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arXiv · 2502.10168

CMB lensing tomography with clustering estimation of lens redshift distributions

Shun Arai·John A. Peacock·Hironao Miyatake·Atsushi J. Nishizawa
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Abstract

We develop a clustering-based redshift estimation approach for CMB lensing tomography, focusing on the kernel function of the lensing galaxies. Within a linear galaxy bias framework, we derive estimators for this kernel from two-point cross-correlations between lens mass and reference samples. The reconstructed kernel then enables a theoretical prediction for the angular cross-power spectrum \(C_{g\kappa}\) between CMB lensing convergence and lens galaxies. As a proof of concept, we measure \(C_{g\kappa}\) by correlating the \emph{Planck} PR4 convergence map with NVSS+SUMSS radio galaxies (\(0\lesssim z\lesssim 3\)). We estimate the radio-galaxy kernel by collectively cross-correlating their distribution with spectroscopic and photometric surveys (2MPZ, LOWZ-CMASS, eBOSS DR16 LRGs, and Gaia-unWISE QSOs). From the measured \(C_{g\kappa}\), we obtain \(\sigma_8 = 0.86^{+0.12}_{-0.09}\) when the density parameter is set to the {\it Planck} value of $\Omega_m = 0.315$; this is in good agreement with the \emph{Planck} normalisation of $\sigma_8 = 0.812$.

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Shun Arai, John A. Peacock, Hironao Miyatake, Atsushi J. Nishizawa. 2025-02-14. CMB lensing tomography with clustering estimation of lens redshift distributions. https://doi.org/10.1093/mnras%2Fstaf692

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