On the role of AGN feedback on the thermal and chemodynamical properties of the hot intra-cluster medium

We present an analysis of the properties of the ICM in an extended set of cosmological hydrodynamical simulations of galaxy clusters and groups performed with the TreePM+SPH GADGET-3 code. Besides a set of non-radiative simulations, we carried out two sets of simulations including radiative cooling, star formation, metal enrichment and feedback from supernovae, one of which also accounts for the effect of feedback from AGN resulting from gas accretion onto super-massive black holes. These simulations are analysed with the aim of studying the relative role played by SN and AGN feedback on the general properties of the diffuse hot baryons in galaxy clusters and groups: scaling relations, temperature, entropy and pressure radial profiles, and ICM chemical enrichment. We find that simulations including AGN feedback produce scaling relations that are in good agreement with X-ray observations at all mass scales. However, our simulations are not able to account for the observed diversity between CC and NCC clusters: unlike for observations, we find that temperature and entropy profiles of relaxed and unrelaxed clusters are quite similar and resemble more the observed behaviour of NCC clusters. As for the pattern of metal enrichment, we find that an enhanced level of iron abundance is produced by AGN feedback with respect to the case of purely SN feedback. As a result, while simulations including AGN produce values of iron abundance in groups in agreement with observations, they over-enrich the ICM in massive clusters. The efficiency of AGN feedback in displacing enriched gas from halos into the inter-galactic medium at high redshift also creates a widespread enrichment in the outskirts of clusters and produces profiles of iron abundance whose slope is in better agreement with observations.Comment: 23 pages, 14 figures, 1 table, accepted for publication in MNRA

Cool Core Clusters from Cosmological Simulations

We present results obtained from a set of cosmological hydrodynamic simulations of galaxy clusters, aimed at comparing predictions with observational data on the diversity between cool-core (CC) and non-cool-core (NCC) clusters. Our simulations include the effects of stellar and AGN feedback and are based on an improved version of the smoothed particle hydrodynamics code GADGET-3, which ameliorates gas mixing and better captures gas-dynamical instabilities by including a suitable artificial thermal diffusion. In this Letter, we focus our analysis on the entropy profiles, the primary diagnostic we used to classify the degree of cool-coreness of clusters, and on the iron profiles. In keeping with observations, our simulated clusters display a variety of behaviors in entropy profiles: they range from steadily decreasing profiles at small radii, characteristic of cool-core systems, to nearly flat core isentropic profiles, characteristic of non-cool-core systems. Using observational criteria to distinguish between the two classes of objects, we find that they occur in similar proportions in both simulations and in observations. Furthermore, we also find that simulated cool-core clusters have profiles of iron abundance that are steeper than those of NCC clusters, which is also in agreement with observational results. We show that the capability of our simulations to generate a realistic cool-core structure in the cluster population is due to AGN feedback and artificial thermal diffusion: their combined action allows us to naturally distribute the energy extracted from super-massive black holes and to compensate for the radiative losses of low-entropy gas with short cooling time residing in the cluster core.Comment: 6 pages, 4 figures, accepted in ApJL, v2 contains some modifications on the text (results unchanged

The Halo Mass-Bias Redshift Evolution in the Λ\LambdaCDM Cosmology

We derive an analytic model for the redshift evolution of linear-bias, allowing for interactions and merging of the mass-tracers, by solving a second order differential equation based on linear perturbation theory and the Friedmann-Lemaitre solutions of the cosmological field equations. We then study the halo-mass dependence of the bias evolution, using the dark matter halo distribution in a $\Lambda$CDM simulation in order to calibrate the free parameters of the model. Finally, we compare our theoretical predictions with available observational data and find a good agreement. In particular, we find that the bias of optical QSO's evolve differently than those selected in X-rays and that their corresponding typical dark matter halo mass is $\sim 10^{13} h^{-1} M_{\odot}$ and \magcir 5 \times 10^{13} h^{-1} M_{\odot}, respectively.Comment: 8 pages, 5 figures, accepted for publication in Ap

