2022
DOI: 10.1093/mnras/stac2451
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Validation of TESS exoplanet candidates orbiting solar analogues in the all-sky PLATO input catalogue

Abstract: The Transiting Exoplanet Survey Satellite (TESS) is focusing on relatively bright stars and has found thousands of planet candidates. However, mainly because of the low spatial resolution of its cameras (≈ 21 arcsec/pixel), TESS is expected to detect several false positives (FPs); hence, vetting needs to be done. Here, we present a follow-up program of TESS candidates orbiting solar-analogue stars that are in the all-sky PLATO input catalogue. Using Gaia photometry and astrometry we built an absolute colour-ma… Show more

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Cited by 9 publications
(1 citation statement)
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References 51 publications
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“…Exoplanet candidate lists from large-scale efforts of transit detection and vetting include the Kepler Objects of Interest (Jenkins et al 2010(Jenkins et al , 2020Batalha et al 2010;McCauliff et al 2015;Coughlin et al 2014), NGTS Armstrong et al (2018), AstroNet (Yu et al 2019), TESS Objects of Interest (TOIs, Guerrero et al 2021), and DIAmante TESS candidates (Montalto et al 2020). Additional recent vetting efforts include Zink et al (2021), Dvash et al (2022), Ofman et al (2022), Kunimoto et al (2022), Kostov et al (2022), Cacciapuoti et al (2022), Mantovan et al (2022), and Magliano et al (2023). McCauliff et al (2015); Coughlin et al (2016) and autovet for ground-based NGTS data by Armstrong et al (2018).…”
Section: Introductionmentioning
confidence: 99%
“…Exoplanet candidate lists from large-scale efforts of transit detection and vetting include the Kepler Objects of Interest (Jenkins et al 2010(Jenkins et al , 2020Batalha et al 2010;McCauliff et al 2015;Coughlin et al 2014), NGTS Armstrong et al (2018), AstroNet (Yu et al 2019), TESS Objects of Interest (TOIs, Guerrero et al 2021), and DIAmante TESS candidates (Montalto et al 2020). Additional recent vetting efforts include Zink et al (2021), Dvash et al (2022), Ofman et al (2022), Kunimoto et al (2022), Kostov et al (2022), Cacciapuoti et al (2022), Mantovan et al (2022), and Magliano et al (2023). McCauliff et al (2015); Coughlin et al (2016) and autovet for ground-based NGTS data by Armstrong et al (2018).…”
Section: Introductionmentioning
confidence: 99%