Monday, September 17, 2012

1209.3014 (Timothy D. Brandt et al.)

New Techniques for High-Contrast Imaging with ADI: the ACORNS-ADI SEEDS Data Reduction Pipeline    [PDF]

Timothy D. Brandt, Michael W. McElwain, Edwin L. Turner, L. Abe, W. Brandner, J. Carson, S. Egner, M. Feldt, T. Golota, M. Goto, C. A. Grady, O. Guyon, J. Hashimoto, Y. Hayano, M. Hayashi, S. Hayashi, T. Henning, K. W. Hodapp, M. Ishii, M. Iye, M. Janson, R. Kandori, G. R. Knapp, T. Kudo, N. Kusakabe, M. Kuzuhara, J. Kwon, T. Matsuo, S. Miyama, J. -I. Morino, A. Moro-Martin, T. Nishimura, T. -S. Pyo, E. Serabyn, H. Suto, R. Suzuki, M. Takami, N. Takato, H. Terada, C. Thalmann, D. Tomono, M. Watanabe, J. P. Wisniewski, T. Yamada, H. Takami, T. Usuda, M. Tamura
We describe Algorithms for Calibration, Optimized Registration, and Nulling the Star in Angular Differential Imaging (ACORNS-ADI), a new, parallelized software package to reduce high-contrast imaging data, and its application to data from the SEEDS survey. We implement several new algorithms, including a method to centroid saturated images, a trimmed mean for combining an image sequence that reduces noise by up to ~20%, and a robust and computationally fast method to compute the sensitivity of a high-contrast observation everywhere on the field-of-view without introducing artificial sources. We also include a description of image processing steps to remove electronic artifacts specific to Hawaii2-RG detectors like the one used for SEEDS, and a detailed analysis of the Locally Optimized Combination of Images (LOCI) algorithm commonly used to reduce high-contrast imaging data. ACORNS-ADI is efficient and open-source, and includes several optional features which may improve performance on data from other instruments. ACORNS-ADI is freely available for download at www.github.com/t-brandt/acorns-adi under a BSD license.
View original: http://arxiv.org/abs/1209.3014

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