The interplay between AGN feedback and precipitation of the intracluster medium in simulations of galaxy groups and clusters

Using high-resolution hydrodynamical simulations of galaxy clusters, we study the interaction between the brightest cluster galaxy, its supermassive black hole (BH) and the intracluster medium (ICM). We create initial conditions for which the ICM is in hydrostatic equilibrium within the gravitational potential from the galaxy and an NFW dark matter halo. Two free parameters associated with the thermodynamic profiles determine the cluster gas fraction and the central temperature, where the latter can be used to create cool-core or non-cool-core systems. Our simulations include radiative cooling, star formation, BH accretion, and stellar and active galactic nucleus (AGN) feedback. Even though the energy of AGN feedback is injected thermally and isotropically, it leads to anisotropic outflows and buoyantly rising bubbles. We find that the BH accretion rate (BHAR) is highly variable and only correlates strongly with the star formation rate (SFR) and the ICM when it is averaged over more than $1~\rm Myr$. We generally find good agreement with the theoretical precipitation framework. In $10^{13}~\rm M_\odot$ haloes, AGN feedback quenches the central galaxy and converts cool-core systems into non-cool-core systems. In contrast, higher-mass, cool-core clusters evolve cyclically. Episodes of high BHAR raise the entropy of the ICM out to the radius where the ratio of the cooling time and the local dynamical time $t_{\rm cool}/t_{\rm dyn} > 10$, thus suppressing condensation and, after a delay, the BHAR. The corresponding reduction in AGN feedback allows the ICM to cool and become unstable to precipitation, thus initiating a new episode of high SFR and BHAR.Comment: 22 pages, 15 figures (including appendix); submitted to MNRAS; Supplementary material is available on Youtube at https://youtu.be/HQhc_mytj0A and online on a single website page at https://home.strw.leidenuniv.nl/~nobels/supplementary_idealised_cluster_paper.ph

The stellar mass function and evolution of the density profile of galaxy clusters from the Hydrangea simulations at 0<z<1.50<z<1.5

Galaxy clusters are excellent probes to study the effect of environment on galaxy formation and evolution. Along with high-quality observational data, accurate cosmological simulations are required to improve our understanding of galaxy evolution in these systems. In this work, we compare state-of-the-art observational data of massive galaxy clusters ($>10^{14} \textrm{M}_{\odot}$) at different redshifts ($0<z<1.5$) with predictions from the Hydrangea suite of cosmological hydrodynamic simulations of 24 massive galaxy clusters ($>10^{14} \textrm{M}_{\odot}$ at $z=0$). We compare three fundamental observables of galaxy clusters: the total stellar mass to halo mass ratio, the stellar mass function (SMF), and the radial mass density profile of the cluster galaxies. In the first two of these, the simulations agree well with the observations, albeit with a slightly too high abundance of $M_\star \lesssim 10^{10} \textrm{M}_{\odot}$ galaxies at $z \gtrsim 1$. The NFW concentrations of cluster galaxies increase with redshift, in contrast to the decreasing dark matter halo concentrations. This previously observed behaviour is therefore due to a qualitatively different assembly of the smooth DM halo compared to the satellite population. Quantitatively, we however find a discrepancy in that the simulations predict higher stellar concentrations than observed at lower redshifts ($z<0.3$), by a factor of $\approx$2. This may be due to selection bias in the simulations, or stem from shortcomings in the build-up and stripping of their inner satellite halo.Comment: 14 pages, 9 figures (excluding appendices), Accepted for publication in MNRA

Too dense to go through: The importance of low-mass clusters for satellite quenching

