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The Jiangmen Underground Neutrino Observatory is a multipurpose neutrino experiment designed to determine neutrino mass hierarchy and precisely measure oscillation parameters by detecting reactor neutrinos from the Yangjiang and Taishan Nuclear Power Plants, observe supernova neutrinos, study the atmospheric, solar neutrinos and geo-neutrinos, and perform exotic searches, with a 20-thousand-ton liquid scintillator detector of unprecedented 3% energy resolution (at 1 MeV) at 700-meter deep underground. In this proceeding, the subsystems of the experiment, including the cental detector, the online scintillator internal radioactivity investigation system, the PMT, the veto detector, the calibration system and the taishan antineutrino observatory, will be described. The construction is expected to be completed in 2021.
A cable loop source calibration system is developed for the Jiangmen Underground Neutrino Observatory, a 20 kton spherical liquid scintillator neutrino experiment. This system is capable of deploying radioactive sources into different positions of th
The Jiangmen Underground Neutrino Observatory (JUNO), a 20ktons multi-purpose underground liquid scintillator detector, was proposed with the determination of the neutrino mass hierarchy as a primary physics goal. Due to low background requirement of
The Jiangmen Underground Neutrino Observatory is proposed to determine neutrino mass hierarchy using a 20~ktonne liquid scintillator detector. Strict radio-purity requirements have been put forward for all the components of the detector. According to
The large next generation liquid-scintillator detector LENA (Low Energy Neutrino Astronomy) offers an excellent opportunity for neutrino oscillometry. The characteristic spatial pattern of very low monoenergetic neutrino disappearance from artificial
The assessment of neutrino absolute mass scale is still a crucial challenge in today particle physics and cosmology. Beta or electron capture spectrum end-point study is currently the only experimental method which can provide a model independent mea