Primordial Non-Gaussianity from the 21 cm Power Spectrum during the Epoch of Reionization

Primordial non-Gaussianity is a crucial test of inflationary cosmology. We consider the impact of non-Gaussianity on the ionization power spectrum from 21 cm emission at the epoch of reionization. We focus on the power spectrum on large scales at redshifts of 7 to 8 and explore the expected constraint on the local non-Gaussianity parameter f_(NL) for current and next-generation 21 cm experiments. We show that experiments such as SKA and MWA could measure f_(NL) values of order 10. This can be improved by an order of magnitude with a fast-Fourier transform telescope like Omniscope

Radio Galaxy populations and the multi-tracer technique: pushing the limits on primordial non-Gaussianity

We explore the use of different radio galaxy populations as tracers of different mass halos and therefore, with different bias properties, to constrain primordial non-Gaussianity of the local type. We perform a Fisher matrix analysis based on the predicted auto and cross angular power spectra of these populations, using simulated redshift distributions as a function of detection flux and the evolution of the bias for the different galaxy types (Star forming galaxies, Starburst galaxies, Radio-Quiet Quasars, FRI and FRII AGN galaxies). We show that such a multi-tracer analysis greatly improves the information on non-Gaussianity by drastically reducing the cosmic variance contribution to the overall error budget. By using this method applied to future surveys, we predict a constraint of sigma_fnl=3.6 on the local non-Gaussian parameter for a galaxy detection flux limit of 10 \muJy and sigma_fnl=2.2 for 1 \muJy. We show that this significantly improves on the constraints obtained when using the whole undifferentiated populations (sigma_fnl=48 for 10 \muJy and sigma_fnl=12 for 1 \muJy). We conclude that continuum radio surveys alone have the potential to constrain primordial non-Gaussianity to an accuracy at least a factor of two better than the present constraints obtained with Planck data on the CMB bispectrum, opening a window to obtain sigma_fnl~1 with the Square Kilometer Array.Comment: 9 pages, 5 figures, submitted to MNRA

Twenty-one centimeter tomography with foregrounds

Twenty-one centimeter tomography is emerging as a powerful tool to explore the end of the cosmic dark ages and the reionization epoch, but it will only be as good as our ability to accurately model and remove astrophysical foreground contamination. Previous treatments of this problem have focused on the angular structure of the signal and foregrounds and what can be achieved with limited spectral resolution (bandwidths in the 1 MHz range). In this paper we introduce and evaluate a ``blind'' method to extract the multifrequency 21cm signal by taking advantage of the smooth frequency structure of the Galactic and extragalactic foregrounds. We find that 21 cm tomography is typically limited by foregrounds on scales $k\ll 1h/$Mpc and limited by noise on scales $k\gg 1h/$Mpc, provided that the experimental bandwidth can be made substantially smaller than 0.1 MHz. Our results show that this approach is quite promising even for scenarios with rather extreme contamination from point sources and diffuse Galactic emission, which bodes well for upcoming experiments such as LOFAR, MWA, PAST, and SKA.Comment: 10 pages, 6 figures. Revised version including various cases with high noise level. Major conclusions unchanged. Accepted for publication in Ap

Nonlinear modulation of the HI power spectrum on ultra-large scales. I

Intensity mapping of the neutral hydrogen brightness temperature promises to provide a three-dimensional view of the universe on very large scales. Nonlinear effects are typically thought to alter only the small-scale power, but we show how they may bias the extraction of cosmological information contained in the power spectrum on ultra-large scales. For linear perturbations to remain valid on large scales, we need to renormalize perturbations at higher order. In the case of intensity mapping, the second-order contribution to clustering from weak lensing dominates the nonlinear contribution at high redshift. Renormalization modifies the mean brightness temperature and therefore the evolution bias. It also introduces a term that mimics white noise. These effects may influence forecasting analysis on ultra-large scales