PAIRWISE VELOCITIES OF GALAXIES IN THE CFA AND SSRS2 REDSHIFT SURVEYS

(compressed version) We combine the CfA Redshift Survey (CfA2) and the Southern Sky Redshift Survey (SSRS2) to estimate the pairwise velocity dispersion of galaxies \sig12 on a scale of \sim 1 \hmpc. Both surveys are complete to an apparent magnitude limit $B(0)=15.5$. Our sample includes 12,812 galaxies distributed in a volume 1.8 \times 10^6 \hmpc3. We conclude: 1) The pairwise velocity dispersion of galaxies in the combined CfA2+SSRS2 redshift survey is \sig12=540 \kms \pm 180 \kms. Both the estimate and the variance of \sig12 significantly exceed the canonical values \sig12=340 \pm40 measured by Davis \& Peebles (1983) using CfA1. 2) We derive the uncertainty in \sig12 from the variation among subsamples with volumes on the order of $7 \times 10^5$ \hmpc3. This variation is nearly an order of magnitude larger than the formal error, 36 \kms, derived using least-squares fits to the CfA2+SSRS2 correlation function. This variation among samples is consistent with the conclusions of Mo \etal (1993) for a number of smaller surveys and with the analysis of CfA1 by Zurek \etal (1994). 3) When we remove Abell clusters with $R\ge1$ from our sample, the pairwise velocity dispersion of the remaining galaxies drops to 295 \pm 99 \kms. Thus the dominant source of variance in \sig12 is the shot noise contributed by dense virialized systems. 4) The distribution of pairwise velocities is consistent with an isotropic exponential with velocity dispersion independent of scale.Comment: 61 pages uuencoded, compressed postscript in 5 pieces. Also available in one piece at http://www.dao.nrc.ca/DAO/SCIENCE/science.htm

Properties of Very Luminous Galaxies

Recent analysis of the SSRS2 data based on cell-counts and two-point correlation function has shown that very luminous galaxies are much more strongly clustered than fainter galaxies. In fact, the amplitude of the correlation function of very luminous galaxies ($L > L^*$) asymptotically approaches that of $R \ge 0$ clusters. In this paper we investigate the properties of the most luminous galaxies, with blue absolute magnitude $M_B \le -21$. We find that: 1) the population mix is comparable to that in other ranges of absolute magnitudes; 2) only a small fraction are located in bona fide clusters; 3) the bright galaxy-cluster cross-correlation function is significantly higher on large scales than that measured for fainter galaxies; 4) the correlation length of galaxies brighter than \MB $\sim -20.0$, expressed as a function of the mean interparticle distance, appears to follow the universal dimensionless correlation function found for clusters and radio galaxies; 5) a large fraction of the bright galaxies are in interacting pairs, others show evidence for tidal distortions, while some appear to be surrounded by faint satellite galaxies. We conclude that very luminous optical galaxies differ from the normal population of galaxies both in the clustering and other respects. We speculate that this population is highly biased tracers of mass, being associated to dark halos with masses more comparable to clusters than typical loose groups.Comment: 29 pages (6 figures) + 2 tables; paper with all figures and images available at http://boas5.bo.astro.it/~cappi/papers.html; The Astronomical Journal, in pres

2D pattern evolution constrained by complex network dynamics

Complex networks have established themselves along the last years as being particularly suitable and flexible for representing and modeling several complex natural and human-made systems. At the same time in which the structural intricacies of such networks are being revealed and understood, efforts have also been directed at investigating how such connectivity properties define and constrain the dynamics of systems unfolding on such structures. However, lesser attention has been focused on hybrid systems, \textit{i.e.} involving more than one type of network and/or dynamics. Because several real systems present such an organization (\textit{e.g.} the dynamics of a disease coexisting with the dynamics of the immune system), it becomes important to address such hybrid systems. The current paper investigates a specific system involving a diffusive (linear and non-linear) dynamics taking place in a regular network while interacting with a complex network of defensive agents following Erd\"os-R\'enyi and Barab\'asi-Albert graph models, whose nodes can be displaced spatially. More specifically, the complex network is expected to control, and if possible to extinguish, the diffusion of some given unwanted process (\textit{e.g.} fire, oil spilling, pest dissemination, and virus or bacteria reproduction during an infection). Two types of pattern evolution are considered: Fick and Gray-Scott. The nodes of the defensive network then interact with the diffusing patterns and communicate between themselves in order to control the spreading. The main findings include the identification of higher efficiency for the Barab\'asi-Albert control networks.Comment: 18 pages, 32 figures. A working manuscript, comments are welcome

