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Abstract We present initial results from extremely well-resolved 3D magnetohydrodynamical simulations of idealized galaxy clusters, conducted using the AthenaPK code on the Frontier exascale supercomputer. These simulations explore the self-regulation of galaxy groups and cool-core clusters by cold gas-triggered active galactic nucleus (AGN) feedback incorporating magnetized kinetic jets. Our simulation campaign includes simulations of galaxy groups and clusters with a range of masses and intragroup and intracluster medium properties. In this paper, we present results that focus on a Perseus-like cluster. We find that the simulated clusters are self-regulating, with the cluster cores staying at a roughly constant thermodynamic state and AGN jet power staying at physically reasonable values (≃10⁴⁴–10⁴⁵erg s^–1) for billions of years without a discernible duty cycle. These simulations also produce significant amounts of cold gas, with calculations having strong magnetic fields generally both promoting cold gas formation and allowing cold gas out to much larger cluster-centric radii (≃100 kpc) than simulations with weak or no fields (≃10 kpc), and also having more filamentary cold gas morphology. We find that AGN feedback significantly increases the strength of magnetic fields at the center of the cluster. We also find that the magnetized turbulence generated by the AGN results in turbulence where the velocity power spectra are tied to AGN activity, whereas the magnetic energy spectra are much less impacted after reaching a stationary state. 

ABSTRACT Precipitation of cold gas due to thermal instability in both galaxy clusters and the circumgalactic medium may regulate active galactic nucleus feedback. We investigate thermal instability in idealized simulations of the circumgalactic medium with a parameter study of over 600 three-dimensional hydrodynamic simulations of stratified turbulence with cooling, each evolved for 10 Gyr. The entropy profiles are maintained in a steady state via an idealized ‘thermostat’ process, consistent with galaxy cluster entropy profiles. In the presence of external turbulent driving, we find cold gas precipitates, with a strong dependence whether the turbulent driving mechanism is solenoidal, compressive, or purely vertical. In the purely vertical turbulent driving regime, we find that significant cold gas may form when the cooling time to free-fall time $$t_{\rm cool} / t_{\text{ff}} \lesssim 5$$. Our simulations with a ratio of $$t_{\rm cool} / t_{\text{ff}} \sim 10$$ do not precipitate under any circumstances, perhaps because the thermostat mechanism we use maintains a significant non-zero entropy gradient. 

ABSTRACT The combination of galaxy–galaxy lensing (GGL) and galaxy clustering is a powerful probe of low-redshift matter clustering, especially if it is extended to the non-linear regime. To this end, we use an N-body and halo occupation distribution (HOD) emulator method to model the redMaGiC sample of colour-selected passive galaxies in the Dark Energy Survey (DES), adding parameters that describe central galaxy incompleteness, galaxy assembly bias, and a scale-independent multiplicative lensing bias Alens. We use this emulator to forecast cosmological constraints attainable from the GGL surface density profile ΔΣ(rp) and the projected galaxy correlation function wp, gg(rp) in the final (Year 6) DES data set over scales $$r_p=0.3\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$$. For a $$3{{\ \rm per\ cent}}$$ prior on Alens we forecast precisions of $$1.9{{\ \rm per\ cent}}$$, $$2.0{{\ \rm per\ cent}}$$, and $$1.9{{\ \rm per\ cent}}$$ on Ωm, σ8, and $$S_8 \equiv \sigma _8\Omega _m^{0.5}$$, marginalized over all halo occupation distribution (HOD) parameters as well as Alens. Adding scales $$r_p=0.3\!-\!3.0\, h^{-1} \, \mathrm{Mpc}$$ improves the S8 precision by a factor of ∼1.6 relative to a large scale ($$3.0\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$$) analysis, equivalent to increasing the survey area by a factor of ∼2.6. Sharpening the Alens prior to $$1{{\ \rm per\ cent}}$$ further improves the S8 precision to $$1.1{{\ \rm per\ cent}}$$, and it amplifies the gain from including non-linear scales. Our emulator achieves per cent-level accuracy similar to the projected DES statistical uncertainties, demonstrating the feasibility of a fully non-linear analysis. Obtaining precise parameter constraints from multiple galaxy types and from measurements that span linear and non-linear clustering offers many opportunities for internal cross-checks, which can diagnose systematics and demonstrate the robustness of cosmological results.