Simulations Predicting the Ability of Multi-Color Simultaneous Photometry to Distinguish TESS Candidate Exoplanets from False Positives

TL;DR

This study uses simulations to evaluate how multi-color photometry with MuSCAT instruments can effectively distinguish true exoplanets from false positives in TESS data, aiding validation efforts.

Contribution

The paper introduces software tools to simulate multi-color observations, quantifying the effectiveness of MuSCAT and MuSCAT2 in identifying false positives among TESS exoplanet candidates.

Findings

MuSCAT can distinguish ~17% of TESS discoveries from false positives.

MuSCAT2 can distinguish ~18% of TESS discoveries from false positives.

High-confidence validation is possible for over 50% of TOIs with larger transit depths.

Abstract

The Transiting Exoplanet Survey Satellite (TESS) is currently concluding its 2-year primary science mission searching 85% of the sky for transiting exoplanets. TESS has already discovered well over one thousand TESS objects of interest (TOIs), but these candidate exoplanets must be distinguished from astrophysical false positives using other instruments or techniques. The 3-band Multi-color Simultaneous Camera for Studying Atmospheres of Transiting Planets (MuSCAT), as well as the 4-band MuSCAT2, can be used to validate TESS discoveries. Transits of exoplanets are achromatic when observed in multiple bandpasses, while transit depths for false positives often vary with wavelength. We created software tools to simulate MuSCAT/MuSCAT2 TESS follow-up observations and reveal which planet candidates can be efficiently distinguished from blended eclipsing binary (BEB) false positives using these two instruments, and which must be validated using other techniques. We applied our software code to the Barclay et al. (2018) predicted TESS discoveries, as well as to TOIs downloaded from the ExoFOP-TESS website. We estimate that MuSCAT (MuSCAT2 values in parentheses) will be able to use its multi-color capabilities to distinguish BEB false positives for $\sim$17% ($\sim$18%) of all TESS discoveries, and $\sim$13% ($\sim$15%) of $R_{\rm pl} < 4R_\oplus$ discoveries. Our TOI analysis shows that MuSCAT (MuSCAT2) can distinguish BEB false positives for $\sim$55% ($\sim$52%) of TOIs with transit depths greater than 0.001, for $\sim$64% ($\sim$61%) of TOIs with transit depths greater than 0.002, and for $\sim$70% ($\sim$68%) of TOIs with transit depth greater than 0.003. Our work shows that MuSCAT and MuSCAT2 can validate hundreds of $R_{\rm pl} < 4R_\oplus$ candidate exoplanets, thus supporting the TESS mission in achieving its Level 1 Science Requirement.