M. L. Lares

Clues on void evolution I: Large scale galaxy distributions around voids

We perform a statistical study focused on void environments. We examine galaxy density profiles around voids in the SDSS, finding a correlation betwe en void‐centric distance to the shell of maximum density and void radius when a maximum in overdensity exists. We analyze voids with and without a surrounding over-dense shell in the SDSS. We find that small voids are more frequently surrounded by over-dense shells whereas the radial galaxy density profile of large voids tends to rise smoothly towards the mean galaxy density. We analyse the fraction of voids surrounded by overdense shells finding a continuous trend with void radius. The differences between voids with and without an overdense shell around them can be understood in terms of whether the voids are, on average, in the process of collapsing or continuing their expansion, respectively, in agreement with previous theoretical expectations. We use numerical simulations coupled to semi-analytic models of galaxy formation in order to test and interpret our results. The very good agreement between the mock catalog results and

Future virialized structures: an analysis of superstructures in the SDSS-DR7

We construct catalogues of present superstructures that, according to a A cold dark matter (∧CDM) scenario, will evolve into isolated, virialized structures in the future. We use a smoothed luminosity density map derived from galaxies in SDSS-DR7, Abazajian et al., data and separate high-luminosity density peaks. The luminosity density map is obtained from a volume-limited sample of galaxies in the spectroscopic galaxy catalogue, within the SDSS-DR7 footprint area and in the redshift range 0.04 < z < 0.12. Other two samples are constructed for calibration and testing purposes, up to z = 0.10 and 0.15. The luminosity of each galaxy is spread using an Epanechnikov kernel of 8 Mpc h ―1 radius, and the map is constructed on a 1 Mpc h ―1 cubic cell grid. Future virialized structures (FVSs) are identified as regions with overdensity above a given threshold, calibrated using a ACDM numerical simulation and the criteria presented by Dunner et al. We assume a constant mass-to-luminosity ratio and impose the further condition of a minimum luminosity of 10 12 L ⊙ . According to our calibrations with a numerical simulation, these criteria lead to a negligible contamination by less overdense (non-FVS) superstructures. We present a catalogue of superstructures in the SDSS-DR7 area within redshift 0.04 < z < 0.12 and test the reliability of our method by studying different subsamples as well as a mock catalogue. We compute the luminosity and volume distributions of the superstructures, finding that about 10 per cent of the luminosity (mass) will end up in future virialized structures. The fraction of groups and X-ray clusters in these superstructures is higher for groups/clusters of higher mass, suggesting that future cluster mergers will involve the most massive systems. We also analyse known structures in the present Universe and compare with our catalogue of FVSs.

Effects of superstructure environment on galaxy groups

We analyse properties of galaxy groups and their dependence on the large-scale environment as defined by superstructures. We find that group‐galaxy cross‐correlations depend only on group properties regardless the groups reside in superstructures. This indicates that the total galaxy density profile around groups is independent of the global environment. At a given global luminosity, a proxy to group total mass, groups have a larger stellar mass content by a factor 1.3, a relative excess independent of the group luminosity. Groups in superstructures have 40 per cent higher velocity dispersions and systematically larger minimal enclosing radii. We also find that the stellar population of galaxies in groups in superstructures is systematically older as infered from the galaxy spectra Dn4000 parameter. Although the galaxy number density profile of groups is independent of environment, the star‐formation rate and stellar mass profile of the groups residing in superstructures differs from groups elsewhere. For groups residing in superstructures, the combination of a larger stellar mass content and star‐formation rate produces a larger time‐scale for star formation regardless the distance to the group center. Our results provide evidence that groups in superstructures formed earlier than elsewhere, as expected in the assembly bias scenario.

The sparkling Universe: the coherent motions of cosmic voids

Wecomputethebulkmotionsofcosmicvoids,usingacolddarkmatternumericalsimulation considering the mean velocities of the dark matter inside the void itself and that of the haloes in the surrounding shell. We find coincident values of these two measures in the range ∼300-400kms −1 , not far from the expected mean peculiar velocities of groups and galaxy clusters. When analysing the distribution of the pairwise relative velocities of voids, we find a remarkable bimodal behaviour consistent with an excess of both systematically approaching and receding voids. We determine that the origin of this bimodality resides in the voidlarge-scaleenvironment,sinceoncevoidsareclassifiedintovoid-in-void(R-type)orvoid- in-cloud (S-type), R-types are found mutually receding away, while S-types approach each other. The magnitude of these systematic relative velocities account for more than 100kms −1 , reaching large coherence lengths of up to 200 h −1 Mpc . We have used samples of voids from the Sloan Digital Sky Survey Data Release 7 and the peculiar velocity field inferred from linear theory, finding fully consistent results with the simulation predictions. Thus, their relative motion suggests a scenario of a sparkling universe, with approaching and receding voids according to their local environment.

