Violation in Mixing

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140 Measurement of Branching Fractions for � ¦ � Ã � ¦ decays Fit Variable Input Value Fitted Value Test 3: continuum MC with fixed asymmetry Æ Ë Ã Ë � Æ Ë Ã Ë Ã Æ � Ã Ë � Æ � Ã Ë Ã � ¦ �� ¦ �� ¦ �� ¦ �� Ã Ë � � � � ¦ � �� Ã Ë Ã ¦ Test 4: continuum MC with fixed asymmetry Æ Ë Ã Ë � Æ Ë Ã Ë Ã Æ � Ã Ë � Æ � Ã Ë Ã � � Ã Ë � � � Ã Ë Ã � ¦ �� ¦ �� ¦ � �� ¦ �� ¦ � � � � ¦ � �� Test 5: continuum MC with fixed asymmetry Æ Ë Ã Ë � Æ Ë Ã Ë Ã Æ � Ã Ë � Æ � Ã Ë Ã � ¦ �� ¦ �� ¦ �� ¦ �� Ã Ë � � � � �� ¦ � � � � Ã Ë Ã � � � �� ¦ � �� Table 5-7. Summary of tests performed with continuum Monte Carlo with fixed charged asymmetry: in the fit the asymmetry of the signal is fixed to 0 MARCELLA BONA
5.5 Maximum likelihood analysis 141 Table 5-8. Systematics errors ( ) for Ã Ë � yield Ñ�Ë (Signal) Mean Ñ�Ë (Signal) Ñ�Ë (Bkg) �Ñ�Ë (Signal) ¡� (Signal) Mean ¡� (Signal) �¡� (Signal) Æ Ë Ã Ë � Ë Æ ÃË� �� ¡� (Bkg) ¦ �� Fisher Fisher (Signal) ¦ � �� Fisher (Bkg) ¦�� : Frac Sat Peak � �� : Resolution ¦ �� Total � : Offset ¦ � � : charge dependent PDFs - - systematic uncertainties in the unbinned likelihood analysis come primarily from the imperfect knowledge of the correct parameterizations for each of the PDFs. Each parameter in each PDF was varied within ¦ � and different samples of data were used to obtain alternative parameterizations. The global fit was repeated changing every time one PDF parameter or using another parameterization for a single PDF and the difference of the fit results from the central values of the nominal fit are taken to be the estimated systematic uncertainty. These studies are summarized below: ¯ Ñ�Ë � The mean value of Ñ�Ë for signal decays was varied by ¦ ��Å�Î� and the width of ¦ � Å�Î� . The � parameter of the Argus function used to model the background shape, was allowed to vary within ¦ �. This uncertainty is estimated from the different values of � obtained by fitting on-resonance side-bands, off-resonance and continuum Monte Carlo data. ¯ ¡� � The mean for the ¡� distribution for signal events are varied from Å�Î to Å�Î. The � �� is varied of �� Å�Î, consistently with � � analysis (see Ref. [57]). Alternative parameterizations of background ¡� distribution obtained fitting off-resonance and continuum Monte Carlo data are used. MEASUREMENT OF BRANCHING FRACTIONS FOR � ¦ � Ã � ¦ 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
Page 95 and 96: 3.3 Studies on data 89 N(π + π -
Page 97 and 98: 3.3 Studies on data 91 0.508 0.506
Page 99 and 100: 3.3 Studies on data 93 Figure 3-13.
Page 101 and 102: 3.3 Studies on data 95 0.508 0.506
Page 103 and 104: 4 Strategy and Tools for Charmless
Page 105 and 106: 4.2 Event selection 99 channel sele
Page 107 and 108: 4.2 Event selection 101 ÀÐ �
Page 109 and 110: 4.2 Event selection 103 Figure 4-2.
Page 111 and 112: 4.3 Background fighting 105 Figure
Page 113 and 114: 4.4 PID selection 107 In the case o
Page 115 and 116: 4.4 PID selection 109 θ c Cut Effi
Page 117 and 118: 4.5 Tracking Corrections 111 Ë�
Page 119 and 120: 4.6 Analysis methods 113 Ñ�Ë si
Page 121 and 122: 4.6 Analysis methods 115 Events/2.5
Page 123 and 124: 4.6 Analysis methods 117 Figure 4-1
Page 125 and 126: 4.6 Analysis methods 119 θ c radia
Page 127 and 128: 5 Measurement of Branching Fraction
Page 129 and 130: 5.2 Ã Ë reconstruction 123 1 0.8
Page 131 and 132: 5.3 Analysis Strategy 125 0.35 0.3
Page 133 and 134: 5.4 Background Suppression and PDF
Page 139 and 140: 5.5 Maximum likelihood analysis 133
Page 145: 5.5 Maximum likelihood analysis 139
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
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7.8 Validation studies 191 Paramete
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7.9 Results 193 Parameter Fit Resul
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7.9 Results 195 Events/2 MeV/c 2 Ev
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7.10 Systematic studies 197 Categor
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7.11 Summary 199 �Ã� Ë��
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7.11 Summary 201 �Ã� Ë��
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7.11 Summary 203 Variation �Ã�
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BIBLIOGRAFIA 205 Bibliografia Chapt
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BIBLIOGRAFIA 207 [38] J. Charles, P
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BIBLIOGRAFIA 209 Chapter 7 [67] D.
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Violation in Mixing

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