Brightest cluster galaxies in cosmological simulations: achievements and limitations of AGN feedback models

We analyze the basic properties of Brightest Cluster Galaxies (BCGs) produced by state of the art cosmological zoom-in hydrodynamical simulations. These simulations have been run with different sub-grid physics included. Here we focus on the results obtained with and without the inclusion of the prescriptions for supermassive black hole (SMBH) growth and of the ensuing Active Galactic Nuclei (AGN) feedback. The latter process goes in the right direction of decreasing significantly the overall formation of stars. However, BCGs end up still containing too much stellar mass, a problem that increases with halo mass, and having an unsatisfactory structure. This is in the sense that their effective radii are too large, and that their density profiles feature a flattening on scales much larger than observed. We also find that our model of thermal AGN feedback has very little effect on the stellar velocity dispersions, which turn out to be very large. Taken together, these problems, which to some extent can be recognized also in other numerical studies typically dealing with smaller halo masses, indicate that on one hand present day sub-resolution models of AGN feedback are not effective enough in diminishing the global formation of stars in the most massive galaxies, but on the other hand they are relatively too effective in their centers. It is likely that a form of feedback generating large scale gas outflows from BCGs precursors, and a more widespread effect over the galaxy volume, can alleviate these difficulties.Comment: 17 pages, 14 figures, accepted for publication on MNRAS, comments welcom

Graph-Based Multi-Label Classification for WiFi Network Traffic Analysis

Network traffic analysis, and specifically anomaly and attack detection, call for sophisticated tools relying on a large number of features. Mathematical modeling is extremely difficult, given the ample variety of traffic patterns and the subtle and varied ways that malicious activity can be carried out in a network. We address this problem by exploiting data-driven modeling and computational intelligence techniques. Sequences of packets captured on the communication medium are considered, along with multi-label metadata. Graph-based modeling of the data are introduced, thus resorting to the powerful GRALG approach based on feature information granulation, identification of a representative alphabet, embedding and genetic optimization. The obtained classifier is evaluated both under accuracy and complexity for two different supervised problems and compared with state-of-the-art algorithms. We show that the proposed preprocessing strategy is able to describe higher level relations between data instances in the input domain, thus allowing the algorithms to suitably reconstruct the structure of the input domain itself. Furthermore, the considered Granular Computing approach is able to extract knowledge on multiple semantic levels, thus effectively describing anomalies as subgraphs-based symbols of the whole network graph, in a specific time interval. Interesting performances can thus be achieved in identifying network traffic patterns, in spite of the complexity of the considered traffic classes

Intrusion detection in wi-fi networks by modular and optimized ensemble of classifiers

4noopenWith the breakthrough of pervasive advanced networking infrastructures and paradigms such as 5G and IoT, cybersecurity became an active and crucial field in the last years. Furthermore, machine learning techniques are gaining more and more attention as prospective tools for mining of (possibly malicious) packet traces and automatic synthesis of network intrusion detection systems. In this work, we propose a modular ensemble of classifiers for spotting malicious attacks on Wi-Fi networks. Each classifier in the ensemble is tailored to characterize a given attack class and is individually optimized by means of a genetic algorithm wrapper with the dual goal of hyper-parameters tuning and retaining only relevant features for a specific attack class. Our approach also considers a novel false alarm management procedure thanks to a proper reliability measure formulation. The proposed system has been tested on the well-known AWID dataset, showing performances comparable with other state of the art works both in terms of accuracy and knowledge discovery capabilities. Our system is also characterized by a modular design of the classification model, allowing to include new possible attack classes in an efficient way.openAccademicoGiuseppe Granato; Alessio Martino; Luca Baldini; Antonello RizziGranato, Giuseppe; Martino, Alessio; Baldini, Luca; Rizzi, Antonell

