Disintegrating Exoplanets: Creating Size Constraints by Statistically Peering Through the Debris
Keith Baka, Everett Schlawin

TL;DR
This study introduces a statistical method to better estimate the true size of disintegrating exoplanets by modeling their lightcurve noise distributions, successfully constraining K2-22b's radius but not Kepler-1520b.
Contribution
It presents a novel approach combining Gaussian and Rayleigh noise modeling with Markov Chain Monte Carlo to improve exoplanet size constraints from complex transit data.
Findings
Constrained K2-22b's radius to approximately 15,000 km.
Failed to constrain Kepler-1520b's radius due to observational challenges.
Demonstrated the effectiveness of joint noise modeling in exoplanet characterization.
Abstract
We study two intriguing exoplanets, Kepler-1520b and K2-22b, that are being disintegrated by their host stars, producing dust and debris pulled from their surface into tails that trail and precede the exoplanets in their orbits, making it difficult to discern the true nature of the objects. Our goal is to constrain the radius of the underlying objects, and while previous studies have done this in the past by selecting shallow transit events, we attempt a new statistical approach to model the intrinsic astrophysical and photon noise distributions simultaneously. We assume that the lightcurve flux distribution is distributed as a convolution of a Gaussian photon noise component and a Raleigh astrophysical component. The Raleigh curve has a finite flux maximum, which we fit with a Hamiltonian Markov Chain. With these methods, a more accurate flux maximum may be estimated, producing a…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Astro and Planetary Science
