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Super-sample covariance (SSC) is an important effect for cosmological analyses that use the deep structure of the cosmic web; it may, however, be nontrivial to include it practically in a pipeline. We solve this difficulty by presenting a formula for the precision (inverse covariance) matrix and show applications to update likelihood or Fisher forecast pipelines. The formula has several advantages in terms of speed, reliability, stability, and ease of implementation. We present an analytical application to show the formal equivalence between three approaches to SSC: (i) at the usual covariance level, (ii) at the likelihood level, and (iii) with a quadratic estimator. We then present an application of this computationally efficient framework for studying the impact of inaccurate modelling of SSC responses for cosmological constraints from stage IV surveys. We find that a weak-lensing-only analysis is very sensitive to inaccurate modelling of the scale dependence of the response, which needs to be calibrated at the $\sim15\%$ level. The sensitivity to this scale dependence is less severe for the joint weak-lensing and galaxy clustering analysis (also known as 3x2pt). Nevertheless, we find that both the amplitude and scale-dependence of the responses have to be calibrated at better than 30\%., Comment: 12+2 pages, 5 figures. Version published in A&A

We derive an estimator for the lensing potential from galaxy number counts which contains a linear and a quadratic term. We show that this estimator has a much larger signal-to-noise ratio than the corresponding estimator from intensity mapping. We show that this is due to the additional lensing term in the number count angular power spectrum which is present already at linear order. We estimate the signal-to-noise ratio for future photometric surveys. We find that particularly at high redshifts, $z\gtrsim 1.5$, the signal to noise ratio can become of order 30. We therefore claim that number counts in photometric surveys are an excellent means to measure tomographic lensing spectra., Comment: 21 pages, 9 figures, 4 tables

AliCPT-1 is the first Chinese CMB experiment aiming for high precision measurement of Cosmic Microwave Background B-mode polarization. The telescope, currently under deployment in Tibet, will observe in two frequency bands centered at 90 and 150 GHz. We forecast the CMB lensing reconstruction, lensing-galaxy as well as lensing-CIB (Cosmic Infrared Background) cross correlation signal-to-noise ratio (SNR) for AliCPT-1. We consider two stages with different integrated observation time, namely "4 module*yr" (first stage) and "48 module*yr" (final stage). For lensing reconstruction, we use three different quadratic estimators, namely temperature-only, polarization-only and minimum-variance estimators, using curved sky geometry. We take into account the impact of inhomogeneous hit counts as well as of the mean-field bias due to incomplete sky coverage. In the first stage, our results show that the 150 GHz channel is able to measure the lensing signal at $15\sigma$ significance with the minimum-variance estimator. In the final stage, the measurement significance will increase to $31\sigma$. We also combine the two frequency data in the harmonic domain to optimize the SNR. Our result show that the coadding procedure can significantly reduce the reconstruction bias in the multiple range l>800. Thanks to the high quality of the polarization data in the final stage of AliCPT-1, the EB estimator will dominate the lensing reconstruction in this stage. We also estimate the SNR of cross-correlations between AliCPT-1 CMB lensing and other tracers of the large scale structure of the universe. For its cross-correlation with DESI galaxies/quasars, we report the cross-correlation SNR = 10-20 for the 4 redshift bins at 0.05, Comment: 18 pages, 8 figures, 3 tables

We reconstruct the Cosmic Microwave Background (CMB) lensing potential on the latest Planck CMB PR4 (NPIPE) maps, which include slightly more data than the 2018 PR3 release, and implement quadratic estimators using more optimal filtering. We increase the reconstruction signal to noise by almost $20\%$, constraining the amplitude of the CMB-marginalized lensing power spectrum in units of the Planck 2018 best-fit to $1.004 \pm 0.024$ ($68\%$ limits), which is the tightest constraint on the CMB lensing power spectrum to date. For a base $\Lambda$CDM cosmology we find $\sigma_8 \Omega_m^{0.25} = 0.599\pm 0.016$ from CMB lensing alone in combination with weak priors and element abundance observations. Combination with baryon acoustic oscillation data gives tight $68\%$ constraints on individual $\Lambda$CDM parameters $\sigma_8 = 0.814\pm 0.016$, $H_0 = 68.1^{+1.0}_{-1.1}$km s$^{-1}$ Mpc$^{-1}$, $\Omega_m = 0.313^{+0.014}_{-0.016}$. Planck polarized maps alone now constrain the lensing power to $7\%$., Comment: 15 pages, 9 figures, 4 tables. Matches version accepted for publication

Precise reconstruction of the cosmic microwave background lensing potential can be achieved with deep polarization surveys by iteratively removing lensing-induced $B$ modes. We introduce a lensing spectrum estimator and its likelihood for such optimal iterative reconstruction. Our modelling share similarities to the state-of-the-art likelihoods for quadratic estimator-based (QE) lensing reconstruction. In particular, we generalize the $N_L^{(0)}$ and $N_L^{(1)}$ lensing biases, and design a realization-dependent spectrum debiaser, making this estimator robust to uncertainties in the data modelling. We demonstrate unbiased recovery of the cosmology using map-based reconstructions, focussing on lensing-only cosmological constraints and neutrino mass measurement in combination with CMB spectra and acoustic oscillation data. We find this spectrum estimator is essentially optimal and with a diagonal covariance matrix. For a CMB-S4 survey, this likelihood can double the constraints on the lensing amplitude compared to the QE on a wide range of scales, while at the same time keeping numerical cost under control and being robust to errors., 10 pages, 7 figures, submitted to PRD