Detecting the power spectrum turnover with HI intensity mapping

Abstract

A goal for pathfinder intensity mapping (IM) surveys will be detecting features in the neutral hydrogen (H ) power spectrum, which serve as conclusive evidence of cosmological signals. Observing such features at the expected scales in H IM auto-correlations, where contribution from systematics is uncertain, will provide a more convincing cosmological detection. We demonstrate how the turnover, i.e. the peak of the power spectrum at ultra-large scales, can be detected with H IM. We find that a MeerKAT 4,000 deg 2 survey using the UHF-band is capable of a 3.1𝜎 detection of the turnover, relative to a null model power spectrum with no turnover. This should exceed that capable from current galaxy surveys in optical and near-infrared. The detection significance falls to ∼1𝜎 in MeerKAT's L-band but can reach ∼13𝜎 with the SKAO, which should easily surpass the constraint capable from future Stage-IV-like spectroscopic galaxy surveys. We also propose a new model-independent methodology for constraining the precise turnover scale (𝑘 0 ) and our tests on UHF-band simulated data achieved a precision of 10%. This improved to 2.4% when using the full SKAO. We demonstrate how the results are robust to foreground contamination by using transfer functions, even when an incorrect cosmology has been assumed in their construction. Given that the turnover is related to the horizon scale at matter-radiation equality, a sufficiently precise constraint of 𝑘 0 presents the possibility for a novel probe of cosmology. We therefore present a potential methodology for constructing a standard-ruler-based distance measurement, independent of the sound horizon, using the turnover location in the H power spectrum.

Constraining primordial non-Gaussianity by combining next-generation galaxy and 21 cm intensity mapping surveys

“…For a simplified Fisher forecast we can instead use a foreground avoidance approach, by excising the regions of Fourier space where the foregrounds are significant. This means removing large radial scales, which can be modelled via an exponential suppression factor [73,82]:…”