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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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arxiv 2109.12733 v3 pith:SUWNI2XP submitted 2021-09-27 astro-ph.IM astro-ph.CO

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

Dara Storer , Joshua S. Dillon , Daniel C. Jacobs , Miguel F. Morales , Bryna J. Hazelton , Aaron Ewall-Wice , Zara Abdurashidova , James E. Aguirre
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Paul Alexander Zaki S. Ali Yanga Balfour Adam P. Beardsley Gianni Bernardi Tashalee S. Billings Judd D. Bowman Richard F. Bradley Philip Bull Jacob Burba Steven Carey Chris L. Carilli Carina Cheng David R. DeBoer Eloy de Lera Acedo Matt Dexter Scott Dynes John Ely Nicolas Fagnoni Randall Fritz Steven R. Furlanetto Kingsley Gale-Sides Brian Glendenning Deepthi Gorthi Bradley Greig Jasper Grobbelaar Ziyaad Halday Jacqueline N. Hewitt Jack Hickish Tian Huang Alec Josaitis Austin Julius MacCalvin Kariseb Nicholas S. Kern Joshua Kerrigan Piyanat Kittiwisit Saul A. Kohn Matthew Kolopanis Adam Lanman Paul La Plante Adrian Liu Anita Loots David MacMahon Lourence Malan Cresshim Malgas Zachary E. Martinot Andrei Mesinger Mathakane Molewa Tshegofalang Mosiane Steven G. Murray Abraham R. Neben Bojan Nikolic Chuneeta Devi Nunhokee Aaron R. Parsons Robert Pascua Nipanjana Patra Samantha Pieterse Jonathan C. Pober Nima Razavi-Ghods Daniel Riley James Robnett Kathryn Rosie Mario G. Santos Peter Sims Saurabh Singh Craig Smith Jianrong Tan Nithyanandan Thyagarajan Peter K. G. Williams Haoxuan Zheng
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keywords metricsantennasantennaarraycasedataepochflagging
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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.

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