Constraining large-scale Hi bias using redshifted 21-cm signal from the post-reionization epoch

• Published in: Monthly notices of the Royal Astronomical Society 2012-04, Vol.421 (4), p.3570-3578
• Main Authors: Guha Sarkar, Tapomoy, Mitra, Sourav, Majumdar, Suman, Choudhury, Tirthankar Roy
• Format: Article
• Language: English
• Subjects: Astrophysics; Dark matter; Mathematical models; Radio astronomy; Red shift
• ISSN: 0035-8711; 1365-2966
• DOI: 10.1111/j.1365-2966.2012.20582.x

In the absence of complex astrophysical processes that characterize the reionization era, the 21-cm emission from neutral hydrogen (Hi) in the post-reionization epoch is believed to be an excellent tracer of the underlying dark matter distribution. Assuming a background cosmology, it is modelled through (i) a bias function b(k, z), which relates Hi to the dark matter distribution and (ii) a mean neutral fraction () which sets its amplitude. In this paper, we investigate the nature of large-scale Hi bias. The post-reionization Hi is modelled using gravity only N-body simulations and a suitable prescription for assigning gas to the dark matter haloes. Using the simulated bias as the fiducial model for Hi distribution at z≤ 4, we have generated a hypothetical data set for the 21-cm angular power spectrum (C) using a noise model based on parameters of an extended version of the Giant Metrewave Radio Telescope (GMRT). The binned C is assumed to be measured with S/N 4 in the range 400 ≤≤ 8000 at a fiducial redshift z= 2.5. We explore the possibility of constraining b(k) using the principal component analysis on these simulated data. Our analysis shows that in the range 0.2 < k < 2Mpc-1, the simulated data set cannot distinguish between models exhibiting different k-dependences, provided 1 b(k) 2 which sets the 2σ limits. This justifies the use of linear bias model on large scales. The largely uncertain is treated as a free parameter resulting in degradation of the bias reconstruction. The given simulated data are found to constrain the fiducial with an accuracy of 4per cent (2σ error). The method outlined here could be successfully implemented on future observational data sets to constrain b(k, z) and and thereby enhance our understanding of the low-redshift Universe. [PUBLICATION ABSTRACT]