Implemented transit models#

PyTransit implements a set of transit models that all share a common interface that is described in more detail in Transit Models.

Road Runner model#

RoadRunner (pytransit.RoadRunnerModel) is a fast and flexible transit model presented in Parviainen (accepted to MNRAS 2020). I’ll write a proper documentation soon, but these example notebooks should help you up to speed until then

Uniform model#

The uniform model (pytransit.UniformModel and pytransit.UniformModelCL) reproduces an exoplanet transit over a uniform disc. This model is useful when modelling secondary eclipses, or when the effects from the stellar limb darkening can be ignored.

Quadratic model#

The quadratic transit model (pytransit.QuadraticModel and pytransit.QuadraticModelCL) reproduces an exoplanet transit over a stellar disk with the limb darkening modelled by a quadratic limb darkening model, as presented in Mandel & Agol (ApJ 580, 2001).

Oblate star model#


Power-2 model#

Power-2 model (pytransit.QPower2Model and pytransit.QPower2ModelCL) implements the transit model with a power-2 law limb darkening profile presented by Maxted & Gill (A&A 622, A33 2019). The model is fast to evaluate and aims to model the limb darkening accurately for cool stars.


  • Accurate limb darkening model for cool stars.

  • Fast to evaluate.

General model#

The general model (pytransit.GeneralModel) implements the flexible transit model presented by Giménez (A&A 450, 2006). The stellar limb darkening follows a “general” limb darkening model, and the accuracy of limb darkening can be increased as needed.

The model is calculated using a polynomial series and both the number of polynomials npoly and the number of limb darkening coefficients nldc can be set in the initialisation. Higher npoly leads to a more accurate transit model, but also increases computation time. Increasing the number of limb darkening coefficients doesn’t significantly increase computation time, but


  • A flexible model that can model limb darkening accurately.

  • Somewhat slower to evaluate than the specialized models.

  • PyTransit implements a special “transmission spectroscopy mode” for the general model that accelerates the transit model evaluation significantly for transmission spectroscopy where the light curves are computed from a spectroscopic time series.

  • The four-coefficient model presented in Mandel & Agol (ApJ 580, 2001) is not implemented in PyTransit since the Giménez model offers the same functionality with higher flexibility.

Chromosphere model#

Optically thin shell model (pytransit.ChromosphereModel and pytransit.ChromosphereModelCL) by Schlawin et al. (ApJL 722, 2010) to model a transit over a chromosphere.