Predicting Exoplanet Masses and Radii: A Nonparametric Approach

• Published in: The Astrophysical journal Vol. 869; no. 1; pp. 5 - 20
• Main Authors: Ning, Bo, Wolfgang, Angie, Ghosh, Sujit
• Format: Journal Article
• Language: English
• Published: Philadelphia The American Astronomical Society 10.12.2018; IOP Publishing
• Subjects: Astrophysics; Datasets; Estimating techniques; Extrasolar planets; methods: statistical; Nonparametric statistics; Planetary composition; planets and satellites: composition; Polynomials; Power law; Statistical methods
• ISSN: 0004-637X; 1538-4357
• DOI: 10.3847/1538-4357/aaeb31

A fundamental endeavor in exoplanetary research is to characterize the bulk compositions of planets via measurements of their masses and radii. With future sample sizes of hundreds of planets to come from TESS and PLATO, we develop a statistical method that can flexibly yet robustly characterize these compositions empirically, via the exoplanet M-R relation. Although the M-R relation has been explored in many prior works, they mostly use a power-law model, with assumptions that are not flexible enough to capture important features in current and future M-R diagrams. To address these shortcomings, a nonparametric approach is developed using a sequence of Bernstein polynomials. We demonstrate the benefit of taking the nonparametric approach by benchmarking our findings with previous work and showing that a power law can only reasonably describe the M-R relation of the smallest planets and that the intrinsic scatter can change non-monotonically with different values of a radius. We then apply this method to a larger data set, consisting of all the Kepler observations in the NASA Exoplanet Archive. Our nonparametric approach provides a tool to estimate the M-R relation by incorporating heteroskedastic measurement errors into the model. As more observations will be obtained in the near future, this approach can be used with the provided R code to analyze a larger data set for a better understanding of the M-R relation.