171,835 research outputs found
QCD string model for hybrid adiabatic potentials
Hybrid adiabatic potentials are considered in the framework of the QCD string
model. The einbein field formalism is applied to obtain the large-distance
behaviour of adiabatic potentials. The calculated excitation curves are shown
to be the result of interplay between potential-type longitudinal and
string-type transverse vibrations. The results are compared with recent lattice
data.Comment: LATEX2e, 10 pages, 4 PS figures. Plenary talk at HADRON2001,
Protvino. Comment adde
The neural network art which uses the Hamming distance to measure an image similarity score
This study reports a new discrete neural network of Adaptive Resonance Theory (ART-1H) in which the Hamming distance is used for the first time to estimate the measure of binary images (vectors) proximity. For the development of a new neural network of adaptive resonance theory, architectures and operational algorithms of discrete neural networks ART-1 and discrete Hamming neural networks are used. Unlike the discrete neural network adaptive resonance theory ART-1 in which the similarity parameter which takes into account single images components only is used as a measure of images (vectors) proximity in the new network in the Hamming distance all the components of black and white images are taken into account. In contrast to the Hamming network, the new network allows the formation of typical vector classes representatives in the learning process not using information from the teacher which is not always reliable. New neural network can combine the advantages of the Hamming neural network and ART-1 by setting a part of source information in the form of reference images (distinctive feature and advantage of the Hamming neural network) and obtaining some of typical image classes representatives using learning algorithms of the neural network ART-1 (the dignity of the neural network ART-1). The architecture and functional algorithms of the new neural network ART which has the properties of both neural network ART-1 and the Hamming network were proposed and investigated. The network can use three methods to get information about typical image classes representatives: teacher information, neural network learning process, third method uses a combination of first two methods. Property of neural network ART-1 and ART-1H, related to the dependence of network learning outcomes or classification of input information to the order of the vectors (images) can be considered not as a disadvantage of the networks but as a virtue. This property allows to receive various types of input information classification which cannot be obtained using other neural networks
Vibrating the QCD string
The large distance behaviour of the adiabatic hybrid potentials is studied in
the framework of the QCD string model. The calculated spectra are shown to be
the result of interplay between potential-type longitudinal and string-type
transverse vibrations.Comment: LaTeX2e, 9 pages, 2 Postscript figures, final version to appear in
Yad.Fi
A short distance quark-antiquark potential
Leading terms of the static quark-antiquark potential in the background
perturbation theory are reviewed, including perturbative, nonperturbative and
interference ones. The potential is shown to describe lattice data at short
quark-antiquark separations with a good accuracy.Comment: 4 pages, 2 figures, talk at the NPD-2002 Conference, December 2-6,
ITEP, Moscow, references update
Influence of Cooper pairing on the inelastic processes in a gas of Fermi atoms
Correlation properties in ultracold Fermi gas with negative scattering length
and its impact on the three-body recombination is analyzed. We find that Cooper
pairing enhances the recombination rate in contrast to the decrease of this
rate accompanying Bose-Einstein condensation in a Bose gas. This trend is
characteristic for all interval of temperatures T<Tc
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