Extracting HI cosmological signal with Generalized Needlet Internal Linear Combination

TL;DR

This paper evaluates the GNILC method's effectiveness in removing astrophysical foregrounds from HI intensity mapping data to accurately recover the cosmological HI signal, crucial for studying dark energy.

Contribution

It introduces and tests the GNILC technique for foreground subtraction in HI intensity mapping, demonstrating its robustness and accuracy in simulated observations.

Findings

GNILC can reconstruct the HI power spectrum with 6% accuracy.

The method is effective across complex foreground scenarios.

Successful recovery of the HI signal at redshift z ~ 0.25.

Abstract

HI intensity mapping is a new observational technique to map fluctuations in the large-scale structure of matter using the 21 cm emission line of atomic hydrogen (HI). Sensitive radio surveys have the potential to detect Baryon Acoustic Oscillations (BAO) at low redshifts (z < 1) in order to constrain the properties of dark energy. Observations of the HI signal will be contaminated by instrumental noise and, more significantly, by astrophysical foregrounds, such as Galactic synchrotron emission, which is at least four orders of magnitude brighter than the HI signal. Foreground cleaning is recognised as one of the key challenges for future radio astronomy surveys. We study the ability of the Generalized Needlet Internal Linear Combination (GNILC) method to subtract radio foregrounds and to recover the cosmological HI signal for a general HI intensity mapping experiment. The GNILC method is a new technique that uses both frequency and spatial information to separate the components of the observed data. Our results show that the method is robust to the complexity of the foregrounds. For simulated radio observations including HI emission, Galactic synchrotron, Galactic free-free, radio sources and 0.05 mK thermal noise, we find that we can reconstruct the HI power spectrum for multipoles 30 < l < 150 with 6% accuracy on 50% of the sky for a redshift z ~ 0.25.