Directed follow-up strategy of low-cadence photometric surveys in Search of transiting exoplanets - I. Bayesian approach for adaptive scheduling

TL;DR

This paper introduces a Bayesian method for optimizing follow-up observations in low-cadence photometric surveys to improve the detection of transiting exoplanets, even when initial data is inconclusive.

Contribution

It presents a novel Bayesian approach for adaptive scheduling of follow-up observations in low-cadence surveys, enhancing exoplanet transit detection efficiency.

Findings

Simulated cases demonstrate the effectiveness of the approach.

Method can be applied to Gaia mission data for improved exoplanet detection.

Approach increases the likelihood of detecting transits in low-cadence surveys.

Abstract

We propose a novel approach to utilize low-cadence photometric surveys for exoplanetary transit search. Even if transits are undetectable in the survey database alone, it can still be useful for finding preferred times for directed follow-up observations that will maximize the chances to detect transits. We demonstrate the approach through a few simulated cases. These simulations are based on the Hipparcos Epoch Photometry data base, and the transiting planets whose transits were already detected there. In principle, the approach we propose will be suitable for the directed follow-up of the photometry from the planned Gaia mission, and it can hopefully significantly increase the yield of exoplanetary transits detected, thanks to Gaia.