I. P. Carucci, J. L. Bernal, S. Cunnington, M. G. Santos, J. Wang, J. Fonseca, K. Grainge, M. O. Irfan, Y. Li, A. Pourtsidou, M. Spinelli, L. Wolz
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 (ΩH I) and linear clustering bias (bH I) up to a cross-correlation coefficient (r). We measured ΩH IbH 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. ⋆ On behalf of the MeerKLASS Collaboration.
Keywords
methods: data analysis / methods: statistical / cosmology: observations / large-scale structure of Universe
Astronomy & Astrophysics
Volume 703, Article Number A222, Number of pages 25
2025 November
