839 research outputs found
A new decay mode of higher charmonium
We calculate the partial decay width of the
excited vector charmonium states around 4.6 GeV with the quark pair creation
model. We find that the partial decay width of the
mode can reach up to several MeV for . In contrast, the
partial decay width of the states
is less than one MeV. If the enhancement reported by the Belle
Collaboration in invariant-mass distribution is the
same structure as , the resonance is most likely to be a
-wave charmonium state.Comment: 8 pages, 4 figure
Bis[2-(2-pyridylsulfanyl)ethyl]ammonium perchlorate
The cation and anion of the title salt, C14H18N3S2
+·ClO4
−, lie on a twofold rotation axis. The cation is a W-shaped entity with the aromatic rings at the ends; the ammonium NH2
+ group is a hydrogen-bond donor to the pyridyl N atoms. The perchlorate ion has one O atom disordered over two sites in a 0.50:0.50 ratio
Image Super-Resolution using Efficient Striped Window Transformer
Transformers have achieved remarkable results in single-image
super-resolution (SR). However, the challenge of balancing model performance
and complexity has hindered their application in lightweight SR (LSR). To
tackle this challenge, we propose an efficient striped window transformer
(ESWT). We revisit the normalization layer in the transformer and design a
concise and efficient transformer structure to build the ESWT. Furthermore, we
introduce a striped window mechanism to model long-term dependencies more
efficiently. To fully exploit the potential of the ESWT, we propose a novel
flexible window training strategy that can improve the performance of the ESWT
without additional cost. Extensive experiments show that ESWT outperforms
state-of-the-art LSR transformers, and achieves a better trade-off between
model performance and complexity. The ESWT requires fewer parameters, incurs
faster inference, smaller FLOPs, and less memory consumption, making it a
promising solution for LSR.Comment: SOTA lightweight super-resolution transformer. 8 pages, 9 figures and
6 tables. The Code is available at
https://github.com/Fried-Rice-Lab/FriedRiceLa
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