Validation of the HERA Phase i Epoch of Reionization 21 cm Power Spectrum Software Pipeline

James E. Aguirre, Steven G. Murray, Robert Pascua, Zachary E. Martinot, Jacob Burba, Joshua S. Dillon, Daniel C. Jacobs, Nicholas S. Kern, Piyanat Kittiwisit, Matthew Kolopanis, Adam Lanman, Adrian Liu, Lily Whitler, Zara Abdurashidova, Paul Alexander, Zaki S. Ali, Yanga Balfour, Adam P. Beardsley, Gianni Bernardi, Tashalee S. BillingsJudd D. Bowman, Richard F. Bradley, Philip Bull, Steve Carey, Chris L. Carilli, Carina Cheng, David R. Deboer, Matt Dexter, Eloy De Lera Acedo, John Ely, Aaron Ewall-Wice, Nicolas Fagnoni, Randall Fritz, Steven R. Furlanetto, Kingsley Gale-Sides, Brian Glendenning, Deepthi Gorthi, Bradley Greig, Jasper Grobbelaar, Ziyaad Halday, Bryna J. Hazelton, Jacqueline N. Hewitt, Jack Hickish, Austin Julius, Joshua Kerrigan, Saul A. Kohn, Paul La Plante, Telalo Lekalake, David Lewis, David Macmahon, Lourence Malan, Cresshim Malgas, Matthys Maree, Eunice Matsetela, Andrei Mesinger, Mathakane Molewa, Miguel F. Morales, Tshegofalang Mosiane, Abraham R. Neben, Bojan Nikolic, Aaron R. Parsons, Nipanjana Patra, Samantha Pieterse, Jonathan C. Pober, Nima Razavi-Ghods, Jon Ringuette, James Robnett, Kathryn Rosie, Mario G. Santos, Peter Sims, Saurabh Singh, Craig Smith, Angelo Syce, Nithyanandan Thyagarajan, Peter K.G. Williams, Haoxuan Zheng

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


We describe the validation of the HERA Phase I software pipeline by a series of modular tests, building up to an end-to-end simulation. The philosophy of this approach is to validate the software and algorithms used in the Phase I upper-limit analysis on wholly synthetic data satisfying the assumptions of that analysis, not addressing whether the actual data meet these assumptions. We discuss the organization of this validation approach, the specific modular tests performed, and the construction of the end-to-end simulations. We explicitly discuss the limitations in scope of the current simulation effort. With mock visibility data generated from a known analytic power spectrum and a wide range of realistic instrumental effects and foregrounds, we demonstrate that the current pipeline produces power spectrum estimates that are consistent with known analytic inputs to within thermal noise levels (at the 2σ level) for k > 0.2h Mpc-1 for both bands and fields considered. Our input spectrum is intentionally amplified to enable a strong "detection"at k ∼ 0.2 h Mpc-1 - at the level of ∼25σ - with foregrounds dominating on larger scales and thermal noise dominating at smaller scales. Our pipeline is able to detect this amplified input signal after suppressing foregrounds with a dynamic range (foreground to noise ratio) of ⪆107. Our validation test suite uncovered several sources of scale-independent signal loss throughout the pipeline, whose amplitude is well-characterized and accounted for in the final estimates. We conclude with a discussion of the steps required for the next round of data analysis.

Original languageEnglish (US)
Article number85
JournalAstrophysical Journal
Issue number2
StatePublished - Jan 10 2022

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science


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