1,461 research outputs found

    Nonequilibrium Quantum Phase Transitions in the Dicke Model

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    We establish a set of nonequilibrium quantum phase transitions in the Dicke model by considering a monochromatic nonadiabatic modulation of the atom-field coupling. For weak driving the system exhibits a set of sidebands which allow the circumvention of the no-go theorem which otherwise forbids the occurence of superradiant phase transitions. At strong driving we show that the system exhibits a rich multistable structure and exhibits both first- and second-order nonequilibrium quantum phase transitions.Comment: 4 pages, 3 Figures, and supplementary material. This new version contains corrected typos, new references and new versions of the figures. Published by Physical Review Letter

    Universal Conductance and Conductivity at Critical Points in Integer Quantum Hall Systems

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    The sample averaged longitudinal two-terminal conductance and the respective Kubo-conductivity are calculated at quantum critical points in the integer quantum Hall regime. In the limit of large system size, both transport quantities are found to be the same within numerical uncertainty in the lowest Landau band, 0.60±0.02e2/h0.60\pm 0.02 e^2/h and 0.58±0.03e2/h0.58\pm 0.03 e^2/h, respectively. In the 2nd lowest Landau band, a critical conductance 0.61±0.03e2/h0.61\pm 0.03 e^2/h is obtained which indeed supports the notion of universality. However, these numbers are significantly at variance with the hitherto commonly believed value 1/2e2/h1/2 e^2/h. We argue that this difference is due to the multifractal structure of critical wavefunctions, a property that should generically show up in the conductance at quantum critical points.Comment: 4 pages, 3 figure

    A Sparse Stress Model

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    Force-directed layout methods constitute the most common approach to draw general graphs. Among them, stress minimization produces layouts of comparatively high quality but also imposes comparatively high computational demands. We propose a speed-up method based on the aggregation of terms in the objective function. It is akin to aggregate repulsion from far-away nodes during spring embedding but transfers the idea from the layout space into a preprocessing phase. An initial experimental study informs a method to select representatives, and subsequent more extensive experiments indicate that our method yields better approximations of minimum-stress layouts in less time than related methods.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

    Spin relaxation in a GaAs quantum dot embedded inside a suspended phonon cavity

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    The phonon-induced spin relaxation in a two-dimensional quantum dot embedded inside a semiconductor slab is investigated theoretically. An enhanced relaxation rate is found due to the phonon van Hove singularities. Oppositely, a vanishing deformation potential may also result in a suppression of the spin relaxation rate. For larger quantum dots, the interplay between the spin orbit interaction and Zeeman levels causes the suppression of the relaxation at several points. Furthermore, a crossover from confined to bulk-like systems is obtained by varying the width of the slab.Comment: 5 pages, 4 figures, to apper in Phys. Rev. B (2006

    Current-Induced Entanglement of Nuclear Spins in Quantum Dots

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    We propose an entanglement mechanism of nuclear spins in quantum dots driven by the electric current accompanied by the spin flip. This situation is relevant to a leakage current in spin-blocked regions where electrons cannot be transported unless their spins are flipped. The current gradually increases the components of larger total spin of nuclei. This correlation among the nuclear spins markedly enhances the spin-flip rate of electrons and hence the leakage current. The enhancement of the current is observable when the residence time of electrons in the quantum dots is shorter than the dephasing time T*_2 of nuclear spins.Comment: 4 pages, 4 figure

    A Regularized Graph Layout Framework for Dynamic Network Visualization

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    Many real-world networks, including social and information networks, are dynamic structures that evolve over time. Such dynamic networks are typically visualized using a sequence of static graph layouts. In addition to providing a visual representation of the network structure at each time step, the sequence should preserve the mental map between layouts of consecutive time steps to allow a human to interpret the temporal evolution of the network. In this paper, we propose a framework for dynamic network visualization in the on-line setting where only present and past graph snapshots are available to create the present layout. The proposed framework creates regularized graph layouts by augmenting the cost function of a static graph layout algorithm with a grouping penalty, which discourages nodes from deviating too far from other nodes belonging to the same group, and a temporal penalty, which discourages large node movements between consecutive time steps. The penalties increase the stability of the layout sequence, thus preserving the mental map. We introduce two dynamic layout algorithms within the proposed framework, namely dynamic multidimensional scaling (DMDS) and dynamic graph Laplacian layout (DGLL). We apply these algorithms on several data sets to illustrate the importance of both grouping and temporal regularization for producing interpretable visualizations of dynamic networks.Comment: To appear in Data Mining and Knowledge Discovery, supporting material (animations and MATLAB toolbox) available at http://tbayes.eecs.umich.edu/xukevin/visualization_dmkd_201

    Transdifferentiation of blood-derived human adult endothelial progenitor cells into functionally active cardiomyocytes

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    Background - Further to promoting angiogenesis, cell therapy may be an approach for cardiac regeneration. Recent studies suggest that progenitor cells can transdifferentiate into other lineages. However, the transdifferentiation potential of endothelial progenitor cells (EPCs) is unknown

    Anisotropic Radial Layout for Visualizing Centrality and Structure in Graphs

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    This paper presents a novel method for layout of undirected graphs, where nodes (vertices) are constrained to lie on a set of nested, simple, closed curves. Such a layout is useful to simultaneously display the structural centrality and vertex distance information for graphs in many domains, including social networks. Closed curves are a more general constraint than the previously proposed circles, and afford our method more flexibility to preserve vertex relationships compared to existing radial layout methods. The proposed approach modifies the multidimensional scaling (MDS) stress to include the estimation of a vertex depth or centrality field as well as a term that penalizes discord between structural centrality of vertices and their alignment with this carefully estimated field. We also propose a visualization strategy for the proposed layout and demonstrate its effectiveness using three social network datasets.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

    Load distribution in weighted complex networks

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    We study the load distribution in weighted networks by measuring the effective number of optimal paths passing through a given vertex. The optimal path, along which the total cost is minimum, crucially depend on the cost distribution function pc(c)p_c(c). In the strong disorder limit, where pc(c)∼c−1p_c(c)\sim c^{-1}, the load distribution follows a power law both in the Erd\H{o}s-R\'enyi (ER) random graphs and in the scale-free (SF) networks, and its characteristics are determined by the structure of the minimum spanning tree. The distribution of loads at vertices with a given vertex degree also follows the SF nature similar to the whole load distribution, implying that the global transport property is not correlated to the local structural information. Finally, we measure the effect of disorder by the correlation coefficient between vertex degree and load, finding that it is larger for ER networks than for SF networks.Comment: 4 pages, 4 figures, final version published in PR
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