Understanding and predicting cadence effects in the characterization of exoplanet transits
Julio Hernandez Camero, Cynthia S. K. Ho, Vincent Van Eylen

TL;DR
This study quantifies how shorter observing cadences improve the precision of exoplanet radius measurements from transit light curves, using TESS data and a novel predictive method called PEPITA.
Contribution
The paper introduces PEPITA, a numerical Information Analysis method that predicts the impact of observing cadence on parameter precision in exoplanet transit studies.
Findings
Median 50% improvement in radius ratio precision when reducing cadence from 1800s to 20s or 120s.
PEPITA reliably predicts precision improvements with less than 0.5% error in most cases.
Identification of 10 exoplanet candidates that would benefit most from reobservations at shorter cadences.
Abstract
We investigate the effect of observing cadence on the precision of radius ratio values obtained from transit light curves by performing uniform Markov Chain Monte Carlo fits of 46 exoplanets observed by the Transiting Exoplanet Survey Satellite (TESS) in multiple cadences. We find median improvements of almost 50% when comparing fits to 20s and 120s cadence light curves to 1800s cadence light curves, and of 37% when comparing 600s cadence to 1800s cadence. Such improvements in radius precision are important, for example, to precisely constrain the properties of the radius valley or to characterize exoplanet atmospheres. We also implement a numerical Information Analysis to predict the precision of parameter estimates for different observing cadences. We tested this analysis on our sample and found it reliably predicts the effect of shortening observing cadence with errors in the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
