1 水质契仑科夫探测器中的中子识别张海兵清华大学 2008.4.28, 南京 First Study of Neutron Tagging with a Water Cherenkov Detector.

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Presentation transcript:

1 水质契仑科夫探测器中的中子识别张海兵清华大学 , 南京 First Study of Neutron Tagging with a Water Cherenkov Detector

2 Neutrino Detection at Super-Kamiokande e Electron (e)  Muon (  ) The products are charged particles. The neutrino is observed by “seeing” the product of its interaction with water. Charged particles with β>1/n emits Cherenkov light

3 -All 6 types of neutrino emitted when supernovae explode but only is most likely to observe. - Detection of is the key step to see SRN at SK. Neutrinos from Space Confirmed neutrinos from space Who’s next? Supernova relic neutrino (SRN)? a) Solar neutrino b) SN 1987A

4 Previous Searches for SRN SK-I limit : <1.25 /cm 2 /s SK SRN Limits vs. Theoretical Predictions The result can be significantly improved if SK enhanced with neutron tagging capability.

5 Why Neutron Tagging? Neutron tagging plays a role in identifying inverse beta decay. A delayed coincidence technique can be used to identify reaction chain.

6 Methods of Tagging Neutron from Inverse βDecay

7 Forced Trigger (FOG) Generate 500 additional “forced triggers” at the interval of 1us after primary trigger by e +. Search 2.2MeV candidates in the 500 us data pack. Threshold

8 Test with a Simulated Signal 5 cm Am/Be Am/Be neutron source embedded in BGO crystal

9 Experimental Setup n 5 cm Am/Be (1)Forced trigger case (2)Gadolinium case

10 Signal and Background in Forced Trigger Data Source run (Am/Be+BGO) BG run (BGO only) – for neutron tagging efficiency study – Signal FOG: 500 BG events + one 2.2 MeV  – for cross checking and background estimation – BG FOG: 500 BG events # of PMT hits time The main difficulty rests with how to extract the weak 2.2 MeV  signal from heavy background, e.g. PMT noise and other low energy events.

11 Data Pre-process 2.2MeV  Because of time-of-flight difference to individual PMT, the PMT timings of 2.2MeV  can not form a peak against BG. Thermal neutron free mean path ~50cm, even smaller than vertex resolution at SK. So the first step is to use e + vertex to do time-of-flight correction to restore timing information. # of hits PMT time Averaged BG n  ~200  s Thermal neutron free mean path ~50cm

12 Distinctive Variables Several distinctive variables introduced, e.g. anisotropy, N10, etc. Anisotropy: average open angle of hits N10: PMT hits in 10ns window Green: signal; Red: background Neural Net method adopted to optimize results.

13 Neural Net Method Event with NN>0.99 is identified as 2.2MeV gamma signal. Signal Efficiency vs. BG probability

14 Measurement of Neutron Capture Time Expected exponential distribution clearly observed in source run (right). Y x A B C

15 Neutron Lifetime & Tagging Efficiency Efficiency from data is in agreement with M.C. *

16 Summary Neutron tagging in large water Cherenkov detector studied for the first time. Two methods tested at SK: Add 0.2% Gd in water: High efficiency but complicated, application delayed for at least 5 years. Tag 2.2MeV γwith forced trigger: Low efficiency(~20%) but simple, approved for SRN detection at SK now.