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A triple-band miniaturized end-fire antenna based on odd-mode spoof surface plasmonic polariton waveguide resonator
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作者 BAI Yukun MAO Mengqun 《Optoelectronics Letters》 2025年第8期462-467,共6页
A triple-band miniaturized end-fire antenna based on the odd modes of spoof surface plasmonic polariton(SSPP)waveguide resonator is proposed in this paper.To meet the ever increasing demand for more communication chan... A triple-band miniaturized end-fire antenna based on the odd modes of spoof surface plasmonic polariton(SSPP)waveguide resonator is proposed in this paper.To meet the ever increasing demand for more communication channels and less antenna sizes,multi-band antennas are currently under intensive investigation.By a novel feeding method,three odd modes are excited on an SSPP waveguide resonator,which performs as an end-fire antenna operating at three bands,7.15-7.26 GHz,11.6-12.2 GHz and 13.5-13.64 GHz.It exhibits reasonably high and stable maximum gains of 5.26 dBi,7.97 dBi and 10.1 dBi and maximum efficiencies of 64%,92%and 98%at the three bands,respectively.Moreover,in the second band,the main beam angle shows a frequency dependence with a total scanning angle of 19°.The miniaturized triple-band antenna has a great potential in wireless communication systems,satellite communication and radar systems. 展开更多
关键词 odd modes waveguide resonatorwhich triple band antenna end fire antenna feeding methodthree spoof surface plasmonic polariton sspp waveguide communication channels miniaturized antenna
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Photonics and microwaves merge to improve computing flexibility
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作者 Hongwei Wang Guangwei Hu 《Light: Science & Applications》 2025年第10期2863-2864,共2页
In artificial neural networks,data structures usually exist in the form of vectors,matrices,or higher-dimensional tensors.However,traditional electronic computing architectures are limited by the bottleneck of separat... In artificial neural networks,data structures usually exist in the form of vectors,matrices,or higher-dimensional tensors.However,traditional electronic computing architectures are limited by the bottleneck of separation of storage and computing,making it difficult to efficiently handle large-scale tensor operations.The research team has developed a photonic tensor processing unit based on a single microring resonator,which performs tensor convolution operations in multiple dimensions of time,wavelength,and microwave frequency by precisely adjusting the operating state of multi-wavelength lasers.This innovative design increases the photonic computing density to 34.04 TOPS/mm²,significantly surpassing the performance level of existing photonic computing chips. 展开更多
关键词 photonic tensor processing unit electronic computing architectures artificial neural networks microring resonatorwhich microwaves tensor convolution operations PHOTONICS artificial neural networksdata structures
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