9,695 research outputs found
Critical exponents of Nikolaevskii turbulence
We study the spatial power spectra of Nikolaevskii turbulence in
one-dimensional space. First, we show that the energy distribution in
wavenumber space is extensive in nature. Then, we demonstrate that, when
varying a particular parameter, the spectrum becomes qualitatively
indistinguishable from that of Kuramoto-Sivashinsky turbulence. Next, we derive
the critical exponents of turbulent fluctuations. Finally, we argue that in
some previous studies, parameter values for which this type of turbulence does
not appear were mistakenly considered, and we resolve inconsistencies obtained
in previous studies.Comment: 9 pages, 6 figure
Engineering Entanglement: The Fast-Approach Phase Gate
Optimal-control techniques and a fast-approach scheme are used to implement a
collisional control phase gate in a model of cold atoms in an optical lattice,
significantly reducing the gate time as compared to adiabatic evolution while
maintaining high fidelity. New objective functionals are given for which
optimal paths are obtained for evolution that yields a control-phase gate up to
single-atom Rabi shifts. Furthermore, the fast-approach procedure is used to
design a path to significantly increase the fidelity of non-adiabatic transport
in a recent experiment. Also, the entanglement power of phase gates is
quantified.Comment: 7 pages, 4 figures. Phys. Rev. A (in press
Swarm-Oscillators
Nonlinear coupling between inter- and intra-element dynamics appears as a
collective behaviour of elements. The elements in this paper denote symptoms
such as a bacterium having an internal network of genes and proteins, a
reactive droplet, a neuron in networks, etc. In order to elucidate the
capability of such systems, a simple and reasonable model is derived. This
model exhibits the rich patterns of systems such as cell membrane, cell fusion,
cell growing, cell division, firework, branch, and clustered clusters
(self-organized hierarchical structure, modular network). This model is
extremely simple yet powerful; therefore, it is expected to impact several
disciplines.Comment: 9 pages, 4 figure
Results Visualization in the XBrain XML Interface to a Relational Database
The University of Washington's XBrain application is used to dynamically export relational data over the web in XML format, as a prelude to data exchange. We describe additional tools to aid the human user in visualizing the dynamically generated XML results returned by the web application
Establishing the Relative Merits of Interior and Spoke-Type Permanent-Magnet Machines With Ferrite or NdFeB Through Systematic Design Optimization
In this paper, a multiobjective design optimization method combining design-of-experiments techniques and differential-evolution algorithms is presented. The method was implemented and utilized in order to provide practical engineering insights for the optimal design of interior and spoke-type permanent-magnet machines. Two combinations with 12 slots and 8 poles and 12 slots and 10 poles, respectively, have been studied in conjunction with rare-earth neodymium-iron-boron (NdFeB) and ferrites. As part of the optimization process, a computationally efficient finite-element electromagnetic analysis was employed for estimating the performance of thousands of candidate designs. Three optimization objectives were concurrently considered for minimum total material cost, power losses, and torque ripple, respectively. Independent variables were considered for both the stator and rotor geometries. A discussion based on a systematic comparison is included, showing, among other things and despite common misconception, that comparable cost versus loss Paretos can be achieved with any of the rotor topologies studied
Sentiment Recognition in Egocentric Photostreams
Lifelogging is a process of collecting rich source of information about daily
life of people. In this paper, we introduce the problem of sentiment analysis
in egocentric events focusing on the moments that compose the images recalling
positive, neutral or negative feelings to the observer. We propose a method for
the classification of the sentiments in egocentric pictures based on global and
semantic image features extracted by Convolutional Neural Networks. We carried
out experiments on an egocentric dataset, which we organized in 3 classes on
the basis of the sentiment that is recalled to the user (positive, negative or
neutral)
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