# An Investigation into Exoplanet Transits and Uncertainties

## TL;DR

This paper presents a simple transit model tested against Kepler data, utilizing MCMC for error estimation, and applies it to four Kepler candidate systems to derive new results with quantified uncertainties.

## Contribution

It introduces a transit modeling approach combined with MCMC error analysis and applies it to new Kepler data, providing improved uncertainty estimates.

## Key findings

- Model matches published results for known systems.
- MCMC effectively estimates errors, especially for high S/N data.
- New results for four Kepler candidate systems with error estimates.

## Abstract

A simple transit model is described along with tests of this model against published results for 4 exoplanet systems (Kepler-1, 2, 8, and 77). Data from the Kepler mission are used. The Markov Chain Monte Carlo (MCMC) method is applied to obtain realistic error estimates. Optimization of limb darkening coefficients is subject to data quality. It is more likely for MCMC to derive an empirical limb darkening coefficient for light curves with S/N (signal to noise) above 15. Finally, the model is applied to Kepler data for 4 Kepler candidate systems (KOI 760.01, 767.01, 802.01, and 824.01) with previously unpublished results. Error estimates for these systems are obtained via the MCMC method.