Spectro-Morphology of Galaxies

We present a quantitative method to classify galaxies, based on multi-wavelength data and elaborated from the properties of nearby galaxies. Our objective is to define an evolutionary method that can be used for low and high redshift objects. We estimate the concentration of light (C) at the galaxy center and the 180 degree-rotational asymmetry (A), computed at several wavelengths, from ultraviolet (UV) to I-band. The variation of the indices of concentration and asymmetry with the wavelength reflects the proportion and the distribution of young and old stellar populations in galaxies. In general C is found to decrease from optical to UV, and A is found to increase from optical to UV: the patchy appearance of galaxies in UV with no bulge is often very different from their counterpart at optical wavelengths, with prominent bulges and more regular disks. The variation of C and A with the wavelength is quantified. By this way, we are able to distinguish five types of galaxies that we call spectro-morphological types: compact, ringed, spiral, irregular and central-starburst galaxies, which can be differentiated by the repartition of their stellar populations. We discuss in detail the morphology of galaxies of the sample, and describe the morphological characteristics of each spectro-morphological type. We apply spectro-morphology to three objects at a redshift z=1 in the Hubble Deep Field North, that gives encouraging results for applications to large samples of high-redshift galaxies. This method of morphological classification could be used to study the evolution of the morphology with the redshift and is expected to bring observational constraints on scenarios of galaxy evolution.Comment: Accepted for publication in Astronomy & Astrophysic

Can Neuroscience Help Predict Future Antisocial Behavior?

Part I of this Article reviews the tools currently available to predict antisocial behavior. Part II discusses legal precedent regarding the use of, and challenges to, various prediction methods. Part III introduces recent neuroscience work in this area and reviews two studies that have successfully used neuroimaging techniques to predict recidivism. Part IV discusses some criticisms that are commonly levied against the various prediction methods and highlights the disparity between the attitudes of the scientific and legal communities toward risk assessment generally and neuroscience specifically. Lastly, Part V explains why neuroscience methods will likely continue to help inform and, ideally, improve the tools we use to help assess, understand, and predict human behavior

SAGE measurements of the stratospheric aerosol dispersion and loading from the Soufriere Volcano

Explosions of the Soufriere volcano on the Caribbean Island of St. Vincent reduced two major stratospheric plumes which the stratospheric aerosol and gas experiment (SAGE) satellite tracked to West Africa and the North Atlantic Ocean. The total mass of the stratospheric ejecta measured is less than 0.5% of the global stratospheric aerosol burden. No significant temperature or climate perturbation is expected. It is found that the movement and dispersion of the plumes agree with those deduced from high altitude meteorological data and dispersion theory. The stratospheric aerosol dispersion and loading from the Soufrier volcano was measured

Efficient calculation of the antiferromagnetic phase diagram of the 3D Hubbard model

The Dynamical Cluster Approximation with Betts clusters is used to calculate the antiferromagnetic phase diagram of the 3D Hubbard model at half filling. Betts clusters are a set of periodic clusters which best reflect the properties of the lattice in the thermodynamic limit and provide an optimal finite-size scaling as a function of cluster size. Using a systematic finite-size scaling as a function of cluster space-time dimensions, we calculate the antiferromagnetic phase diagram. Our results are qualitatively consistent with the results of Staudt et al. [Eur. Phys. J. B 17 411 (2000)], but require the use of much smaller clusters: 48 compared to 1000

Critical Currents of Josephson-Coupled Wire Arrays

We calculate the current-voltage characteristics and critical current I_c^{array} of an array of Josephson-coupled superconducting wires. The array has two layers, each consisting of a set of parallel wires, arranged at right angles, such that an overdamped resistively-shunted junction forms wherever two wires cross. A uniform magnetic field equal to f flux quanta per plaquette is applied perpendicular to the layers. If f = p/q, where p and q are mutually prime integers, I_c^{array}(f) is found to have sharp peaks when q is a small integer. To an excellent approximation, it is found in a square array of n^2 plaquettes, that I_c^{array}(f) \propto (n/q)^{1/2} for sufficiently large n. This result is interpreted in terms of the commensurability between the array and the assumed q \times q unit cell of the ground state vortex lattice.Comment: 4 pages, 4 figure

Pseudogap and antiferromagnetic correlations in the Hubbard model

Using the dynamical cluster approximation and quantum monte carlo we calculate the single-particle spectra of the Hubbard model with next-nearest neighbor hopping $t'$. In the underdoped region, we find that the pseudogap along the zone diagonal in the electron doped systems is due to long range antiferromagnetic correlations. The physics in the proximity of $(0,\pi)$ is dramatically influenced by $t'$ and determined by the short range correlations. The effect of $t'$ on the low energy ARPES spectra is weak except close to the zone edge. The short range correlations are sufficient to yield a pseudogap signal in the magnetic susceptibility, produce a concomitant gap in the single-particle spectra near $(\pi,\pi/2)$ but not necessarily at a location in the proximity of Fermi surface.Comment: 5 pages, 4 figure

Systematic study of d-wave superconductivity in the 2D repulsive Hubbard model

The cluster size dependence of superconductivity in the conventional two-dimensional Hubbard model, commonly believed to describe high-temperature superconductors, is systematically studied using the Dynamical Cluster Approximation and Quantum Monte Carlo simulations as cluster solver. Due to the non-locality of the d-wave superconducting order parameter, the results on small clusters show large size and geometry effects. In large enough clusters, the results are independent of the cluster size and display a finite temperature instability to d-wave superconductivity.Comment: 4 pages, 3 figures; updated with version published in PRL; added values of Tc obtained from fit

Magnetoresistance due to Domain Walls in Micron Scale Fe Wires with Stripe Domains

The magnetoresistance (MR) associated with domain boundaries has been investigated in microfabricated bcc Fe (0.65 to 20 $\mu$m linewidth) wires with controlled stripe domains. Domain configurations have been characterized using magnetic force microscopy. MR measurements as a function of field angle, temperature and domain configuration are used to estimate MR contributions due to resistivity anisotropy and domain walls. Evidence is presented that domain boundaries enhance the conductivity in such microstructures over a broad range of temperatures (1.5 K to 80 K).Comment: 8 pages, 3 postscript figures, and 2 jpg images (Fig 1 and 2) to appear in IEEE Transactions on Magnetics (Fall 1998