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An Empirical Bayesian Approach to Limb Darkening in Modeling WASP-121b Transit Light Curves

Yang, Fan and Long, Richard J. and Liu, Ji-feng and Shan, Su-su and Guo, Rui and Zhang, Bo and Yi, Tuan and Zheng, Ling-Lin and Zhao, Zhi-Chao (2021) An Empirical Bayesian Approach to Limb Darkening in Modeling WASP-121b Transit Light Curves. Astronomical Journal, 161 (6). Art. No. 294. ISSN 0004-6256. doi:10.3847/1538-3881/abf92f.

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We present a novel, iterative method using an empirical Bayesian approach for modeling the limb-darkened WASP-121b transit from the TESS light curve. Our method is motivated by the need to improve R_p/R_* estimates for exoplanet atmosphere modeling and is particularly effective with the limb-darkening (LD) quadratic law requiring no prior central value from stellar atmospheric models. With the nonlinear LD law, the method has all the advantages of not needing atmospheric models but does not converge. The iterative method gives a different R_p/R_* for WASP-121b at a significance level of 1σ when compared with existing noniterative methods. To assess the origins and implications of this difference, we generate and analyze light curves with known values of the LD coefficients (LDCs). We find that noniterative modeling with LDC priors from stellar atmospheric models results in an inconsistent R_p/R_* at a 1.5σ level when the known LDC values are the same as those previously found when modeling real data by the iterative method. In contrast, the LDC values from the iterative modeling yield the correct value of R_p/R_* to within 0.25σ. For more general cases with different known inputs, Monte Carlo simulations show that the iterative method obtains unbiased LDCs and correct R_p/R_* to within a significance level of 0.3σ. Biased LDC priors can cause biased LDC posteriors and lead to bias in the R_p/R_* of up to 0.82%, 2.5σ for the quadratic law and 0.32%, 1.0σ for the nonlinear law. Our improvement in R_p/R_* estimation is important when analyzing exoplanet atmospheres.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Yang, Fan0000-0002-6039-8212
Long, Richard J.0000-0002-8559-0067
Shan, Su-su0000-0002-5744-2016
Guo, Rui0000-0001-5536-0669
Zhang, Bo0000-0002-6434-7201
Yi, Tuan0000-0002-5839-6744
Additional Information:© 2021. The American Astronomical Society. Received 2020 September 17; revised 2021 April 14; accepted 2021 April 15; published 2021 June 3. Data Availability. The data underlying this paper are available in the paper and its online supplementary material. This work made use of Astroquery and the NASA Exoplanet Archive. We would like to thank Ranga-Ram Chary for many fruitful discussions and Juan Carlos Segovia for very useful contributions. We also thank You-Jun Lu for feedback on our work. F.Y., J.-F.L., and S.-S.S. acknowledge funding from the National Science Fund for Distinguished Young Scholars (No. 11425313), National Key Research and Development Program of China (No. 2016YFA0400800), and National Natural Science Foundation of China (NSFC.11988101)
Group:Infrared Processing and Analysis Center (IPAC)
Funding AgencyGrant Number
National Science Fund for Distinguished Young Scholars11425313
National Key Research and Development Program of China2016YFA0400800
National Natural Science Foundation of China11988101
Subject Keywords:Exoplanet atmospheres; Exoplanet detection methods; Transit photometry; Exoplanet systems
Issue or Number:6
Classification Code:Unified Astronomy Thesaurus concepts: Exoplanet atmospheres (487); Exoplanet detection methods (489); Transit photometry (1709); Exoplanet systems (484)
Record Number:CaltechAUTHORS:20210604-111534656
Persistent URL:
Official Citation:Fan Yang et al 2021 AJ 161 294
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109382
Deposited By: George Porter
Deposited On:07 Jun 2021 15:16
Last Modified:16 Nov 2021 19:35

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