Title of article :
Near threshold pulse shape discrimination techniques in scintillating CsI(Tl) crystals
Author/Authors :
Wu، نويسنده , , S.C and Yue، نويسنده , , Q and Lai، نويسنده , , W.P. and Li، نويسنده , , H.B. and Li، نويسنده , , J and Lin، نويسنده , , S.T. and Liu، نويسنده , , Y and Singh، نويسنده , , V and Wang، نويسنده , , M.Z and Wong، نويسنده , , H.T and Xin، نويسنده , , B and Zhou، نويسنده , , Z.Y، نويسنده ,
Pages :
10
From page :
116
To page :
125
Abstract :
There are recent interests with CsI(Tl) scintillating crystals for Dark Matter experiments. The key merit is the capability to differentiate nuclear recoil (nr) signatures from the background β/γ-events due to ambient radioactivity on the basis of their different pulse shapes. One of the major experimental challenges is to perform such pulse shape analysis in the statistics-limited domain where the light output is close to the detection threshold. Using data derived from measurements with low-energy γʹs and nuclear recoils due to neutron elastic scatterings, it was verified that the pulse shapes between β/γ-events are different. Several methods of pulse shape discrimination (PSD) are studied, and their relative merits are compared. Full digitization of the pulse shapes is crucial to achieve good discrimination. Advanced software techniques with mean time, neural network and likelihood ratios give rise to satisfactory performance, and are superior to the conventional Double Charge method commonly applied at higher energies. PSD becomes effective starting at a light yield of about 20 photo-electrons. This corresponds to a detection threshold of about 5 keV electron-equivalence energy, or 40–50 keV recoil kinetic energy, in realistic experiments.
Keywords :
Data analysis , Scintillation detectors , NEURAL NETWORKS
Journal title :
Astroparticle Physics
Record number :
2023336
Link To Document :
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