ESR Study of (C_5H_{12}N)_2CuBr_4

ESR studies at 9.27, 95.4, and 289.7 GHz have been performed on (C$_5$H$_{12}$N)$_2$CuBr$_4$ down to 3.7 K. The 9.27 GHz data were acquired with a single crystal and do not indicate the presence of any structural transitions. The high frequency data were collected with a polycrystalline sample and resolved two absorbances, consistent with two crystallographic orientations of the magnetic sites and with earlier ESR studies performed at 300 K. Below $B_{C1}=6.6$ T, our data confirm the presence of a spin singlet ground state.Comment: 2 pages, 4 figs., submitted 23rd International Conference on Low Temperature Physics (LT-23), Aug. 200

Statistical mechanics of systems with heterogeneous agents: Minority Games

We study analytically a simple game theoretical model of heterogeneous interacting agents. We show that the stationary state of the system is described by the ground state of a disordered spin model which is exactly solvable within the simple replica symmetric ansatz. Such a stationary state differs from the Nash equilibrium where each agent maximizes her own utility. The latter turns out to be characterized by a replica symmetry broken structure. Numerical results fully agree with our analytic findings.Comment: 4 pages, 1 Postscript figure. Revised versio

Extracting non-linear integrate-and-fire models from experimental data using dynamic I–V curves

The dynamic I–V curve method was recently introduced for the efficient experimental generation of reduced neuron models. The method extracts the response properties of a neuron while it is subject to a naturalistic stimulus that mimics in vivo-like fluctuating synaptic drive. The resulting history-dependent, transmembrane current is then projected onto a one-dimensional current–voltage relation that provides the basis for a tractable non-linear integrate-and-fire model. An attractive feature of the method is that it can be used in spike-triggered mode to quantify the distinct patterns of post-spike refractoriness seen in different classes of cortical neuron. The method is first illustrated using a conductance-based model and is then applied experimentally to generate reduced models of cortical layer-5 pyramidal cells and interneurons, in injected-current and injected- conductance protocols. The resulting low-dimensional neuron models—of the refractory exponential integrate-and-fire type—provide highly accurate predictions for spike-times. The method therefore provides a useful tool for the construction of tractable models and rapid experimental classification of cortical neurons

Statistical-Mechanical Measure of Stochastic Spiking Coherence in A Population of Inhibitory Subthreshold Neurons

By varying the noise intensity, we study stochastic spiking coherence (i.e., collective coherence between noise-induced neural spikings) in an inhibitory population of subthreshold neurons (which cannot fire spontaneously without noise). This stochastic spiking coherence may be well visualized in the raster plot of neural spikes. For a coherent case, partially-occupied "stripes" (composed of spikes and indicating collective coherence) are formed in the raster plot. This partial occupation occurs due to "stochastic spike skipping" which is well shown in the multi-peaked interspike interval histogram. The main purpose of our work is to quantitatively measure the degree of stochastic spiking coherence seen in the raster plot. We introduce a new spike-based coherence measure $M_s$ by considering the occupation pattern and the pacing pattern of spikes in the stripes. In particular, the pacing degree between spikes is determined in a statistical-mechanical way by quantifying the average contribution of (microscopic) individual spikes to the (macroscopic) ensemble-averaged global potential. This "statistical-mechanical" measure $M_s$ is in contrast to the conventional measures such as the "thermodynamic" order parameter (which concerns the time-averaged fluctuations of the macroscopic global potential), the "microscopic" correlation-based measure (based on the cross-correlation between the microscopic individual potentials), and the measures of precise spike timing (based on the peri-stimulus time histogram). In terms of $M_s$, we quantitatively characterize the stochastic spiking coherence, and find that $M_s$ reflects the degree of collective spiking coherence seen in the raster plot very well. Hence, the "statistical-mechanical" spike-based measure $M_s$ may be used usefully to quantify the degree of stochastic spiking coherence in a statistical-mechanical way.Comment: 16 pages, 5 figures, to appear in the J. Comput. Neurosc

Linear optical implementation of a single mode quantum filter and generation of multi-photon polarization entangled state

We propose a scheme to implement a single-mode quantum filter, which selectively eliminates the one-photon state in a quantum state $\alpha|0>+\beta|1>+\gamma|2>$. The vacuum state and the two photon state are transmitted without any change. This scheme requires single-photon sources, linear optical elements and photon detectors. Furthermore we demonstrate, how this filter can be used to realize a two-qubit projective measurement and to generate multi-photon polarization entangled states.Comment: revision submitted to PR

Symmetric sequence processing in a recurrent neural network model with a synchronous dynamics

The synchronous dynamics and the stationary states of a recurrent attractor neural network model with competing synapses between symmetric sequence processing and Hebbian pattern reconstruction is studied in this work allowing for the presence of a self-interaction for each unit. Phase diagrams of stationary states are obtained exhibiting phases of retrieval, symmetric and period-two cyclic states as well as correlated and frozen-in states, in the absence of noise. The frozen-in states are destabilised by synaptic noise and well separated regions of correlated and cyclic states are obtained. Excitatory or inhibitory self-interactions yield enlarged phases of fixed-point or cyclic behaviour.Comment: Accepted for publication in Journal of Physics A: Mathematical and Theoretica

Temporal decorrelation of collective oscillations in neural networks with local inhibition and long-range excitation

We consider two neuronal networks coupled by long-range excitatory interactions. Oscillations in the gamma frequency band are generated within each network by local inhibition. When long-range excitation is weak, these oscillations phase-lock with a phase-shift dependent on the strength of local inhibition. Increasing the strength of long-range excitation induces a transition to chaos via period-doubling or quasi-periodic scenarios. In the chaotic regime oscillatory activity undergoes fast temporal decorrelation. The generality of these dynamical properties is assessed in firing-rate models as well as in large networks of conductance-based neurons.Comment: 4 pages, 5 figures. accepted for publication in Physical Review Letter

Chaînes de Markov cachées multivariées à bruit corrélé non gaussien, avec applications à la segmentation du signal radar

Nous proposons un modèle de signal multivarié, corrélé temporellement et spectralement, adapté à la modélisation du signal Radar. Le modèle proposé est une chaîne de Markov cachée telle que la loi des observations appartienne à la famille des SIRV et dont la corrélation temporelle de la texture est décrite au moyen d'une copule. Il demeure alors possible d'estimer les paramètres de la loi des observations, et nous étudions la robustesse de cette estimation en faisant varier le type et la force de la dépendance temporelle en utilisant différentes familles de copules. Finalement, nous explorons l'influence de la non prise en compte de cette dépendance dans les procédures de segmentation statistique des signaux Radar fondées sur des chaînes de Markov cachées

Optimal static and dynamic recycling of defective binary devices

The binary Defect Combination Problem consists in finding a fully working subset from a given ensemble of imperfect binary components. We determine the typical properties of the model using methods of statistical mechanics, in particular, the region in the parameter space where there is almost surely at least one fully-working subset. Dynamic recycling of a flux of imperfect binary components leads to zero wastage.Comment: 14 pages, 15 figure