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dc.date.accessioned2021-10-27T20:05:36Z
dc.date.available2021-10-27T20:05:36Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/1721.1/134566
dc.description.abstract© 2020. The American Astronomical Society. All rights reserved. We present TRICERATOPS, a new Bayesian tool that can be used to vet and validate TESS Objects of Interest (TOIs). We test the tool on 68 TOIs that have been previously confirmed as planets or rejected as astrophysical false positives. By looking in the false-positive probability (FPP)-nearby false-positive probability (NFPP) plane, we define criteria that TOIs must meet to be classified as validated planets (FPP < 0.015 and NFPP < 10-3), likely planets (FPP < 0.5 and NFPP < 10-3), and likely nearby false positives (NFPP > 10-1). We apply this procedure on 384 unclassified TOIs and statistically validate 12, classify 125 as likely planets, and classify 52 as likely nearby false positives. Of the 12 statistically validated planets, 9 are newly validated. TRICERATOPS is currently the only TESS vetting and validation tool that models transits from nearby contaminant stars in addition to the target star. We therefore encourage use of this tool to prioritize follow-up observations that confirm bona fide planets and identify false positives originating from nearby stars.en_US
dc.language.isoen
dc.publisherAmerican Astronomical Societyen_US
dc.relation.isversionof10.3847/1538-3881/ABC6AFen_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceThe American Astronomical Societyen_US
dc.titleVetting of 384 TESS Objects of Interest with TRICERATOPS and Statistical Validation of 12 Planet Candidatesen_US
dc.typeArticleen_US
dc.relation.journalAstronomical Journalen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2021-09-28T17:38:05Z
dspace.orderedauthorsGiacalone, S; Dressing, CD; Jensen, ELN; Collins, KA; Ricker, GR; Vanderspek, R; Seager, S; Winn, JN; Jenkins, JM; Barclay, T; Barkaoui, K; Cadieux, C; Charbonneau, D; Collins, KI; Conti, DM; Doyon, R; Evans, P; Ghachoui, M; Gillon, M; Guerrero, NM; Hart, R; Jehin, E; Kielkopf, JF; McLean, B; Murgas, F; Palle, E; Parviainen, H; Pozuelos, FJ; Relles, HM; Shporer, A; Socia, Q; Stockdale, C; Tan, T-G; Torres, G; Twicken, JD; Waalkes, WC; Waite, IAen_US
dspace.date.submission2021-09-28T17:38:06Z
mit.journal.volume161en_US
mit.journal.issue1en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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