Etude et impact du bruit de fond corrÃ©lÃ© pour la mesure de l'angle ...

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134 5. Correlated background evt. IVT 110 3 ¯⌫ e +IV /n 19 IVT bkg. subtracted 89 Table 5.7: Summary of the number of IVT events, background events and the total number of events upon background subtraction. 5.4.4 Fast Neutron shape and rate tel-00821629, version 1 - 11 May 2013 The FN spectral shape S FN (E) is obtained by fitting the background subtracted IVT spectrum shown in Fig. 5.18. Since the IVT spectrum appear to be rather flat, a linear model is fitted. The total untagged FN rate (R FN ) is obtained by Eq. 5.6: R FN = ⇢ t ⇥ 1 Z 12.2 MeV ⇥ ✏ t ⇥ ✏ IV T t live 0.7 MeV S FN(E)dE (5.6) where the IVT rate is corrected for the FN/SM separation e ciency (✏ t ) and purity (⇢ t ) and scaled for the IVT e ciency (✏ IV T ), summarised in Tab. 5.8. ✏ IV T ✏ t ⇢ t t live [d] 0.33 ± 0.05 0.78 ± 0.01 0.97 ± 0.08 240.17 Table 5.8: Scaling factors to obtain the untagged amount of FN events and total detector live time for rate computation. Tab. 5.9 summarise the total statistical uncertainty, the uncertainty coming from the backgrounds subtraction and the systematic uncertainties induced by the scaling factors. The most important contribution to the total uncertainty comes from the backgrounds subtraction, which is limited by the low statistic of the background sample as summarised in Tab. 5.7. While the uncertainty on the ¯⌫ e +IV /n background is expected to improve only with a bigger data sample, the uncertainty on the background is expected to improve by selecting the background with multiple o↵-time window, in order to increase the statics of the sample. Systematic uncertainties are propagated to the IVT spectrum bin by bin. The linear fit to the IVT spectrum and its 1 uncertainty are shown in Fig. 5.19 . Both a flat and a sloped linear model are tested and the results are
5.4 Fast Neutrons analysis 135 tel-00821629, version 1 - 11 May 2013 Figure 5.19: IVT FN spectrum fit with flat model (top) and sloped linear model (bottom). The flat linear model gives 2 /ndf = 9.4/9 and a fit probability of ⇠ 40 %, while the sloped linear model gives 2 /ndf =7.3/8 and a fit probability of ⇠ 50 %. Since the sloped linear model shows a better agreement with the data, it is assumed as FN spectral shape. A total rate of (0.33 ± 0.16) cpd is found.
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UNIVERSITÉ DENANTES FACULTÉ DES S
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tel-00821629, version 1 - 11 May 20
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Abstract tel-00821629, version 1 -
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Acknowledgments Since so many peopl
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Contents 1 Introduction 13 tel-0082
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CONTENTS 11 tel-00821629, version 1
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Chapter 1 Introduction tel-00821629
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15 tel-00821629, version 1 - 11 May
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Chapter 2 Neutrino physics tel-0082
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2.2 Neutrino history in brief 19 ma
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2.3 Neutrino oscillation, the theor
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2.4 Measuring neutrino oscillation
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3-flavour oscillations The dominant
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After the Sun, the other main natur
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2.5 The problem with the neutrino m
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2.6 Summary and open questions 37 s
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In the next future, reactor experim
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Chapter 3 The Double Chooz experime
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3.1 The Double Chooz detector 43 to
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3.1 The Double Chooz detector 45 te
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3.1 The Double Chooz detector 47 it
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3.1 The Double Chooz detector 49 te
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3.2 The detector read-out 51 40 m o
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3.3 The online system 53 IV trigger
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3.3 The online system 55 tions as s
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3.3 The online system 57 tel-008216
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3.4 The calibration system 59 tel-0
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loosing their kinetic energy 3 and
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3.5 Reactor neutrino flux simulatio
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3.8 Data reconstruction 69 A dedica
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Regarding the pulse information, th
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3.8 Data reconstruction 73 tel-0082
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3.8 Data reconstruction 75 Gain (ch
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3.9 Conclusions 77 tel-00821629, ve
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Chapter 4 Measurement of ✓ 13 wit
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4.1 Data sample 81 create a signal
Page 83 and 84: 4.2 ¯⌫ e signal selection 83 Liv
Page 85 and 86: 4.2 ¯⌫ e signal selection 85 Pro
Page 87 and 88: 4.2 ¯⌫ e signal selection 87 Neu
Page 89 and 90: 4.3 Backgrounds 89 energy spectrum
Page 91 and 92: 4.3 Backgrounds 91 tel-00821629, ve
Page 93 and 94: 4.4 Selection e ciencies and system
Page 95 and 96: 4$&14+#':"'$"$468'#21%$;' ! $"$468'
Page 97 and 98: 4.4 Selection ! e ciencies and syst
Page 99 and 100: 4.5 Data analysis summary 99 4.4.3
Page 101 and 102: 4.6 Final fit and measurement of
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Page 105 and 106: 4.7 Summary and Conclusions 105 tel
Page 107 and 108: Chapter 5 Correlated background tel
Page 109 and 110: 5.1 Measuring correlated background
Page 111 and 112: 5.2 High energy analysis 111 in a l
Page 113 and 114: 5.2 High energy analysis 113 tel-00
Page 115 and 116: 5.3 OV Tag analysis 115 The t cut v
Page 117 and 118: 5.4 Fast Neutrons analysis 117 bigg
Page 119 and 120: 5.4 Fast Neutrons analysis 119 5.4.
Page 121 and 122: 5.4 Fast Neutrons analysis 121 tel-
Page 123 and 124: 5.4 Fast Neutrons analysis 123 esti
Page 125 and 126: 5.4 Fast Neutrons analysis 125 Corr
Page 129 and 130: 5.4 Fast Neutrons analysis 129 Prom
Page 131 and 132: 5.4 Fast Neutrons analysis 131 lect
Page 133: 5.4 Fast Neutrons analysis 133 mari
Page 139 and 140: 5.5 Stopping Muon analysis 139 5.5.
Page 141 and 142: 5.5 Stopping Muon analysis 141 tel-
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Page 145 and 146: 5.5 Stopping Muon analysis 145 Sour
Page 147 and 148: 5.5 Stopping Muon analysis 147 belo
Page 149 and 150: 5.5 Stopping Muon analysis 149 The
Page 151 and 152: 5.6 Estimation of correlated backgr
Page 157 and 158: 5.7 Conclusion 157 5.7 Conclusion t
Page 159 and 160: Chapter 6 Conclusions tel-00821629,
Page 161 and 162: 161 • The SM analysis could be im
Page 163 and 164: Chapter 7 Contributions to Double C
Page 165 and 166: 165 from this study and from [64] f
Page 167 and 168: List of Figures tel-00821629, versi
Page 169 and 170: LIST OF FIGURES 169 tel-00821629, v
Page 179 and 180: List of Tables 3.1 Mean energy rele
Page 181 and 182: Bibliography [1] [2] tel-00821629,
Page 183 and 184: BIBLIOGRAPHY 183 [31] J.K. Ahn et a
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BIBLIOGRAPHY 185 [61] W. Hampel et
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BIBLIOGRAPHY 187 [92] A. Stueken et
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