Details

Autor(en) / Beteiligte

• Kostov, Veselin B.
• Kuchner, Marc J.
• Cacciapuoti, Luca
• Acharya, Sovan
• Ahlers, John P.
• Andrés-Carcasona, Marc
• Brande, Jonathan
• de Lima, Lucas T.
• Di Fraia, Marco Z.
• Fornear, Aline U.
• Gallo, Francesco
• Hyogo, Michiharu
• Ienco, Riccardo M.
• de Lambilly, Julien S.
• Luca, Hugo A. D.
• Quintana, Elisa
• Salik, Ryan
• Yablonsky, John M.

Titel

Planet Patrol: Vetting Transiting Exoplanet Candidates with Citizen Science

Ist Teil von

• Publications of the Astronomical Society of the Pacific, 2022-04, Vol.134 (1034), p.44401

Ort / Verlag

Philadelphia: The Astronomical Society of the Pacific

Erscheinungsjahr

2022

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Abstract NASA’s TESS mission yields light curves for tens of millions of stars spread across the entire sky, a data set that will be a challenge to fully exploit without help from citizen scientists. To address this, we launched a new citizen science project, called “Planet Patrol”, designed to analyze TESS data on exoplanet and eclipsing binary candidates. The project will also serve to benchmark different data reduction pipelines and help analyze unusual light curves that might defeat automated algorithms. The first stage of the project ran on the Zooniverse platform between 2020 September and November and involved more than 5500 registered volunteers. The Planet Patrol citizen scientists produced nearly 400,000 classifications of difference images used for photocenter analysis of about 1000 planet candidates from TESS. The results were incorporated into the photocenter module of the Discovery And Vetting of Exoplanets (DAVE) pipeline to improve its reliability. Specifically, the classifications indicated that all per-transit difference images are appropriate for photocenter analysis for about 40% of the planet candidates, and the corresponding measurements are sound. In contrast, the volunteers found that all per-transit difference images are dominated by astrophysical contamination and/or systematic effects for about 10% of the planet candidates. This indicated that the corresponding photocenter measurements are unreliable. Finally, the fraction of images appropriate for photocenter analysis varies between 0 and 1 for half the candidates. Removing the images classified as poor from DAVE’s analysis of most of these candidates helped reduce the corresponding photocenter uncertainty by up to ∼30%. We plan to implement the output from another module of DAVE, designed for lightcurve vetting, into a second stage of the Planet Patrol project.