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At least 667 records · Page 37Linked to original sources

PubMed2004

Ensemble averages and nonextensivity at the edge of chaos of one-dimensional maps.

Ensemble averages of the sensitivity to initial conditions xi(t) and the entropy production per unit of time of a new family of one-dimensional dissipative maps, x(t+1)=1-ae(-1/|x(t)|(z))(z>0), and of the known logisticlike maps, x(t+1)=1-a|x(t)|(z)(z>1), are numerically studied, both for strong (Lyapunov exponent lambda(1)>0) and weak (chaos threshold, i.e., lambda(1)=0) chaotic cases. In all cases we verify the following: (i) both [ln((q)x triple bond (x(1-q)-1)/(1-q); ln((1)x=ln(x] and [S(q) triple bond (1- sigma p(q)(i))/(q-1); S(1)=- sigma p(i)ln(p(i)] linearly increase with time for (and only for) a special value of q, q(av)(sen), and (ii) the slope of and that of coincide, thus interestingly extending the well known Pesin theorem. For strong chaos, q(av)(sen)=1, whereas at the edge of chaos q(av)(sen)(z)<1.

Journal Article↗

PubMed2004

Continuous weak measurement and nonlinear dynamics in a cold spin ensemble.

A weak continuous quantum measurement of an atomic spin ensemble can be implemented via Faraday rotation of an off-resonance probe beam, and may be used to create and probe nonclassical spin states and dynamics. We show that the probe light shift leads to nonlinearity in the spin dynamics and limits the useful Faraday measurement window. Removing the nonlinearity allows a nonperturbing measurement on the much longer time scale set by decoherence. The nonlinear spin Hamiltonian is of interest for studies of quantum chaos and real-time quantum state estimation.

Journal Article↗

PubMed2004

Bayesian ensemble approach to error estimation of interatomic potentials.

Using a Bayesian approach a general method is developed to assess error bars on predictions made by models fitted to data. The error bars are estimated from fluctuations in ensembles of models sampling the model-parameter space with a probability density set by the minimum cost. The method is applied to the development of interatomic potentials for molybdenum using various potential forms and databases based on atomic forces. The calculated error bars on elastic constants, gamma-surface energies, structural energies, and dislocation properties are shown to provide realistic estimates of the actual errors for the potentials.

Bayes Theorem↗

PubMed2004

Ensemble quantum computation with atoms in periodic potentials.

We show how to perform universal quantum computation with atoms confined in optical lattices which works both in the presence of defects and without individual addressing. The method is based on using the defects in the lattice, wherever they are, both to "mark" different copies on which ensemble quantum computation is carried out and to define pointer atoms which perform the quantum gates. We also show how to overcome the problem of scalability in this system.

Journal Article↗

PubMed2004

Temporal dynamics of photon pairs generated by an atomic ensemble.

The time dependence of nonclassical correlations is investigated for two fields (1,2) generated by an ensemble of cold cesium atoms via the protocol of Duan et al. [Nature (London) 414, 413 (2001)]]. The correlation function R(t1,t2) for the ratio of cross to autocorrelations for the (1,2) fields at times (t1,t2) is found to have a maximum value R(max=292+/-57, which significantly violates the Cauchy-Schwarz inequality R< or =1 for classical fields. Decoherence of quantum correlations is observed over taud approximately 175 ns, and is described by our model, as is a new scheme to mitigate this effect.

Journal Article↗

PubMed2005

Sample-specific and ensemble-averaged magnetoconductance of individual single-wall carbon nanotubes.

We discuss magnetotransport measurements on individual single-wall carbon nanotubes (SWNTs) with low contact resistance, performed as a function of temperature and gate voltage. We find that the application of a magnetic field perpendicular to the tube axis results in a large magnetoconductance of the order of e2/h at low temperature. We demonstrate that this magnetoconductance consists of a sample-specific and of an ensemble-averaged contribution, both of which decrease with increasing temperature. The observed behavior resembles very closely the behavior of more conventional multichannel mesoscopic wires, exhibiting universal conductance fluctuations and weak localization. A theoretical analysis of our experiments will enable us to reach a deeper understanding of phase-coherent one-dimensional electronic motion in SWNTs.

