Effective transport barriers in nontwist systems

In fluids and plasmas with zonal flow reversed shear, a peculiar kind of transport barrier appears in the shearless region, one that is associated with a proper route of transition to chaos. These barriers have been identified in symplectic nontwist maps that model such zonal flows. We use the so-called standard nontwist map, a paradigmatic example of nontwist systems, to analyze the parameter dependence of the transport through a broken shearless barrier. On varying a proper control parameter, we identify the onset of structures with high stickiness that give rise to an effective barrier near the broken shearless curve. Moreover, we show how these stickiness structures, and the concomitant transport reduction in the shearless region, are determined by a homoclinic tangle of the remaining dominant twin island chains. We use the finite-time rotation number, a recently proposed diagnostic, to identify transport barriers that separate different regions of stickiness. The identified barriers are comparable to those obtained by using finite-time Lyapunov exponents.FAPESPCNPqCAPESMCT/CNEN (Rede Nacional de Fusao)Fundacao AraucariaUS Department of Energy DE-FG05-80ET-53088Physic

Optimal Cosmic-Ray Detection for Nondestructive Read Ramps

Cosmic rays are a known problem in astronomy, causing both loss of data and data inaccuracy. The problem becomes even more extreme when considering data from a high-radiation environment, such as in orbit around Earth or outside the Earth's magnetic field altogether, unprotected, as will be the case for the James Webb Space Telescope (JWST). For JWST, all the instruments employ nondestructive readout schemes. The most common of these will be "up the ramp" sampling, where the detector is read out regularly during the ramp. We study three methods to correct for cosmic rays in these ramps: a two-point difference method, a deviation from the fit method, and a y-intercept method. We apply these methods to simulated nondestructive read ramps with single-sample groups and varying combinations of flux, number of samples, number of cosmic rays, cosmic-ray location in the exposure, and cosmic-ray strength. We show that the y-intercept method is the optimal detection method in the read-noise-dominated regime, while both the y-intercept method and the two-point difference method are best in the photon-noise-dominated regime, with the latter requiring fewer computations.Comment: To be published in PASP. This paper is 12 pages long and includes 15 figure

On the quantumness of correlations in nuclear magnetic resonance

Nuclear Magnetic Resonance (NMR) was successfully employed to test several protocols and ideas in Quantum Information Science. In most of these implementations the existence of entanglement was ruled out. This fact introduced concerns and questions about the quantum nature of such bench tests. In this article we address some issues related to the non-classical aspects of NMR systems. We discuss some experiments where the quantum aspects of this system are supported by quantum correlations of separable states. Such quantumness, beyond the entanglement-separability paradigm, is revealed via a departure between the quantum and the classical versions of information theory. In this scenario, the concept of quantum discord seems to play an important role. We also present an experimental implementation of an analogous of the single-photon Mach-Zehnder interferometer employing two nuclear spins to encode the interferometric paths. This experiment illustrate how non-classical correlations of separable states may be used to simulate quantum dynamics. The results obtained are completely equivalent to the optical scenario, where entanglement (between two field modes) may be present

Statics and dynamics of an Ashkin-Teller neural network with low loading

An Ashkin-Teller neural network, allowing for two types of neurons is considered in the case of low loading as a function of the strength of the respective couplings between these neurons. The storage and retrieval of embedded patterns built from the two types of neurons, with different degrees of (in)dependence is studied. In particular, thermodynamic properties including the existence and stability of Mattis states are discussed. Furthermore, the dynamic behaviour is examined by deriving flow equations for the macroscopic overlap. It is found that for linked patterns the model shows better retrieval properties than a corresponding Hopfield model.Comment: 20 pages, 6 figures, Latex with postscript figures in one tar.gz fil

The complex channel networks of bone structure

Bone structure in mammals involves a complex network of channels (Havers and Volkmann channels) required to nourish the bone marrow cells. This work describes how three-dimensional reconstructions of such systems can be obtained and represented in terms of complex networks. Three important findings are reported: (i) the fact that the channel branching density resembles a power law implies the existence of distribution hubs; (ii) the conditional node degree density indicates a clear tendency of connection between nodes with degrees 2 and 4; and (iii) the application of the recently introduced concept of hierarchical clustering coefficient allows the identification of typical scales of channel redistribution. A series of important biological insights is drawn and discussedComment: 3 pages, 1 figure, The following article has been submitted to Applied Physics Letters. If it is published, it will be found online at http://apl.aip.org

Breaking Cosmological Degeneracies in Galaxy Cluster Surveys with a Physical Model of Cluster Structure

Forthcoming large galaxy cluster surveys will yield tight constraints on cosmological models. It has been shown that in an idealized survey, containing > 10,000 clusters, statistical errors on dark energy and other cosmological parameters will be at the percent level. It has also been shown that through "self-calibration", parameters describing the mass-observable relation and cosmology can be simultaneously determined, though at a loss in accuracy by about an order of magnitude. Here we examine the utility of an alternative approach of self-calibration, in which a parametrized ab-initio physical model is used to compute cluster structure and the resulting mass-observable relations. As an example, we use a modified-entropy ("pre-heating") model of the intracluster medium, with the history and magnitude of entropy injection as unknown input parameters. Using a Fisher matrix approach, we evaluate the expected simultaneous statistical errors on cosmological and cluster model parameters. We study two types of surveys, in which a comparable number of clusters are identified either through their X-ray emission or through their integrated Sunyaev-Zel'dovich (SZ) effect. We find that compared to a phenomenological parametrization of the mass-observable relation, using our physical model yields significantly tighter constraints in both surveys, and offers substantially improved synergy when the two surveys are combined. These results suggest that parametrized physical models of cluster structure will be useful when extracting cosmological constraints from SZ and X-ray cluster surveys. (abridged)Comment: 22 pages, 8 figures, accepted to Ap

Thermodynamic properties of extremely diluted symmetric Q-Ising neural networks

Using the replica-symmetric mean-field theory approach the thermodynamic and retrieval properties of extremely diluted {\it symmetric} $Q$-Ising neural networks are studied. In particular, capacity-gain parameter and capacity-temperature phase diagrams are derived for $Q=3, 4$ and $Q=\infty$. The zero-temperature results are compared with those obtained from a study of the dynamics of the model. Furthermore, the de Almeida-Thouless line is determined. Where appropriate, the difference with other $Q$-Ising architectures is outlined.Comment: 16 pages Latex including 6 eps-figures. Corrections, also in most of the figures have been mad