Article: Savransky, D; (2015) “Sequential Covariance Calculation for Exoplanet Image Processing”, Astrophysical Journal, 800 (2)
Abstract: Direct imaging of exoplanets involves the extraction of very faint signals from highly noisy data sets, with noise that often exhibits significant spatial, spectral, and temporal correlations. As a result, a large number of post-processing algorithms have been developed in order to optimally decorrelate the signal from the noise. In this paper, we explore four such closely related algorithms, all of which depend heavily on the calculation of covariances between large data sets of imaging data. We discuss the similarities and differences between these methods, and demonstrate how the use sequential calculation techniques can significantly improve their computational efficiencies.
Funding Acknowledgement: U.S. Department of Energy by Lawrence Livermore National Laboratory [DE-AC52-07NA27344]
Funding Text: Many thanks to the attendees of the 2012 Exoplanet Imaging Workshop, and especially Lisa Poyneer, Harry Barret, Luca Caucci, Laurent Pueyo, Remi Soummer, Christian Marois, and Dimitri Mawet for many useful discussions and patient explanations. Thanks also to Bruce Macintosh for his very helpful comments and suggestions and to Jean-Baptiste Ruffio for his feedback. Portions of this work were performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.