2015
DOI: 10.1093/mnras/stv1857
|View full text |Cite
|
Sign up to set email alerts
|

ldtk: Limb Darkening Toolkit

Abstract: We present a Python package LDTK that automates the calculation of custom stellar limb darkening (LD) profiles and model-specific limb darkening coefficients (LDC) using the library of PHOENIX-generated specific intensity spectra by Husser et al. (2013). The aim of the package is to facilitate analyses requiring custom generated limb darkening profiles, such as the studies of exoplanet transits-especially transmission spectroscopy, where the transit modelling is carried out for custom narrow passbands-eclipsin… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
192
0
1

Year Published

2016
2016
2021
2021

Publication Types

Select...
6
3
1

Relationship

2
8

Authors

Journals

citations
Cited by 245 publications
(193 citation statements)
references
References 27 publications
0
192
0
1
Order By: Relevance
“…Different from previous EBOP-based models, this implementation uses the analytic method of Mandel & Agol (2002) for the quadratic limb-darkening law. GP-EBOP utilizes the LDtk toolkit (Parviainen & Aigrain 2015), which allows uncertainties in the stellar parameters (effective temperature, surface gravity, and metallicity) to be propagated through the PHOENIX stellar atmosphere models (Husser et al 2013) and into priors on the limbdarkening coefficients. Limb-darkening parameterization within the fitting process follows the triangular sampling method of Kipping (2013).…”
Section: Gp-ebopmentioning
confidence: 99%
“…Different from previous EBOP-based models, this implementation uses the analytic method of Mandel & Agol (2002) for the quadratic limb-darkening law. GP-EBOP utilizes the LDtk toolkit (Parviainen & Aigrain 2015), which allows uncertainties in the stellar parameters (effective temperature, surface gravity, and metallicity) to be propagated through the PHOENIX stellar atmosphere models (Husser et al 2013) and into priors on the limbdarkening coefficients. Limb-darkening parameterization within the fitting process follows the triangular sampling method of Kipping (2013).…”
Section: Gp-ebopmentioning
confidence: 99%
“…Instead, we run a Levenberg-Marquardt minimization on each planet candidate to fit a Mandel & Agol (2002) transit model. The stellar limbdarkening parameters are fixed to values derived using the PyLDTk package 25 (Parviainen & Aigrain 2015) and stellar parameters derived in Section 4.1. We find that this fit gives us a more reliable estimate of the transit ephemerides than TERRA.…”
Section: Triage and Vettingmentioning
confidence: 99%
“…The transit model uses the quadratic limb darkening formalism by Mandel & Agol (2002), and is calculated using PyTransit (Parviainen & Aigrain 2015). PyTransit contains optimisations to compute a transit in multiple passbands with only a minor additional computational cost to the computation of a single passband transit, which reduces the computational burden due to the joint modelling approach.…”
Section: Overviewmentioning
confidence: 99%