Journal Article

A Gaussian process framework for modelling instrumental systematics: application to transmission spectroscopy

N. P. Gibson, S. Aigrain, S. Roberts, T. M. Evans, M. Osborne and F. Pont

in Monthly Notices of the Royal Astronomical Society

Published on behalf of The Royal Astronomical Society

Volume 419, issue 3, pages 2683-2694
Published in print January 2012 | ISSN: 0035-8711
Published online January 2012 | e-ISSN: 1365-2966 | DOI:
A Gaussian process framework for modelling instrumental systematics: application to transmission spectroscopy

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Transmission spectroscopy, which consists of measuring the wavelength-dependent absorption of starlight by a planet’s atmosphere during a transit, is a powerful probe of atmospheric composition. However, the expected signal is typically orders of magnitude smaller than instrumental systematics and the results are crucially dependent on the treatment of the latter. In this paper, we propose a new method to infer transit parameters in the presence of systematic noise using Gaussian processes, a technique widely used in the machine learning community for Bayesian regression and classification problems. Our method makes use of auxiliary information about the state of the instrument, but does so in a non-parametric manner, without imposing a specific dependence of the systematics on the instrumental parameters, and naturally allows for the correlated nature of the noise. We give an example application of the method to archival NICMOS transmission spectroscopy of the hot Jupiter HD 189733, which goes some way towards reconciling the controversy surrounding this data set in the literature. Finally, we provide an appendix giving a general introduction to Gaussian processes for regression, in order to encourage their application to a wider range of problems.

Keywords: methods: data analysis; techniques: spectroscopic; stars: individual: HD 189733; planetary systems

Journal Article.  8265 words.  Illustrated.

Subjects: Astronomy and Astrophysics

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