Exploration in Free Word Association Networks: Models and Experiment

Free association is a task that requires a subject to express the first word to come to their mind when presented with a certain cue. It is a task which can be used to expose the basic mechanisms by which humans connect memories. In this work we have made use of a publicly available database of free associations to model the exploration of the averaged network of associations using a statistical and the \emph{ACT-R} model. We performed, in addition, an online experiment asking participants to navigate the averaged network using their individual preferences for word associations. We have investigated the statistics of word repetitions in this guided association task. We find that the considered models mimic some of the statistical properties, viz the probability of word repetitions, the distance between repetitions and the distribution of association chain lengths, of the experiment, with the \emph{ACT-R} model showing a particularly good fit to the experimental data for the more intricate properties as, for instance, the ratio of repetitions per length of association chains.Comment: Cognitive Processing, in pres

Spin-charge separation at small lengthscales in the 2D t-J model

We consider projected wavefunctions for the 2D $t-J$ model. For various wavefunctions, including correlated Fermi-liquid and Luttinger-type wavefunctions we present the static charge-charge and spin-spin structure factors. Comparison with recent results from a high-temperature expansion by Putikka {\it et al.} indicates spin-charge separation at small lengthscales.Comment: REVTEX, 5 pages, 5 figures hardcopies availabl

Attractor Metadynamics in Adapting Neural Networks

Slow adaption processes, like synaptic and intrinsic plasticity, abound in the brain and shape the landscape for the neural dynamics occurring on substantially faster timescales. At any given time the network is characterized by a set of internal parameters, which are adapting continuously, albeit slowly. This set of parameters defines the number and the location of the respective adiabatic attractors. The slow evolution of network parameters hence induces an evolving attractor landscape, a process which we term attractor metadynamics. We study the nature of the metadynamics of the attractor landscape for several continuous-time autonomous model networks. We find both first- and second-order changes in the location of adiabatic attractors and argue that the study of the continuously evolving attractor landscape constitutes a powerful tool for understanding the overall development of the neural dynamics

Gamma-ray line emission from Al-26 produced by Wolf-Rayet stars

The recent satellite observations of the 1.8 MeV line from the decay of Al-26 has given a new impetus to the study of the nucleosynthesis of Al-26. The production and ejection of Al-26 by massive mass-losing stars (Of and WR stars) is discussed in the light of recent stellar models. The longitude distribution of the Al-26 gamma ray line emission produced by the galactic collection of WR stars is derived based on various estimates of their radial distribution. This longitude profile provides: (1) a specific signature of massive stars on the background of other potential Al-26 sources, as novae, supernovae, certain red giants and possibly AGB stars; and (2) a possible tool to improve the data analysis of the HEAO 3 and SMM experiments

A Real-time MHE and NMPC Scheme for Wind Turbine Control

Among the several problems arising in the Airborne Wind Energy paradigm, an essential one is the control of the tethered airfoil trajectory during power generation. Tethered flight is a fast, strongly nonlinear, unstable and constrained process, motivating control approaches based on fast Non-linear Model Predictive Control. In this paper, a computationally efficient model is proposed, based on Differential-Algebraic equations. A control scheme based on Nonlinear Model Predictive Control (NMPC) and an estimator based on Moving Horizon Estimation (MHE) is proposed to handle the wind turbulences. In order to make a real-time application of Non-linear Model Predictive Control possible, a Real-Time Iteration scheme is proposed

Properties of the energetic particle distributions during the October 28, 2003 solar flare from INTEGRAL/SPI observations

Analysis of spectra obtained with the gamma-ray spectrometer SPI onboard INTEGRAL of the GOES X17-class flare on October 28, 2003 is presented. In the energy range 600 keV - 8 MeV three prominent narrow lines at 2.223, 4.4 and 6.1 MeV, resulting from nuclear interactions of accelerated ions within the solar atmosphere could be observed. Time profiles of the three lines and the underlying continuum indicate distinct phases with several emission peaks and varying continuum-to-line ratio for several minutes before a smoother decay phase sets in. Due to the high-resolution Ge detectors of SPI and the exceptional intensity of the flare, detailed studies of the 4.4 and 6.1 MeV line shapes was possible for the first time. Comparison with calculated line shapes using a thick target interaction model and several energetic particle angular distributions indicates that the nuclear interactions were induced by downward-directed particle beams with alpha-to-proton ratios of the order of 0.1. There are also indications that the 4.4 MeV to 6.1 MeV line fluence ratio changed between the beginning and the decay phase of the flare, possibly due to a temporal evolution of the energetic particle alpha-to-proton ratio.Comment: 24 pages, 10 figures, accepted for publication by A&

Pairing and superconductivity driven by strong quasiparticle renormalization in two-dimensional organic charge transfer salts

We introduce and analyze a variational wave function for quasi two-dimensional kappa-ET organic salts containing strong local and nonlocal correlation effects. We find an unconventional superconducting ground state for intermediate charge carrier interaction, sandwiched between a conventional metal at weak coupling and a spin liquid at larger coupling. Most remarkably, the excitation spectrum is dramatically renormalized and is found to be the driving force for the formation of the unusual superconducting state.Comment: 4 pages, 4 figure