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Register a new userComparing Simulations of AGN Feedback
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We perform adaptive mesh refinement (AMR) and smoothed particle hydrodynamics (SPH) cosmological zoom simulations of a region around a forming galaxy cluster, comparing the ability of the methods to handle successively more complex baryonic physics. In the simplest, non-radiative case, the two methods are in good agreement with each other, but the SPH simulations generate central cores with slightly lower entropies and virial shocks at slightly larger radii, consistent with what has been seen in previous studies. The inclusion of radiative cooling, star formation, and stellar feedback leads to much larger differences between the two methods. Most dramatically, at z=5, rapid cooling in the AMR case moves the accretion shock well within the virial radius, while this shock remains near the virial radius in the SPH case, due to excess heating, coupled with poorer capturing of the shock width. On the other hand, the addition of feedback from active galactic nuclei (AGN) to the simulations results in much better agreement between the methods. In this case both simulations display halo gas entropies of 100 keV cm^2, similar decrements in the star-formation rate, and a drop in the halo baryon content of roughly 30%. This is consistent with AGN growth being self-regulated, regardless of the numerical method. However, the simulations with AGN feedback continue to differ in aspects that are not self-regulated, such that in SPH a larger volume of gas is impacted by feedback, and the cluster still has a lower entropy central core.
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We use the IllustrisTNG simulations to show how the fractions of quenched galaxies vary across different environments and cosmic time, and to quantify the role AGN feedback and preprocessing play in quenching group and cluster satellites. At $z=0$, we select galaxies with $M_* = 10^{9-12} M_{odot}$ residing within ($leq R_{200c}$) groups and clusters of total host mass $M_{200c}=10^{13-15.2} M_{odot}$. TNG predicts a quenched fraction of $sim70-90%$ (on average) for centrals and satellites $gtrsim 10^{10.5} M_{odot}$, regardless of host mass, cosmic time ($0leq zleq0.5$), clustercentric distance and time since infall in the $z=0$ host. Low-mass centrals ($lesssim 10^{10} M_{odot}$), instead, are rarely quenched unless they become members of groups ($10^{13-14} M_{odot}$) or clusters ($geq10^{14} M_{odot}$), where the quenched fraction rises to $sim80%$. The fraction of low-mass passive galaxies is higher closer to the host center and for more massive hosts. The population of low-mass satellites accreted $gtrsim$4-6 Gyr ago in massive hosts is almost entirely passive, thus suggesting an upper limit for the time needed for environmental quenching to occur. In fact, $sim30%$ of group and cluster satellites that are quenched at $z=0$ were already quenched before falling into their current host, and the bulk of them quenched as early as 4 to 10 billion years ago. For low-mass galaxies ($lesssim10^{10-10.5}M_{odot}$), this is due to preprocessing, whereby current satellites may have been members of other hosts, and hence have undergone environmental processes, before falling into their final host, this mechanism being more common and more effective for the purposes of quenching for satellites found today in more massive hosts. On the other hand, massive galaxies quench on their own and because of AGN feedback, regardless of whether they are centrals or satellites.
Feedback from active galactic nuclei (AGN) remains controversial despite its wide acceptance as necessary to regulate massive galaxy growth. A dedicated workshop was held on 16-20 October 2017 at the Lorentz Center in Leiden to distinguish between the reality and myths of AGN feedback from the observational side. Here, we summarize briefly all the sessions and outcome of the stimulating workshop. More details on the outcome of the discussions are provided in a series of articles.
Powerful relativistic jets in radio galaxies are capable of driving strong outflows but also inducing star-formation by pressure-triggering collapse of dense clouds. We review theoretical work on negative and positive active galactic nuclei feedback, discussing insights gained from recent hydrodynamical simulations of jet-driven feedback on galaxy scales that are applicable to compact radio sources. The simulations show that the efficiency of feedback and the relative importance of negative and positive feedback depends strongly on interstellar medium properties, especially the column depth and spatial distribution of clouds. Negative feedback is most effective if clouds are distributed spherically and individual clouds have small column depths, while positive feedback is most effective if clouds are predominantly in a disc-like configuration.
[abridged] Aims: We test the effects of re-orienting jets from an active galactic nucleus (AGN) on the intracluster medium in a galaxy cluster environment with short central cooling time. We investigate appearance and properties of the resulting cavities, and the efficiency of jets in providing near-isotropic heating to the cooling cluster core. Methods: We use numerical simulations to explore four models of jets over several active/inactive cycles. We keep the jet power and duration fixed, varying only the jet angle prescription. We track the total energy of the intracluster medium (ICM) in the cluster core over time, and the fraction of the jet energy transferred to the ICM, paying attention to where the energy is deposited. We also compare synthetic X-ray images of the simulated cluster to actual observations. Results: Jets whose re-orientation is minimal ($lesssim 20^{circ}$) typically produce conical structures of interconnected cavities, with the opening angle of the cones being $sim 15-20^{circ}$, extending to $sim 300$ kpc from the cluster centre. Such jets transfer about $60%$ of their energy to the ICM, yet they are not very efficient at heating the cluster core, as the jet energy is deposited further out. Jets that re-orient by $gtrsim 20^{circ}$ generally produce multiple pairs of detached cavities. Although smaller, these cavities are inflated within the central 50~kpc and are more isotropically distributed, resulting in more effective heating of the core. Such jets, over few hundreds Myr, can deposit up to $80%$ of their energy where it is required. Consequently, these models come the closest to an heating/cooling balance and to mitigating runaway cooling of the core, even though all models have identical power/duration profiles. Additionally, the corresponding synthetic X-ray images exhibit structures closely resembling those seen in real cool-core clusters.
The Lyman-$alpha$ forest is a powerful probe for cosmology, but it is also strongly impacted by galaxy evolution and baryonic processes such as Active Galactic Nuclei (AGN) feedback, which can redistribute mass and energy on large scales. We constrain the signatures of AGN feedback on the 1D power spectrum of the Lyman-$alpha$ forest using a series of eight hydro-cosmological simulations performed with the Adaptative Mesh Refinement code RAMSES. This series starts from the Horizon-AGN simulation and varies the sub-grid parameters for AGN feeding, feedback and stochasticity. These simulations cover the whole plausible range of feedback and feeding parameters according to the resulting galaxy properties. AGNs globally suppress the Lyman-$alpha$ power at all scales. On large scales, the energy injection and ionization dominate over the supply of gas mass from AGN-driven galactic winds, thus suppressing power. On small scales, faster cooling of denser gas mitigates the suppression. This effect increases with decreasing redshift. We provide lower and upper limits of this signature at nine redshifts between $z=4.25$ and $z=2.0$, making it possible to account for it at post-processing stage in future work given that running simulations without AGN feedback can save considerable amounts of computing resources. Ignoring AGN feedback in cosmological inference analyses leads to strong biases with 2% shift on $sigma_8$ and 1% shift on $n_s$, which represents twice the standards deviation of the current constraints on $n_s$.
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