermeta.idintTargetIdentifier of the target starmeta.id;meta.maincharUUIDUnique identifier for the candidatemeta.idcharDate1Date 1 of observation of the candidatetime.epoch;obsnullableDate2Date 2 of observation of the candidatetime.epoch;obsnullableDate3Date 3 of observation of the candidatetime.epoch;obsnullableKsmagKs magnitude of the candidatemagphot.mag;em.IR.Kdoublee_KsmagKs magnitude error of the candidatemagstat.error;phot.magdouble2DnmodelLikelihood ratio of the covariance methodstat.likelihood;stat.fit;arith.ratiodoublepmmodelLikelihood ratio of the pm only methodstat.likelihood;pos.pm;stat.fitdoublecatalogue[gaiacalctmass] Catalogues used to determine the ratiosmeta.codecharrefepoch1Epoch of observation 1yrmeta.ref;pos.framefloatrefepoch2Epoch of observation 2yrmeta.ref;pos.framefloatrefepoch3? Epoch of observation 3yrmeta.ref;pos.framefloatnullable_RARight Ascension (J2000) from SIMBAD (not part of the original data)degpos.eq.ra;meta.main_DEDeclination (J2000) from SIMBAD (not part of the original data)degpos.eq.dec;meta.main