A global descriptor of spatial pattern interaction in the galaxy distribution

We present the function J as a morphological descriptor for point patterns formed by the distribution of galaxies in the Universe. This function was recently introduced in the field of spatial statistics, and is based on the nearest neighbor distribution and the void probability function. The J descriptor allows to distinguish clustered (i.e. correlated) from ``regular'' (i.e. anti-correlated) point distributions. We outline the theoretical foundations of the method, perform tests with a Matern cluster process as an idealised model of galaxy clustering, and apply the descriptor to galaxies and loose groups in the Perseus-Pisces Survey. A comparison with mock-samples extracted from a mixed dark matter simulation shows that the J descriptor can be profitably used to constrain (in this case reject) viable models of cosmic structure formation.Comment: Significantly enhanced version, 14 pages, LaTeX using epsf, aaspp4, 7 eps-figures, accepted for publication in the Astrophysical Journa

The Dynamics of Poor Systems of Galaxies

We assemble and observe a sample of poor galaxy systems that is suitable for testing N-body simulations of hierarchical clustering (Navarro, Frenk, & White 1997; NFW) and other dynamical halo models (e.g., Hernquist 1990). We (1) determine the parameters of the density profile rho(r) and the velocity dispersion profile sigma(R), (2) separate emission-line galaxies from absorption-line galaxies, examining the model parameters and as a function of spectroscopic type, and (3) for the best-behaved subsample, constrain the velocity anisotropy parameter, beta, which determines the shapes of the galaxy orbits. The NFW universal profile and the Hernquist (1990) model both provide good descriptions of the spatial data. In most cases an isothermal sphere is ruled out. Systems with declining sigma(R) are well-matched by theoretical profiles in which the star-forming galaxies have predominantly radial orbits (beta > 0); many of these galaxies are probably falling in for the first time. There is significant evidence for spatial segregation of the spectroscopic classes regardless of sigma(R).Comment: 36 pages, 20 figures, and 5 tables. To appear in the Astrophysical Journa

A Constraint-based Querying System for Exploratory Pattern Discovery

In this article we present CONQUEST, a constraint-based querying system able to support the intrinsically exploratory (i.e., human-guided, interactive and iterative) nature of pattern discovery. Following the inductive database vision, our framework provides users with an expressive constraint-based query language, which allows the discovery process to be effectively driven toward potentially interesting patterns. Such constraints are also exploited to reduce the cost of pattern mining computation. CONQUEST is a comprehensive mining system that can access real-world relational databases from which to extract data. Through the interaction with a friendly graphical user interface (GUI), the user can define complex mining queries by means of few clicks. After a pre-processing step, mining queries are answered by an efficient and robust pattern mining engine which entails the state-of-the-art of data and search space reduction techniques. Resulting patterns are then presented to the user in a pattern browsing window, and possibly stored back in the underlying database as relations

The redshift-space two-point correlation functions of galaxies and groups in the Nearby Optical Galaxy sample

We use the two-point correlation function in redshift space, $\xi(s)$, to study the clustering of the galaxies and groups of the Nearby Optical Galaxy (NOG) sample, which is a nearly all-sky, complete, magnitude-limited sample of $\sim$7000 bright and nearby optical galaxies. The correlation function of galaxies is well described by a power law, $\xi(s)=(s/s_0)^{-\gamma}$, with slope $\gamma\sim1.5$ and $s_0\sim6.4 h^{-1}$Mpc (on scales $2.7 - 12 h^{-1}$Mpc), in agreement with previous results of several redshift surveys of optical galaxies. We confirm the existence of morphological segregation between early- and late-type galaxies and, in particular, we find a gradual decreasing of the strength of clustering from the S0 galaxies to the late-type spirals, on intermediate scales. Furthermore, luminous galaxies turn out to be more clustered than dim galaxies. The luminosity segregation, which is significant for both early- and late-type objects, starts to become appreciable only for galaxies brighter than $M_B\sim -19.5 + 5 \log h$ ($\sim 0.6 L^*$) and is independent on scale. The NOG group correlation functions are characterized by $s_0$-values ranging from $\sim 8 h^{-1}$ Mpc (for groups with at least three members) to $\sim10 h^{-1}$ Mpc (for groups with at least five members). The degree of group clustering depends on the physical properties of groups. Specifically, groups with greater velocity dispersions, sizes and masses tend to be more clustered than those with lower values of these quantities.Comment: Astrophysical Journal, in press, 72 pages, 16 eps figure

