When determining the parameters of an exoplanet system, the characteristics of the whole system (star and planet) contribute to the transit shape observed. Without taking into account the limb darkening of the host star appropriately, the planetary radius and impact parameter inferred from the transit shape will be biased.
In this talk I will discuss the features of the methods currently used for modelling limb darkening, and present a new method for sampling limb darkening to use in exoplanet transit fits. Observed stellar parameters are used as constraints for limb darkening and mapped onto a stellar intensity profile through the use of Artificial Neural Networks. I will show how this new method offers a strong physical constraint on the form of the limb darkened stellar profile for the host star directly from stellar atmosphere models, and will prevent bias in the transit parameters introduced from low order limb darkening laws. Ensuring that the form of limb darkening used is physically justified also allows for more robust fitting of third order system effects, such as exo-moons or planetary shape inhomogeneities.