Machine learning classification of TESS data for 6 million stars in the LOPS2 field identifies 28% as candidate variables after filtering out 72% instrumental signals, producing one of the largest automated variability catalogs.
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The paper presents quantitative metrics and thresholds for selecting the Prime Sample of 15,000 stars in the PLATO LOPS2 field to enable ground-based follow-up of exoplanet candidates.
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Variability classification of TESS targets in LOPS2, the first long-term pointing field of PLATO. Version 1 of the public variability catalogue
Machine learning classification of TESS data for 6 million stars in the LOPS2 field identifies 28% as candidate variables after filtering out 72% instrumental signals, producing one of the largest automated variability catalogs.
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The PLATO field selection process III. Selection of the Prime Sample for the LOPS2 field
The paper presents quantitative metrics and thresholds for selecting the Prime Sample of 15,000 stars in the PLATO LOPS2 field to enable ground-based follow-up of exoplanet candidates.