Comparison of methods for estimating continuous distributions of relaxation times

The nonparametric estimation of the distribution of relaxation times approach is not as frequently used in the analysis of dispersed response of dielectric or conductive materials as are other immittance data analysis methods based on parametric curve fitting techniques. Nevertheless, such distributions can yield important information about the physical processes present in measured material. In this letter, we apply two quite different numerical inversion methods to estimate the distribution of relaxation times for glassy \lila\ dielectric frequency-response data at 225 \kelvin. Both methods yield unique distributions that agree very closely with the actual exact one accurately calculated from the corrected bulk-dispersion Kohlrausch model established independently by means of parametric data fit using the corrected modulus formalism method. The obtained distributions are also greatly superior to those estimated using approximate functions equations given in the literature.Comment: 4 pages and 4 figure

Spin wave dispersion in La2CuO4

We calculate the antiferromagnetic spin wave dispersion in the half-filled Hubbard model for a two-dimensional square lattice and find it to be in excellent agreement with recent high-resolution inelastic neutron scattering performed on La2CuO4 [Phys. Rev. Lett. 86, 5377 (2001)].Comment: typos correcte

Schur Partial Derivative Operators

A lattice diagram is a finite list L=((p_1,q_1),...,(p_n,q_n) of lattice cells. The corresponding lattice diagram determinant is \Delta_L(X;Y)=\det \| x_i^{p_j}y_i^{q_j} \|. These lattice diagram determinants are crucial in the study of the so-called ``n! conjecture'' of A. Garsia and M. Haiman. The space M_L is the space spanned by all partial derivatives of \Delta_L(X;Y). The ``shift operators'', which are particular partial symmetric derivative operators are very useful in the comprehension of the structure of the M_L spaces. We describe here how a Schur function partial derivative operator acts on lattice diagrams with distinct cells in the positive quadrant.Comment: 8 pages, LaTe

Langevin approach to synchronization of hyperchaotic time-delay dynamics

In this paper, we characterize the synchronization phenomenon of hyperchaotic scalar non-linear delay dynamics in a fully-developed chaos regime. Our results rely on the observation that, in that regime, the stationary statistical properties of a class of hyperchaotic attractors can be reproduced with a linear Langevin equation, defined by replacing the non-linear delay force by a delta-correlated noise. Therefore, the synchronization phenomenon can be analytically characterized by a set of coupled Langevin equations. We apply this formalism to study anticipated synchronization dynamics subject to external noise fluctuations as well as for characterizing the effects of parameter mismatch in a hyperchaotic communication scheme. The same procedure is applied to second order differential delay equations associated to synchronization in electro-optical devices. In all cases, the departure with respect to perfect synchronization is measured through a similarity function. Numerical simulations in discrete maps associated to the hyperchaotic dynamics support the formalism.Comment: 12 pages, 6 figure

Charge and spin Hall conductivity in metallic graphene

Graphene has an unusual low-energy band structure with four chiral bands and half-quantized and quantized Hall effects that have recently attracted theoretical and experimental attention. We study the Fermi energy and disorder dependence of its spin Hall conductivity. In the metallic regime we find that vertex corrections enhance the intrinsic spin Hall conductivity and that skew scattering can lead to its values that exceed the quantized ones expected when the chemical potential is inside the spin-orbit induced energy gap. We predict that large spin Hall conductivities will be observable in graphene even when the spin-orbit gap does not survive disorder.Comment: 4 pages, 2 figure

Can distributed delays perfectly stabilize dynamical networks?

Signal transmission delays tend to destabilize dynamical networks leading to oscillation, but their dispersion contributes oppositely toward stabilization. We analyze an integro-differential equation that describes the collective dynamics of a neural network with distributed signal delays. With the gamma distributed delays less dispersed than exponential distribution, the system exhibits reentrant phenomena, in which the stability is once lost but then recovered as the mean delay is increased. With delays dispersed more highly than exponential, the system never destabilizes.Comment: 4pages 5figure

Observability of counterpropagating modes at fractional-quantum-Hall edges

When the bulk filling factor is equal to 1 - 1/m with m odd, at least one counterpropagating chiral collective mode occurs simultaneously with magnetoplasmons at the edge of fractional-quantum-Hall samples. Initial experimental searches for an additional mode were unsuccessful. In this paper, we address conditions under which its observation should be expected in experiments where the electronic system is excited and probed by capacitive coupling. We derive realistic expressions for the velocity of the slow counterpropagating mode, starting from a microscopic calculation which is simplified by a Landau-Silin-like separation between long-range Hartree and residual interactions. The microscopic calculation determines the stiffness of the edge to long-wavelength neutral excitations, which fixes the slow-mode velocity, and the effective width of the edge region, which influences the magnetoplasmon dispersion.Comment: 18 pages, RevTex, 6 figures, final version to be published in Physical Review

Management of incidentally detected heart murmurs in dogs and cats

A dog or a cat has an incidentally detected heart murmur if the murmur is an unexpected discovery during a veterinary consultation that was not initially focused on the cardiovascular system. This document presents approaches for managing dogs and cats that have incidentally-detected heart murmurs, with an emphasis on murmur characteristics, signalment profiling, and multifactorial decision-making to choose an optimal course for a given patient