Kinetic AGN Feedback Effects on Cluster Cool Cores Simulated using SPH

We implement novel numerical models of AGN feedback in the SPH code GADGET-3, where the energy from a supermassive black hole (BH) is coupled to the surrounding gas in the kinetic form. Gas particles lying inside a bi-conical volume around the BH are imparted a one-time velocity (10,000 km/s) increment. We perform hydrodynamical simulations of isolated cluster (total mass 10^14 /h M_sun), which is initially evolved to form a dense cool core, having central T<10^6 K. A BH resides at the cluster center, and ejects energy. The feedback-driven fast wind undergoes shock with the slower-moving gas, which causes the imparted kinetic energy to be thermalized. Bipolar bubble-like outflows form propagating radially outward to a distance of a few 100 kpc. The radial profiles of median gas properties are influenced by BH feedback in the inner regions (r<20-50 kpc). BH kinetic feedback, with a large value of the feedback efficiency, depletes the inner cool gas and reduces the hot gas content, such that the initial cool core of the cluster is heated up within a time 1.9 Gyr, whereby the core median temperature rises to above 10^7 K, and the central entropy flattens. Our implementation of BH thermal feedback (using the same efficiency as kinetic), within the star-formation model, cannot do this heating, where the cool core remains. The inclusion of cold gas accretion in the simulations produces naturally a duty cycle of the AGN with a periodicity of 100 Myr.Comment: 22 pages, 11 figures, version accepted for publication in MNRAS, references and minor revisions adde

The early phases of galaxy clusters formation in IR: coupling hydrodynamical simulations with GRASIL3D

We compute and study the infrared and sub-mm properties of high redshift ($z \gtrsim 1$) simulated clusters and proto-clusters. The results of a large set of hydro-dynamical zoom-in simulations including active galactic nuclei (AGN) feedback, have been treated with the recently developed radiative transfer code GRASIL-3D, which accounts for the effect of dust reprocessing in an arbitrary geometry. Here, we have slightly generalized the code to adapt it to the present purpose. Then we have post-processed boxes of physical size 2 Mpc encompassing each of the 24 most massive clusters identified at z=0, at several redshifts between 0.5 and 3, producing IR and sub-mm mock images of these regions and SEDs of the radiation coming out from them. While this field is in its infancy from the observational point of view, rapid development is expected in the near future thanks to observations performed in the far IR and sub-mm bands. Notably, we find that in this spectral regime our prediction are little affected by the assumption required by this post-processing, and the emission is mostly powered by star formation rather than accretion onto super massive black hole (SMBH). The comparison with the little observational information currently available, highlights that the simulated cluster regions never attain the impressive star formation rates suggested by these observations. This problem becomes more intriguing taking into account that the brightest cluster galaxies (BCGs) in the same simulations turn out to be too massive. It seems that the interplay between the feedback schemes and the star formation model should be revised, possibly incorporating a positive feedback mode.Comment: 14 pages, 11 figures, MNRAS in press. Minor editorial improvement

Temperature Structure of the Intra-Cluster Medium from SPH and AMR simulations

Analyses of cosmological hydrodynamic simulations of galaxy clusters suggest that X-ray masses can be underestimated by 10% to 30%. The largest bias originates by both violation of hydrostatic equilibrium and an additional temperature bias caused by inhomogeneities in the X-ray emitting intra-cluster medium (ICM). To elucidate on this large dispersion among theoretical predictions, we evaluate the degree of temperature structures in cluster sets simulated either with smoothed-particle-hydrodynamics (SPH) and adaptive-mesh-refinement (AMR) codes. We find that the SPH simulations produce larger temperature variations connected to the persistence of both substructures and their stripped cold gas. This difference is more evident in no-radiative simulations, while it is reduced in the presence of radiative cooling. We also find that the temperature variation in radiative cluster simulations is generally in agreement with the observed one in the central regions of clusters. Around R_500 the temperature inhomogeneities of the SPH simulations can generate twice the typical hydrostatic-equilibrium mass bias of the AMR sample. We emphasize that a detailed understanding of the physical processes responsible for the complex thermal structure in ICM requires improved resolution and high sensitivity observations in order to extend the analysis to higher temperature systems and larger cluster-centric radii.Comment: 13 pages, 12 figures, 4 table

