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C. Ragone-Figueroa

Publications and source records attributed to C. Ragone-Figueroa.

15 recordsLinked to original sources

CLASH-VLT: The variance in the velocity anisotropy profiles of galaxy clusters

The velocity anisotropy profiles, $β(r)$, of galaxy clusters are directly related to the shape of the orbits of their member galaxies. Knowledge of $β(r)$ is important to understand the assembly process of clusters and the evolutionary processes of their galaxies, and to improve the determination of cluster masses based on cluster kinematics. We determined the $β(r)$ of nine massive clusters at redshift $0.19 \leq z \leq 0.45$ from the CLASH-VLT data set, with 150 to 950 spectroscopic members each. We selected spectroscopic cluster members with the CLUMPS algorithm calibrated on cosmological simulations. We applied the MAMPOSSt code to the distribution of cluster members in projected phase-space to constrain the cluster mass profile, $M(r)$, using priors derived from a previous gravitational lensing analysis. Given the MAMPOSSt best-fit solution for $M(r)$, we then solved the inversion of the Jeans equation to determine $β(r)$ without assumptions of its functional form. We also ran the DS+ code to identify subclusters and characterize the dynamical status of our clusters. The average $β(r)$ is slightly radial, with the anisotropy increasing from $β\simeq 0.2$ at the cluster center, to $β\simeq 0.5$ at the virial radius. There is substantial variance in the $β(r)$ of the individual clusters, that cannot be entirely accounted for by the observational uncertainties. Clusters of lower mass and with a low concentration per given mass have more tangential $β(r)$. A comparison with cluster-sized halos in cosmological hydrodynamical simulations indicates a very good agreement for the average $β(r)$, but a smaller variance in the profiles than observed. We conclude that massive clusters cannot be characterized by a unique universal $β(r)$ and that the orbital distribution of cluster galaxies carries information on the merging history of the cluster.

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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 outskirt, 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 $z<1$, at different resolution levels and with significantly different subgrid models. The phase-space structure is examined to assess whether the general properties of the stellar components are recovered: (i) the transition radius between BCG-dominated and ICL-dominated region is identified at $0.04$ \r200; (ii) the BCG outskirt ($> 0.1$ \r200) 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.

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Velocity dispersion of the brightest cluster galaxies in cosmological simulations

Using the DIANOGA hydrodynamical zoom-in simulation set of galaxy clusters, we analyze the dynamics traced by stars belonging to the Brightest Cluster Galaxies (BCGs) and their surrounding diffuse component, forming the intracluster light (ICL), and compare it to the dynamics traced by dark matter and galaxies identified in the simulations. We compute scaling relations between the BCG and cluster velocity dispersions and their corresponding masses (i.e. $M_\mathrm{BCG}^{\star}$- $σ_\mathrm{BCG}^{\star}$, $M_{200}$- $σ_{200}$, $M_\mathrm{BCG}^{\star}$- $M_{200}$, $σ_\mathrm{BCG}^{\star}$- $σ_{200}$), we find in general a good agreement with observational results. Our simulations also predict $σ_\mathrm{BCG}^{\star}$- $σ_{200}$ relation to not change significantly up to redshift $z=1$, in line with a relatively slow accretion of the BCG stellar mass at late times. We analyze the main features of the velocity dispersion profiles, as traced by stars, dark matter, and galaxies. As a result, we discuss that observed stellar velocity dispersion profiles in the inner cluster regions are in excellent agreement with simulations. We also report that the slopes of the BCG velocity dispersion profile from simulations agree with what is measured in observations, confirming the existence of a robust correlation between the stellar velocity dispersion slope and the cluster velocity dispersion (thus, cluster mass) when the former is computed within $0.1 R_{500}$. Our results demonstrate that simulations can correctly describe the dynamics of BCGs and their surrounding stellar envelope, as determined by the past star-formation and assembly histories of the most massive galaxies of the Universe.

