English

SKAO HI Intensity Mapping: Blind Foreground Subtraction Challenge

Cosmology and Nongalactic Astrophysics 2021-11-03 v2

Abstract

Neutral Hydrogen Intensity Mapping (HI IM) surveys will be a powerful new probe of cosmology. However, strong astrophysical foregrounds contaminate the signal and their coupling with instrumental systematics further increases the data cleaning complexity. In this work, we simulate a realistic single-dish HI IM survey of a 50005000~deg2^2 patch in the 9501400950 - 1400 MHz range, with both the MID telescope of the SKA Observatory (SKAO) and MeerKAT, its precursor. We include a state-of-the-art HI simulations and explore different foreground models and instrumental effects such as non-homogeneous thermal noise and beam side-lobes. We perform the first Blind Foreground Subtraction Challenge for HI IM on these synthetic data-cubes, aiming to characterise the performance of available foreground cleaning methods with no prior knowledge of the sky components and noise level. Nine foreground cleaning pipelines joined the Challenge, based on statistical source separation algorithms, blind polynomial fitting, and an astrophysical-informed parametric fit to foregrounds. We devise metrics to compare the pipeline performances quantitatively. In general, they can recover the input maps' 2-point statistics within 20 per cent in the range of scales least affected by the telescope beam. However, spurious artefacts appear in the cleaned maps due to interactions between the foreground structure and the beam side-lobes. We conclude that it is fundamental to develop accurate beam deconvolution algorithms and test data post-processing steps carefully before cleaning. This study was performed as part of SKAO preparatory work by the HI IM Focus Group of the SKA Cosmology Science Working Group.

Keywords

Cite

@article{arxiv.2107.10814,
  title  = {SKAO HI Intensity Mapping: Blind Foreground Subtraction Challenge},
  author = {Marta Spinelli and Isabella P. Carucci and Steven Cunnington and Stuart E. Harper and Melis O. Irfan and José Fonseca and Alkistis Pourtsidou and Laura Wolz},
  journal= {arXiv preprint arXiv:2107.10814},
  year   = {2021}
}

Comments

Accepted version for publication in MNRAS

R2 v1 2026-06-24T04:26:21.995Z