κ Andromedae Hosts a 22 Jupiter Mass SuperJupiter

The Age of the Directly-Imaged Planet Host Star κ Andromedae Determined From Interferometric Observations

Authors:

Jones et al

Abstract:

κ Andromedae, an early type star that hosts a directly imaged low mass companion, is expected to be oblate due to its rapid rotational velocity (vsini = ∼162 km s−1). We observed the star with the CHARA Array's optical beam combiner, PAVO, measuring its size at multiple orientations and determining its oblateness. The interferometric measurements, combined with photometry and this vsini value are used to constrain an oblate star model that yields the fundamental properties of the star and finds a rotation speed that is ∼85\% of the critical rate and a low inclination of ∼30∘. Three modeled properties (the average radius, bolometric luminosity, and equatorial velocity) are compared to MESA evolution models to determine an age and mass for the star. In doing so, we determine an age for the system of 47+27−40 Myr. Based on this age and previous measurements of the companion's temperature, the BHAC15 evolution models imply a mass for the companion of 22+8−9 MJ.

The Measurement, Treatment, and Impact of Spectral Covariance and Bayesian Priors in Integral-Field Spectroscopy of Exoplanets

The Measurement, Treatment, and Impact of Spectral Covariance and Bayesian Priors in Integral-Field Spectroscopy of Exoplanets

Authors:

Greco et al

Abstract:

The recovery of an exoplanet's atmospheric parameters from its spectrum requires accurate knowledge of the spectral errors and covariances. Unfortunately, the complex image processing used in high-contrast integral-field spectrograph (IFS) observations generally produces spectral covariances that are poorly understood and often ignored. In this work, we show how to measure the spectral errors and covariances and include them self-consistently in parameter retrievals. By combining model exoplanet spectra with a realistic noise model generated from GPI early science data, we show that ignoring spectral covariance in high-contrast IFS data can both bias inferred parameters and lead to unreliable confidence regions on those parameters. This problem is made worse by the common practice of scaling the χ2 per degree of freedom to unity; the input parameters then fall outside the 95% confidence regions in as many as ∼80% of noise realizations. Accounting for realistic priors in fully Bayesian parameter retrievals can also have a significant impact on the inferred parameters. As an example, we show that plausible priors on effective temperature and surface gravity can vary by as much as an order of magnitude across the 95% confidence regions appropriate for objects with weak age constraints like GJ 504b and κ And b. Our methods are directly applicable to existing high-contrast IFSs including GPI and SPHERE, as well as upcoming instruments like CHARIS and, ultimately, WFIRST-AFTA.