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Statistical studies of the circumgalactic medium (CGM) using Sunyaev-Zeldovich (SZ) observations offer a promising method of studying the gas properties of galaxies and the astrophysics that govern their evolution. Forward modeling profiles from theory and simulations allows them to be refined directly off of data, but there are currently significant differences between the thermal SZ (tSZ) observations of the CGM and the predicted tSZ signal. While these discrepancies could be real, they could also be the result of decisions in the forward modeling used to build statistical measures from theory. In order to see effects of this, we compare an analysis utilizing halo occupancy distributions (HODs) implemented in halo models to simulate the galaxy distribution against previous studies, which weighted their results to match the CMASS galaxy sample, which contains nearly one million galaxies, mainly centrals of group-sized halos, selected for relatively uniform stellar mass across redshifts between 0.4 <z< 0.7. We review some of the implementation differences that can account for changes, such as miscentering, one-halo/two-halo cutoff radii, and mass ranges, all of which will need to be given the proper attention in future high-signal-to-noise studies. We find that our more thorough model predicts a signal with a 33% improved fit than the one from previous studies on the exact same sample. Additionally, we find that modifications that change the satellite fraction even by just a few percent, such as editing the halo mass range and certain HOD parameters, result in strong changes in the final signal. Although significant, this discrepancy from the modeling choices is not large enough to completely account for the existing disagreements between simulations and measurements. 

Weak gravitational lensing of the cosmic microwave background (CMB) has been established as a robust and powerful observable for precision cosmology. However, the impact of Galactic foregrounds, which has been studied less extensively than many other potential systematics, could in principle pose a problem for CMB lensing measurements. These foregrounds are inherently non-Gaussian and hence might mimic the characteristic signal that lensing estimators are designed to measure. We present an analysis that quantifies the level of contamination from Galactic dust in lensing measurements, focusing particularly on measurements with the Atacama Cosmology Telescope and the Simons Observatory. We employ a whole suite of foreground models and study the contamination of lensing measurements with both individual frequency channels and multifrequency combinations. We test the sensitivity of different estimators to the level of foreground non-Gaussianity and the dependence on sky fraction and multipole range used. We find that Galactic foregrounds do not present a problem for the Atacama Cosmology Telescope experiment (the bias in the inferred CMB lensing power spectrum amplitude remains below $0.3\sigma$ ). For Simons Observatory, not all foreground models remain below this threshold. Although our results are conservative upper limits, they suggest that further work on characterizing dust biases and determining the impact of mitigation methods is well motivated, especially for the largest sky fractions. 

We use the full-mission Planck PR4 data to measure the CMB lensing convergence (κ)-thermal Sunyaev-Zel'dovich (tSZ, y ) cross-correlation signal, Cℓyκ. This is only the second measurement to date of this signal, following Hill and Spergel [J. Cosmol. Astropart. Phys. 02 (2014) 030, 10.1088/1475-7516/2014/02/030]. We perform the measurement using foreground-cleaned tSZ maps built from the PR4 frequency maps via a tailored needlet internal linear combination (NILC) code in our companion paper [F. McCarthy and J. C. Hill, companion paper, Phys. Rev. D 109, 023528 (2024)., 10.1103/PhysRevD.109.023528], in combination with the Planck PR4 κ maps and various systematic-mitigated PR3 κ maps. A serious systematic is the residual cosmic infrared background (CIB) signal in the tSZ map, as the high CIB—κ cross-correlation can significantly bias the inferred tSZ—κ cross-correlation. We mitigate this contamination by deprojecting the CIB in our NILC algorithm, using a moment deprojection approach to avoid leakage due to incorrect modeling of the CIB frequency dependence. We validate this method on mm-wave sky simulations. We fit a theoretical halo model to our measurement, finding a best-fit amplitude of A =0.82 ±0.21 (for the highest signal-to-noise PR4 κ map) or A =0.56 ±0.24 (for a PR3 κ map built from a tSZ-deprojected CMB map), indicating that the data are consistent with our fiducial model within ≈1 -2 σ . Although our error bars are similar to those of the previous measurement [J. C. Hill and D. N. Spergel, J. Cosmol. Astropart. Phys. 02 (2014) 030, 10.1088/1475-7516/2014/02/030], our method is significantly more robust to CIB contamination. Our moment-deprojection approach lays the foundation for future measurements of this signal with higher signal-to-noise κ and y maps from ground-based telescopes, which will precisely probe the astrophysics of the intracluster medium of galaxy groups and clusters in the intermediate-mass (M ∼1013- 1014h-1M⊙), high-z (z ≲1.5 , c.f. z ≲0.8 for the tSZ auto-power signal) regime, as well as CIB-decontaminated measurements of tSZ cross-correlations with other large-scale structure probes. 

We use the full-mission Planck PR4 data to construct maps of the thermal Sunyaev-Zel'dovich effect (Compton-y parameter) in our Universe. To do so, we implement a custom needlet internal linear combination (NILC) pipeline in a Python package, PYILC, which we make publicly available. We publicly release our Compton-y maps, which we construct using various constrained ILC ("deprojection") options in order to minimize contamination from the cosmic infrared background (CIB) in the reconstructed signal. In particular, we use a moment-based deprojection that minimizes sensitivity to the assumed frequency dependence of the CIB. Our code PYILC performs needlet or harmonic ILC on mm-wave sky maps in a flexible manner, with options to deproject various components on all or some scales. We validate our maps and compare them to the official Planck 2015 y map, finding that we obtain consistent results on large scales and 10-20% lower noise on small scales. We expect that these maps will be useful for many auto- and cross-correlation analyses; in a companion paper, we use them to measure the tSZ—CMB lensing cross-correlation. We anticipate that PYILC will be useful both for data analysis and for pipeline validation on simulations to understand the propagation of foreground components through a full NILC pipeline. 

