1,260 research outputs found
Quasi-two-body decays in the perturbative QCD approach
We study the quasi-two-body decays by employing
the perturbative QCD approach. The two-meson distribution amplitudes
\Phi_{K\pi}^{\text{P-wave}} are adopted to describe the final state
interactions of the kaon-pion pair in the resonance region. The resonance line
shape for the -wave component in the time-like form factor
is parameterized by the relativistic Breit-Wigner function. For
most considered decay modes, the theoretical predictions for their branching
ratios are consistent with currently available experimental measurements within
errors. We also disscuss some ratios of the branching fractions of the
concerned decay processes. More precise data from LHCb and Belle-II are
expected to test our predictions.Comment: 10 pages, 3 figures and 2 tables.To be published in EPJ
Production of proton-rich nuclei around Z=84-90 in fusion-evaporation reactions
Within the framework of the dinuclear system model, production cross sections
of proton-rich nuclei with charged numbers of Z=84-90 are investigated
systematically. Possible combinations with the Si, S, Ar
bombarding the target nuclides Ho, Tm, Yb,
Lu, Hf and Ta are analyzed thoroughly. The
optimal excitation energies and evaporation channels are proposed to produce
the proton-rich nuclei. The systems are feasible to be constructed in
experiments. It is found that the neutron shell closure of N=126 is of
importance during the evaporation of neutrons. The experimental excitation
functions in the Ar induced reactions can be nicely reproduced. The
charged particle evaporation is comparable with neutrons in cooling the excited
proton-rich nuclei, in particular for the channels with and proton
evaporation. The production cross section increases with the mass asymmetry of
colliding systems because of the decrease of the inner fusion barrier. The
channels with pure neutron evaporation depend on the isotopic targets. But it
is different for the channels with charged particles and more sensitive to the
odd-even effect.Comment: 15 pages, 10 figures. arXiv admin note: text overlap with
arXiv:0803.1117, arXiv:0707.258
Multi-wavelet residual dense convolutional neural network for image denoising
Networks with large receptive field (RF) have shown advanced fitting ability
in recent years. In this work, we utilize the short-term residual learning
method to improve the performance and robustness of networks for image
denoising tasks. Here, we choose a multi-wavelet convolutional neural network
(MWCNN), one of the state-of-art networks with large RF, as the backbone, and
insert residual dense blocks (RDBs) in its each layer. We call this scheme
multi-wavelet residual dense convolutional neural network (MWRDCNN). Compared
with other RDB-based networks, it can extract more features of the object from
adjacent layers, preserve the large RF, and boost the computing efficiency.
Meanwhile, this approach also provides a possibility of absorbing advantages of
multiple architectures in a single network without conflicts. The performance
of the proposed method has been demonstrated in extensive experiments with a
comparison with existing techniques.Comment: 9 pages, 9 figure
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