Violation in Mixing

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80 Ã Ë reconstruction and efficiency studies 3.3.1 Data samples Monte Carlo sample � � Â��Ã Ë (Ã Ë � � � ) #ÃË 2980 #ÃË associated 2007 (67.3% of associated) #Ã Ë within geometrical acceptance 2553 #Ã Ë associated within geometrical acceptance 1995 (78.1% of associated) #ÃË unassociated within geometrical acceptance 194 -two pions reconstructed- (35.8% of unassociated) #ÃË unassociated within geometrical acceptance 164 -� reconstructed- (30.3% of unassociated) #ÃË unassociated within geometrical acceptance 158 -� reconstructed- (29.2% of unassociated) #ÃË unassociated within geometrical acceptance 26 -no pion reconstructed- (4.8% of unassociated) Table 3-1. Number of (un)reconstructed Ã Ë for certain event categories. Data used for this analysis correspond to a subsample of the Run1 data set. In order to limit the underlying systematics another sample of off-peak (continuum) data has been used from Run 1 data set. All samples are split into the so called block 1 and block 2 subsamples: they differ in different DCH operating high voltage (HV). Block 1 corresponds to the DCH HV set at � Î , while block 2 corresponds to �� Î . The HV difference in the DCH configuration is expected to lead to different tracking efficiencies and thus to different Ã Ë reconstruction efficiencies. The data sample consists of: ¯ on-resonance data from block 1, corresponding to a luminosity of � �� pb and to a number of �� ¦ ��(stat+syst) giving an average cross-section of � � ¦ � ��(stat) ¦ � ��(syst) nb; ¯ on-resonance data from block 2, corresponding to a luminosity of � �� pb and to a number of �� ¦ �� (stat+syst) giving an average cross-section of � �� ¦ � ��(stat) ¦ � ��(syst) nb ¯ off-resonance data from block 1, corresponding to a luminosity of � pb MARCELLA BONA
3.3 Studies on data 81 ¯ off-resonance data from block 2, corresponding to a luminosity of � � pb ¯ Monte Carlo simulation dataset Æ ��: million events Æ : million events Æ Ù�×: million events this Monte Carlo dataset has been produced for both the block 1 equivalent Monte Carlo sample and the block 2 equivalent sample: Æ block 1 MC sample corresponds to � �� pb (assuming the �� cross section of � nb) for �� Monte Carlo and �� pb for continuum Monte Carlo. Æ block 2 MC sample corresponds to �� pb (assuming the �� cross section of � nb) for �� Monte Carlo and �� pb for continuum Monte Carlo. The Ã Ë are reconstructed pairing all the opposite charged tracks of the event and using “GeoKin” fitter algorithm. The charged tracks used are requested to be in the fiducial region �� Ð�� (i.e. inside the active region of the SVT). No selection is applied apart from the so-called hadronic selection that consists of: ¯ BGFMultiHadron 3 tag bit set ¯ number of ChargedTracks in the fiducial region in the event � 4 ¯ Ê � �� 4 ¯ the sum of energy of charged tracks in the fiducial region plus calorimeter clusters greater than 5 GeV ¯ primary vertex within 0.5 cm of beam spot in x and y. This selection is the one used for � counting analysis: it is described and discussed in Ref. [44]. The efficiency of this hadronic selection is shown in table 3-2. No other selection is applyed in the analysis: the number of observed Ã Ë and their average invariant mass are evaluated from a fit to the invariant mass plot, using a double Gaussian with a linear background. The resolution on the Ã Ë mass is evaluated using a single Gaussian and linear background fit. 3.3.2 Mass and Resolution Studies Possible dependencies of the reconstructed Ã Ë mass and resolution on various quantities were investigated. The � and the � angles of the Ã Ë daughters have been considered in figures (3-3) and (3-4). The data-Monte Carlo comparison of the reconstructed invariant mass and resolution is shown as function of those angles. It is to be noted that Monte Carlo reconstructed invariant mass is shifted from the simulated one and that the 3 the BGFMultiHadron selection consists of requiring at least 3 charged tracks and Ê � ��. 4 see Eq. (4.4) for the definition of this variable. Ã Ë RECONSTRUCTION AND EFFICIENCY STUDIES
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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
Page 35 and 36: 1.4 �È Violation in the Standard
Page 43 and 44: 1.5 Determination of « 37 1.5 Dete
Page 45 and 46: 1.5 Determination of « 39 Assuming
Page 47 and 48: 1.5 Determination of « 41 Figure 1
Page 49 and 50: 1.5 Determination of « 43 b q (a)
Page 51 and 52: 1.5 Determination of « 45 � �
Page 53 and 54: 2 The BABAR Experiment 2.1 Physics
Page 55 and 56: 2.1 Physics at � � B Factory op
Page 57 and 58: 2.2 The BABAR detector. 51 Integrat
Page 59 and 60: 2.2 The BABAR detector. 53 The dete
Page 61 and 62: 2.2 The BABAR detector. 55 two oute
Page 63 and 64: 2.2 The BABAR detector. 57 SVT Effi
Page 65 and 66: 2.2 The BABAR detector. 59 324 1015
Page 67 and 68: Efficiency 2.2 The BABAR detector.
Page 69 and 70: 2.2 The BABAR detector. 63 2.2.4 Th
Page 71 and 72: entries per mrad 2.2 The BABAR dete
Page 73 and 74: 2.2 The BABAR detector. 67 entries
Page 75 and 76: 2.2 The BABAR detector. 69 energies
Page 77 and 78: 2.2 The BABAR detector. 71 The main
Page 79 and 80: Efficiency 2.2 The BABAR detector.
Page 81 and 82: 2.2 The BABAR detector. 75 Table 2-
Page 83 and 84: 3 Ã Ë reconstruction and efficien
Page 85: 3.3 Studies on data 79 19.5° BINS
Page 89 and 90: 3.3 Studies on data 83 0.504 0.502
Page 91 and 92: 3.3 Studies on data 85 0.03 0.025 0
Page 95 and 96: 3.3 Studies on data 89 N(π + π -
Page 99 and 100: 3.3 Studies on data 93 Figure 3-13.
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 135 and 136: 5.4 Background Suppression and PDF
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5.4 Background Suppression and PDF
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5.5 Maximum likelihood analysis 133
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5.6 Counting analysis 145 Table 5-1
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5.7 Determination of branching frac
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6 Measurement of Branching Fraction
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6.3 The maximum likelihood analysis
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6.4 Counting analysis 157 120 100 8
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6.5 Analysis choice 159 6.5 Analysi
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6.6 Results on the Run1 data-set 16
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6.7 Determination of the branching
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7 Analysis of the time-dependent
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7.3 Analysis strategy 167 Parameter
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7.4 Data samples and event selectio
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7.4 Data samples and event selectio
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7.5 Background characterization 173
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7.5 Background characterization 175
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7.8 Validation studies 185 Figure 7
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7.8 Validation studies 187 100 75 5
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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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