2022
DOI: 10.48550/arxiv.2206.07937
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Stellar ages, masses, extinctions and orbital parameters based on spectroscopic parameters of Gaia DR3

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Cited by 3 publications
(3 citation statements)
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“…To select the candidate low-mass objects for spectroscopic follow up, we use the photometric and astrometric data from Gaia DR3 (Gaia Collaboration et al 2016;Gaia Collaboration 2022). We extract the Gaia DR3 data for our survey area (∼21′ × 21′) and for those sources in our WIRCam data with counterparts in Gaia DR3 we apply the following astrometric quality conditions: (1) renormalized unit weight error (RUWE) < 1.4 -sources with higher values can possibly have unreliable astrometric solutions (Fabricius et al 2021;Manara et al 2021;Kordopatis et al 2022;Stoop et al 2022) and (2) σ π /π <0.1, where π is the parallax and σ π is the uncertainty in the parallax (Esplin & Luhman 2022;Penoyre et al 2022). We then selected for follow-up spectroscopy 11sources lying along the PMS branch in the Gaia G -J versus absolute Gaia G CMD.…”
Section: Member Selection Using Gaia Dr3mentioning
confidence: 99%
“…To select the candidate low-mass objects for spectroscopic follow up, we use the photometric and astrometric data from Gaia DR3 (Gaia Collaboration et al 2016;Gaia Collaboration 2022). We extract the Gaia DR3 data for our survey area (∼21′ × 21′) and for those sources in our WIRCam data with counterparts in Gaia DR3 we apply the following astrometric quality conditions: (1) renormalized unit weight error (RUWE) < 1.4 -sources with higher values can possibly have unreliable astrometric solutions (Fabricius et al 2021;Manara et al 2021;Kordopatis et al 2022;Stoop et al 2022) and (2) σ π /π <0.1, where π is the parallax and σ π is the uncertainty in the parallax (Esplin & Luhman 2022;Penoyre et al 2022). We then selected for follow-up spectroscopy 11sources lying along the PMS branch in the Gaia G -J versus absolute Gaia G CMD.…”
Section: Member Selection Using Gaia Dr3mentioning
confidence: 99%
“…In order to propagate the errors, we considered the correlations between the astrometric parameters. Motivated by the approach of Gaia Collaboration (2022b) and Kordopatis et al (2022), we modelled the distribution of the errors of the geometric distances with a broken Gaussian distribution parameterised by the input confidence intervals (i.e. r lo and r hi in Bailer-Jones et al 2021).…”
Section: Gaia Data and Selection Criteriamentioning
confidence: 99%
“…More recently, Gaia DR3 data present the latest general stellar information, including around 1.5 billion sources with full astrometric solution (e.g., Gaia Collaboration et al 2021;Gaia Collaboration et al 2023a;Kordopatis et al 2022), and it helps us to better hunt and/or reidentify possible OCs. In this study, we revisit 77 special OC candidates with multiple main sequences (MSs) using Gaia DR3 from LISC catalog.…”
Section: Introductionmentioning
confidence: 99%