We study the evolution of satellite galaxies in clusters of the C-EAGLE simulations, a suite of 30 high-resolution cosmological hydrodynamical zoom-in simulations based on the EAGLE code. We find that the majority of galaxies that are quenched at $z=0$ ($\gtrsim$ 80$\%$) reached this state in a dense environment (log$_{10}$M$_{200}$[M$_{\odot}$]$\geq$13.5). At low redshift, regardless of the final cluster mass, galaxies appear to reach their quenching state in low mass clusters. Moreover, galaxies quenched inside the cluster that they reside in at $z=0$ are the dominant population in low-mass clusters, while galaxies quenched in a different halo dominate in the most massive clusters. When looking at clusters at $z>0.5$, their in-situ quenched population dominates at all cluster masses. This suggests that galaxies are quenched inside the first cluster they fall into. After galaxies cross the cluster's $r_{200}$ they rapidly become quenched ($\lesssim$ 1Gyr). Just a small fraction of galaxies ($\lesssim 15\%$) is capable of retaining their gas for a longer period of time, but after 4Gyr, almost all galaxies are quenched. This phenomenon is related to ram pressure stripping and is produced when the density of the intracluster medium reaches a threshold of $\rho_{\rm ICM}$ $\sim 3 \times 10 ^{-5}$ n$_{\rm H}$ (cm$^{-3}$). These results suggest that galaxies start a rapid-quenching phase shortly after their first infall inside $r_{200}$ and that, by the time they reach $r_{500}$, most of them are already quenched.Comment: 14 pages, 8 figures, Submitted to MNRA

A machine learning approach to mapping baryons on to dark matter haloes using the eagle and C-EAGLE simulations

High-resolution cosmological hydrodynamic simulations are currently limited to relatively small volumes due to their computational expense. However, much larger volumes are required to probe rare, overdense environments, and measure clustering statistics of the large scale structure. Typically, zoom simulations of individual regions are used to study rare environments, and semi-analytic models and halo occupation models applied to dark matter only (DMO) simulations are used to study the Universe in the large-volume regime. We propose a new approach, using a machine learning framework to explore the halo-galaxy relationship in the periodic EAGLE simulations, and zoom C-EAGLE simulations of galaxy clusters. We train a tree based machine learning method to predict the baryonic properties of galaxies based on their host dark matter halo properties. The trained model successfully reproduces a number of key distribution functions for an infinitesimal fraction of the computational cost of a full hydrodynamic simulation. By training on both periodic simulations as well as zooms of overdense environments, we learn the bias of galaxy evolution in differing environments. This allows us to apply the trained model to a larger DMO volume than would be possible if we only trained on a periodic simulation. We demonstrate this application using the (800 Mpc)3 P-Millennium simulation, and present predictions for key baryonic distribution functions and clustering statistics from the EAGLE model in this large volume

EAGLE-like simulation models do not solve the entropy core problem in groups and clusters of galaxies

Recent high-resolution cosmological hydrodynamic simulations run with a variety of codes systematically predict large amounts of entropy in the intra-cluster medium at low redshift, leading to flat entropy profiles and a suppressed cool-core population. This prediction is at odds with X-ray observations of groups and clusters. We use a new implementation of the EAGLE galaxy formation model to investigate the sensitivity of the central entropy and the shape of the profiles to changes in the sub-grid model applied to a suite of zoom-in cosmological simulations of a group of mass M500 = 8.8 × 1012 M⊙ and a cluster of mass 2.9 × 1014 M⊙. Using our reference model, calibrated to match the stellar mass function of field galaxies, we confirm that our simulated groups and clusters contain hot gas with too high entropy in their cores. Additional simulations run without artificial conduction, metal cooling or active galactic nuclei (AGN) feedback produce lower entropy levels but still fail to reproduce observed profiles. Conversely, the two objects run without supernova feedback show a significant entropy increase which can be attributed to excessive cooling and star formation. Varying the AGN heating temperature does not greatly affect the profile shape, but only the overall normalization. Finally, we compared runs with four AGN heating schemes and obtained similar profiles, with the exception of bipolar AGN heating, which produces a higher and more uniform entropy distribution. Our study leaves open the question of whether the entropy core problem in simulations, and particularly the lack of power-law cool-core profiles, arise from incorrect physical assumptions, missing physical processes, or insufficient numerical resolution

Star formation concentration as a tracer of environmental quenching in action: a study of the Eagle and C-Eagle simulations

