Detection of Dark Matter Concentrations in the Field of Cl 1604+4304 from Weak Lensing Analysis

We present a weak-lensing analysis of a region around the galaxy cluster Cl 1604+4304 (z=0.897) on the basis of the deep observations with the HST/WFPC2. We apply a variant of Schneider's aperture mass technique to the observed WFPC2 field and obtain the distribution of weak-lensing signal-to-noise (S/N) ratio within the field. The resulting S/N map reveals a clear pronounced peak located about 1.7 arcmin (850h_{50}^{-1} kpc at z=0.897) southwest of the second peak associated with the optical cluster center determined from the dynamical analysis of Postman et al. A non-linear finite-field inversion method has been used to reconstruct the projected mass distribution from the observed shear field. The reconstructed mass map shows a super-critical feature at the location of the S/N peak as well as in the cluster central region. Assuming the redshift distribution of field galaxies, we obtain the total mass in the observed field to be 1.0 h_{50}^{-1} 10^{15} M_sun for =1.0. The estimated mass within a circular aperture of radius 280h_{50}^{-1} kpc centered on the dark clump is 2.4h_{50}^{-1} 10^{14} M_sun. We have confirmed the existence of the ` dark ' mass concentration from another deep HST observation with a slightly different ~20 arcsec pointing.Comment: 7 pages, 3 figure

The Gains from Variety in the European Union

Over the last decade, European Union members have experienced a dramatic increase in imports. This increase was accompanied by a strong growth in the number of imported goods and trading partners, indicating positive welfare gains for consumers via an extended set of consumption possibilities, as pointed out in the "New Trade Theory". In this paper, we apply the methodology developed by Feenstra (1994) and Broda and Weinstein (2006) to estimate structurally the gains from imported variety for the 27 countries of the European Union using highly disaggregated trade data at the HTS-8 level from Eurostat for the period of 1999 to 2008. Our results show that, within the European Union, especially “newer” and smaller member states exhibit high gains from newly imported varieties. Furthermore, we find that the vast majority of the gains from variety for consumers stem from intra-European Union trade

Consumption inequality and intrahousehold allocations

The current literature on consumption inequality treats all adults within the household equally, making the implicit assumption that all consumption inequality is between, not within, households. However, increased marital sorting on earnings and the subsequent rise in the share of women's income in the household may have important implications for consumption inequality measured at the individual level. We use an extension of the collective framework of Chiappori to estimate a rule for assigning resources to individual household members. We then construct a measure of individual level inequality by looking at implied changes in intra-household allocations and explore the implications of our framework for the measurement of individual level, versus household level, consumption inequality. Our analysis, which is based on households comprising one or two adults, suggests that the conventional approach of ignoring intra-household allocations underestimates the level of cross-sectional consumption inequality by 30% and overstates the trend by two-thirds. Our findings also indicate that increases in marital sorting on wages and hours worked can simultaneously explain virtually all of the decline in within household inequality and a substantial fraction of the rise in between household inequality in the UK since the 1970s

A Neural Model of How the Cortical Subplate Coordinates the Laminar Development of Orientation and Ocular Dominance Maps

Air Force Office of Scientific Research (F49620-98-1-0108, F49620-0 1-1-0397); Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (IIS-97-20333); Office of Naval Research (N00014-01-1-0624

The noise of cluster mass reconstructions from a source redshift distribution

The parameter-free reconstruction of the surface-mass density of clusters of galaxies is one of the principal applications of weak gravitational lensing. From the observable ellipticities of images of background galaxies, the tidal gravitational field (shear) of the mass distribution is estimated, and the corresponding surface mass density is constructed. The noise of the resulting mass map is investigated here, generalizing previous work which included mainly the noise due to the intrinsic galaxy ellipticities. Whereas this dominates the noise budget if the lens is very weak, other sources of noise become important, or even dominant, for the medium-strong lensing regime close to the center of clusters. In particular, shot noise due to a Poisson distribution of galaxy images, and increased shot noise owing to the correlation of galaxies in angular position and redshift, can yield significantly larger levels of noise than that from the intrinsic ellipticities only. We estimate the contributions from these various effects for two widely used smoothing operations, showing that one of them effectively removes the Poisson and the correlation noises related to angular positions of galaxies. Noise sources due to the spread in redshift of galaxies are still present in the optimized estimator and are shown to be relevant in many cases. We show how (even approximate) redshift information can be profitably used to reduce the noise in the mass map. The dependence of the various noise terms on the relevant parameters (lens redshift, strength, smoothing length, redshift distribution of background galaxies) are explicitly calculated and simple estimates are provided.Comment: 18 pages, A&A in pres

Ordered increasing k-trees: Introduction and analysis of a preferential attachment network model

We introduce a random graph model based on k-trees, which can be generated by applying a probabilistic preferential attachment rule, but which also has a simple combinatorial description. We carry out a precise distributional analysis of important parameters for the network model such as the degree, the local clustering coefficient and the number of descendants of the nodes and root-to-node distances. We do not only obtain results for random nodes, but in particular we also get a precise description of the behaviour of parameters for the j-th inserted node in a random k-tree of size n, where j = j(n) might grow with n. The approach presented is not restricted to this specific k-tree model, but can also be applied to other evolving k-tree models.Comment: 12 pages, 2 figure