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A. G. Sanchez

Publications and source records attributed to A. G. Sanchez.

3 recordsLinked to original sources

The SRG/eROSITA All-Sky Survey: Tracing the Large-Scale Structure with a clustering study of galaxy clusters

The spatial distribution of galaxy clusters provides a reliable tracer of the large-scale distribution of matter in the Universe. The clustering signal depends on intrinsic cluster properties and cosmological parameters. The ability of eROSITA onboard Spectrum-Roentgen-Gamma (SRG) to discover galaxy clusters allows probing the association of extended X-ray emission to dark matter haloes. We aim to measure the projected two-point correlation function to study the occupation of dark matter halos by clusters and groups detected by the first eROSITA all-sky survey (eRASS1). We create five volume-limited samples probing clusters with different redshift and X-ray luminosity. We interpret the correlation function with halo occupation distribution (HOD) and halo abundance matching (HAM) models. We simultaneously fit cosmological parameters and halo bias of a flux-limited sample of 6493 clusters with purity > 96%. Results. We obtain a detailed view of the halo occupation for eRASS1 clusters. The fainter population at low redshift (S0: LX = 4.63E43 erg/s, 0.1 < z < 0.2) is the least biased compared to dark matter, with b = 2.95 $\pm$ 0.21. The brightest clusters up to higher redshift (S4: LX = 1.77E44 erg/s , 0.1 < z < 0.6) exhibit a higher bias b = 4.34 $\pm$ 0.62. Satellite groups are rare, with a satellite fraction < 14.9% (8.1) for the S0 (S4) sample. We combine the HOD prediction with a HAM procedure to constrain the scaling relation between LX and mass in a new way and find a scatter of 0.36. We obtain cosmological constraints for the physical cold dark matter density 0.12+0.03-0.02 and an average halo bias b = 3.63+1.02-0.85. We model the clustering of galaxy clusters with a HOD approach for the first time, paving the way for future studies combining eROSITA with 4MOST, SDSS, Euclid, Rubin, and DESI to unravel the cluster distribution in the Universe.

astro-ph.CO

Dynamical segregation of galaxies in groups and clusters

We have performed a systematic analysis of the dynamics of different galaxy populations in galaxy groups from the 2dFGRS. For this purpose we have combined all the groups into a single system, where velocities v and radius r are expressed adimensionally. We have used several methods to compare the distributions of relative velocities of galaxies with respect to the group centre for samples selected according to their spectral type (as defined by Madgwick et al., 2002), bj band luminosity and B-R colour index. We have found strong segregation effects: spectral type I objects show a statistically narrower velocity distribution than that of galaxies with a substantial star formation activity (type II-IV). Similarly, the same behavior is observed for galaxies with colour index B-R>1 compared to galaxies with B-R<1. Bright (Mb<-19) and faint (Mb>-19) galaxies show the same segregation. It is not important once the sample is restricted to a given spectral type. These effects are particularly important in the central region (Rp<Rvirial/2) and do not have a strong dependence on the mass of the parent group. These trends show a strong correlation between the dynamics of galaxies in groups and star formation rate reflected both by spectral type and by colour index.

astro-ph

Determination of the Linear Mass Power Spectrum From the Mass Function of Galaxy Clusters

We develop a new method to determine the linear mass power spectrum using the mass function of galaxy clusters. We obtain the rms mass fluctuation sigma (M) using the expression for the mass function in the Press & Schechter (1974), Sheth, Mo & Tormen (2001) and Jenkins et al. (2001) formalisms. We apply different techniques to recover the adimensional power spectrum Delta ^{2}(k) from sigma (M) namely the k_{eff} approximation, the singular value decomposition and the linear regularization method. The application of these techniques to the tCDM and LCDM GIF simulations shows a high efficiency in recovering the theoretical power spectrum over a wide range of scales. We compare our results with those derived from the power spectrum of the spatial distribution of the same sample of clusters in the simulations obtained by application of the classical Feldman, Kaiser & Peacock (1994), FKP, method. We find that the mass function based method presented here can provide a very accurate estimate of the linear power spectrum, particularly for low values of k. This estimate is comparable, or even better behaved, than the FKP solution. The principal advantage of our method is that it allows the determination of the linear mass power spectrum using the joint information of objects of a wide range of masses without dealing with specific assumptions on the bias relative to the underlying mass distribution.

astro-ph