Clustering of loose groups and galaxies from the Perseus--Pisces Survey

We investigate the clustering properties of loose groups in the Perseus--Pisces redshift Survey (PPS). Previous analyses based on CfA and SSRS surveys led to apparently contradictory results. We investigate the source of such discrepancies, finding satisfactory explanations for them. Furthermore, we find a definite signal of group clustering, whose amplitude $A_G$ exceeds the amplitude $A_g$ of galaxy clustering ($A_G=14.5^{+3.8}_{-3.0}$, $A_g=7.42^{+0.20}_{-0.19}$ for the most significant case; distances are measured in \hMpc). Groups are identified with the adaptive Friends--Of--Friends (FOF) algorithms HG (Huchra \& Geller 1982) and NW (Nolthenius \& White 1987), systematically varying all search parameters. Correlation strenght is especially sensitive to the sky--link $D_L$ (increasing for stricter normalization $D_0$), and to the (depth \mlim of the) galaxy data. It is only moderately dependent on the galaxy luminosity function $\phi(L)$, while it is almost insensitive to the redshift--link $V_L$ (both to the normalization $V_0$ and to the scaling recipes HG or NW).Comment: 28 pages (LaTeX aasms4 style) + 5 Postscript figures ; ApJ submitted on May 4th, 1996; group catalogs available upon request ([email protected]

Loose Groups of Galaxies in the Las Campanas Redshift Survey

A ``friends-of-friends'' percolation algorithm has been used to extract a catalogue of dn/n = 80 density enhancements (groups) from the six slices of the Las Campanas Redshift Survey (LCRS). The full catalogue contains 1495 groups and includes 35% of the LCRS galaxy sample. A clean sample of 394 groups has been derived by culling groups from the full sample which either are too close to a slice edge, have a crossing time greater than a Hubble time, have a corrected velocity dispersion of zero, or contain a 55-arcsec ``orphan'' (a galaxy with a mock redshift which was excluded from the original LCRS redshift catalogue due to its proximity to another galaxy -- i.e., within 55 arcsec). Median properties derived from the clean sample include: line-of-sight velocity dispersion sigma_los = 164km/s, crossing time t_cr = 0.10/H_0, harmonic radius R_h = 0.58/h Mpc, pairwise separation R_p = 0.64/h Mpc, virial mass M_vir = (1.90x10^13)/h M_sun, total group R-band luminosity L_tot = (1.30x10^11)/h^2 L_sun, and R-band mass-to-light ratio M/L = 171h M_sun/L_sun; the median number of observed members in a group is 3.Comment: 32 pages of text, 27 figures, 7 tables. Figures 1, 4, 6, 7, and 8 are in gif format. Tables 1 and 3 are in plain ASCII format (in paper source) and are also available at http://www-sdss.fnal.gov:8000/~dtucker/LCLG . Accepted for publication in the September 2000 issue of ApJ

Nearby Optical Galaxies: Selection of the Sample and Identification of Groups

In this paper we describe the Nearby Optical Galaxy (NOG) sample, which is a complete, distance-limited ($cz\leq$6000 km/s) and magnitude-limited (B$\leq$14) sample of $\sim$7000 optical galaxies. The sample covers 2/3 (8.27 sr) of the sky ($|b|>20^{\circ}$) and appears to have a good completeness in redshift (98%). We select the sample on the basis of homogenized corrected total blue magnitudes in order to minimize systematic effects in galaxy sampling. We identify the groups in this sample by means of both the hierarchical and the percolation {\it friends of friends} methods. The resulting catalogs of loose groups appear to be similar and are among the largest catalogs of groups presently available. Most of the NOG galaxies ($\sim$60%) are found to be members of galaxy pairs ($\sim$580 pairs for a total of $\sim$15% of objects) or groups with at least three members ($\sim$500 groups for a total of $\sim$45% of objects). About 40% of galaxies are left ungrouped (field galaxies). We illustrate the main features of the NOG galaxy distribution. Compared to previous optical and IRAS galaxy samples, the NOG provides a denser sampling of the galaxy distribution in the nearby universe. Given its large sky coverage, the identification of groups, and its high-density sampling, the NOG is suited for the analysis of the galaxy density field of the nearby universe, especially on small scales.Comment: 47 pages including 6 figures. Accepted for publication in Ap

