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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. 

Abstract The circumgalactic medium (CGM) around massive galaxies plays a crucial role in regulating star formation and feedback. Using the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) suite, we develop emulators for the X-ray surface brightness profile and the X-ray luminosity–stellar mass scaling relation, to investigate how stellar and active galactic nucleus (AGN) feedback shape the X-ray properties of the hot CGM. Our analysis shows that at CGM scales (10¹²≲M_halo/M_⊙≲ 10¹³, 10 ≲rkpc⁻¹≲ 400), stellar feedback more significantly impacts the X-ray properties than AGN feedback within the parameters studied. Comparing the emulators to recent eROSITA All Sky Survey (eRASS) observations, it is found that stronger feedback than is currently implemented in the IllustrisTNG, SIMBA, and Astrid simulations is required to match the observed CGM properties. However, adopting these enhanced feedback parameters causes deviations in the stellar mass–halo mass relations from observational constraints below the group-mass scale. This tension suggests possible unaccounted-for systematics in X-ray CGM observations or inadequacies in the feedback models of cosmological simulations. 

Abstract We discuss the model of astrophysical emission at millimeter wavelengths used to characterize foregrounds in the multi-frequency power spectra of the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6), expanding on Louis et al. (2025) (2503.14452). We detail several tests to validate the capability of the DR6 parametric foreground model to describe current observations and complex simulations, and show that cosmological parameter constraints are robust against model extensions and variations. We demonstrate consistency of the model with pre-DR6 ACT data and observations fromPlanckand the South Pole Telescope. We evaluate the implications of using different foreground templates and extending the model with new components and/or free parameters. In all scenarios, the DR6 ΛCDM and ΛCDM+N_effcosmological parameters shift by less than 0.5σrelative to the baseline constraints. Some foreground parameters shift more; we estimate their systematic uncertainties associated with modeling choices. From our constraint on the kinematic Sunyaev-Zel'dovich power, we obtain a conservative limit on the duration of reionization of Δz_rei< 4.4, assuming a reionization midpoint consistent with optical depth measurements and a minimal low-redshift contribution, with varying assumptions for this component leading to tighter limits. Finally, we analyze realistic non-Gaussian, correlated microwave sky simulations containing Galactic and extragalactic foreground fields, built independently of the DR6 parametric foreground model. Processing these simulations through the DR6 power spectrum and likelihood pipeline, we recover the input cosmological parameters of the underlying cosmic microwave background field, a new demonstration for small-scale CMB analysis. These tests validate the robustness of the ACT DR6 foreground model and cosmological parameter constraints. 

Abstract As cosmic microwave background (CMB) photons traverse the universe, anisotropies can be induced via Thomson scattering (proportional to the electron density; optical depth) and inverse Compton scattering (proportional to the electron pressure; thermal Sunyaev–Zel’dovich effect). Measurements of anisotropy in optical depthτand Comptonyparameters are imprinted by the galaxies and galaxy clusters and are thus sensitive to the thermodynamic properties of the circumgalactic medium and intergalactic medium. We use an analytic halo model to predict the power spectrum of the optical depth (ττ), the cross-correlation between the optical depth and the Comptonyparameter (τy), and the cross-correlation between the optical depth and galaxy clustering (τg), and compare this model to cosmological simulations. We constrain the optical depths of halos atz≲ 3 using a technique originally devised to constrain patchy reionization at a higher redshift range. The forecasted signal-to-noise ratio is 2.6, 8.5, and 13, respectively, for a CMB-S4-like experiment and a Vera C. Rubin Observatory–like optical survey. We show that a joint analysis of these probes can constrain the amplitude of the density profiles of halos to 6.5% and the pressure profiles to 13%. These constraints translate to astrophysical parameters, such as the gas mass fraction,f_g, which can be constrained to 5.3% uncertainty atz∼ 0. The cross-correlations presented here are complementary to other CMB and galaxy cross-correlations since they do not require spectroscopic galaxy redshifts and are another example of how such correlations are a powerful probe of the astrophysics of galaxy evolution. 

Complex astrophysical systems often exhibit low-scatter relations between observable properties (e.g., luminosity, velocity dispersion, oscillation period). These scaling relations illuminate the underlying physics, and can provide observational tools for estimating masses and distances. Machine learning can provide a fast and systematic way to search for new scaling relations (or for simple extensions to existing relations) in abstract high-dimensional parameter spaces. We use a machine learning tool called symbolic regression (SR), which models patterns in a dataset in the form of analytic equations. We focus on the Sunyaev-Zeldovich flux−cluster mass relation ( Y SZ − M ), the scatter in which affects inference of cosmological parameters from cluster abundance data. Using SR on the data from the IllustrisTNG hydrodynamical simulation, we find a new proxy for cluster mass which combines Y SZ and concentration of ionized gas ( c gas ): M ∝ Y conc 3/5 ≡ Y SZ 3/5 (1 − A c gas ). Y conc reduces the scatter in the predicted M by ∼20 − 30% for large clusters ( M ≳ 10 14 h −1 M ⊙ ), as compared to using just Y SZ . We show that the dependence on c gas is linked to cores of clusters exhibiting larger scatter than their outskirts. Finally, we test Y conc on clusters from CAMELS simulations and show that Y conc is robust against variations in cosmology, subgrid physics, and cosmic variance. Our results and methodology can be useful for accurate multiwavelength cluster mass estimation from upcoming CMB and X-ray surveys like ACT, SO, eROSITA and CMB-S4. 

Abstract Rayleigh scattering of the cosmic microwave background (CMB) by neutral hydrogen shortly after recombination leaves frequency-dependent imprints on intensity and polarization fluctuations. High signal-to-noise observations of CMB Rayleigh scattering would provide additional insight into the physics of recombination, including greater constraining power for parameters like the primordial helium fraction, the light relic density, and the sum of neutrino masses. However, such a measurement of CMB Rayleigh scattering is challenging due to the presence of astrophysical foregrounds, which are more intense at the high frequencies, where the effects of Rayleigh scattering are most prominent. Here we forecast the detectability of CMB Rayleigh scattering including foreground removal using blind internal linear combination methods for a set of near-future surveys. We show that atmospheric effects for ground-based observatories and astrophysical foregrounds pose a significant hindrance to detecting CMB Rayleigh scattering with experiments planned for this decade, though a high-significance measurement should be possible with a future CMB satellite. 

We present Weak Gravitational Lensing measurements of a sample of 157 clusters within the Kilo Degree Survey (KiDS), detected with a > 5σthermal Sunyaev-Zel’dovich (SZ) signal by the Atacama Cosmology Telescope (ACT). Using a halo-model approach, we constrained the average total cluster mass,M_WL, accounting for the ACT cluster selection function of the full sample. We find that the SZ cluster mass estimateM_SZ, which was calibrated using X-ray observations, is biased withM_SZ/M_WL = (1 − b_SZ) = 0.65 ± 0.05. Separating the sample into six mass bins, we find no evidence of a strong mass dependency for the mass bias, (1 − b_SZ). Adopting this ACT-KiDS SZ mass calibration would bring thePlanckSZ cluster count into agreement with the counts expected from thePlanckcosmic microwave background ΛCDM cosmological model, although it should be noted that the cluster sample considered in this work has a lower average massM_SZ, uncor = 3.64 × 10¹⁴ M_⊙compared to thePlanckcluster sample which has an average mass in the rangeM_SZ, uncor = (5.5 − 8.5)×10¹⁴ M_⊙, depending on the sub-sample used.