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We forecast ability of dedicated 21 cm intensity mapping experiments to constraint primordial non-Gaussianity using power spectrum and bispectrum. We model the signal including the non-linear biasing expansion using a generalized halo model approach. We consider the importance of foreground filtering scale and of the foreground wedge. We find that the current generation intensity mapping experiments like CHIME do not posses sufficient sensitivity to be competitive with the existing limits. On the other hand, upcoming experiments like HIRAX can improve the current constraints and the proposed PUMA experiment can substantially improve them, reaching sensitivities below $sigma (f_{rm NL})<5$ for equilateral and orthogonal configurations and $sigma( f_{rm NL}) < 1$ for the local shape if good foreground control is achieved.
The 21-cm line of neutral hydrogen (HI) opens a new avenue in our exploration of the Universes structure and evolution. It provides complementary data with different systematics, which aim to improve our current understanding of the $Lambda$CDM model
We investigate future constraints on primordial local-type non-Gaussianity from 21 cm angular power spectrum from minihalos. We particularly focus on the trispectrum of primordial curvature perturbations which are characterized by the non-linearity p
Measuring the small primordial nonGaussianity (PNG) predicted by cosmic inflation theories may help diagnose them. The detectability of PNG by its imprint on the 21cm power spectrum from the epoch of reionization is reassessed here in terms of $f_{NL
Using the 21 cm line, observed all-sky and across the redshift range from 0 to 5, the large scale structure of the Universe can be mapped in three dimensions. This can be accomplished by studying specific intensity with resolution ~ 10 Mpc, rather th
We forecast constraints on cosmological parameters in the interacting dark energy models using the mock data generated for neutral hydrogen intensity mapping (IM) experiments. In this work, we only consider the interacting dark energy models with ene