Hydrogen intensity mapping with MeerKAT: Preserving cosmological signal by optimising contaminant separation^⋆

¹ INAF – Osservatorio Astronomico di Trieste, Via G.B. Tiepolo 11, 34131 Trieste, Italy
² IFPU – Institute for Fundamental Physics of the Universe, Via Beirut 2, 34151 Trieste, Italy
³ Instituto de Física de Cantabria (IFCA), CSIC-Univ. de Cantabria, Avda. de los Castros s/n, E-39005 Santander, Spain
⁴ Jodrell Bank Centre for Astrophysics, Department of Physics & Astronomy, The University of Manchester, Manchester M13 9PL, UK
⁵ Department of Physics and Astronomy, University of the Western Cape, Robert Sobukwe Road, Cape Town 7535, South Africa
⁶ Shanghai Astronomical Observatory, Chinese Academy of Sciences, 80 Nandan Road, Shanghai 200030, China
⁷ Instituto de Astrofisica e Ciências do Espaço, Universidade do Porto CAUP, Rua das Estrelas, PT4150-762 Porto, Portugal
⁸ Institute of Astronomy, Madingley Road, Cambridge CB3 0HA, UK
⁹ Liaoning Key Laboratory of Cosmology and Astrophysics, College of Sciences, Northeastern University, Shenyang 110819, China
¹⁰ Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ, UK
¹¹ Higgs Centre for Theoretical Physics, School of Physics and Astronomy, University of Edinburgh, Edinburgh EH9 3FD, UK
¹² Observatoire de la Côte d’Azur, Laboratoire Lagrange, Bd de l’Observatoire, CS 34229, 06304 Nice cedex 4, France

^⋆⋆ Corresponding author: isabella.carucci@inaf.it

Received: 16 December 2024
Accepted: 24 August 2025

Abstract

Removing contaminants is a delicate, yet crucial step in neutral hydrogen (H I) intensity mapping and often considered the technique’s greatest challenge. Here, we address this challenge by analysing H I intensity maps of about 100 deg² at redshift z ≈ 0.4 collected by the MeerKAT radio telescope, an SKA Observatory (SKAO) precursor, with a combined 10.5-hour observation. Using unsupervised statistical methods, we removed the contaminating foreground emission and systematically tested, step-by-step, some common pre-processing choices to facilitate the cleaning process. We also introduced and tested a novel multiscale approach: the data were redundantly decomposed into subsets referring to different spatial scales (large and small), where the cleaning procedure was performed independently. We confirm the detection of the H I cosmological signal in cross-correlation with an ancillary galactic data set, without the need to correct for signal loss. In the best set-up we achieved, we were able to constrain the H I distribution through the combination of its cosmic abundance (Ω_H I) and linear clustering bias (b_H I) up to a cross-correlation coefficient (r). We measured Ω_H Ib_H Ir = [0.93 ± 0.17] × 10⁻³ with a ≈6σ confidence, which is independent of scale cuts at both edges of the probed scale range (0.04 ≲ k ≲ 0.3 h Mpc⁻¹), corroborating its robustness. Our new pipeline has successfully found an optimal compromise in separating contaminants without incurring a catastrophic signal loss. This development instills an added degree of confidence in the outstanding science we can deliver with MeerKAT on the path towards H I intensity mapping surveys with the full SKAO.