Characterization of a Set of Small Planets with TESS and CHEOPS and an Analysis of Photometric Performance

The radius valley carries implications for how the atmospheres of small planets form and evolve, but this feature is visible only with highly precise characterizations of many small planets. We present the characterization of nine planets and one planet candidate with both NASA TESS and ESA CHEOPS observations, which adds to the overall population of planets bordering the radius valley. While five of our planets-TOI 118 b, TOI 262 b, TOI 455 b, TOI 560 b, and TOI 562 b-have already been published, we vet and validate transit signals as planetary using follow-up observations for four new TESS planets, including TOI 198 b, TOI 244 b, TOI 444 b, and TOI 470 b. While a three times increase in primary mirror size should mean that one CHEOPS transit yields an equivalent model uncertainty in transit depth as about nine TESS transits in the case that the star is equally as bright in both bands, we find that our CHEOPS transits typically yield uncertainties equivalent to between two and 12 TESS transits, averaging 5.9 equivalent transits. Therefore, we find that while our fits to CHEOPS transits provide overall lower uncertainties on transit depth and better precision relative to fits to TESS transits, our uncertainties for these fits do not always match expected predictions given photon-limited noise. We find no correlations between number of equivalent transits and any physical parameters, indicating that this behavior is not strictly systematic, but rather might be due to other factors such as in-transit gaps during CHEOPS visits or nonhomogeneous detrending of CHEOPS light curves.

Automated summary

This study presents the characterization of nine planets and one planet candidate using both NASA TESS and ESA CHEOPS observations, adding to the overall population of planets bordering the radius valley. While CHEOPS observations provide lower uncertainties and better precision, the uncertainties for these fits do not always match expected predictions. This mismatch may be due to factors such as in-transit gaps during CHEOPS visits or nonhomogeneous detrending of CHEOPS light curves.