What is a Peculiar Galaxy ?

Following the recent surge of interest in peculiar galaxies at high redshifts we consider the definition, or lack thereof, of morphological peculiarities on a sample of local universe galaxies. Studying the morphology of local universe galaxies is also of interest in trying to understand galaxy dynamics and quantifying the relations between morphology and environment. We use classifications given by five experts for a sample of 827 APM galaxies and find that there is little agreement between them on what qualifies as a peculiar galaxy. We attempt several objective approaches : matching galaxy images to ``templates''; examinig the 180-degree Asymmetry against Light Concentration (following Abraham et al. 1995); and exploring angle-dependent asymmetry measures. While none of the quantities we use results in a clean distinction between normal and peculiar galaxies, there is a rough correlation between some parameters and image peculiarity. However, the mixing between the two classes is significant. We conclude that the class of peculiar galaxies is not totally distinct from the class of normal galaxies, and that what we are seeing is really a sequence. It is therefore more useful to consider distribution functions of morphological parameters. The current and possibly other, more accurate parametrisations require better data, which is becoming available through CCD imaging.Comment: 6 pages, latex, 12 figures. Postscript also available from ftp://ftp.ast.cam.ac.uk/pub/hn/pecs . Submitted to Mon. Not. R. Astr. Soc

AUTOMATED MORPHOLOGICAL CLASSIFICATION OF APM GALAXIES BY SUPERVISED ARTIFICIAL NEURAL NETWORKS

We train Artificial Neural Networks to classify galaxies based solely on the morphology of the galaxy images as they appear on blue survey plates. The images are reduced and morphological features such as bulge size and the number of arms are extracted, all in a fully automated manner. The galaxy sample was first classified by 6 independent experts. We use several definitions for the mean type of each galaxy, based on those classifications. We then train and test the network on these features. We find that the rms error of the network classifications, as compared with the mean types of the expert classifications, is 1.8 Revised Hubble Types. This is comparable to the overall rms dispersion between the experts. This result is robust and almost completely independent of the network architecture used.Comment: The full paper contains 25 pages, and includes 22 figures. It is available at ftp://ftp.ast.cam.ac.uk/pub/hn/apm2.ps . The table in the appendix is available on request from [email protected]. Mon. Not. R. Astr. Soc., in pres

Dynamics of Three Agent Games

We study the dynamics and resulting score distribution of three-agent games where after each competition a single agent wins and scores a point. A single competition is described by a triplet of numbers $p$, $t$ and $q$ denoting the probabilities that the team with the highest, middle or lowest accumulated score wins. We study the full family of solutions in the regime, where the number of agents and competitions is large, which can be regarded as a hydrodynamic limit. Depending on the parameter values $(p,q,t)$, we find six qualitatively different asymptotic score distributions and we also provide a qualitative understanding of these results. We checked our analytical results against numerical simulations of the microscopic model and find these to be in excellent agreement. The three agent game can be regarded as a social model where a player can be favored or disfavored for advancement, based on his/her accumulated score. It is also possible to decide the outcome of a three agent game through a mini tournament of two-a gent competitions among the participating players and it turns out that the resulting possible score distributions are a subset of those obtained for the general three agent-games. We discuss how one can add a steady and democratic decline rate to the model and present a simple geometric construction that allows one to write down the corresponding score evolution equations for $n$-agent games

Dynamics of Multi-Player Games

We analyze the dynamics of competitions with a large number of players. In our model, n players compete against each other and the winner is decided based on the standings: in each competition, the mth ranked player wins. We solve for the long time limit of the distribution of the number of wins for all n and m and find three different scenarios. When the best player wins, the standings are most competitive as there is one-tier with a clear differentiation between strong and weak players. When an intermediate player wins, the standings are two-tier with equally-strong players in the top tier and clearly-separated players in the lower tier. When the worst player wins, the standings are least competitive as there is one tier in which all of the players are equal. This behavior is understood via scaling analysis of the nonlinear evolution equations.Comment: 8 pages, 8 figure

Soccer: is scoring goals a predictable Poissonian process?

The non-scientific event of a soccer match is analysed on a strictly scientific level. The analysis is based on the recently introduced concept of a team fitness (Eur. Phys. J. B 67, 445, 2009) and requires the use of finite-size scaling. A uniquely defined function is derived which quantitatively predicts the expected average outcome of a soccer match in terms of the fitness of both teams. It is checked whether temporary fitness fluctuations of a team hamper the predictability of a soccer match. To a very good approximation scoring goals during a match can be characterized as independent Poissonian processes with pre-determined expectation values. Minor correlations give rise to an increase of the number of draws. The non-Poissonian overall goal distribution is just a consequence of the fitness distribution among different teams. The limits of predictability of soccer matches are quantified. Our model-free classification of the underlying ingredients determining the outcome of soccer matches can be generalized to different types of sports events

