Application of an Empirical Bayesian Technique to Systematic Error Correction and Data Conditioning of Kepler Photometry

Details Application of an Empirical Bayesian Technique to Systematic Error Correction and Data Conditioning of Kepler Photometry Application of an Empirical Bayesian Technique to Systematic Error Correction and Data Conditioning of Kepler Photometry

May 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011aas...21822707s&link_type=abstract

American Astronomical Society, AAS Meeting #218, #227.07; Bulletin of the American Astronomical Society, Vol. 43, 2011

Astronomy and Astrophysics

Astrophysics

Scientific paper

We present a Bayesian Maximum A Posteriori (MAP) approach to systematic error removal in Kepler photometric data, in which a subset of highly correlated stars is used to establish the range of "reasonable” robust fit parameters, and hence mitigate the loss of astrophysical signal and noise injection on transit time scales (<3d), which afflict Least Squares (LS) fitting. A numerical and empirical approach is taken where the Bayesian Prior PDFs are generated from fits to the light curve distributions themselves versus an analytical approach, which uses a Gaussian fit to the Priors. Along with the systematic effects there are also Sudden Pixel Sensitivity Dropouts (SPSDs) resulting in abrupt steps in the light curves that should be removed. A joint fitting technique is therefore presented that simultaneously applies MAP and SPSD removal. The concept will be illustrated in detail by applying MAP to publicly available Kepler data, and give an overview of its application to all Kepler data collected through the present. We show that the light curve correlation matrix after treatment is diagonal, and present diagnostics such as correlation coefficient histograms, singular value spectra, and principal component plots. The benefits of MAP is shown applied to variable stars with RR Lyrae, harmonic, chaotic, and eclipsing binary waveforms, and examine the impact of MAP on transit waveforms and detectability of transiting planets. We conclude with a discussion of current work on selecting input vectors for the design matrix, generating the Prior PDFs and suppressing high-frequency noise injection with Bandpass Filtering. Funding for this work is provided by the NASA Science Mission Directorate.

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