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Identifying Exoplanets with Deep Learning. III. Automated Triage and Vetting of TESS Candidates

  • Authors: Liang Yu, Andrew Vanderburg, Chelsea Huang, Christopher J. Shallue, Ian J. M. Crossfield, B. Scott Gaudi, Tansu Daylan, Anne Dattilo, David J. Armstrong, George R. Ricker, Roland K. Vanderspek, David W. Latham, Sara Seager, Jason Dittmann, John P. Doty, Ana Glidden, and Samuel N. Quinn

2019 The Astronomical Journal 158 25.

  • Provider: AAS Journals

Caption: Figure 1.

For each TCE, we prepare three phase-folded, depth-normalized representations of the light curve: the “global view” (left column) is a fixed-length representation of the entire period; the “local view” (middle column) is a close-up view of the putative transit; the “secondary eclipse view” (right column), only present in vetting mode, is a close-up view of the most likely secondary eclipse. Each row presents an example from one of the four categories of TCEs: PC (planet candidates), EB (eclipsing binaries), V (stellar variability), and IS (instrumental artifact).

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