English

Detecting the power spectrum turnover with HI intensity mapping

Cosmology and Nongalactic Astrophysics 2022-03-25 v2

Abstract

A goal for pathfinder intensity mapping (IM) surveys will be detecting features in the neutral hydrogen (HI) power spectrum, which serve as conclusive evidence of cosmological signals. Observing such features at the expected scales in HI 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 HI IM. We find that a MeerKAT 4,000deg2\,{\rm deg}^2 survey using the UHF-band is capable of a 3.1σ3.1\sigma detection of the turnover, relative to a null model power spectrum with no turnover. This should exceed what is capable by current galaxy surveys in optical and near-infrared. The detection significance falls to 1σ{\sim}1\sigma in MeerKAT's L-band but can reach 13σ{\sim}13\sigma with the SKAO, which should easily surpass the constraints from future Stage-IV-like spectroscopic galaxy surveys. We also propose a new model-independent methodology for constraining the precise turnover scale (k0k_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 k0k_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 HI power spectrum.

Keywords

Cite

@article{arxiv.2202.13828,
  title  = {Detecting the power spectrum turnover with HI intensity mapping},
  author = {Steven Cunnington},
  journal= {arXiv preprint arXiv:2202.13828},
  year   = {2022}
}

Comments

18 pages, 10 figures. See Fig 4 for main forecast of turnover detection for different HI IM surveys. See Fig 7 for constraints possible on turnover scale and Fig 8 for demo of how this can be used for cosmology. Accepted for publication in MNRAS. Minor grammatical edits made for V2 in response to editors' final proofs

R2 v1 2026-06-24T09:56:24.391Z