Entanglement between collective operators in a linear harmonic chain

We investigate entanglement between collective operators of two blocks of oscillators in an infinite linear harmonic chain. These operators are defined as averages over local operators (individual oscillators) in the blocks. On the one hand, this approach of "physical blocks" meets realistic experimental conditions, where measurement apparatuses do not interact with single oscillators but rather with a whole bunch of them, i.e., where in contrast to usually studied "mathematical blocks" not every possible measurement is allowed. On the other, this formalism naturally allows the generalization to blocks which may consist of several noncontiguous regions. We quantify entanglement between the collective operators by a measure based on the Peres-Horodecki criterion and show how it can be extracted and transferred to two qubits. Entanglement between two blocks is found even in the case where none of the oscillators from one block is entangled with an oscillator from the other, showing genuine bipartite entanglement between collective operators. Allowing the blocks to consist of a periodic sequence of subblocks, we verify that entanglement scales at most with the total boundary region. We also apply the approach of collective operators to scalar quantum field theory.

Microscopic models for dielectric relaxation in disordered systems

It is shown how the Debye rotational diffusion model of dielectric relaxation of polar molecules (which may be described in microscopic fashion as the diffusion limit of a discrete time random walk on the surface of the unit sphere) may be extended to yield the empirical Havriliak-Negami (HN) equation of anomalous dielectric relaxation from a microscopic model based on a kinetic equation just as in the Debye model. This kinetic equation is obtained by means of a generalization of the noninertial Fokker-Planck equation of conventional Brownian motion (generally known as the Smoluchowski equation) to fractional kinetics governed by the HN relaxation mechanism. For the simple case of noninteracting dipoles it may be solved by Fourier transform techniques to yield the Green function and the complex dielectric susceptibility corresponding to the HN anomalous relaxation mechanism.

Correlated electron-ion dynamics: the excitation of atomic motion by energetic electrons

Correlated electron-ion dynamics (CEID) is an extension of molecular dynamics that allows us to introduce in a correct manner the exchange of energy between electrons and ions. The formalism is based on a systematic approximation: small amplitude moment expansion. This formalism is extended here to include the explicit quantum spread of the ions and a generalization of the Hartree-Fock approximation for incoherent sums of Slater determinants. We demonstrate that the resultant dynamical equations reproduce analytically the selection rules for inelastic electron-phonon scattering from perturbation theory, which control the mutually driven excitations of the two interacting subsystems. We then use CEID to make direct numerical simulations of inelastic current-voltage spectroscopy in atomic wires, and to exhibit the crossover from ionic cooling to heating as a function of the relative degree of excitation of the electronic and ionic subsystems.

A timing-specific memory distortion effect in young children

It has been suggested that there are systematic distortions in children's memory for temporal durations, such that children's memory is not just less accurate than that of adults but qualitatively different. Experiment I replicated the memory distortion effect by demonstrating developmental change in the tendency to confuse a reference duration with one that is shorter rather than longer than it. When the long-term memory demands of the task were reduced by providing reminders of the reference duration on every trial, there were no such qualitative changes in error patterns (Experiment 2). Further evidence for developmental changes in memory distortion was found in the temporal generalization task of Experiment 3, in which stimuli were spaced logarithmically rather than linearly. In Experiment 4, a similar distortion pattern was absent in a task in which children made judgments about the pitch rather than the duration of stimuli, suggesting the effect may be specific to time estimation. (C) 2003 Elsevier Inc. All rights reserved.

Secondary Transfer Effects of Intergroup Contact: Alternative Accounts and Underlying Processes

Although intergroup contact is one of the most prominent interventions to reduce prejudice. the generalization of contact effects is still a contentious issue This research further examined the rarely studied secondary transfer effect (STE, Pettigrew, 2009) by which contact with a primary outgroup reduces prejudice toward secondary groups that are not directly involved in the contact Across 3 cross-sectional studies conducted in Cyprus (N = 1.653), Northern Ireland (N = 1,973). and Texas (N = 275) and 1 longitudinal study conducted in Northern Ireland (N = 411). the present research sought to systematically rule out alternative accounts of the STE and to investigate 2 potential mediating mechanisms (ingroup reappraisal and attitude generalization) Results indicated that, consistent with the STE. contact with a primary outgroup predicts attitudes toward secondary outgroups. over and above contact with the secondary outgroup, socially desirable responding. and prior attitudes Mediation analyses found strong evidence for attitude generalization but only limited evidence for ingroup reappraisal as an underlying process Two out of 3 tests of a reverse model, where contact with the secondary outgroup predicts attitudes toward the primary outgroup. provide further evidence for an indirect effect through attitude generalization Theoretical and practical implications of these results are discussed, and directions for future research are identified

Measuring conflict and agreement between two prioritized knowledge bases in possibilistic logic.

