Data Reduction and Image Reconstruction Techniques for Non-redundant Masking
AffiliationUniv Arizona, Astron Dept
Keywordsmethods: data analysis
techniques: high angular resolution
techniques: image processing techniques: interferometric
MetadataShow full item record
PublisherIOP PUBLISHING LTD
CitationData Reduction and Image Reconstruction Techniques for Non-redundant Masking 2017, 233 (1):9 The Astrophysical Journal Supplement Series
Rights© 2017. The American Astronomical Society. All rights reserved.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractThe technique of non-redundant masking (NRM) transforms a conventional telescope into an interferometric array. In practice, this provides a much better constrained point-spread function than a filled aperture and thus higher resolution than traditional imaging methods. Here, we describe an NRM data reduction pipeline. We discuss strategies for NRM observations regarding dithering patterns and calibrator selection. We describe relevant image calibrations and use example Large Binocular Telescope data sets to show their effects on the scatter in the Fourier measurements. We also describe the various ways to calculate Fourier quantities, and discuss different calibration strategies. We present the results of image reconstructions from simulated observations where we adjust prior images, weighting schemes, and error bar estimation. We compare two imaging algorithms and discuss implications for reconstructing images from real observations. Finally, we explore how the current state of the art compares to next-generation Extremely Large Telescopes.
VersionFinal published version
SponsorsNational Science Foundation under A.A.G ; National Science Foundation [1228509, DGE-1143953]