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The DIANOGA simulations of galaxy clusters: characterizing star formation in proto-clusters

We studied the star formation rate (SFR) in cosmological hydrodynamical simulations of galaxy (proto-)clusters in the redshift range $0<z<4$, comparing them to recent observational studies; we also investigated the effect of varying the parameters of the star formation model on galaxy properties such as SFR, star-formation efficiency, and gas fraction. We analyze a set of zoom-in cosmological hydrodynamical simulations centred on twelve clusters. The simulations are carried out with the GADGET-3 TreePM/SPH code which includes various subgrid models to treat unresolved baryonic physics, including AGN feedback. Simulations do not reproduce the high values of SFR observed within protoclusters cores, where the values of SFR are underpredicted by a factor $\gtrsim 4$ both at $z\sim2$ and $z\sim 4$. The difference arises as simulations are unable to reproduce the observed starburst population and is worsened at $z\sim 2$ because simulations underpredict the normalization of the main sequence of star forming galaxies (i.e., the correlation between stellar mass and SFR) by a factor of $\sim 3$. As the low normalization of the main sequence seems to be driven by an underestimated gas fraction, it remains unclear whether numerical simulations miss starburst galaxies due to a too low predicted gas fractions or too low star formation efficiencies. Our results are stable against varying several parameters of the star formation subgrid model and do not depend on the details of the AGN feedback.

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BCG Mass Evolution in Cosmological Hydro-Simulations

We analyze the stellar growth of Brightest Cluster Galaxies (BCGs) produced by cosmological zoom-in hydrodynamical simulations of the formation of massive galaxy clusters. The evolution of the stellar mass content is studied considering different apertures, and tracking backwards either the main progenitor of the $z=0$ BCG or that of the cluster hosting the BCG at $z=0$. Both methods lead to similar results up to $z \simeq 1.5$. The simulated BCGs masses at $z=0$ are in agreement with recent observations. In the redshift interval from $z=1$ to $z=0$ we find growth factors 1.3, 1.6 and 3.6 for stellar masses within 30kpc, 50kpc and 10% of $R_{500}$ respectively. The first two factors, and in general the mass evolution in this redshift range, are in agreement with most recent observations. The last larger factor is similar to the growth factor obtained by a semi-analytical model (SAM). Half of the star particles that end up in the inner 50 kpc was typically formed by redshift $\sim$ 3.7, while the assembly of half of the BCGs stellar mass occurs on average at lower redshifts $\sim 1.5$. This assembly redshift correlates with the mass attained by the cluster at high $z \gtrsim 1.3$, due to the broader range of the progenitor clusters at high-$z$. The assembly redshift of BCGs decreases with increasing apertures. Our results are compatible with the {\it inside-out} scenario. Simulated BCGs could lack intense enough star formation (SF) at high redshift, while possibly exhibit an excess of residual SF at low redshift.

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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.

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Pressure of the hot gas in simulations of galaxy clusters

We analyze the radial pressure profiles, the ICM clumping factor and the Sunyaev-Zel'dovich (SZ) scaling relations of a sample of simulated galaxy clusters and groups identified in a set of hydrodynamical simulations based on an updated version of the TreePM-SPH GADGET-3 code. Three different sets of simulations are performed: the first assumes non-radiative physics, the others include, among other processes, AGN and/or stellar feedback. Our results are analyzed as a function of redshift, ICM physics, cluster mass and cluster cool-coreness or dynamical state. In general, the mean pressure profiles obtained for our sample of groups and clusters show a good agreement with X-ray and SZ observations. Simulated cool-core (CC) and non-cool-core (NCC) clusters also show a good match with real data. We obtain in all cases a small (if any) redshift evolution of the pressure profiles of massive clusters, at least back to z=1. We find that the clumpiness of gas density and pressure increases with the distance from the cluster center and with the dynamical activity. The inclusion of AGN feedback in our simulations generates values for the gas clumping ($\sqrt C_ρ\sim 1.2$ at $R_{200}$) in good agreement with recent observational estimates. The simulated $Y_{SZ}-M$ scaling relations are in good accordance with several observed samples, especially for massive clusters. As for the scatter of these relations, we obtain a clear dependence on the cluster dynamical state, whereas this distinction is not so evident when looking at the subsamples of CC and NCC clusters.

