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    Automated Detection of Antenna Malfunctions in Large-N Interferometers: A Case Study With the Hydrogen Epoch of Reionization Array

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    Storer_Hydrogen Epoch of Reionization_2021.pdf (31.47Mb)
    Date
    2022
    Author
    Storer, Dara
    Dillon, Joshua S.
    Kittiwisit, Piyanat
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    Abstract
    We present a framework for identifying and flagging malfunctioning antennas in large radio interferometers. We outline two distinct categories of metrics designed to detect outliers along known failure modes of large arrays: cross-correlation metrics, based on all antenna pairs, and auto-correlation metrics, based solely on individual antennas. We define and motivate the statistical framework for all metrics used, and present tailored visualizations that aid us in clearly identifying new and existing systematics. We implement these techniques using data from 105 antennas in the Hydrogen Epoch of Reionization Array (HERA) as a case study. Finally, we provide a detailed algorithm for implementing these metrics as flagging tools on real data sets.
    URI
    https://doi. org/10.1029/2021RS007376
    http://hdl.handle.net/10566/7298
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