Development of a Liquid Scintillator and of Data ... - Borexino - Infn

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5 Particle Identification with a Neural Network 5.3 Results 5.3.1 Simulated Data In a Monte Carlo simulation, 20 000 alpha and beta events were generated all over the Inner Vessel, with random energies from 0 to 3 MeV. Fig. 5.6 shows a typical simulated alpha and a beta pulse for the CTF2 geometry. The time spectrum recorded was binned in such a way to reproduce the flash ADC output (2.5 ns sampling time, 8 bit depth). The input values for the NN were: - 100 bins of the normalized flash ADC spectrum (250 ns); - the radial distance from the center (reconstructed position), normalized to the Inner Vessel radius; - the energy of the event, in MeV. The NN had 102 neurons in the input layer, 102 neurons in the hidden layer, and 1 neuron in the output layer, giving ¢ weights Û. The output parameter of the net is called nn¬ and can take values between 0 and 1. Ideally it should be 1 for beta events and 0 for alpha events. If nn¬ is between 0 and 0.5, the event is classified as alpha event; if nn¬ is larger than 0.5, the event is classified as beta event. The training set consisted of 8000 events. After each 10 events the weights were updated using the backpropagation algorithm. The validation set consisted of 8000 events (different from the training set). The results of the NN after 5000 generations are shown in in fig. 5.7 for events with energies greater than 0.2 MeV. From 3629 beta events only 46 were misidentified as alpha events. From 3607 alpha events 42 were misidentified as beta events. This means, that for 98.7 % beta identification efficiency, 98.8 % of the alpha events are rejected. For a comparison I also calculated the tail-total-ratio from the flash ADC spectrum with the tail starting after 47.5 ns (see fig. 5.8). For the same beta identification efficiency (98.7 %) with this method, I also got the same alpha rejection efficiency (98.8 %). The neural network has the same discrimination capability as the standard tail-to-total ratio, but it cannot beat this simpler and more straightforward technique. 68
Figure 5.6: A simulated alpha and beta pulse in the CTF2. 5.3 Results 69
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Fakultät für Physik der Technisch
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Abstract The first chapter contains
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Übersicht an Radionukliden in BORE
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Contents 3 The Counting Test Facili
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Contents viii
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1 Solar Neutrinos Figure 1.1: The p
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1 Solar Neutrinos 1.2 Detection of
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1 Solar Neutrinos With this detecti
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1 Solar Neutrinos 1.2.3 Future Expe
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1 Solar Neutrinos 1.3.2 Astrophysic
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1 Solar Neutrinos Using the unitari
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1 Solar Neutrinos km in the earth.
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1 Solar Neutrinos 16 Solution ¡Ñ
Page 28 and 29: 2 The Borexino Experiment The relat
Page 30 and 31: 2 The Borexino Experiment Figure 2.
Page 32 and 33: 2 The Borexino Experiment 2.2 The D
Page 34 and 35: 2 The Borexino Experiment 2.3 Detec
Page 36 and 37: 2 The Borexino Experiment 2.3.2 Anc
Page 38 and 39: 2 The Borexino Experiment which per
Page 40 and 41: 2 The Borexino Experiment 2.4 Backg
Page 42 and 43: 2 The Borexino Experiment ns; Rn-
Page 44 and 45: 2 The Borexino Experiment volume wo
Page 46 and 47: 3 The Counting Test Facility (CTF)
Page 56 and 57: 4 Position Reconstruction of Scinti
Page 72 and 73: 5 Particle Identification with a Ne
Page 86 and 87: 6 Test of a PXE based scintillator
Page 108 and 109: 7 The Source Runs in CTF2 transpare
Page 110 and 111: 7 The Source Runs in CTF2 7.3 The S
Page 112 and 113: 7 The Source Runs in CTF2 102 of th
Page 114 and 115: 7 The Source Runs in CTF2 7.4 Analy
Page 116 and 117: 7 The Source Runs in CTF2 7.4.2 Rec
Page 118 and 119: 7 The Source Runs in CTF2 7.4.3 Ene
Page 120 and 121: 7 The Source Runs in CTF2 45 40 35
Page 122 and 123: 7 The Source Runs in CTF2 112 reemi
Page 124 and 125: Summary and Outlook possible to dis
Page 126 and 127: Bibliography [Ade98] E. G. Adelberg
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Bibliography [Bra00] L. De Braeckel
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Bibliography [Lom97] P. Lombardi, D
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Bibliography [Vog96] R. B. Vogelaar
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Danksagung An dieser Stelle möchte
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Development of a Liquid Scintillator and of Data ... - Borexino - Infn

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