The Power Spectrum of Galaxies in the Nearby Universe

We compute the power spectrum of galaxy density fluctuations in a recently completed redshift survey of optically-selected galaxies in the southern hemisphere (SSRS2). The amplitude and shape of the SSRS2 power spectrum are consistent with results of the Center for Astrophysics redshift survey of the northern hemisphere (CfA2), including the abrupt change of slope on a scale of 30-50Mpc/h; these results are reproducible for independent volumes of space and variations are consistent with the errors estimated from mock surveys. Taken together, the SSRS2 and CfA2 form a complete sample of 14,383 galaxies which covers one-third of the sky. The power spectrum of this larger sample continues to rise on scales up to ~ 200Mpc/h, with weak evidence for flattening on the largest scales. The SSRS2+CfA2 power spectrum and the power spectrum constraints implied by COBE are well-matched by an Omega*h ~ 0.2, Omega+lambda_0=1 CDM model with minimal biasing of optically-selected galaxies.Comment: Accepted for publication in The Astrophysical Journal Letters, Sept. 23, 1994. 10 pages uuencoded compressed postscript, including two figures. JHU-9410200

Labels for non-individuals

Quasi-set theory is a first order theory without identity, which allows us to cope with non-individuals in a sense. A weaker equivalence relation called ``indistinguishability'' is an extension of identity in the sense that if $x$ is identical to $y$ then $x$ and $y$ are indistinguishable, although the reciprocal is not always valid. The interesting point is that quasi-set theory provides us a useful mathematical background for dealing with collections of indistinguishable elementary quantum particles. In the present paper, however, we show that even in quasi-set theory it is possible to label objects that are considered as non-individuals. We intend to prove that individuality has nothing to do with any labelling process at all, as suggested by some authors. We discuss the physical interpretation of our results.Comment: 11 pages, no figure

New Techniques for Relating Dynamically Close Galaxy Pairs to Merger and Accretion Rates : Application to the SSRS2 Redshift Survey

We introduce two new pair statistics, which relate close galaxy pairs to the merger and accretion rates. We demonstrate the importance of correcting these (and other) pair statistics for selection effects related to sample depth and completeness. In particular, we highlight the severe bias that can result from the use of a flux-limited survey. The first statistic, denoted N_c, gives the number of companions per galaxy, within a specified range in absolute magnitude. N_c is directly related to the galaxy merger rate. The second statistic, called L_c, gives the total luminosity in companions, per galaxy. This quantity can be used to investigate the mass accretion rate. Both N_c and L_c are related to the galaxy correlation function and luminosity function in a straightforward manner. We outline techniques which account for various selection effects, and demonstrate the success of this approach using Monte Carlo simulations. If one assumes that clustering is independent of luminosity (which is appropriate for reasonable ranges in luminosity), then these statistics may be applied to flux-limited surveys. These techniques are applied to a sample of 5426 galaxies in the SSRS2 redshift survey. Using close dynamical pairs, we find N_c(-21<M_B<-18) = 0.0226+/-0.0052 and L_c(-21<M_B<-18) = 0.0216+/-0.0055 10^{10} h^2 L_sun at z=0.015. These are the first secure estimates of low-z close pair statistics. If N_c remains fixed with redshift, simple assumptions imply that ~ 6.6% of present day galaxies with -21<M_B<-18 have undergone mergers since z=1. When applied to redshift surveys of more distant galaxies, these techniques will yield the first robust estimates of evolution in the galaxy merger and accretion rates. [Abridged]Comment: 26 pages (including 10 postscript figures) plus 3 gif figures. Accepted for publication in ApJ. Paper (including full resolution images) also available at http://www.astro.utoronto.ca/~patton/ssrs2, along with associated pair classification experiment (clickable version of Figure 5

How Active Inference Could Help Revolutionise Robotics

Recent advances in neuroscience have characterised brain function using mathematical formalisms and first principles that may be usefully applied elsewhere. In this paper, we explain how active inference—a well-known description of sentient behaviour from neuroscience—can be exploited in robotics. In short, active inference leverages the processes thought to underwrite human behaviour to build effective autonomous systems. These systems show state-of-the-art performance in several robotics settings; we highlight these and explain how this framework may be used to advance robotics

A cana-de-açúcar na Transamazônica, PA: resultados de 8 anos de pesquisa, 1974/82.

bitstream/item/57751/1/Altamira-Doc5.pd

Beyond the average: Detecting global singular nodes from local features in complex networks

Deviations from the average can provide valuable insights about the organization of natural systems. The present article extends this important principle to the systematic identification and analysis of singular motifs in complex networks. Six measurements quantifying different and complementary features of the connectivity around each node of a network were calculated, and multivariate statistical methods applied to identify singular nodes. The potential of the presented concepts and methodology was illustrated with respect to different types of complex real-world networks, namely the US air transportation network, the protein-protein interactions of the yeast Saccharomyces cerevisiae and the Roget thesaurus networks. The obtained singular motifs possessed unique functional roles in the networks. Three classic theoretical network models were also investigated, with the Barab\'asi-Albert model resulting in singular motifs corresponding to hubs, confirming the potential of the approach. Interestingly, the number of different types of singular node motifs as well as the number of their instances were found to be considerably higher in the real-world networks than in any of the benchmark networks