New techniques for high-contrast imaging with ADI: The ACORNS-ADI seeds data reduction pipeline

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. IyeM. Janson, R. Kandori, G. R. Knapp, T. Kudo, N. Kusakabe, M. Kuzuhara, J. Kwon, T. Matsuo, S. Miyama, J. I. Morino, A. Moro-Martín, 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

Research output: Contribution to journalArticle

46 Citations (Scopus)

Abstract

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 ∼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.

Original languageEnglish
Article number183
JournalAstrophysical Journal
Volume764
Issue number2
DOIs
Publication statusPublished - 2013 Feb 20

Keywords

  • methods: data analysis
  • planetary systems
  • techniques: high angular resolution
  • techniques: image processing

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

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    Brandt, T. D., McElwain, M. W., Turner, E. L., Abe, L., Brandner, W., Carson, J., Egner, S., Feldt, M., Golota, T., Goto, M., Grady, C. A., Guyon, O., Hashimoto, J., Hayano, Y., Hayashi, M., Hayashi, S., Henning, T., Hodapp, K. W., Ishii, M., ... Tamura, M. (2013). New techniques for high-contrast imaging with ADI: The ACORNS-ADI seeds data reduction pipeline. Astrophysical Journal, 764(2), [183]. https://doi.org/10.1088/0004-637X/764/2/183