Improved measurement of the reactor antineutrino flux and spectrum at Daya Bay

  • A new measurement of the reactor antineutrino flux and energy spectrum by the Daya Bay reactor neutrino experiment is reported. The antineutrinos were generated by six 2.9 GWth nuclear reactors and detected by eight antineutrino detectors deployed in two near (560 m and 600 m flux-weighted baselines) and one far (1640 m flux-weighted baseline) underground experimental halls. With 621 days of data, more than 1.2 million inverse beta decay (IBD) candidates were detected. The IBD yield in the eight detectors was measured, and the ratio of measured to predicted flux was found to be 0:946±0:020 (0:992±0:021) for the Huber+Mueller (ILL+Vogel) model. A 2.9σ deviation was found in the measured IBD positron energy spectrum compared to the predictions. In particular, an excess of events in the region of 4-6 MeV was found in the measured spectrum, with a local signi cance of 4.4σ. A reactor antineutrino spectrum weighted by the IBD cross section is extracted for model-independent predictions.
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F. P. An and et al(Daya Bay Collaboration). Improved measurement of the reactor antineutrino flux and spectrum at Daya Bay[J]. Chinese Physics C, 2017, 41(1): 013002. doi: 10.1088/1674-1137/41/1/013002
F. P. An and et al(Daya Bay Collaboration). Improved measurement of the reactor antineutrino flux and spectrum at Daya Bay[J]. Chinese Physics C, 2017, 41(1): 013002.  doi: 10.1088/1674-1137/41/1/013002 shu
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Received: 2016-07-19
Revised: 2016-09-29
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    Supported in part by the Ministry of Science and Technology of China, the United States Department of Energy, the Chinese Academy of Sciences, the CAS Center for Excellence in Particle Physics, the National Natural Science Foundation of China, the Guangdong provincial government, the Shenzhen municipal government, the China General Nuclear Power Group, the Research Grants Council of the Hong Kong Special Administrative Region of China, the MOST and MOE in Taiwan, the U.S. National Science Foundation, the Ministry of Education, Youth and Sports of the Czech Republic, the Joint Institute of Nuclear Research in Dubna, Russia, the NSFC-RFBR joint research program, the National Commission for Scientific and Technological Research of Chile

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Improved measurement of the reactor antineutrino flux and spectrum at Daya Bay

Fund Project:  Supported in part by the Ministry of Science and Technology of China, the United States Department of Energy, the Chinese Academy of Sciences, the CAS Center for Excellence in Particle Physics, the National Natural Science Foundation of China, the Guangdong provincial government, the Shenzhen municipal government, the China General Nuclear Power Group, the Research Grants Council of the Hong Kong Special Administrative Region of China, the MOST and MOE in Taiwan, the U.S. National Science Foundation, the Ministry of Education, Youth and Sports of the Czech Republic, the Joint Institute of Nuclear Research in Dubna, Russia, the NSFC-RFBR joint research program, the National Commission for Scientific and Technological Research of Chile

Abstract: A new measurement of the reactor antineutrino flux and energy spectrum by the Daya Bay reactor neutrino experiment is reported. The antineutrinos were generated by six 2.9 GWth nuclear reactors and detected by eight antineutrino detectors deployed in two near (560 m and 600 m flux-weighted baselines) and one far (1640 m flux-weighted baseline) underground experimental halls. With 621 days of data, more than 1.2 million inverse beta decay (IBD) candidates were detected. The IBD yield in the eight detectors was measured, and the ratio of measured to predicted flux was found to be 0:946±0:020 (0:992±0:021) for the Huber+Mueller (ILL+Vogel) model. A 2.9σ deviation was found in the measured IBD positron energy spectrum compared to the predictions. In particular, an excess of events in the region of 4-6 MeV was found in the measured spectrum, with a local signi cance of 4.4σ. A reactor antineutrino spectrum weighted by the IBD cross section is extracted for model-independent predictions.

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