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20242026
most citedRadiometer Calibration using Machine Learning

3 citations · 4 across the 8 of their papers we have counts for

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astro-ph.IM2026

Scalable Bayesian data curation for next-generation radio experiments

S. A. K. Leeney, E. de Lera Acedo, W. J. Handley +42

Next-generation radio telescopes produce data volumes that preclude manual quality assessment, yet data curation remains essential for science. We present a general, fully automati…

astro-ph.IM2026

Optimisation of calibration sources for global 21-cm experiments: the REACH case

Adarsh Kumar Dash, Dominic Anstey, Harry T. J. Bevins +41

The spin-flip 21-cm signal from the Cosmic Dawn and the Epoch of Reionization is an essential probe of the conditions that led to the formation of the first luminous objects in the…

astro-ph.CO2026

Impact of Antenna Structure and Orientation on Forward-Modelled Global 21 cm Signal Recovery

Joe H. N. Pattison, John M. Cumner, Dominic J. Anstey +4

The redshifted 21 cm absorption trough from cosmic atomic hydrogen is one of the most promising probes of the early Universe, but its detection is challenged by bright foregrounds…

astro-ph.IM2026

Circuit Modeling for In Situ 21 cm Radiometer Calibration

Gary Vincent Charles Allen, Saurabh Pegwal, Dirk de Villiers +42

Recent experiments in cosmology, particularly those aimed at detecting the faint, redshifted, global 21 cm hydrogen line (depth < ~200 mK, z > 7.5), have imposed stringent new requ…

astro-ph.IM2026

Optimizing Foreground Modelling for Global 21cm Cosmology with GPU-Accelerated Nested Sampling

Jacob L. Tutt, Peter H. Sims, Joe H. N. Pattison +3

The global 21-cm signal provides a powerful probe of early-Universe astrophysics, but its detection is hindered by Galactic foregrounds that are orders of magnitude brighter than t…