The sparkling Universe: a scenario for cosmic void motions

Cosmic voids are prominent features of the Universe at large scales, encoding relevant information of the growth and evolution of structure through their dynamics. Here, we perform a statistical study of the global motion of cosmic voids using both a numerical simulation and observational data. We analyse their relation to large‐scale mass flows and the physical effects that drive those motions. We analyse the bulk motions of voids, defined by the mean velocity of haloes in the surrounding shells in the numerical simulation, and by galaxies in the Sloan Digital Sky Survey Data Release 7. We find void mean bulk velocities close to 400 km s 1 , comparable to those of haloes ( 500 600 km s 1 ), depending on void size and the large‐scale environment. Statistically, small voids move faster than large ones, and voids in relatively higher density environments have higher bulk velocities than those placed in large underdense regions. Also, we analyze the mean mass density around voids finding, as expected, large‐scale overdensities (underdensities) along (opposite to) the void motion direction, suggesting that void motions respond to a pull‐push mechanism. This contrasts with massive cluster motions who are mainly governed by the pull of the large-scale overdense regions. Our analysis of void pairwise velocities shows how their relative motions are generated by large‐scale density fluctuations. In agreement with linear theory, voids embedded in low (high) density regions mutually recede (attract) each other, providing the general mechanism to understand the bimodal behavior of void motions. In order to compare the theoretical results and the observations we have inferred void motions in the Sloan Digital Sky Survey using linear theory, finding that the estimated observational void motions are in statistical agreement with the results of the simulation. Regarding large‐scale flows, our results suggest a scenario of galaxies and galaxy systems flowing away from void centers with the additional, and more relevant, contribution of the void bulk motion to the total velocity.

Brightest group galaxies and the large-scale environment

We study the dependence of the properties of group galaxies on the surrounding large‐scale environment, using SDSS-DR7 data. Galaxies are ranked according to their luminosity within each group and classified morphologically by the S´ ersic index. We have considered samples of the host groups in superstructures of galaxies, and elsewhere. We find a significant dependence of the properties of late‐type brightest group galaxies on the large‐scale environment: they show statistically significant higher luminosities and stellar masses, redder u-r colours, lower star formation activity and longer star‐formation time‐scale when embedded in superstructures. By contrast, the properties of the early‐type brightest group galaxies are remarkably similar regardless of the group global environment. The other group member galaxies exhibit only the local influence of the group they inhabit. Our analysis comprises tests against the dependence on the host group luminosity and we argue that group brightest member properties are not only determined by the host halo, but also by the large‐scale structure which can influence the accretion process onto their late‐type brightest galaxies.

The influence of superstructures on bright galaxy environments: clustering properties

We analyse the dependence of clustering properties of galaxies as a function of their large-scale environment. In order to characterize the environment on large scales, we use the catalogue of future virialized superstructures (FVS) by Luparello et al. and separate samples of luminous galaxies according to whether or not they belong to FVS. In order to avoid biases in the selection of galaxies, we have constructed different subsamples so that the distributions of luminosities and masses are comparable outside and within FVS. As expected, at large scales, there is a strong difference between the clustering of galaxies inside and outside FVS. However, this behaviour changes at scales r ≤ 1 h−1 Mpc, where the correlations have similar amplitudes. The amplitude of the two-halo term of the correlation function for objects inside FVS does not depend on their mass, but rather on that of the FVS. This is confirmed by comparing this amplitude with that expected from extended Press–Schechter fits. In order to compare these observational results with current models for structure formation, we have performed a similar analysis using a semi-analytic implementation in a Λcold dark matter (ΛCDM) cosmological model. We find that the cross-correlation functions from the mock catalogue depend on the large-scale structures in a similar way to the observations. From our analysis, we conclude that the clustering of galaxies within the typical virialized regions of groups mainly depends on the halo mass, irrespective of the large-scale environment.

Corral framework: Trustworthy and fully functional data intensive parallel astronomical pipelines

Abstract Data processing pipelines represent an important slice of the astronomical software library that include chains of processes that transform raw data into valuable information via data reduction and analysis. In this work we present Corral, a Python framework for astronomical pipeline generation. Corral features a Model-View-Controller design pattern on top of an SQL Relational Database capable of handling: custom data models; processing stages; and communication alerts, and also provides automatic quality and structural metrics based on unit testing. The Model-View-Controller provides concept separation between the user logic and the data models, delivering at the same time multi-processing and distributed computing capabilities. Corral represents an improvement over commonly found data processing pipelines in astronomysince the design pattern eases the programmer from dealing with processing flow and parallelization issues, allowing them to focus on the specific algorithms needed for the successive data transformations and at the same time provides a broad measure of quality over the created pipeline. Corral and working examples of pipelines that use it are available to the community at https://github.com/toros-astro .