4 research outputs found

    基于SDN与NFV融合的UDN移动性管理算法

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    针对超密集网络(UDN)下传统切换流程的信令交互过多造成切换总时延的增加,导致用户体验质量下降的问题,文章提出了基于软件定义网络(SDN)和网络功能虚拟化(NFV)融合的超密集网络移动性管理算法,该算法给出了将SDN与NFV相结合的适应超密集网络的网络架构模型,在此基础上提出了优化的切换信令流程,并建立数学模型,进行性能分析。仿真结果表明,相较于传统算法,该算法可以减少切换总时延

    JUNO Sensitivity on Proton Decay pνˉK+p\to \bar\nu K^+ Searches

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    The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in pνˉK+p\to \bar\nu K^+ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via pνˉK+p\to \bar\nu K^+ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is 9.6×10339.6 \times 10^{33} years, competitive with the current best limits on the proton lifetime in this channel

    JUNO sensitivity on proton decay pνK+p → νK^{+} searches

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    JUNO sensitivity on proton decay p → ν K + searches*

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    The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the pνˉK+ p\to \bar{\nu} K^+ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via pνˉK+ p\to \bar{\nu} K^+ is 36.9% ± 4.9% with a background level of 0.2±0.05(syst)±0.2\pm 0.05({\rm syst})\pm 0.2(stat) 0.2({\rm stat}) events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is 9.6×1033 9.6 \times 10^{33} years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies
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