Bayesian estimation of cross-coupling and reflection systematics in 21cm array visibility data

Abstract Observations with radio arrays that target the 21-cm signal originating from the early Universe suffer from a variety of systematic effects. An important class of these are reflections and spurious couplings between antennas. We apply a Hamiltonian Monte Carlo sampler to the modelling and mitigation of these systematics in simulated Hydrogen Epoch of Reionisation Array (HERA) data. This method allows us to form statistical uncertainty estimates for both our models and the recovered visibilities, which is an important ingredient in establishing robust upper limits on the Epoch of Reionisation (EoR) power spectrum. In cases where the noise is large compared to the EoR signal, this approach can constrain the systematics well enough to mitigate them down to the noise level for both systematics studied. Incoherently averaging the recovered power spectra can further reduce the noise and improve recovery. Where the noise level is lower than the EoR, our modelling can mitigate the majority of the reflections and coupling with there being only a minor level of residual systematics. Our approach performs similarly to existing filtering/fitting techniques used in the HERA pipeline, but with the added benefit of rigorously propagating uncertainties. In all cases it does not significantly attenuate the underlying signal.

Authors

Institutions

Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2024-09-27
DOI
https://doi.org/10.1093/mnras/stae2242
Citations
3
Primary Topic
Advanced Optical Sensing Technologies
Type
article
Field-Weighted Citation Impact
1.52

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bayesian estimation of cross-coupling and reflection systematics in 21cm array visibility data

Bradley Marero, Eloy de Lera Acedo, Hans Nuwegeld, Tashalee S. Billings et al.
3 citations
Monthly Notices of the Royal Astronomical Society
Advanced Optical Sensing Technologies
1.52
article

Bayesian estimation of cross-coupling and reflection systematics in 21cm array visibility data

Bradley Marero, Eloy de Lera Acedo, Hans Nuwegeld, Tashalee S. Billings, James Robnett, Piyanat Kittiwisit, Mário G. Santos, M. F. Morales, Ziyaad Halday, Randall Fritz, Adrian Liu, Aaron Ewall‐Wice, Jackson Sipple, Jacob Burba, Joshua Kerrigan, G. Bernardi, Zaki S. Ali, Nico Eksteen, Philip Bull, Anita Loots, Joshua S. Dillon, Peter Sims, David R. DeBoer, J. Hickish, Zara Abdurashidova, Mathakane Molewa, Cresshim Malgas, Lourence Malan, Adam P. Beardsley, Steven Murray, N. Razavi‐Ghods, Adam Lanman, Keith Malgas, Nipanjana Patra, Hilton Swarts, Daniel Jacobs, Deepthi Gorthi, Tshegofalang Mosiane, Richard F. Bradley, David H. E. MacMahon, Nicholas S. Kern, Matthew Kolopanis, Paul La Plante, C. L. Carilli, Nicolas Fagnoni, Samantha Pieterse, MacCalvin Kariseb, Yanga Balfour, Zachary E. Martinot, Nithyanandan Thyagarajan, Pieter van Wyngaarden, Bradley Greig, Christopher Cain, Brian Glendenning, Jasper Grobbelaar, Haimei Zheng, Saul A. Kohn, James Aguirre, Steven R. Furlanetto, Andrei Mesinger, Bojan Nikolic, Paul Alexander, Tyrone Adams, Peter K. G. Williams, Geoff Murphy, Jacqueline N. Hewitt, B. J. Hazelton, Abraham R. Neben, Judd D. Bowman, Rushelle Baartman, Aaron R. Parsons, Kingsley Gale‐Sides, Steven Carey, Craig Smith, Kathryn Rosie, Matt Dexter, Austin Julius, Carina Cheng, John Ely
article en
3 citations

Abstract

Abstract Observations with radio arrays that target the 21-cm signal originating from the early Universe suffer from a variety of systematic effects. An important class of these are reflections and spurious couplings between antennas. We apply a Hamiltonian Monte Carlo sampler to the modelling and mitigation of these systematics in simulated Hydrogen Epoch of Reionisation Array (HERA) data. This method allows us to form statistical uncertainty estimates for both our models and the recovered visibilities, which is an important ingredient in establishing robust upper limits on the Epoch of Reionisation (EoR) power spectrum. In cases where the noise is large compared to the EoR signal, this approach can constrain the systematics well enough to mitigate them down to the noise level for both systematics studied. Incoherently averaging the recovered power spectra can further reduce the noise and improve recovery. Where the noise level is lower than the EoR, our modelling can mitigate the majority of the reflections and coupling with there being only a minor level of residual systematics. Our approach performs similarly to existing filtering/fitting techniques used in the HERA pipeline, but with the added benefit of rigorously propagating uncertainties. In all cases it does not significantly attenuate the underlying signal.

Monthly Notices of the Royal Astronomical Society
American Astronomical Society (US), Commonwealth Scientific and Industrial Research Organisation (AU), Space Science Institute (US), Scuola Normale Superiore (IT), University of California, Los Angeles (US), The University of Melbourne (AU), University of Washington (US), Rhodes University (ZA), University of Cambridge (GB), National Radio Astronomy Observatory (US), Brown University (US), University of Manchester (GB), Istituto di Radioastronomia di Bologna (IT), South African Radio Astronomy Observatory (ZA), Center for Astrophysics Harvard & Smithsonian (US), McGill University (CA), Arizona State University (US), Winona State University (US), Massachusetts Institute of Technology (US), University of Pennsylvania (US), University of the Western Cape (ZA), University of California, Berkeley (US)
European Commission, National Research Foundation, University of Pretoria, University of the Western Cape, Universiteit Stellenbosch, Cape Peninsula University of Technology, University of Cape Town, Science and Technology Facilities Council
Life in Land
Openalex Percentile: Top 15%
Advanced Optical Sensing Technologies
1.52
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.