Dust evolution with MUPPI in cosmological volumes

We study the evolution of dust in a cosmological volume using a hydrodynamical simulation in which the dust production is coupled with the MUPPI (MUlti Phase Particle Integrator) sub-resolution model of star formation and feedback. As for the latter, we keep as reference the model setup calibrated previously to match the general properties of Milky Way-like galaxies in zoom-in simulations. However, we suggest that an increase of the star formation efficiency with the local dust-to-gas ratio would better reproduce the observed evolution of the cosmic star formation density. Moreover, the paucity of quenched galaxies at low redshift demands a stronger role of active galactic nucleus feedback. We tune the parameters ruling direct dust production from evolved stars and accretion in the interstellar medium to get scaling relations involving dust, stellar mass and metallicity in good agreement with observations. In low-mass galaxies, the accretion process is inefficient. As a consequence, they remain poorer in silicate and small grains than higher mass ones. We reproduce reasonably well the few available data on the radial distribution of dust outside the galactic region, supporting the assumption that the dust and gas dynamics are well coupled at galactic scales

Impact of AGN feedback on galaxies and their multiphase ISM across cosmic time

We present simulations of galaxy formation, based on the GADGET-3 code, in which a sub-resolution model for star formation and stellar feedback is interfaced with a new model for AGN feedback. Our sub-resolution model describes a multiphase ISM, accounting for hot and cold gas within the same resolution element: we exploit this feature to investigate the impact of coupling AGN feedback energy to the different phases of the ISM over cosmic time. Our fiducial model considers that AGN feedback energy coupling is driven by the covering factors of the hot and cold phases. We perform a suite of cosmological hydrodynamical simulations of disc galaxies (Mhalo, DM 43 2 . 1012 M&09, at z = 0), to investigate: (i) the effect of different ways of coupling AGN feedback energy to the multiphase ISM; (ii) the impact of different prescriptions for gas accretion (i.e. only cold gas, both cold and hot gas, with the additional possibility of limiting gas accretion from cold gas with high angular momentum); (iii) how different models of gas accretion and coupling of AGN feedback energy affect the coevolution of supermassive BHs and their host galaxy. We find that at least a share of the AGN feedback energy has to couple with the diffuse gas, in order to avoid an excessive growth of the BH mass. When the BH only accretes cold gas, it experiences a growth that is faster than in the case in which both cold and hot gas are accreted. If the accretion of cold gas with high angular momentum is reduced, the BH mass growth is delayed, the BH mass at z = 0 is reduced by up to an order of magnitude, and the BH is prevented from accreting below z 72 2, when the galaxy disc forms

Modulation of telomerase activity, bTERT and c-Myc induced by 2,3,7,8-tetrachlorodibenzo-p-dioxin during Bovine Herpesvirus 1 infection in MDBK cells.

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) influences infection of kidney cells (MDBK) with Bovine Herpesvirus 1 (BHV-1) through an increase in virus replication and an acceleration of BHV-1-induced apoptosis. Previously our group demonstrated that BHV-1, in the early stages of infection, significantly up-regulates telomerase activity in MDBK cells, while, in the late phases of infection, when BHV-1-induced apoptosis occurred, a down-regulation of telomerase activity was detected. Hence, herein, for the first time, we described the influences of TCDD on telomerase activity during virus infection. In kidney cells (MDBK) infected with BHV-1 and exposed to different doses of TCDD we explored telomerase activity by TRAP assay. Concomitantly, we examined protein levels of both bTERT and c-Myc by Western blot analysis. In all groups, TCDD induced an acceleration in down-regulation of telomerase activity. Particularly, TCDD drastically and significantly decreased telomerase activity when virus-induced apoptosis took place. This result was accompanied from an accelerated down-regulation of bTERT and c-Myc. Finally, in the presence of TCDD, we evidenced a dose-dependent overexpression of aryl hydrocarbon receptor. Hence, our data suggest that TCDD, through a significant acceleration in down-regulation of telomerase activity, bTERT and c-Myc, may contribute to accelerated BHV-1-induced apoptosis