Journal Article↗

PubMed2005

Statistics of real eigenvalues in Ginibre's ensemble of random real matrices.

The integrable structure of Ginibre's orthogonal ensemble of random matrices is looked at through the prism of the probability p(n,k) to find exactly k real eigenvalues in the spectrum of an n x n real asymmetric Gaussian random matrix. The exact solution for the probability function p(n,k) is presented, and its remarkable connection to the theory of symmetric functions is revealed. An extension of the Dyson integration theorem is a key ingredient of the theory presented.

Journal Article↗

PubMed2005

Atom counting statistics in ensembles of interacting Rydberg atoms.

We show that the probability distributions for the number of Rydberg excitations in small ensembles of cold atoms, excited using short (100 ns) laser pulses, can be highly sub-Poissonian. The phenomenon occurs if the atom density and the principal quantum number of the excited Rydberg level are sufficiently high. Our observations are attributed to a blockade of the Rydberg atom excitation.

Journal Article↗

PubMed2006

Photonic anisotropic magnetoresistance in dense co particle ensembles.

In this Letter, we experimentally show that the amplitude and arrival time of the terahertz optical transmission through dense ensembles of subwavelength-size ferromagnetic particles is strongly dependent on the orientation of an externally applied magnetic field. The attenuation and delay have the same magnetic field orientation dependence as the electrical anisotropic magnetoresistance inherent to bulk ferromagnetic metals. We envision the application of this magnetic effect in terahertz photonic devices.

Journal Article↗

PubMed2006

Loop updates for quantum Monte Carlo simulations in the canonical ensemble.

We present a new nonlocal updating scheme for quantum Monte Carlo simulations, which conserves particle number and other symmetries. It allows exact symmetry projection and direct evaluation of the equal-time Green's function and other observables in the canonical ensemble. The method is applicable to a wide variety of systems. We show results for bosonic atoms in optical lattices, neutron pairs in atomic nuclei, and electron pairs in ultrasmall superconducting grains.

Journal Article↗

PubMed2006

Elasticity from the force network ensemble in granular media.

Transmission of forces in static granular materials is studied within the framework of the force network ensemble, by numerically evaluating the mechanical response of hexagonal packings of frictionless grains and rectangular packings of frictional grains. In both cases, close to the point of application of the overload, the response is nonlinear and displays two peaks, while at larger length scales, it is linear and elasticlike. The crossover between these two behaviors occurs at a depth that increases with the magnitude of the overload and decreases with increasing friction.

Journal Article↗

PubMed2001

Coincidence site lattice theory of multicrystalline ensembles.

It is shown how the coincidence site lattice theory, developed originally for grain boundaries and extended recently to triple junctions, can be applied to more complex ensembles of crystallites with the cubic crystal structure. These include quadruple points, multiple junctions of grains and other multicrystal assemblies. Application of the theory is demonstrated on hypothetical examples, which may help elucidate some practically important problems.

Journal Article↗

PubMed2004

WHEATSHEAF: an algorithm to average protein structure ensembles.

A new algorithm is described that forms a single structure representative of ensembles of structures from files in the format used by the Protein Data Bank. A first attempt is made by averaging in the space spanned by bond lengths, inter-bond rotations and symmetry-multiplied dihedral rotations. This normally produces well formed regular secondary-structure elements, but the intervening less well ordered regions are often distorted because of the invalidity of averaging large rotations about divergent axes. For this reason, the algorithm includes a second stage that pulls the interatomic distances towards more fully representative values. Results produced by this method have proved better as judged by conventional quality checks than any input structure in nearly all cases tested so far, especially for the backbone, and much better than those produced by commonly used alternative methods.

Algorithms↗

PubMed2006

An ensemble of crystallographic models enables the description of novel bromate-oxoanion species trapped within a protein crystal.

