NEW TECHNIQUES FOR HIGH-CONTRAST IMAGING WITH ADI: THE ACORNS-ADI SEEDS DATA REDUCTION PIPELINE

Journal Article · Wed Feb 20 00:00:00 EST 2013 · Astrophysical Journal

DOI:https://doi.org/10.1088/0004-637X/764/2/183· OSTI ID:22167702

Brandt, Timothy D.; Turner, Edwin L. ^[1]; McElwain, Michael W.; Grady, C. A. ^[2]; Abe, L. ^[3]; Brandner, W.; Feldt, M.; Henning, T. ^[4]; Carson, J. ^[5]; Egner, S.; Golota, T.; Guyon, O.; Hayano, Y.; Hayashi, S.; Ishii, M. ^[6]; Goto, M. ^[7]; Hashimoto, J.; Hayashi, M.; Iye, M. ^[8]; Hodapp, K. W. ^[9] ; others, and

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1. Department of Astrophysical Sciences, Princeton University, Princeton, NJ (United States)
2. Goddard Space Flight Center, Greenbelt, MD (United States)
3. Laboratoire Hippolyte Fizeau, Nice (France)
4. Max Planck Institute for Astronomy, Heidelberg (Germany)
5. College of Charleston, Charleston, SC (United States)
6. Subaru Telescope, Hilo, HI (United States)
7. Universitaets-Sternwarte Muenchen, Ludwig-Maximilians-Universitaet, Munich (Germany)
8. National Astronomical Observatory of Japan, Tokyo (Japan)
9. Institute for Astronomy, University of Hawai'i, Hilo, HI (United States)

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 register saturated images, a trimmed mean for combining an image sequence that reduces noise by up to {approx}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 written in python. It is efficient and open-source, and includes several optional features which may improve performance on data from other instruments. ACORNS-ADI requires minimal modification to reduce data from instruments other than HiCIAO. It is freely available for download at www.github.com/t-brandt/acorns-adi under a Berkeley Software Distribution (BSD) license.

• OSTI ID: 22167702
• Journal Information: Astrophysical Journal, Vol. 764, Issue 2; Other Information: Country of input: International Atomic Energy Agency (IAEA); ISSN 0004-637X
• Country of Publication: United States
• Language: English

Related Subjects

79 ASTROPHYSICS
COSMOLOGY AND ASTRONOMY
A CODES
ALGORITHMS
ASTRONOMY
ASTROPHYSICS
CALIBRATION
DATA ANALYSIS
IMAGE PROCESSING
IMAGES
L CODES
PLANETS
SENSITIVITY
STARS