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

Numerical study of rainbows and glories in water-drop clouds

In this paper we study scattering phase functions in water-drop clouds for various distributions of droplet size and various conditions of glory, rainbow and corona formation, and discuss the hypothesis proposed by A. N. Nevzorov that a considerable amount of water in cold clouds can exist in a specific phase state with the refractive index ≈ 1.8 (so called A-water). Polarization and angular distributions are studied by the Monte Carlo method for radiation reflected by cloud layers with drops of water or hypothetical A-water taking into account multiple scattering. Computational results make it possible to develop procedures for analysis of microphysical structure of clouds and confirmation or disproof of the existence of A-water

Cytoplasmic localization of Hug1p, a negative regulator of the MEC1 pathway, coincides with the compartmentalization of Rnr2p-Rnr4p

The evolutionarily conserved MEC1 checkpoint pathway mediates cell cycle arrest and induction of genes including the RNR (Ribonucleotide reductase) genes and HUG1 (Hydroxyurea, ultraviolet, and gamma radiation) in response to DNA damage and replication arrest. Rnr complex activity is in part controlled by cytoplasmic localization of the Rnr2p-Rnr4p subunits and inactivation of negative regulators Sml1p and Dif1p upon DNA damage and hydroxyurea (HU) treatment. We previously showed that a deletion of HUG1 rescues lethality of mec1 Delta and suppresses dun1 Delta strains. In this study, multiple approaches demonstrate the regulatory response of Hug1p to DNA damage and HU treatment and support its role as a negative effector of the MEC1 pathway. Consistent with our hypothesis, wild-type cells are sensitive to DNA damage and HU when HUG1 is overexpressed. A Hug1 polyclonal antiserum reveals that HUG1 encodes a protein in budding yeast and its MEC1-dependent expression is delayed compared to the rapid induction of Rnr3p in response to HU treatment. Cell biology and subcellular fractionation experiments show localization of Hug1p-GFP to the cytoplasm upon HU treatment. The cytoplasmic localization of Hug1p-GFP is dependent on MEC1 pathway genes and coincides with the cytoplasmic localization of Rnr2p-Rnr4p. Taken together, the genetic interactions, gene expression, and localization studies support a novel role for Hug1p as a negative regulator of the MEC1 checkpoint response through its compartmentalization with Rnr2p-Rnr4p. Published by Elsevier Inc

Biased-estimations of the Variance and Skewness

Nonlinear combinations of direct observables are often used to estimate quantities of theoretical interest. Without sufficient caution, this could lead to biased estimations. An example of great interest is the skewness $S_3$ of the galaxy distribution, defined as the ratio of the third moment \xibar_3 and the variance squared \xibar_2^2. Suppose one is given unbiased estimators for \xibar_3 and \xibar_2^2 respectively, taking a ratio of the two does not necessarily result in an unbiased estimator of $S_3$. Exactly such an estimation-bias affects most existing measurements of $S_3$. Furthermore, common estimators for \xibar_3 and \xibar_2 suffer also from this kind of estimation-bias themselves: for \xibar_2, it is equivalent to what is commonly known as the integral constraint. We present a unifying treatment allowing all these estimation-biases to be calculated analytically. They are in general negative, and decrease in significance as the survey volume increases, for a given smoothing scale. We present a re-analysis of some existing measurements of the variance and skewness and show that most of the well-known systematic discrepancies between surveys with similar selection criteria, but different sizes, can be attributed to the volume-dependent estimation-biases. This affects the inference of the galaxy-bias(es) from these surveys. Our methodology can be adapted to measurements of analogous quantities in quasar spectra and weak-lensing maps. We suggest methods to reduce the above estimation-biases, and point out other examples in LSS studies which might suffer from the same type of a nonlinear-estimation-bias.Comment: 28 pages of text, 9 ps figures, submitted to Ap

Luminosity- and morphology-dependent clustering of galaxies

How does the clustering of galaxies depend on their inner properties like morphological type and luminosity? We address this question in the mathematical framework of marked point processes and clarify the notion of luminosity and morphological segregation. A number of test quantities such as conditional mark-weighted two-point correlation functions are introduced. These descriptors allow for a scale-dependent analysis of luminosity and morphology segregation. Moreover, they break the degeneracy between an inhomogeneous fractal point set and actual present luminosity segregation. Using the Southern Sky Redshift Survey~2 (da Costa et al. 1998, SSRS2) we find both luminosity and morphological segregation at a high level of significance, confirming claims by previous works using these data (Benoist et al. 1996, Willmer et al. 1998). Specifically, the average luminosity and the fluctuations in the luminosity of pairs of galaxies are enhanced out to separations of 15Mpc/h. On scales smaller than 3Mpc/h the luminosities on galaxy pairs show a tight correlation. A comparison with the random-field model indicates that galaxy luminosities depend on the spatial distribution and galaxy-galaxy interactions. Early-type galaxies are also more strongly correlated, indicating morphological segregation. The galaxies in the PSCz catalog (Saunders et al. 2000) do not show significant luminosity segregation. This again illustrates that mainly early-type galaxies contribute to luminosity segregation. However, based on several independent investigations we show that the observed luminosity segregation can not be explained by the morphology-density relation alone.Comment: aastex, emulateapj5, 20 pages, 13 figures, several clarifying comments added, ApJ accepte

