The onset of synchronization in networks of networks is investigated. Specifically, we consider networks of interacting phase oscillators in which the set of oscillators is composed of several distinct populations. Th...
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The onset of synchronization in networks of networks is investigated. Specifically, we consider networks of interacting phase oscillators in which the set of oscillators is composed of several distinct populations. The oscillators in a given population are heterogeneous in that their natural frequencies are drawn from a given distribution, and each population has its own such distribution. The coupling among the oscillators is global, however, we permit the coupling strengths between the members of different populations to be separately specified. We determine the critical condition for the onset of coherent collective behavior, and develop the illustrative case in which the oscillator frequencies are drawn from a set of (possibly different) Cauchy-Lorentz distributions. One motivation is drawn from neurobiology, in which the collective dynamics of several interacting populations of oscillators (such as excitatory and inhibitory neurons and glia) are of interest.
Coherent G-mode vibrations of single-walled carbon nanotubes are observed in the spectrum-resolved pump-probe measurements. The G-mode oscillation is relatively strong in the edge side of the laser spectrum while bein...
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We study level crossing in the optical whispering-gallery (WG) modes by using toroidal microcavities. Experimentally, we image the stationary envelope patterns of the composite optical modes that arise when WG modes o...
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We study level crossing in the optical whispering-gallery (WG) modes by using toroidal microcavities. Experimentally, we image the stationary envelope patterns of the composite optical modes that arise when WG modes of different wavelengths coincide in frequency. Numerically, we calculate crossings of levels that correspond with the observed degenerate modes, where our method takes into account the not perfectly transverse nature of their field polarizations. In addition, we analyze anticrossing with a large avoidance gap between modes of the same azimuthal number.
While data could be discrete and continuous (defined as ordinal numerical features), some classifiers, like Naive Bayes (NB), work only with or may perform better with the discrete data. We focus on NB due to its popu...
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While data could be discrete and continuous (defined as ordinal numerical features), some classifiers, like Naive Bayes (NB), work only with or may perform better with the discrete data. We focus on NB due to its popularity and linear training time. We investigate the impact of eight discretization algorithms (Equal Width, Equal Frequency, Maximum Entropy, IEM, CADD, CAIM, MODL, and CACC) on the classification with NB and two modern semi-NB classifiers, LBR and *** comprehensive empirical study indicates that unsupervised discretization algorithms are the fastest while among the supervised algorithms the fastest is maximum entropy, followed by CAIM and IEM. The CAIM and MODL discretizers generate the lowest and the highest number of discrete values, *** compare the time to build the classification model and classification accuracy when using raw and discretized data. We show that discretization helps to improve the classification with the NB when compared with flexible NB which models continuous features using Gaussian kernels. The AODE classifier obtains on average the best accuracy, while the best performing setup includes discretization with IEM and classification with AODE. The runner-up setups include CAIM and CACC coupled with AODE and CAIM and IEM coupled with LBR. IEM and CAIM are shown to provide statistically significant improvements across all considered datasets for LBR and AODE classifiers when compared with using NB on the continuous data. We also show that the improved accuracy comes at the trade-off of substantially increased runtime.
We report an experimental study of femtosecond optically excited emission of terahertz frequency electromagnetic radiation from GaxIn1−xAs bulk crystals with alloy composition in the range between 0<x<0.65. The ...
We report an experimental study of femtosecond optically excited emission of terahertz frequency electromagnetic radiation from GaxIn1−xAs bulk crystals with alloy composition in the range between 0
Quantum cascade lasers are semiconductor devices based on the interplay of perpendicular transport through the heterostructure and the intracavity lasing field. We employ femtosecond time-resolved pump-probe measureme...
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Quantum cascade lasers are semiconductor devices based on the interplay of perpendicular transport through the heterostructure and the intracavity lasing field. We employ femtosecond time-resolved pump-probe measurements to investigate the nature of the transport through the laser structure via the dynamics of the gain. The gain recovery is determined by the time-dependent transport of electrons through both the active regions and the superlattice regions connecting them. As the laser approaches and exceeds threshold, the component of the gain recovery due to the nonzero lifetime of the upper lasing state in the active region shows a dramatic reduction due to the onset of quantum stimulated emission; the drift of the electrons is thus driven by the cavity photon density. The gain recovery is qualitatively different from that in conventional lasers due to the superlattice transport in the cascade.
We experimentally observe the nonlinear dynamics of an optoelectronic time-delayed feedback loop designed for chaotic communication using commercial fiber optic links, and we simulate the system using delay differenti...
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We experimentally observe the nonlinear dynamics of an optoelectronic time-delayed feedback loop designed for chaotic communication using commercial fiber optic links, and we simulate the system using delay differential equations. We show that synchronization of a numerical model to experimental measurements provides a new way to assimilate data and forecast the future of this time-delayed high-dimensional system. For this system, which has a feedback time delay of 22 ns, we show that one can predict the time series for up to several delay periods, when the dynamics is about 15 dimensional.
We report the observation of coherent phonon oscillations of RBMS excited by the E 11 transition in isolated SWNTs. We observe stronger intensity for the (n-m)mod3 = +1 family than for the (n-m)mod3 = -1 family.
ISBN:
(纸本)9781557528599
We report the observation of coherent phonon oscillations of RBMS excited by the E 11 transition in isolated SWNTs. We observe stronger intensity for the (n-m)mod3 = +1 family than for the (n-m)mod3 = -1 family.
The mixture of trajectory models (MTM) decoder has been used to reconstruct arm trajectories from neural activity. While it produces reasonable results, the computational demands of previously published versions may b...
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The mixture of trajectory models (MTM) decoder has been used to reconstruct arm trajectories from neural activity. While it produces reasonable results, the computational demands of previously published versions may be too high for many real-time systems. We have developed a novel method of approximating the MTM state posteriors that does not require the use of Newtonpsilas method. We show that this method results in only a small decrease in decoding performance yet reduces computational cost by 56.4%. Additionally, an MTM algorithm using this method of approximating the state posteriors produces more accurate decoded trajectories when using small bin sizes than an MTM algorithm using a Gaussian observation model. The more efficient formulation of the MTM algorithm presented here provides an alternative approximation of this algorithm for use on resource constrained embedded systems.
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