Neural computation as a tool for galaxy classification : methods and examples

We apply and compare various Artificial Neural Network (ANN) and other algorithms for automatic morphological classification of galaxies. The ANNs are presented here mathematically, as non-linear extensions of conventional statistical methods in Astronomy. The methods are illustrated using different subsets Artificial Neural Network (ANN) and other algorithms for automatic morphological classification of galaxies. The ANNs are presented here mathematically, as non-linear extensions of conventional statistical methods in Astronomy. The methods are illustrated using different subsets from the ESO-LV catalogue, for which both machine parameters and human classification are available. The main methods we explore are: (i) Principal Component Analysis (PCA) which tells how independent and informative the input parameters are. (ii) Encoder Neural Network which allows us to find both linear (PCA-like) and non-linear combinations of the input, illustrating an example of unsupervised ANN. (iii) Supervised ANN (using the Backpropagation or Quasi-Newton algorithms) based on a training set for which the human classification is known. Here the output for previously unclassified galaxies can be interpreted as either a continuous (analog) output (e.g. $T$-type) or a Bayesian {\it a posteriori} probability for each class. Although the ESO-LV parameters are sub-optimal, the success of the ANN in reproducing the human classification is 2 $T$-type units, similar to the degree of agreement between two human experts who classify the same galaxy images on plate material. We also examine the aspects of ANN configurations, reproducibility, scaling of input parameters and redshift information.Comment: uuencoded compressed postscript. The preprint is also available at http://www.ast.cam.ac.uk/preprint/PrePrint.htm

The Morphologically Divided Redshift Distribution of Faint Galaxies

We have constructed a morphologically divided redshift distribution of faint field galaxies using a statistically unbiased sample of 196 galaxies brighter than I = 21.5 for which detailed morphological information (from the Hubble Space Telescope) as well as ground-based spectroscopic redshifts are available. Galaxies are classified into 3 rough morphological types according to their visual appearance (E/S0s, Spirals, Sdm/dE/Irr/Pec's), and redshift distributions are constructed for each type. The most striking feature is the abundance of low to moderate redshift Sdm/dE/Irr/Pec's at I < 19.5. This confirms that the faint end slope of the luminosity function (LF) is steep (alpha < -1.4) for these objects. We also find that Sdm/dE/Irr/Pec's are fairly abundant at moderate redshifts, and this can be explained by strong luminosity evolution. However, the normalization factor (or the number density) of the LF of Sdm/dE/Irr/Pec's is not much higher than that of the local LF of Sdm/dE/Irr/Pec's. Furthermore, as we go to fainter magnitudes, the abundance of moderate to high redshift Irr/Pec's increases considerably. This cannot be explained by strong luminosity evolution of the dwarf galaxy populations alone: these Irr/Pec's are probably the progenitors of present day ellipticals and spiral galaxies which are undergoing rapid star formation or merging with their neighbors. On the other hand, the redshift distributions of E/S0s and spirals are fairly consistent those expected from passive luminosity evolution, and are only in slight disagreement with the non-evolving model.Comment: 11 pages, 4 figures (published in ApJ

Aldehyde Dehydrogenases in Arabidopsis thaliana: Biochemical Requirements, Metabolic Pathways, and Functional Analysis

Aldehyde dehydrogenases (ALDHs) are a family of enzymes which catalyze the oxidation of reactive aldehydes to their corresponding carboxylic acids. Here we summarize molecular genetic and biochemical analyses of selected Arabidopsis ALDH genes. Aldehyde molecules are very reactive and are involved in many metabolic processes but when they accumulate in excess they become toxic. Thus activity of aldehyde dehydrogenases is important in regulating the homeostasis of aldehydes. Overexpression of some ALDH genes demonstrated an improved abiotic stress tolerance. Despite the fact that several reports are available describing a role for specific ALDHs, their precise physiological roles are often still unclear. Therefore a number of genetic and biochemical tools have been generated to address the function with an emphasis on stress-related ALDHs. ALDHs exert their functions in different cellular compartments and often in a developmental and tissue specific manner. To investigate substrate specificity, catalytic efficiencies have been determined using a range of substrates varying in carbon chain length and degree of carbon oxidation. Mutational approaches identified amino acid residues critical for coenzyme usage and enzyme activities

Ballistic Annihilation

Ballistic annihilation with continuous initial velocity distributions is investigated in the framework of Boltzmann equation. The particle density and the rms velocity decay as $c=t^{-\alpha}$ and $=t^{-\beta}$, with the exponents depending on the initial velocity distribution and the spatial dimension. For instance, in one dimension for the uniform initial velocity distribution we find $\beta=0.230472...$. We also solve the Boltzmann equation for Maxwell particles and very hard particles in arbitrary spatial dimension. These solvable cases provide bounds for the decay exponents of the hard sphere gas.Comment: 4 RevTeX pages and 1 Eps figure; submitted to Phys. Rev. Let

Kinetics of Clustering in Traffic Flows

We study a simple aggregation model that mimics the clustering of traffic on a one-lane roadway. In this model, each ``car'' moves ballistically at its initial velocity until it overtakes the preceding car or cluster. After this encounter, the incident car assumes the velocity of the cluster which it has just joined. The properties of the initial distribution of velocities in the small velocity limit control the long-time properties of the aggregation process. For an initial velocity distribution with a power-law tail at small velocities, \pvim as $v \to 0$, a simple scaling argument shows that the average cluster size grows as n \sim t^{\va} and that the average velocity decays as v \sim t^{-\vb} as $t\to \infty$. We derive an analytical solution for the survival probability of a single car and an asymptotically exact expression for the joint mass-velocity distribution function. We also consider the properties of spatially heterogeneous traffic and the kinetics of traffic clustering in the presence of an input of cars.Comment: 18 pages, Plain TeX, 2 postscript figure