Extracting the cosmic microwave background (CMB) blackbody temperature power spectrum—which is dominated by the primary CMB signal and the kinematic Sunyaev-Zel'dovich (kSZ) effect—from millimeter-wave sky maps requires cleaning other sky components. In this work, we develop new methods to use large-scale structure (LSS) tracers to remove cosmic infrared background (CIB) and thermal Sunyaev-Zel'dovich (tSZ) contamination in such measurements. Our methods rely on the fact that LSS tracers are correlated with the CIB and tSZ signals, but their two-point correlations with the CMB and kSZ signals vanish on small scales, thus leaving the CMB blackbody power spectrum unbiased after cleaning. We develop methods analogous to delensing [de-CIB or de-(CIB +tSZ )] to clean CIB and tSZ contaminants using these tracers. We compare these methods to internal linear combination (ILC) methods, including novel approaches that incorporate the tracer maps in the ILC procedure itself, without requiring exact assumptions about the CIB spectral energy distribution. As a concrete example, we use the unWISE galaxy samples as tracers. We provide calculations for a combined Simons Observatory and Planck-like experiment, with our simulated sky model comprising eight frequencies from 93 to 353 GHz. Using unWISE tracers, improvements with our methods over current approaches are already non-negligible: we find improvements up to 20% in the kSZ power spectrum signal-to-noise ratio (SNR) when applying the de-CIB method to a tSZ-deprojected ILC map. These gains could be more significant when using additional LSS tracers from current surveys and will become even larger with future LSS surveys, with improvements in the kSZ power spectrum SNR up to 50%. For the total CMB blackbody power spectrum, these improvements stand at 4% and 7%, respectively. 

ABSTRACT We use the emulation framework CosmoPower to construct and publicly release neural network emulators of cosmological observables, including the cosmic microwave background (CMB) temperature and polarization power spectra, matter power spectrum, distance-redshift relation, baryon acoustic oscillation (BAO) and redshift-space distortion (RSD) observables, and derived parameters. We train our emulators on Einstein–Boltzmann calculations obtained with high-precision numerical convergence settings, for a wide range of cosmological models including ΛCDM, wCDM, ΛCDM + Neff, and ΛCDM + Σmν. Our CMB emulators are accurate to better than 0.5 per cent out to ℓ = 104, which is sufficient for Stage-IV data analysis, and our P(k) emulators reach the same accuracy level out to $$k=50 \, \, \mathrm{Mpc}^{-1}$$, which is sufficient for Stage-III data analysis. We release the emulators via an online repository (CosmoPower Organisation), which will be continually updated with additional extended cosmological models. Our emulators accelerate cosmological data analysis by orders of magnitude, enabling cosmological parameter extraction analyses, using current survey data, to be performed on a laptop. We validate our emulators by comparing them to class and camb and by reproducing cosmological parameter constraints derived from Planck TT, TE, EE, and CMB lensing data, as well as from the Atacama Cosmology Telescope Data Release 4 CMB data, Dark Energy Survey Year-1 galaxy lensing and clustering data, and Baryon Oscillation Spectroscopic Survey Data Release 12 BAO and RSD data. 

We present a joint analysis of the cosmic microwave background (CMB) lensing power spectra measured from the Data Release 6 of the Atacama Cosmology Telescope (ACT) and PR4, cross-correlations between the ACT and lensing reconstruction and galaxy clustering from unWISE, and the unWISE clustering auto-spectrum. We obtain 1.5% constraints on the matter density fluctuations at late times parametrized by the best constrained parameter combination $S_8^{3\mathrm{x}2\mathrm{pt}}\equiv {\sigma }_8({\mathrm{\Omega }}_m/0.3{)}^{0.4}=0.815\pm 0.012$ . The commonly used $S_8\equiv {\sigma }_8({\mathrm{\Omega }}_m/0.3{)}^{0.5}$ parameter is constrained to $S_8=0.816\pm 0.015$ . In combination with baryon acoustic oscillation (BAO) measurements we find ${\sigma }_8=0.815\pm 0.012$ . We also present sound-horizon-independent estimates of the present day Hubble rate of $H_0={66.4}_{-3.7}^{+3.2}\mathrm{km}{\mathrm{s}}^{-1}{\mathrm{Mpc}}^{-1}$ from our large scale structure data alone and $H_0={64.3}_{-2.4}^{+2.1}\mathrm{km}{\mathrm{s}}^{-1}{\mathrm{Mpc}}^{-1}$ in combination with uncalibrated supernovae from . Using parametric estimates of the evolution of matter density fluctuations, we place constraints on cosmic structure in a range of high redshifts typically inaccessible with cross-correlation analyses. Combining lensing cross- and autocorrelations, we derive a 3.3% constraint on the integrated matter density fluctuations above $z=2.4$ , one of the tightest constraints in this redshift range and fully consistent with a $\mathrm{\Lambda }$ cold dark matter ( $\mathrm{\Lambda }\mathrm{CDM}$ ) model fit to the primary CMB from . Finally, combining with primary CMB observations and using the extended low redshift coverage of these combined datasets we derive constraints on a variety of extensions to the $\mathrm{\Lambda }\mathrm{CDM}$ model including massive neutrinos, spatial curvature, and dark energy. We find in flat $\mathrm{\Lambda }\mathrm{CDM}\sum m_{\nu }<0.12\mathrm{eV}$ at 95% confidence using the large scale structure data, BAO measurements from Sloan Digital Sky Survey, and primary CMB observations.