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On the nature of hydrostatic equilibrium in galaxy clusters

In this paper we investigate the level of hydrostatic equilibrium (HE) in the intra-cluster medium of simulated galaxy clusters, extracted from state-of-the-art cosmological hydrodynamical simulations performed with the Smoothed-Particle-Hydrodynamic code GADGET-3. These simulations include several physical processes, among which stellar and AGN feedback, and have been performed with an improved version of the code that allows for a better description of hydrodynamical instabilities and gas mixing processes. Evaluating the radial balance between the gravitational and hydrodynamical forces, via the gas accelerations generated, we effectively examine the level of HE in every object of the sample, its dependence on the radial distance from the center and on the classification of the cluster in terms of either cool-coreness or dynamical state. We find an average deviation of 10-20% out to the virial radius, with no evident distinction between cool-core and non-cool-core clusters. Instead, we observe a clear separation between regular and disturbed systems, with a more significant deviation from HE for the disturbed objects. The investigation of the bias between the hydrostatic estimate and the total gravitating mass indicates that, on average, this traces very well the deviation from HE, even though individual cases show a more complex picture. Typically, in the radial ranges where mass bias and deviation from HE are substantially different, the gas is characterized by a significant amount of random motions (>~30 per cent), relative to thermal ones. As a general result, the HE-deviation and mass bias, at given interesting distance from the cluster center, are not very sensitive to the temperature inhomogeneities in the gas.

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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.

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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.

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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 $χ^2$ 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: $M_h\simeq 6.3 (\pm 2.1) \times 10^{11} h^{-1} M_{\odot}$.

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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.

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The Halo Mass-Bias Redshift Evolution in the $Λ$CDM 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 $Λ$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.

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Environmental Effects of Dark Matter Haloes: The Clustering-Substructure relation of Group-size Haloes

We estimate the two-point correlation function of dark matter haloes, with masses >10^{13} h^{-1} Mo, that have or not significant substructure. The haloes are identified with a friends of friends algorithm in a large LCDM simulation at two redshift snapshots (z=0 and 1), while halo substructure is determined using an observationally driven method. We find in both epochs a clear and significant signal by which haloes with substructure are more clustered than those with no-substructure. This is true for all the considered halo mass ranges, although for the highest halo masses the signal is noisy and present only out to ~20 h^{-1} Mpc. There is also a smooth increase of the halo correlation length with increasing amplitude of the halo substructure. We also find that substructured haloes are typically located in high-density large-scale environments, while the opposite is true for non-substructured haloes. If the haloes found in high-density regions have a relatively earlier formation time, as suggested by recent works, then they do indeed have more time to cluster than haloes, of a similar mass, which form later in the low-density regions. In such a case one would have naively expected that the former (earlier formed) haloes would typically be dynamically more relaxed than the latter (later formed). However, the higher merging and interaction rate,expected in high-density regions, could disrupt their relatively relaxed dynamical state and thus be the cause for the higher fraction of haloes with substructure found in such regions.

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Morphological & Dynamical Properties of low redshift 2dFGRS Groups

We estimate the average group morphological and dynamical characteristics of the Percolation-Inferred Galaxy Group (2PIGG) catalogue within z~0.08, for which the group space density is roughly constant. We quantify the different biases that enter in the determination of these characteristics and we devise statistical correction procedures to recover their bias free values. We find that the only acceptable morphological model is that of prolate, or triaxial with pronounced prolatness, group shapes having a roughly Gaussian intrinsic axial ratio distribution with mean ~0.46 and dispersion of ~0.16. After correcting for various biases, the most important of which is a redshift dependant bias, the median values of the virial mass and virial radius of groups with 4 to 30 galaxy members, is: Mv ~6 x 10^12 h_{72}^{-1} M_solar, Rv~ 0.4 h^{-1}_{72} Mpc, which are significantly smaller than recent literature values that do not take into account the previously mentioned biases. The group mean crossing time is ~1.5 Gyr's, independent of the group galaxy membership. We also find that there is a correlation of the group size, velocity dispersion and virial mass with the number of group member galaxies, a manifestation of the hierarchy of cosmic structures.

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