Search for: All records

ABSTRACT Feedback from active galactic nuclei (AGNs) and supernovae can affect measurements of integrated Sunyaev–Zeldovich (SZ) flux of haloes (YSZ) from cosmic microwave background (CMB) surveys, and cause its relation with the halo mass (YSZ–M) to deviate from the self-similar power-law prediction of the virial theorem. We perform a comprehensive study of such deviations using CAMELS, a suite of hydrodynamic simulations with extensive variations in feedback prescriptions. We use a combination of two machine learning tools (random forest and symbolic regression) to search for analogues of the Y–M relation which are more robust to feedback processes for low masses ($$M\lesssim 10^{14}\, \mathrm{ h}^{-1} \, \mathrm{ M}_\odot$$); we find that simply replacing Y → Y(1 + M*/Mgas) in the relation makes it remarkably self-similar. This could serve as a robust multiwavelength mass proxy for low-mass clusters and galaxy groups. Our methodology can also be generally useful to improve the domain of validity of other astrophysical scaling relations. We also forecast that measurements of the Y–M relation could provide per cent level constraints on certain combinations of feedback parameters and/or rule out a major part of the parameter space of supernova and AGN feedback models used in current state-of-the-art hydrodynamic simulations. Our results can be useful for using upcoming SZ surveys (e.g. SO, CMB-S4) and galaxy surveys (e.g. DESI and Rubin) to constrain the nature of baryonic feedback. Finally, we find that the alternative relation, Y–M*, provides complementary information on feedback than Y–M. 

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. 

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. 

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.