Machine learning to identify ICL and BCG in simulated galaxy clusters

Nowadays, Machine Learning techniques offer fast and efficient solutions for classification problems that would require intensive computational resources via traditional methods. We examine the use of a supervised Random Forest to classify stars in simulated galaxy clusters after subtracting the member galaxies. These dynamically different components are interpreted as the individual properties of the stars in the Brightest Cluster Galaxy (BCG) and IntraCluster Light (ICL). We employ matched stellar catalogues (built from the different dynamical properties of BCG and ICL) of 29 simulated clusters from the DIANOGA set to train and test the classifier. The input features are cluster mass, normalized particle cluster-centric distance, and rest-frame velocity. The model is found to correctly identify most of the stars, while the larger errors are exhibited at the BCG outskirts, where the differences between the physical properties of the two components are less obvious. We investigate the robustness of the classifier to numerical resolution, redshift dependence (up to z = 1), and included astrophysical models. We claim that our classifier provides consistent results in simulations for z 0.1 R-200) is significantly affected by uncertainties in the classification process. In conclusion, this work suggests the importance of employing Machine Learning to speed up a computationally expensive classification in simulations

Cosmological hydrodynamical simulations of galaxy clusters: X-ray scaling relations and their evolution

We analyse cosmological hydrodynamical simulations of galaxy clusters to study the X-ray scaling relations between total masses and observable quantities such as X-ray luminosity, gas mass, X-ray temperature, and $Y_{X}$. Three sets of simulations are performed with an improved version of the smoothed particle hydrodynamics GADGET-3 code. These consider the following: non-radiative gas, star formation and stellar feedback, and the addition of feedback by active galactic nuclei (AGN). We select clusters with $M_{500} > 10^{14} M_{\odot} E(z)^{-1}$, mimicking the typical selection of Sunyaev-Zeldovich samples. This permits to have a mass range large enough to enable robust fitting of the relations even at $z \sim 2$. The results of the analysis show a general agreement with observations. The values of the slope of the mass-gas mass and mass-temperature relations at $z=2$ are 10 per cent lower with respect to $z=0$ due to the applied mass selection, in the former case, and to the effect of early merger in the latter. We investigate the impact of the slope variation on the study of the evolution of the normalization. We conclude that cosmological studies through scaling relations should be limited to the redshift range $z=0-1$, where we find that the slope, the scatter, and the covariance matrix of the relations are stable. The scaling between mass and $Y_X$ is confirmed to be the most robust relation, being almost independent of the gas physics. At higher redshifts, the scaling relations are sensitive to the inclusion of AGNs which influences low-mass systems. The detailed study of these objects will be crucial to evaluate the AGN effect on the ICM.Comment: 24 pages, 11 figures, 5 tables, replaced to match accepted versio

The Relation Between Halo Shape, Velocity Dispersion and Formation Time

We use dark matter haloes identified in the MareNostrum Universe and galaxy groups identified in the Sloan Data Release 7 galaxy catalogue, to study the relation between halo shape and halo dynamics, parametrizing out the mass of the systems. A strong shape-dynamics, independent of mass, correlation is present in the simulation data, which we find it to be due to different halo formation times. Early formation time haloes are, at the present epoch, more spherical and have higher velocity dispersions than late forming-time haloes. The halo shape-dynamics correlation, albeit weaker, survives the projection in 2D (ie., among projected shape and 1-D velocity dispersion). A similar shape-dynamics correlation, independent of mass, is also found in the SDSS DR7 groups of galaxies and in order to investigate its cause we have tested and used, as a proxy of the group formation time, a concentration parameter. We have found, as in the case of the simulated haloes, that less concentrated groups, corresponding to late formation times, have lower velocity dispersions and higher elongations than groups with higher values of concentration, corresponding to early formation times.Comment: MNRAS in press (10 pages, 10 figures