Only a few protein-oxoanion crystal complexes have been described to date. Here, the structure of a protein soaked in a bromate solution has been determined to a resolution of 1.25 A and refined to final overall R/R(free) values of 18.04/21.3 (isotropic) and 11.25/14.67 (anisotropic). In contrast to the single-model approach, refinement of an ensemble of ten models enabled us to determine variances and statistically evaluate bond-length distances and angles in the oxoanions. In total, nine bromate positions, including two BrO(3)(-) x HBrO(3) dimer species, have been identified on the basis of the anomalous signal of the Br atoms. For all bromate ions, the main-chain amide atoms of the protein were identified as the dominant binding positions, a useful property in any experimental phase-determination experiment.

Amides↗

PubMed1992

Identification of time-varying biological systems from ensemble data.

The theory underlying a new method for the identification of time-varying systems is described. The method uses singular value decomposition to obtain least-squares estimates of time-varying impulse response functions from an ensemble of input-output realizations. No a priori assumptions regarding the system structure or form of the time-variation are required and there are few restrictions on the input signal. Simulation studies, using a model of time-varying joint dynamics, show that the method can track rapid changes in system dynamics accurately and is robust in the presence of output noise. An application of the method is demonstrated by using it to track dynamic ankle stiffness during a rapid, voluntary, isometric contraction. During the transient phase of the contraction, low-frequency ankle stiffness gain decreased in a manner which could not be described with the second-order model of joint dynamics often used under stationary conditions.

Adult↗

PubMed1999

A robust ensemble data method for identification of human joint mechanical properties during movement.

This paper describes a perturbation method for the identification of linear time-varying systems with an unknown input (voluntary joint input) using ensemble data. The method separates the unknown input and the perturbation through high-pass filtering and recasts the multi-input single-output system identification into single-input single-output system identification. The method is robust to intertrial variation, and can track changes of system dynamics up to 5 Hz. Analysis and simulation are given for the conditions similar to those for the human arm experiments. Experiments show that mechanical properties of the human elbow joint change with voluntary movement speed and that the mean stiffness with voluntary movement is in the range of the posture and is higher than reported before.

Adult↗

PubMed2000

Overcoming selective ensemble averaging: unsupervised identification of event-related brain potentials.

We present a novel approach to the problem of event-related potential (ERP) identification, based on a competitive artificial neural network (ANN) structure. Our method uses ensembled electroencephalogram (EEG) data just as used in conventional averaging, however without the need for a priori data subgrouping into distinct categories (e.g., stimulus- or event-related), and thus avoids conventional assumptions on response invariability. The competitive ANN, often described as a winner takes all neural structure, is based on dynamic competition among the net neurons where learning takes place only with the winning neuron. Using a simple single-layered structure, the proposed scheme results in convergence of the actual neural weights to the embedded ERP patterns. The method is applied to real event-related potential data recorded during a common odd-ball type paradigm. For the first time, within-session variable signal patterns are automatically identified, dismissing the strong and limiting requirement of a priori stimulus-related selective grouping of the recorded data. The results present new possibilities in ERP research.

Artifacts↗

PubMed2005

Recognizing partially occluded, expression variant faces from single training image per person with SOM and soft kappa-NN ensemble.

Most classical template-based frontal face recognition techniques assume that multiple images per person are available for training, while in many real-world applications only one training image per person is available and the test images may be partially occluded or may vary in expressions. This paper addresses those problems by extending a previous local probabilistic approach presented by Martinez, using the self-organizing map (SOM) instead of a mixture of Gaussians to learn the subspace that represented each individual. Based on the localization of the training images, two strategies of learning the SOM topological space are proposed, namely to train a single SOM map for all the samples and to train a separate SOM map for each class, respectively. A soft kappa nearest neighbor (soft kappa-NN) ensemble method, which can effectively exploit the outputs of the SOM topological space, is also proposed to identify the unlabeled subjects. Experiments show that the proposed method exhibits high robust performance against the partial occlusions and variant expressions.

Algorithms↗