Levy-stable distributions revisited: tail index > 2 does not exclude the Levy-stable regime

Power-law tail behavior and the summation scheme of Levy-stable distributions is the basis for their frequent use as models when fat tails above a Gaussian distribution are observed. However, recent studies suggest that financial asset returns exhibit tail exponents well above the Levy-stable regime ($0<\alpha\le 2$). In this paper we illustrate that widely used tail index estimates (log-log linear regression and Hill) can give exponents well above the asymptotic limit for $\alpha$ close to 2, resulting in overestimation of the tail exponent in finite samples. The reported value of the tail exponent $\alpha$ around 3 may very well indicate a Levy-stable distribution with $\alpha\approx 1.8$.Comment: To be published in Int. J. Modern Physics C (2001) vol. 12 no.

A novel topology of high-speed SRM for high-performance traction applications

A novel topology of high-speed Switched Reluctance Machine (SRM) for high-performance traction applications is presented in this article. The target application, a Hybrid Electric Vehicle (HEV) in the sport segment poses very demanding specifications on the power and torque density of the electric traction machine. After evaluating multiple alternatives, the topology proposed is a 2-phase axial flux machine featuring both segmented twin rotors and a segmented stator core. Electromagnetic, thermal and mechanical models of the proposed topology are developed and subsequently integrated in an overall optimisation algorithm in order to find the optimal geometry for the application. Special focus is laid on the thermal management of the machine, due to the tough thermal conditions resulting from the high frequency, high current and highly saturated operation. Some experimental results are also included in order to validate the modelling and simulation results

Magnetism in the dilute Kondo lattice model

The one dimensional dilute Kondo lattice model is investigated by means of bosonization for different dilution patterns of the array of impurity spins. The physical picture is very different if a commensurate or incommensurate doping of the impurity spins is considered. For the commensurate case, the obtained phase diagram is verified using a non-Abelian density-matrix renormalization-group algorithm. The paramagnetic phase widens at the expense of the ferromagnetic phase as the $f$-spins are diluted. For the incommensurate case, antiferromagnetism is found at low doping, which distinguishes the dilute Kondo lattice model from the standard Kondo lattice model.Comment: 11 pages, 2 figure

From density-matrix renormalization group to matrix product states

In this paper we give an introduction to the numerical density matrix renormalization group (DMRG) algorithm, from the perspective of the more general matrix product state (MPS) formulation. We cover in detail the differences between the original DMRG formulation and the MPS approach, demonstrating the additional flexibility that arises from constructing both the wavefunction and the Hamiltonian in MPS form. We also show how to make use of global symmetries, for both the Abelian and non-Abelian cases.Comment: Numerous small changes and clarifications, added a figur

NMR evidence for two-step phase-separation in Nd_{1.85}Ce_{0.15}CuO_{4-delta}

By Cu NMR we studied the spin and charge structure in Nd_{2-x}Ce_{x}CuO_{4-delta}. For x=0.15, starting from a superconducting sample, the low temperature magnetic order in the sample reoxygenated under 1 bar oxygen at 900^0 C, reveals a peculiar modulation of the internal field, indicative for a phase characterized by large charge droplets ('Blob'-phase). By prolonged reoxygenation at 4 bar the blobs brake up and the spin structure changes to that of an ordered antiferromagnet (AF). We conclude that the superconductivity in the n-type systems competes with a genuine type I Mott-insulating state

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Longitudinal analysis is important in many disciplines, such as the study of behavioral transitions in social science. Only very recently, feature selection has drawn adequate attention in the context of longitudinal modeling. Standard techniques, such as generalized estimating equations, have been modified to select features by imposing sparsity-inducing regularizers. However, they do not explicitly model how a dependent variable relies on features measured at proximal time points. Recent graphical Granger modeling can select features in lagged time points but ignores the temporal correlations within an individual's repeated measurements. We propose an approach to automatically and simultaneously determine both the relevant features and the relevant temporal points that impact the current outcome of the dependent variable. Meanwhile, the proposed model takes into account the non-{\em i.i.d} nature of the data by estimating the within-individual correlations. This approach decomposes model parameters into a summation of two components and imposes separate block-wise LASSO penalties to each component when building a linear model in terms of the past $\tau$ measurements of features. One component is used to select features whereas the other is used to select temporal contingent points. An accelerated gradient descent algorithm is developed to efficiently solve the related optimization problem with detailed convergence analysis and asymptotic analysis. Computational results on both synthetic and real world problems demonstrate the superior performance of the proposed approach over existing techniques.Comment: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 201

Fractional excitations in cold atomic gases

We study the behavior of excitations in the tilted one-dimensional Bose-Hubbard model. In the phase with broken symmetry, fundamental excitations are domain walls which show fractional statistics. Using perturbation theory, we derive an analytic model for the time evolution of these fractional excitations, and demonstrate the existence of a repulsively bound state above a critical center-of-mass momentum. The validity of the perturbative analysis is confirmed by the use of time-adaptive density-matrix renormalization group simulations. These findings open the path for the experimental detection of fractional particles in cold atomic gases

Warren McCulloch and the British cyberneticians

Warren McCulloch was a significant influence on a number of British cyberneticians, as some British pioneers in this area were on him. He interacted regularly with most of the main figures on the British cybernetics scene, forming close friendships and collaborations with several, as well as mentoring others. Many of these interactions stemmed from a 1949 visit to London during which he gave the opening talk at the inaugural meeting of the Ratio Club, a gathering of brilliant, mainly young, British scientists working in areas related to cybernetics. This paper traces some of these relationships and interaction