A Consistent Comparison of Bias Models using Observational Data

We investigate five different models for the dark matter halo bias, ie., the ratio of the fluctuations of mass tracers to those of the underlying mass, by comparing their cosmological evolution using optical QSO and galaxy bias data at different redshifts, consistently scaled to the WMAP7 cosmology. Under the assumption that each halo hosts one extragalactic mass tracer, we use a $\chi^2$ minimization procedure to determine the free parameters of the bias models as well as to statistically quantify their ability to represent the observational data. Using the Akaike information criterion we find that the model that represents best the observational data is the Basilakos & Plionis (2001; 2003) model with the tracer merger extension of Basilakos, Plionis & Ragone-Figueroa (2008) model. The only other statistically equivalent model, as indicated by the same criterion, is the Tinker et al. (2010) model. Finally, we find an average, over the different models, dark matter halo mass that hosts optical QSOs of: $M_h\simeq 2.7 (\pm 0.6) \times 10^{12} h^{-1} M_{\odot}$, while the corresponding value for optical galaxies is: $M_h\simeq 6.3 (\pm 2.1) \times 10^{11} h^{-1} M_{\odot}$.Comment: MNRAS in press, 12 pages, 6 color figures, 4 table

Simulation-based marginal likelihood for cluster strong lensing cosmology

Comparisons between observed and predicted strong lensing properties of galaxy clusters have been routinely used to claim either tension or consistency with \u39b cold dark matter cosmology. However, standard approaches to such cosmological tests are unable to quantify the preference for one cosmology over another. We advocate approximating the relevant Bayes factor using a marginal likelihood that is based on the following summary statistic: the posterior probability distribution function for the parameters of the scaling relation between Einstein radii and cluster mass, \u3b1 and \u3b2. We demonstrate, for the first time, a method of estimating the marginal likelihood using the X-ray selected z > 0.5 Massive Cluster Survey clusters as a case in point and employing both N-body and hydrodynamic simulations of clusters. We investigate the uncertainty in this estimate and consequential ability to compare competing cosmologies, which arises from incomplete descriptions of baryonic processes, discrepancies in cluster selection criteria, redshift distribution and dynamical state. The relation between triaxial cluster masses at various overdensities provides a promising alternative to the strong lensing test

Evolution and role of mergers in the BCG-cluster alignment. A view from cosmological hydrosimulations

Contradictory results have been reported on the time evolution of the alignment between clusters and their brightest cluster galaxy (BCG). We study this topic by analysing cosmological hydrosimulations of 24 massive clusters with M-200 vertical bar z=0 greater than or similar to 10(15) M-circle dot, plus 5 less massive with 1 x 10(14) less than or similar to M-200 vertical bar z=0 less than or similar to 7 x 10(14) M (circle dot), which have already proven to produce realistic BCG masses. We compute the BCG alignment with both the distribution of cluster galaxies and the dark matter (DM) halo. At redshift z = 0, the major axes of the simulated BCGs and their host cluster galaxy distributions are aligned on average within 20 degrees. The BCG alignment with the DM halo is even tighter. The alignment persists up to z less than or similar to 2 with no evident evolution. This result continues, although with a weaker signal, when considering the projected alignment. The cluster alignment with the surrounding distribution of matter (3R(200)) is already in place at z similar to 4 with a typical angle of 35., before the BCG-cluster alignment develops. The BCG turns out to be also aligned with the same matter distribution, albeit always to a lesser extent. These results taken together might imply that the BCG-cluster alignment occurs in an outside-in fashion. Depending on their frequency and geometry, mergers can promote, destroy or weaken the alignments. Clusters that do not experience recent majormergers are typically more relaxed and aligned with their BCG. In turn, accretions closer to the cluster elongation axis tend to improve the alignment as opposed to accretions closer to the cluster minor axis