4,668 research outputs found
The possible members of the meson nonet
The strong decays of the states are evaluated in the
model with two types of space wave functions. Comparing the model
expectations with the experimental data for the , ,
, and , we suggest that the , , and
can be assigned as the members of the meson nonet, while the
assignment for the is not favored by its width. The
kaon is predicted to have a mass of about 2418 MeV and a width of about 163 MeV
or 225 MeV.Comment: 10 pages, 5 figures, version accepted by Eur. Phys. J.
Electromagnetic radiation of baryons containing two heavy quarks
The two heavy quarks in a baryon which contains two heavy quarks and a light
one, can constitute a scalar or axial vector diquark. We study electromagnetic
radiations of such baryons, (i) \Xi_{(bc)_1} -> \Xi_{(bc)_0}+\gamma, (ii)
\Xi_{(bc)_1}^* -> \Xi_{(bc)_0}+\gamma, (iii) \Xi_{(bc)_0}^{**}(1/2, l=1) ->
\Xi_{(bc)_0}+\gamma, (iv) \Xi_{(bc)_0}^{**}(3/2, l=1) -> \Xi_{(bc)_0}+\gamma
and (v) \Xi_{(bc)_0}^{**}(3/2, l=2) -> \Xi_{(bc)_0}+\gamma, where
\Xi_{(bc)_{0(1)}}, \Xi^*_{(bc)_1} are S-wave bound states of a heavy scalar or
axial vector diquark and a light quark, and \Xi_{(bc)_0}^{**}(l is bigger than
1) are P- or D-wave bound states of a heavy scalar diquark and a light quark.
Analysis indicates that these processes can be attributed into two categories
and the physical mechanisms which are responsible for them are completely
distinct. Measurements can provide a good judgment for the diquark structure
and better understanding of the physical picture.Comment: 15 pages, Late
UAV object tracking by correlation filter with adaptive appearance model
With the increasing availability of low-cost, commercially available unmanned aerial vehicles (UAVs), visual tracking using UAVs has become more and more important due to its many new applications, including automatic navigation, obstacle avoidance, traffic monitoring, search and rescue, etc. However, real-world aerial tracking poses many challenges due to platform motion and image instability, such as aspect ratio change, viewpoint change, fast motion, scale variation and so on. In this paper, an efficient object tracking method for UAV videos is proposed to tackle these challenges. We construct the fused features to capture the gradient information and color characteristics simultaneously. Furthermore, cellular automata is introduced to update the appearance template of target accurately and sparsely. In particular, a high confidence model updating strategy is developed according to the stability function. Systematic comparative evaluations performed on the popular UAV123 dataset show the efficiency of the proposed approach
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