The Northern ROSAT All-Sky (NORAS) Galaxy Cluster Survey I: X-ray Properties of Clusters Detected as Extended X-ray Sources

In the construction of an X-ray selected sample of galaxy clusters for cosmological studies, we have assembled a sample of 495 X-ray sources found to show extended X-ray emission in the first processing of the ROSAT All-Sky Survey. The sample covers the celestial region with declination $\delta \ge 0\deg$ and galactic latitude $|b_{II}| \ge 20\deg$ and comprises sources with a count rate $\ge 0.06$ counts s$^{-1}$ and a source extent likelihood of 7. In an optical follow-up identification program we find 378 (76%) of these sources to be clusters of galaxies. ...Comment: 61 pages; ApJS in press; fixed bug in table file; also available at (better image quality) http://www.xray.mpe.mpg.de/theorie/NORAS

(So) Big Data and the transformation of the city

The exponential increase in the availability of large-scale mobility data has fueled the vision of smart cities that will transform our lives. The truth is that we have just scratched the surface of the research challenges that should be tackled in order to make this vision a reality. Consequently, there is an increasing interest among different research communities (ranging from civil engineering to computer science) and industrial stakeholders in building knowledge discovery pipelines over such data sources. At the same time, this widespread data availability also raises privacy issues that must be considered by both industrial and academic stakeholders. In this paper, we provide a wide perspective on the role that big data have in reshaping cities. The paper covers the main aspects of urban data analytics, focusing on privacy issues, algorithms, applications and services, and georeferenced data from social media. In discussing these aspects, we leverage, as concrete examples and case studies of urban data science tools, the results obtained in the “City of Citizens” thematic area of the Horizon 2020 SoBigData initiative, which includes a virtual research environment with mobility datasets and urban analytics methods developed by several institutions around Europe. We conclude the paper outlining the main research challenges that urban data science has yet to address in order to help make the smart city vision a reality

Three-Dimensional Identification and Reconstruction of Galaxy Systems within Deep Redshift Surveys

We have developed a new geometrical method for identifying and reconstructing a homogeneous and highly complete set of galaxy groups in the next generation of deep, flux-limited redshift surveys. Our method combines information from the three-dimensional Voronoi diagram and its dual, the Delaunay triangulation, to obtain group and cluster catalogs that are remarkably robust over wide ranges in redshift and degree of density enhancement. Using the mock DEEP2 catalogs, we demonstrate that the VDM algorithm can be used to identify a homogeneous set of groups in a magnitude-limited sample (I\sbr{AB}\le23.5) throughout the survey redshift window $0.7 < z < 1.2$. The actual group membership can be effectively reconstructed even in the distorted redshift space environment for systems with line of sight velocity dispersion $\sigma_{los}$ greater than $\approx 200$ \kms. By comparing the galaxy cluster catalog derived from the mock DEEP2 observations to the underlying distribution of clusters found in real space with much fainter galaxies included (which should more closely trace mass in the cluster), we can assess completeness in velocity dispersion directly. We conclude that the recovered DEEP2 group and cluster sample should be statistically complete for $\sigma_{los} \gtrsim 400$ \kms. Finally, we argue that the reconstructed bivariate distribution of systems as a function of redshift and velocity dispersion reproduces with high fidelity the underlying real space distribution and can thus be used robustly to constrain cosmological parametersComment: Latex, 21 pages, ApJ submitte