We study environmental quenching in the Eagle}/C-Eagle cosmological hydrodynamic simulations over the last 11 Gyr (i.e. $z=0-2$). The simulations are compared with observations from the SAMI Galaxy Survey at $z=0$. We focus on satellite galaxies in galaxy groups and clusters ($10^{12}\,\rm M_{\odot}$ $\lesssim$ $M_{200}$ < $3 \times 10^{15}\, \rm M_{\odot}$). A star-formation concentration index [$C$-index $= \log_{10}(r_\mathrm{50,SFR} / r_\mathrm{50,rband})$] is defined, which measures how concentrated star formation is relative to the stellar distribution. Both Eagle/C-Eagle and SAMI show a higher fraction of galaxies with low $C$-index in denser environments at $z=0-0.5$. Low $C$-index galaxies are found below the SFR-$M_{\star}$ main sequence (MS), and display a declining specific star formation rate (sSFR) with increasing radii, consistent with ``outside-in'' environmental quenching. Additionally, we show that $C$-index can be used as a proxy for how long galaxies have been satellites. These trends become weaker at increasing redshift and are absent by $z=1-2$. We define a quenching timescale $t_{\rm quench}$ as how long it takes satellites to transition from the MS to the quenched population. We find that simulated galaxies experiencing ``outside-in'' environmental quenching at low redshift ($z=0\sim0.5$) have a long quenching timescale (median $t_{\rm quench}$ > 2 Gyr). The simulated galaxies at higher redshift ($z=0.7\sim2$) experience faster quenching (median $t_{\rm quench}$ < 2Gyr). At $z\gtrsim 1-2$ galaxies undergoing environmental quenching have decreased sSFR across the entire galaxy with no ``outside-in'' quenching signatures and a narrow range of $C$-index, showing that on average environmental quenching acts differently than at $z\lesssim 1$.Comment: 21 pages, 17 figures

Disruption of satellite galaxies in simulated groups and clusters: the roles of accretion time, baryons, and pre-processing

We investigate the disruption of group and cluster satellite galaxies with total mass (dark matter plus baryons) above 1010M⊙ in the Hydrangea simulations, a suite of 24 high-resolution cosmological hydrodynamical zoom-in simulations based on the EAGLE model. The simulations predict that ∼50 per cent of satellites survive to redshift z = 0, with higher survival fractions in massive clusters than in groups and only small differences between baryonic and pure N-body simulations. For clusters, up to 90 per cent of galaxy disruption occurs in lower-mass subgroups (i.e. during pre-processing); 96 per cent of satellites in massive clusters that were accreted at z < 2 and have not been pre-processed survive. Of those satellites that are disrupted, only a few per cent merge with other satellites, even in low-mass groups. The survival fraction changes rapidly from less than 10 per cent of those accreted at high z to more than 90 per cent at low z⁠. This shift, which reflects faster disruption of satellites accreted at higher z⁠, happens at lower z for more massive galaxies and those accreted on to less massive haloes. The disruption of satellite galaxies is found to correlate only weakly with their pre-accretion baryon content, star formation rate, and size, so that surviving galaxies are nearly unbiased in these properties. These results suggest that satellite disruption in massive haloes is uncommon, and that it is predominantly the result of gravitational rather than baryonic processes

The Cluster-EAGLE project: Velocity bias and the velocity dispersion-mass relation of cluster galaxies

We use the Cluster-EAGLE simulations to explore the velocity bias introduced when using galaxies, rather than dark matter particles, to estimate the velocity dispersion of a galaxy cluster, a property known to be tightly correlated with cluster mass. The simulations consist of 30 clusters spanning a mass range 14.0 ≤ log 10 (M 200 c /M ⊙ ) ≤ 15.4, with their sophisticated subgrid physics modelling and high numerical resolution (subkpc gravitational softening), making them ideal for this purpose. We find that selecting galaxies by their total mass results in a velocity dispersion that is 5-10 per cent higher than the dark matter particles. However, selecting galaxies by their stellar mass results in an almost unbiased ( < 5 per cent) estimator of the velocity dispersion. This result holds out to z = 1.5 and is relatively insensitive to the choice of cluster aperture, varying by less than 5 per cent between r 500 c and r 200m . We show that the velocity bias is a function of the time spent by a galaxy inside the cluster environment. Selecting galaxies by their total mass results in a larger bias because a larger fraction of objects have only recently entered the cluster and these have a velocity bias above unity. Galaxies that entered more than 4 Gyr ago become progressively colder with time, as expected from dynamical friction. We conclude that velocity bias should not be a major issue when estimating cluster masses from kinematic methods