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HI intensity mapping with MeerKAT: power spectrum detection in cross-correlation with WiggleZ galaxies

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arxiv 2206.01579 v2 pith:RDUVXDL3 submitted 2022-06-03 astro-ph.CO

classification astro-ph.CO
keywords detectionintensitymeerkatcross-correlationwigglezcosmologygalaxiesmapping
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abstract

We present a detection of correlated clustering between MeerKAT radio intensity maps and galaxies from the WiggleZ Dark Energy Survey. We find a $7.7\sigma$ detection of the cross-correlation power spectrum, the amplitude of which is proportional to the product of the HI density fraction ($\Omega_{\rm HI}$), HI bias ($b_{\rm HI}$) and the cross-correlation coefficient ($r$). We therefore obtain the constraint $\Omega_{\rm HI} b_{\rm HI} r\,{=}\,[0.86\,{\pm}\,0.10\,({\rm stat})\,{\pm}\,0.12\,({\rm sys})]\,{\times}\,10^{-3}$, at an effective scale of $k_{\rm eff}\,{\sim}\,0.13\,h\,{\rm Mpc}^{-1}$. 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 hours of observations using MeerKAT's L-band receivers over six nights covering the 11hr field of WiggleZ, in the frequency range $1015-973\,{\rm MHz}$ (0.400$\,{<}\,z\,{<}\,$0.459 in redshift). This detection is the first practical demonstration of the multi-dish auto-correlation intensity mapping technique for cosmology. This marks an important milestone in the roadmap for the cosmology science case with the full SKAO.

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Forward citations

Cited by 7 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Spectral Data-cube Cleaning for CCAT Deep Spectroscopic Survey. I. Effect of correlated noise and filtering on the power spectrum

    astro-ph.GA 2026-07 conditional novelty 6.0 of 10

    The EoR-Spec Filter-and-Bin pipeline suppresses atmospheric 1/f noise by about four orders of magnitude and recovers the [CII]+CO power spectrum above k ~ 0.1 Mpc^-1, but suppresses large-scale modes below 20% transfe...

  2. Simulation-Based Priors for HI Bias from Halo Occupation Physics

    astro-ph.CO 2026-07 conditional novelty 6.0 of 10

    A conditional normalizing flow learned from two simulation suites maps HI halo-occupation parameters to EFT bias parameters, producing correlated non-Gaussian priors that are much tighter than flat priors for 21 cm analyses.

  3. Seeing Wiggles without Seeing Wiggles: BAO Recovery in 21 cm Intensity Mapping with Deep Learning

    astro-ph.CO 2026-02 conditional novelty 6.0 of 10

    A 3D U-Net trained only on BAO-free 21 cm simulations recovers BAO wiggles from small-scale modes outside the foreground wedge, indicating physical mode coupling.

  4. Deep learning with hybrid frequency differencing and principal component analysis for 21-cm foreground and beam mitigation

    astro-ph.CO 2025-11 conditional novelty 5.0 of 10

    A two-channel UNet combining frequency differencing and PCA preprocessing recovers the 21-cm HI power spectrum at large scales under realistic beam effects, improving cross-correlation by 5-8% over single-channel baselines.

  5. Cosmology from Nx2pt Analyses of SKAO Wide-Area Surveys

    astro-ph.CO 2026-07 conditional novelty 4.0 of 10

    SKA-Mid AA4 N×2pt combinations of continuum and HI surveys are forecast to deliver ~1% precision on ΛCDM parameters and useful constraints on w0–wa, Mν and Ωk.

  6. Cosmology with HI Intensity Mapping

    astro-ph.CO 2026-07 accept novelty 4.0 of 10

    SKAO HI intensity mapping forecasts yield competitive LambdaCDM constraints (e.g. H0 to ~0.3 km/s/Mpc optimistic) via power spectrum, BAO, bispectrum and stacking, complementary to CMB and optical surveys.

  7. Weighing neutrinos with 21cm Intensity Mapping at the SKAO

    astro-ph.CO 2025-04 conditional novelty 4.0 of 10

    Forecasted SKAO 21cm intensity mapping plus Planck 2018 data could push the 95% upper limit on the summed neutrino mass from 0.285 eV to about 0.105 eV (fixed astrophysical nuisances).

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