The Geography of Scientific Productivity: Scaling in U.S. Computer Science

Here we extract the geographical addresses of authors in the Citeseer database of computer science papers. We show that the productivity of research centres in the United States follows a power-law regime, apart from the most productive centres for which we do not have enough data to reach definite conclusions. To investigate the spatial distribution of computer science research centres in the United States, we compute the two-point correlation function of the spatial point process and show that the observed power-laws do not disappear even when we change the physical representation from geographical space to cartogram space. Our work suggests that the effect of physical location poses a challenge to ongoing efforts to develop realistic models of scientific productivity. We propose that the introduction of a fine scale geography may lead to more sophisticated indicators of scientific output.Comment: 6 pages, 3 figures; minor change

Perturbative Analysis of Adaptive Smoothing Methods in Quantifying Large-Scale Structure

Smoothing operation to make continuous density field from observed point-like distribution of galaxies is crucially important for topological or morphological analysis of the large-scale structure, such as, the genus statistics or the area statistics (equivalently the level crossing statistics). It has been pointed out that the adaptive smoothing filters are more efficient tools to resolve cosmic structures than the traditional spatially fixed filters. We study weakly nonlinear effects caused by two representative adaptive methods often used in smoothed hydrodynamical particle (SPH) simulations. Using framework of second-order perturbation theory, we calculate the generalized skewness parameters for the adaptive methods in the case of initially power-law fluctuations. Then we apply the multidimensional Edgeworth expansion method and investigate weakly nonlinear evolution of the genus statistics and the area statistics. Isodensity contour surfaces are often parameterized by the volume fraction of the regions above a given density threshold. We also discuss this parameterization method in perturbative manner.Comment: 42 pages including 9 figure, ApJ 537 in pres

Can we detect Hot or Cold spots in the CMB with Minkowski Functionals?

In this paper, we investigate the utility of Minkowski Functionals as a probe of cold/hot disk-like structures in the CMB. In order to construct an accurate estimator, we resolve a long-standing issue with the use of Minkowski Functionals as probes of the CMB sky -- namely that of systematic differences ("residuals") when numerical and analytical MF are compared. We show that such residuals are in fact by-products of binning, and not caused by pixelation or masking as originally thought. We then derive a map-independent estimator that encodes the effects of binning, applicable to beyond our present work. Using this residual-free estimator, we show that small disk-like effects (as claimed by Vielva et al.) can be detected only when a large sample of such maps are averaged over. In other words, our estimator is noise-dominated for small disk sizes at WMAP resolution. To confirm our suspicion, we apply our estimator to the WMAP7 data to obtain a null result.Comment: 15 pages, 13 figure

Numerical study of rainbows and glories in water-drop clouds

In this paper we study scattering phase functions in water-drop clouds for various distributions of droplet size and various conditions of glory, rainbow and corona formation, and discuss the hypothesis proposed by A. N. Nevzorov that a considerable amount of water in cold clouds can exist in a specific phase state with the refractive index ≈ 1.8 (so called A-water). Polarization and angular distributions are studied by the Monte Carlo method for radiation reflected by cloud layers with drops of water or hypothetical A-water taking into account multiple scattering. Computational results make it possible to develop procedures for analysis of microphysical structure of clouds and confirmation or disproof of the existence of A-water

Analysing Large Scale Structure: I. Weighted Scaling Indices and Constrained Randomisation

The method of constrained randomisation is applied to three-dimensional simulated galaxy distributions. With this technique we generate for a given data set surrogate data sets which have the same linear properties as the original data whereas higher order or nonlinear correlations are not preserved. The analysis of the original and surrogate data sets with measures, which are sensitive to nonlinearities, yields information about the existence of nonlinear correlations in the data. We demonstrate how to generate surrogate data sets from a given point distribution, which have the same linear properties (power spectrum) as well as the same density amplitude distribution. We propose weighted scaling indices as a nonlinear statistical measure to quantify local morphological elements in large scale structure. Using surrogates is is shown that the data sets with the same 2-point correlation functions have slightly different void probability functions and especially a different set of weighted scaling indices. Thus a refined analysis of the large scale structure becomes possible by calculating local scaling properties whereby the method of constrained randomisation yields a vital tool for testing the performance of statistical measures in terms of sensitivity to different topological features and discriminative power.Comment: 10 pages, 5 figures, accepted for publication in MNRA