In this paper we investigate the relationship between two prioritized knowledge bases by measuring both the conflict and the agreement between them.First of all, a quantity of conflict and two quantities of agreement are defined. The former is shown to be a generalization of the well-known Dalal distance which is the hamming distance between two interpretations. The latter are, respectively, a quantity of strong agreement which measures the amount ofinformation on which two belief bases “totally” agree, and a quantity of weak agreement which measures the amount of information that is believed by onesource but is unknown to the other. All three quantity measures are based on the weighted prime implicant, which represents beliefs in a prioritized belief base. We then define a degree of conflict and two degrees of agreement based on our quantity of conflict and quantities of agreement. We also consider the impact of these measures on belief merging and information source ordering.

Genetic testing and the relationship between specific and general self-efficacy

The study examined the extent to which variations in health-specific self-efficacy could affect general self-efficacy. In a repeated measures design, 300 participants were administered an efficacy questionnaire, before and after an alleged news report, aimed at increasing or decreasing self-efficacy over genetic-testing decision making. The results found that self-efficacy over testing was significantly reduced after reading the negative news report in those participants who felt personal efficacy over testing decisions was important. Levels of general self-efficacy were also significantly decreased. The findings suggest that being denied control over a specific area of self-efficacy can have a wider impact, with a lack of perceived efficacy over testing decision making adversely impacting on levels of general well-being. The wider implications of this generalization effect and the processes involved in efficacy generalization are discussed.

Efficient Evaluation of Multidimensional Time-Varying Density Forecasts

We propose two simple evaluation methods for time varying density forecasts of continuous higher dimensional random variables. Both methods are based on the probability integral transformation for unidimensional forecasts. The first method tests multinormal densities and relies on the rotation of the coordinate system. The advantage of the second method is not only its applicability to any continuous distribution but also the evaluation of the forecast accuracy in specific regions of its domain as defined by the user’s interest. We show that the latter property is particularly useful for evaluating a multidimensional generalization of the Value at Risk. In simulations and in an empirical study, we examine the performance of both tests.

Topiramate in pregnancy - Preliminary experience from the UK epilepsy and pregnancy register

Objectives: Topiramate (Topamax (R)) is licensed to be used, either in monotherapy or as adjunctive treatment, for generalized tonic clonic seizures or partial seizures with or without secondary generalization and for prevention of migraine. The safety of topiramate in human pregnancy is largely unknown. Here we report on our experience of pregnancies exposed to topiramate.

Faithful test of nonlocal realism with entangled coherent states

We investigate the violation of Leggett's inequality for nonlocal realism using entangled coherent states and various types of local measurements. We prove mathematically the relation between the violation of the Clauser-Horne-Shimony-Holt form of Bell's inequality and Leggett's one when tested by the same resources. For Leggett inequalities, we generalize the nonlocal realistic bound to systems in Hilbert spaces larger than bidimensional ones and introduce an optimization technique that allows one to achieve larger degrees of violation by adjusting the local measurement settings. Our work describes the steps that should be performed to produce a self-consistent generalization of Leggett's original arguments to continuous-variable states.

Two-stage RBF network construction based on particle swarm optimization

The conventional radial basis function (RBF) network optimization methods, such as orthogonal least squares or the two-stage selection, can produce a sparse network with satisfactory generalization capability. However, the RBF width, as a nonlinear parameter in the network, is not easy to determine. In the aforementioned methods, the width is always pre-determined, either by trial-and-error, or generated randomly. Furthermore, all hidden nodes share the same RBF width. This will inevitably reduce the network performance, and more RBF centres may then be needed to meet a desired modelling specification. In this paper we investigate a new two-stage construction algorithm for RBF networks. It utilizes the particle swarm optimization method to search for the optimal RBF centres and their associated widths. Although the new method needs more computation than conventional approaches, it can greatly reduce the model size and improve model generalization performance. The effectiveness of the proposed technique is confirmed by two numerical simulation examples.

Fast automatic two-stage nonlinear model identification based on the extreme learning machine

It is convenient and effective to solve nonlinear problems with a model that has a linear-in-the-parameters (LITP) structure. However, the nonlinear parameters (e.g. the width of Gaussian function) of each model term needs to be pre-determined either from expert experience or through exhaustive search. An alternative approach is to optimize them by a gradient-based technique (e.g. Newton’s method). Unfortunately, all of these methods still need a lot of computations. Recently, the extreme learning machine (ELM) has shown its advantages in terms of fast learning from data, but the sparsity of the constructed model cannot be guaranteed. This paper proposes a novel algorithm for automatic construction of a nonlinear system model based on the extreme learning machine. This is achieved by effectively integrating the ELM and leave-one-out (LOO) cross validation with our two-stage stepwise construction procedure [1]. The main objective is to improve the compactness and generalization capability of the model constructed by the ELM method. Numerical analysis shows that the proposed algorithm only involves about half of the computation of orthogonal least squares (OLS) based method. Simulation examples are included to confirm the efficacy and superiority of the proposed technique.