Violation in Mixing

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146 Measurement of Branching Fractions for � ¦ � Ã � ¦ decays mode Observed PID-unfolded Ã Ë � �� ¦ �� ¦ �� Ã Ë Ã � ¦ � � ¦ � Table 5-11. Number of observed events and PID-unfolded events in each mode. Applying the base PID cuts, the Fisher cut and the loose SMS selection, we have selected a sample of 166 candidates in which the � ¦ is compatible with the � hypothesis and a sample of 143 candidates in which the � ¦ is compatible with the K hypothesis. Fitting the first sample (Ã Ë � candidates), we get: Æ Ë Ã Ë � � Ë Ã Ë � Æ � Ã Ë � � � Ã Ë � while fitting the second (Ã Ë Ã candidates): Æ Ë Ã Ë Ã � Ë Ã Ë Ã Æ � Ã Ë Ã � � Ã Ë Ã � �� ×Ø�Ø � � � � �� ×Ø�Ø �� ×Ø�Ø � � ¦ � � ×Ø�Ø � � � ×Ø�Ø � � ¦ �� ×Ø�Ø � � � � �� ×Ø�Ø � � � ¦ � � ×Ø�Ø Fig. 5-17 shows the Ñ�Ë distribution with superimposed the fitted function for the candidates compatible with the � hypothesis. Applying the Cross-feed Table (Table 5-10) to the raw yields given by the fits determines the number of unfolded signal events in each mode. Table 5-11 summarizes the results. Taking into account the efficiency of the selection ( � and � for �Ã Ë and ÃÃ Ë respectively) the results are consistent with the finding of the global likelihood method. 5.7 Determination of branching fraction We determine branching fractions for � Ã Ë and an upper limit for the Ã Ã Ë decay using the results of the global likelihood fit. The individual efficiencies are reported in previous sections. The total efficiencies are � �� ¦ �� for � Ã Ë and � � ¦ �� for Ã Ã Ë , where the error is combined statistical and systematic. MARCELLA BONA
5.7 Determination of branching fraction 147 Events / 2.5 MeV/c 2 10 5 BABAR 0 5.2 5.225 5.25 5.275 5.3 10 7.5 5 2.5 0 5.2 5.225 5.25 5.275 5.3 m ES (GeV/c 2 ) Figure 5-17. Ñ�Ë distribution in the ¡� signal region with superimposed the fitted function (sum of an ARGUS function, with � � � , and a Gaussian with Ñ�Ë �� Î� and � Ñ�Ë � ��Å�Î� .) for candidates in which the � ¦ is compatible with the � hypothesis(left) and with the K hypothesis(right). Branching fractions are calculated as �Ê Ã � � �Ê Ã � ÃË ¡ �Ê Ã Ë � � � ÆË Ã Ë � ¯ ¡ Æ �� (5.4) where ÆË is the central value from the fit, ¯ is the total efficiency, and Æ �� ¦ � � ¢ � is the total number of �� pairs in our data-set. �Ê Ã � Ã Ë is taken equal to �� and �Ê Ã Ë � � � equal to �� [14]. Implicit in Eq. 5.4 is the assumption of equal branching fractions for § �Ë � � � and § �Ë � � � . For the Ã Ë Ã mode we calculate the � confidence level upper limit yield and the result is increased by the total systematic error that, in this case, is reduced to the contributions from the efficiency and the number of ��, since no contribution comes from varying the likelihood parameters. The results are summarized in Table. 5-12. The statistical significance of a given signal yield is determined by setting the yield to zero and maximizing the likelihood with respect to all other variables. In summary, the branching fraction for � ¦ � Ã � ¦ is �� of � ¦ � Ã Ã ¦ we set an upper limit of �� ¡ � . � � �� ¡ � , while on the branching fraction 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
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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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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 151: 5.6 Counting analysis 145 Table 5-1
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 and 200: 7.9 Results 193 Parameter Fit Resul
Page 201 and 202: 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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