By detecting light from extrasolar planets,we can measure their compositions and bulk physical properties. The technologies used to make these measurements are still in their infancy, and a lack of self-consistency suggests that previous observations have underestimated their systemic errors.
We demonstrate a statistical method, newly applied to exoplanet characterization, which uses a Bayesian formalism to account for underestimated errorbars. We use this method to compare photometry of a substellar companion, GJ 758b, with custom atmospheric models. Our method produces a probability distribution of atmospheric model parameters including temperature, gravity, cloud model (fsed), and chemical abundance for GJ 758b. This distribution is less sensitive to highly variant data, and appropriately reflects a greater uncertainty on parameter fits.
Cassandra S. Henderson, Andrew J. Skemer, Caroline V. Morley, Jonathan J. Fortney
(Submitted on 14 Jun 2017)
Comments: Accepted to MNRAS
Subjects: Earth and Planetary Astrophysics (astro-ph.EP); Instrumentation and Methods for Astrophysics (astro-ph.IM)
DOI: 10.1093/mnras/stx1495
Cite as: arXiv:1706.04581 [astro-ph.EP] (or arXiv:1706.04581v1 [astro-ph.EP] for this version)
Submission history
From: Cassandra Henderson
[v1] Wed, 14 Jun 2017 16:43:39 GMT (554kb,D)
https://arxiv.org/abs/1706.04581
