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  1. ABSTRACT

    The recent detection of a stochastic gravitational wave background (SGWB) at nanohertz frequencies by pulsar timing arrays (PTAs) has sparked a flurry of interest. Beyond the standard interpretation that the progenitor is a network of supermassive black hole binaries, many exotic models have also been proposed, some of which can potentially offer a better fit to the data. We explore how the various connections between gravitational waves (GWs) and cosmic microwave background (CMB) spectral distortions (SDs) can be leveraged to help determine whether an SGWB was generated primordially or astrophysically. To this end, we present updated k-space window functions that can be used for distortion parameter estimation on enhancements to the primordial scalar power spectrum. These same enhancements can also source GWs directly at second order in perturbation theory, so-called scalar-induced GWs (SIGWs), and indirectly through the formation of primordial black holes (PBHs). We perform a mapping of scalar power spectrum constraints into limits on the GW parameter space of SIGWs for δ-function features. We highlight that broader features in the scalar spectrum can explain the PTA results while simultaneously producing an SD within reach of future experiments. We additionally update PBH constraints from μ- and y-type SDs. Refined treatments of the distortion window functions widen existing SD constraints, and we find that a future CMB spectrometer could play a pivotal role in unravelling the origin of GWs imprinted at or below CMB anisotropy scales.

     
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  2. Free, publicly-accessible full text available February 1, 2025
  3. 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. 
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  4. 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.

     
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  5. Abstract

    The thermal Sunyaev–Zel’dovich (tSZ) effect is a powerful tool with the potential for constraining directly the properties of the hot gas that dominates dark matter halos because it measures pressure and thus thermal energy density. Studying this hot component of the circumgalactic medium (CGM) is important because it is strongly impacted by star formation and active galactic nucleus (AGN) activity in galaxies, participating in the feedback loop that regulates star and black hole mass growth in galaxies. We study the tSZ effect across a wide halo-mass range using three cosmological hydrodynamical simulations: Illustris-TNG, EAGLE, and FIRE-2. Specifically, we present the scaling relation between the tSZ signal and halo mass and the (mass-weighted) radial profiles of gas density, temperature, and pressure for all three simulations. The analysis includes comparisons to Planck tSZ observations and to the thermal pressure profile inferred from the Atacama Cosmology Telescope (ACT) measurements. We compare these tSZ data to simulations to interpret the measurements in terms of feedback and accretion processes in the CGM. We also identify as-yet unobserved potential signatures of these processes that may be visible in future measurements, which will have the capability of measuring tSZ signals to even lower masses. We also perform internal comparisons between runs with different physical assumptions. We conclude (1) there is strong evidence for the impact of feedback atR500, but that this impact decreases by 5R500, and (2) the thermodynamic profiles of the CGM are highly dependent on the implemented model, such as cosmic-ray or AGN feedback prescriptions.

     
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