Detecting the power spectrum turnover with Hi intensity mapping

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 4,000$\,{\rm deg}^2$ survey using the UHF-band is capable of a $3.1\sigma$ 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 ${\sim}1\sigma$ in MeerKAT's L-band but can reach ${\sim}13\sigma$ 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 ($k_0$) 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 HI power spectrum.Comment: 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 proof

The fore ground transfer function for H I intensity mapping signal reconstruction: MeerKLASS and precision cosmology applications

Blind cleaning methods are currently the preferred strategy for handling foreground contamination in single-dish H I intensity mapping surv e ys. Despite the increasing sophistication of blind techniques, some signal loss will be inevitable across all scales. Constructing a corrective transfer function using mock signal injection into the contaminated data has been a practice relied on for H I intensity mapping experiments. Ho we ver, assessing whether this approach is viable for future intensity mapping surv e ys, where precision cosmology is the aim, remains unexplored. In this work, using simulations, we validate for the first time the use of a foreground transfer function to reconstruct power spectra of foreground-cleaned low-redshift intensity maps and look to e xpose an y limitations. We rev eal that ev en when aggressiv e fore ground cleaning is required, which causes > 50 per cent ne gativ e bias on the largest scales, the power spectrum can be reconstructed using a transfer function to within sub-per cent accuracy. We specifically outline the recipe for constructing an unbiased transfer function, highlighting the pitfalls if one deviates from this recipe, and also correctly identify how a transfer function should be applied in an autocorrelation power spectrum. We validate a method that utilizes the transfer function variance for error estimation in foreground-cleaned power spectra. Finally, we demonstrate how incorrect fiducial parameter assumptions (up to ±100 per cent bias) in the generation of mocks, used in the construction of the transfer function, do not significantly bias signal reconstruction or parameter inference (inducing < 5 per cent bias in reco v ered values)

The H I intensity mapping bispectrum including observational effects

The bispectrum is a three-point statistic with the potential to provide additional information beyond power spectra analyses of survey data sets. Radio telescopes that broadly survey the 21-cm emission from neutral hydrogen (H I) are a promising way to probe LSS and in this work we present an investigation into the H I intensity mapping (IM) bispectrum using simulations. We present a model of the redshift space H I IM bispectrum including observational effects from the radio telescope beam and 21-cm foreground contamination. We validate our modelling prescriptions with measurements from robust IM simulations, inclusive of these observational effects. Our foreground simulations include polarization leakage, on which we use a principal component analysis cleaning method. We also investigate the effects from a non-Gaussian beam including side-lobes. For a MeerKAT-like single-dish IM survey at z = 0.39, we find that foreground removal causes an 8 per cent reduction in the equilateral bispectrum’s signal-to-noise ratio, whereas the beam reduces it by 62 per cent. We find our models perform well, generally providing χ2 dof ∼ 1, indicating a good fit to the data. Whilst our focus is on post-reionization, single-dish IM, our modelling of observational effects, especially foreground removal, can also be relevant to interferometers and reionization studies

H I intensity mapping with MeerKAT: Power spectrum detection in cross-correlation with WiggleZ galaxies

We present a detection of correlated clustering between MeerKAT radio intensity maps and galaxies from the WiggleZ Dark Energy Survey. We find a 7.7σ detection of the cross-correlation power spectrum, the amplitude of which is proportional to the product of the HI density fraction (⁠ΩHI ⁠), HI bias (⁠bHI ⁠), and the cross-correlation coefficient (r). We therefore obtain the constraint ΩHIbHIr=[0.86±0.10(stat)±0.12(sys)]×10−3 ⁠, at an effective scale of keff ∼ 0.13hMpc−1 ⁠. The intensity maps were obtained from a pilot survey with the MeerKAT telescope, a 64-dish pathfinder array to the SKA Observatory (SKAO). The data were collected from 10.5 h of observations using MeerKAT’s L-band receivers over six nights covering the 11 h field of WiggleZ, in the frequency range 1015–973 MHz (0.400 <z< 0.459 in redshift)

The foreground transfer function for HI intensity mapping signal reconstruction: MeerKLASS and precision cosmology applications

Blind cleaning methods are currently the preferred strategy for handling foreground contamination in single-dish HI intensity mapping surveys. Despite the increasing sophistication of blind techniques, some signal loss will be inevitable across all scales. Constructing a corrective transfer function using mock signal injection into the contaminated data has been a practice relied on for HI intensity mapping experiments. However, assessing whether this approach is viable for future intensity mapping surveys where precision cosmology is the aim, remains unexplored. In this work, using simulations, we validate for the first time the use of a foreground transfer function to reconstruct power spectra of foreground-cleaned low-redshift intensity maps and look to expose any limitations. We reveal that even when aggressive foreground cleaning is required, which causes ${>}\,50\%$ negative bias on the largest scales, the power spectrum can be reconstructed using a transfer function to within sub-percent accuracy. We specifically outline the recipe for constructing an unbiased transfer function, highlighting the pitfalls if one deviates from this recipe, and also correctly identify how a transfer function should be applied in an auto-correlation power spectrum. We validate a method that utilises the transfer function variance for error estimation in foreground-cleaned power spectra. Finally, we demonstrate how incorrect fiducial parameter assumptions (up to ${\pm}100\%$ bias) in the generation of mocks, used in the construction of the transfer function, do not significantly bias signal reconstruction or parameter inference (inducing ${<}\,5\%$ bias in recovered values).Comment: 25 pages, 20 figures. See Figure 4 for the main demonstration of the transfer function's performance for reconstructing signal loss from foreground cleaning. Submitted to MNRAS for publicatio

SKAO HI intensity mapping: blind foreground subtraction challenge

Neutral Hydrogen Intensity Mapping (H I IM) surveys will be a powerful new probe of cosmology. However, strong astrophysical foregrounds contaminate the signal and their coupling with instrumental systematics further increases the data cleaning complexity. In this work, we simulate a realistic single-dish HI IM survey of a 5000 deg2 patch in the 950–1400 MHz range, with both the MID telescope of the SKA Observatory (SKAO) and MeerKAT, its precursor. We include a state-of-the-art HI simulation and explore different foreground models and instrumental effects such as non-homogeneous thermal noise and beam side lobes. We perform the first Blind Foreground Subtraction Challenge for HI IM on these synthetic data cubes, aiming to characterize the performance of available foreground cleaning methods with no prior knowledge of the sky components and noise level. Nine foreground cleaning pipelines joined the challenge, based on statistical source separation algorithms, blind polynomial fitting, and an astrophysical-informed parametric fit to foregrounds. We devise metrics to compare the pipeline performances quantitatively. In general, they can recover the input maps’ two-point statistics within 20 per cent in the range of scales least affected by the telescope beam. However, spurious artefacts appear in the cleaned maps due to interactions between the foreground structure and the beam side lobes. We conclude that it is fundamental to develop accurate beam deconvolution algorithms and test data post-processing steps carefully before cleaning. This study was performed as part of SKAO preparatory work by the HI IM Focus Group of the SKA Cosmology Science Working Group