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The physics of baryons in haloes, and their subsequent influence on the total matter phase space, has a rich phenomenology and must be well understood in order to pursue a vast set of questions in both cosmology and astrophysics. We use the Cosmology and Astrophysics with MachinE Learning Simulation (Camels) suite to quantify the impact of four different galaxy formation parameters/processes (as well as two cosmological parameters) on the concentration–mass relation, cvir−Mvir. We construct a simulation-informed non-linear model for concentration as a function of halo mass, redshift, and six cosmological/astrophysical parameters. This is done for two galaxy formation models, IllustrisTNG and Simba, using 1000 simulations of each. We extract the imprints of galaxy formation across a wide range in mass $M_{\rm vir}\in [10^{11}, 10^{14.5}] \, {\rm M}_\odot \, h^{-1}$ and in redshift z ∈ [0, 6] finding many strong mass- and redshift-dependent features. Comparisons between the IllustrisTNG and Simba results show the astrophysical model choices cause significant differences in the mass and redshift dependence of these baryon imprints. Finally, we use existing observational measurements of cvir−Mvir to provide rough limits on the four astrophysical parameters. Our non-linear model is made publicly available and can be used to include Camels-based baryon imprints in any halo model-based analysis.

Widefield surveys probe clustered scalar fields – such as galaxy counts, lensing potential, etc. – which are sensitive to different cosmological and astrophysical processes. Constraining such processes depends on the statistics that summarize the field. We explore the cumulative distribution function (CDF) as a summary of the galaxy lensing convergence field. Using a suite of N-body light-cone simulations, we show the CDFs’ constraining power is modestly better than the second and third moments, as CDFs approximately capture information from all moments. We study the practical aspects of applying CDFs to data, using the Dark Energy Survey (DES Y3) data as an example, and compute the impact of different systematics on the CDFs. The contributions from the point spread function and reduced shear approximation are $\lesssim 1~{{\ \rm per\ cent}}$ of the total signal. Source clustering effects and baryon imprints contribute 1–10 per cent. Enforcing scale cuts to limit systematics-driven biases in parameter constraints degrade these constraints a noticeable amount, and this degradation is similar for the CDFs and the moments. We detect correlations between the observed convergence field and the shape noise field at 13σ. The non-Gaussian correlations in the noise field must be modelled accurately to use the CDFs, or other statistics sensitive to all moments, as a rigorous cosmology tool.

We search for signatures of cosmological shocks in gas pressure profiles of galaxy clusters using the cluster catalogues from three surveys: the Dark Energy Survey (DES) Year 3, the South Pole Telescope (SPT) SZ survey, and the Atacama Cosmology Telescope (ACT) data releases 4, 5, and 6, and using thermal Sunyaev–Zeldovich (SZ) maps from SPT and ACT. The combined cluster sample contains around 105 clusters with mass and redshift ranges $10^{13.7} \lt M_{\rm 200m}/\, {\rm M}_\odot \lt 10^{15.5}$ and 0.1 < z < 2, and the total sky coverage of the maps is $\approx 15\, 000 \deg ^2$. We find a clear pressure deficit at R/R200m ≈ 1.1 in SZ profiles around both ACT and SPT clusters, estimated at 6σ significance, which is qualitatively consistent with a shock-induced thermal non-equilibrium between electrons and ions. The feature is not as clearly determined in profiles around DES clusters. We verify that measurements using SPT or ACT maps are consistent across all scales, including in the deficit feature. The SZ profiles of optically selected and SZ-selected clusters are also consistent for higher mass clusters. Those of less massive, optically selected clusters are suppressed on small scales by factors of 2–5 compared to predictions, and we discuss possible interpretations of this behaviour. An oriented stacking of clusters – where the orientation is inferred from the SZ image, the brightest cluster galaxy, or the surrounding large-scale structure measured using galaxy catalogues – shows the normalization of the one-halo and two-halo terms vary with orientation. Finally, the location of the pressure deficit feature is statistically consistent with existing estimates of the splashback radius.

We search for the signature of cosmological shocks in stacked gas pressure profiles of galaxy clusters using data from the South Pole Telescope (SPT). Specifically, we stack the latest Compton-y maps from the 2500 deg2 SPT-SZ survey on the locations of clusters identified in that same data set. The sample contains 516 clusters with mean mass $\langle M_{\rm 200m}\rangle = 10^{14.9} \, {\rm M}_\odot$ and redshift 〈z〉 = 0.55. We analyse in parallel a set of zoom-in hydrodynamical simulations from the three hundred project. The SPT-SZ data show two features: (i) a pressure deficit at R/R200m = 1.08 ± 0.09, measured at 3.1σ significance and not observed in the simulations, and; (ii) a sharp decrease in pressure at R/R200m = 4.58 ± 1.24 at 2.0σ significance. The pressure deficit is qualitatively consistent with a shock-induced thermal non-equilibrium between electrons and ions, and the second feature is consistent with accretion shocks seen in previous studies. We split the cluster sample by redshift and mass, and find both features exist in all cases. There are also no significant differences in features along and across the cluster major axis, whose orientation roughly points towards filamentary structure. As a consistency test, we also analyse clusters from the Planck and Atacama Cosmology Telescope Polarimeter surveys and find quantitatively similar features in the pressure profiles. Finally, we compare the accretion shock radius ($R_{\rm sh,\, acc}$) with existing measurements of the splashback radius (Rsp) for SPT-SZ and constrain the lower limit of the ratio, $R_{\rm sh,\, acc}/R_{\rm sp}\gt 2.16 \pm 0.59$.