Violation in Mixing

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194 Analysis of the time-dependent �È -violating asymmetry in � � � � decays Figure 7-16. Pull distributions for Ë�� and �� from �� toy experiments with fixed yields generated according to the Run 1 + 2 result. Figure 7-17. Error distributions for Ë �� and �� from �� toy experiments with fixed yields generated according to the Run 1 + 2 result. The data result is indicated by the arrows. MARCELLA BONA
7.9 Results 195 Events/2 MeV/c 2 Events/2 MeV/c 2 15 10 5 π + π - B A B AR (GeV/c mES 2 0 5.2 5.3 ) mES 60 40 20 K + π - B A B AR (GeV/c mES 2 0 5.2 5.3 ) mES Events/20 MeV Events/20 MeV 15 10 5 0 60 40 20 0 π + π - B A B AR -0.1 0 0.1 (GeV) ΔE K + π - B A B AR -0.1 0 0.1 (GeV) ΔE Figure 7-18. Distributions of Ñ�Ë and ¡� for samples enhanced in signal �� and Ã� decays using likelihood ratio cuts. The solid curves represent projections of the maximum likelihood fit result. Sample �Ã� Ë�� Run 1 � � ¦ � � � ¦ �� ¦ �� Run 2 � � ¦ �� ¦ � � ¦ � � � tags � � ¦ � � �� ¦ �� ¦ � � � tags � � ¦ � � �� ¦ �� ¦ �� no NT tags � � ¦ � � � � ¦ �� ¦ �� Table 7-21. Separate fits to Run 1 and Run 2, � and � tags, and the subsample of Lepton and Kaon tagged events. against tag category, we fit only the Lepton and Kaon categories and find consistent results, with slightly larger errors for Ë�� and �� (as expected). Figure 7-1 indicates some discrepancy in ARGUS shape between different tag categories. Since we assume one shape in the nominal fit, we have to investigate the possible systematic effect on the �È parameters by refitting the data with different (floating) values of � for each category. Table 7-22 summarizes the results. The Lepton and NT1 categories are somewhat different than the nominal value, but the �� yield changes by only � events, and the values of Ë�� and �� change by only � � and � , respectively. There appears to be no bias in using an average value of �. ANALYSIS OF THE TIME-DEPENDENT �È -VIOLATING ASYMMETRY IN � � � � DECAYS
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ÍÒ�Ú�Ö×�Ø��
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Contents Introduction . ...........
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4 Strategy and Tools for Charmless
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7.2 Branching fraction � � �
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Introduction The main goal of the B
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1 �È Violation in the �� Sys
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1.2 Neutral � Mesons 7 Note, howe
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1.2 Neutral � Mesons 9 Applying t
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1.2 Neutral � Mesons 11 �È �
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1.2 Neutral � Mesons 13 ��
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1.2 Neutral � Mesons 15 � ¡�
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1.2 Neutral � Mesons 17 and � a
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1.2 Neutral � Mesons 19 given tim
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1.3 The Three Types of �È Violat
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1.4 �È Violation in the Standard
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1.5 Determination of « 37 1.5 Dete
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1.5 Determination of « 39 Assuming
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1.5 Determination of « 41 Figure 1
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1.5 Determination of « 43 b q (a)
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1.5 Determination of « 45 � �
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2 The BABAR Experiment 2.1 Physics
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2.1 Physics at � � B Factory op
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2.2 The BABAR detector. 51 Integrat
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2.2 The BABAR detector. 53 The dete
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2.2 The BABAR detector. 55 two oute
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2.2 The BABAR detector. 57 SVT Effi
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2.2 The BABAR detector. 59 324 1015
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Efficiency 2.2 The BABAR detector.
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2.2 The BABAR detector. 63 2.2.4 Th
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entries per mrad 2.2 The BABAR dete
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2.2 The BABAR detector. 67 entries
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2.2 The BABAR detector. 69 energies
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2.2 The BABAR detector. 71 The main
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Efficiency 2.2 The BABAR detector.
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2.2 The BABAR detector. 75 Table 2-
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3 Ã Ë reconstruction and efficien
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3.3 Studies on data 79 19.5° BINS
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3.3 Studies on data 81 ¯ off-reson
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3.3 Studies on data 83 0.504 0.502
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3.3 Studies on data 85 0.03 0.025 0
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3.3 Studies on data 87 0.504 0.502
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3.3 Studies on data 89 N(π + π -
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3.3 Studies on data 91 0.508 0.506
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3.3 Studies on data 93 Figure 3-13.
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3.3 Studies on data 95 0.508 0.506
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4 Strategy and Tools for Charmless
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4.2 Event selection 99 channel sele
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4.2 Event selection 101 ÀÐ �
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4.2 Event selection 103 Figure 4-2.
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4.3 Background fighting 105 Figure
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4.4 PID selection 107 In the case o
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4.4 PID selection 109 θ c Cut Effi
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4.5 Tracking Corrections 111 Ë�
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4.6 Analysis methods 113 Ñ�Ë si
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4.6 Analysis methods 115 Events/2.5
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4.6 Analysis methods 117 Figure 4-1
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4.6 Analysis methods 119 θ c radia
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5 Measurement of Branching Fraction
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5.2 Ã Ë reconstruction 123 1 0.8
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5.3 Analysis Strategy 125 0.35 0.3
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5.4 Background Suppression and PDF
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5.5 Maximum likelihood analysis 133
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Page 149 and 150: 5.5 Maximum likelihood analysis 143
Page 151 and 152: 5.6 Counting analysis 145 Table 5-1
Page 153 and 154: 5.7 Determination of branching frac
Page 155 and 156: 6 Measurement of Branching Fraction
Page 157 and 158: 6.3 The maximum likelihood analysis
Page 163 and 164: 6.4 Counting analysis 157 120 100 8
Page 165 and 166: 6.5 Analysis choice 159 6.5 Analysi
Page 167 and 168: 6.6 Results on the Run1 data-set 16
Page 169 and 170: 6.7 Determination of the branching
Page 171 and 172: 7 Analysis of the time-dependent
Page 173 and 174: 7.3 Analysis strategy 167 Parameter
Page 175 and 176: 7.4 Data samples and event selectio
Page 177 and 178: 7.4 Data samples and event selectio
Page 179 and 180: 7.5 Background characterization 173
Page 181 and 182: 7.5 Background characterization 175
Page 191 and 192: 7.8 Validation studies 185 Figure 7
Page 193 and 194: 7.8 Validation studies 187 100 75 5
Page 195 and 196: 7.8 Validation studies 189 Figure 7
Page 197 and 198: 7.8 Validation studies 191 Paramete
Page 199: 7.9 Results 193 Parameter Fit Resul
Page 203 and 204: 7.10 Systematic studies 197 Categor
Page 205 and 206: 7.11 Summary 199 �Ã� Ë��
Page 207 and 208: 7.11 Summary 201 �Ã� Ë��
Page 209 and 210: 7.11 Summary 203 Variation �Ã�
Page 211 and 212: BIBLIOGRAFIA 205 Bibliografia Chapt
Page 213 and 214: BIBLIOGRAFIA 207 [38] J. Charles, P
Page 215 and 216: BIBLIOGRAFIA 209 Chapter 7 [67] D.
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Violation in Mixing

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