1,461 research outputs found
Nonequilibrium Quantum Phase Transitions in the Dicke Model
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
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, and , respectively. In
the 2nd lowest Landau band, a critical conductance is
obtained which indeed supports the notion of universality. However, these
numbers are significantly at variance with the hitherto commonly believed value
. 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
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
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
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
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
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
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
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 . In the strong disorder limit, where , 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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