Probabilistic Mass-Radius Relationship for Sub-Neptune-Sized Planets
Angie Wolfgang, Leslie A. Rogers, Eric B. Ford

TL;DR
This paper introduces the first probabilistic mass-radius relationship for sub-Neptune-sized exoplanets, accounting for intrinsic scatter and uncertainties, using a Bayesian framework to improve mass estimates from radii.
Contribution
It presents a novel Bayesian probabilistic model for the mass-radius relation of sub-Neptune planets, incorporating intrinsic dispersion and measurement uncertainties.
Findings
Best-fit power law: M/M_⊕=2.7(R/R_⊕)^1.3
Mass scatter of approximately 1.9 M_⊕
Provides a framework for analyzing dependencies on period and stellar properties
Abstract
The Kepler Mission has discovered thousands of planets with radii , paving the way for the first statistical studies of the dynamics, formation, and evolution of these sub-Neptunes and super-Earths. Planetary masses are an important physical property for these studies, and yet the vast majority of Kepler planet candidates do not have theirs measured. A key concern is therefore how to map the measured radii to mass estimates in this Earth-to-Neptune size range where there are no Solar System analogs. Previous works have derived deterministic, one-to-one relationships between radius and mass. However, if these planets span a range of compositions as expected, then an intrinsic scatter about this relationship must exist in the population. Here we present the first probabilistic mass-radius relationship (M-R relation) evaluated within a Bayesian framework, which both…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astro and Planetary Science · SAS software applications and methods
