Violation in Mixing

More documents

Recommendations

Info

156 Measurement of Branching Fractions for � � Ã Ë Ã Ë Decays Table 6-3. Results of several test fits using signal Monte Carlo and real data. sample Æ×�� Æ�� Ã Ë Ã Ë MC �� ¦ �� ¦ � �� continuum MC �� ¦ � Ã Ë Ã Ë MC and �� continuum MC � �� ¦ � � Ã Ë Ã Ë MC and �� continuum MC � �� ¦ � �� ¦ � � off-res � ¦ � Ã Ë Ã Ë MC and �� continuum MC � 6.3.2 Test on the maximum likelihood analysis � on-res lower side-band � ¦ � �� on-res upper side-band �� ¦ � Several checks of the fitting technique were performed before testing the different maximum likelihood analysis hypotheses. Table 6-3 shows the results of fitting pure signal Monte Carlo, continuum Monte Carlo, off-resonance and on-resonance side-band data. No problems are observed. We have used a toy Monte Carlo to estimate the � -CL upper limit that can be obtained assuming 0 signal events. Background candidates are selected randomly from the PDFs for Ñ�Ë, ¡�, and �. The mean number of background events to be generated is estimated from the on-resonance upper and lower side-bands and the off-resonance signal band, properly weighted. The samples generated are then fitted and the result of the fit used to calculate the pulls of the variables to be extracted from the fit: the left plot in Fig. 6-8 shows the pull distribution for the number of background events. On these samples, we also calculate the � CL upper limit on the Ã Ë Ã Ë yield: the right plot in Fig. 6-8 shows the upper limit distribution, whose mean value is 4.4 events that, taking into account the �� efficiency, becomes an upper limit on the Branching Ratio: � � � Ã Ã � �� ¡ to be compared with CLEO result: � � � Ã Ã � � ¡ � . Tab. 6-4 shows the optimization for the � Ó× �Ë� cut and it shows that the upper limit on the achievable Branching Ratio is not improving while tightening the � Ó× �Ë� cut. This test is done using the same ¡� and Ñ�Ë parameterization (from the �� Ó× �Ë� cut, see Section 6.3.1) and varying the Fisher one, since we assume no correlation between � Ó× �Ë� and ¡�(Ñ�Ë), while we expect correlation between � Ó× �Ë� and the Fisher variable. MARCELLA BONA �
6.4 Counting analysis 157 120 100 80 60 40 20 Entries Mean RMS NksksBkg 1000 -0.9253E-01 1.050 81.07 / 17 Constant 97.63 4.016 Mean -0.7045E-01 0.3493E-01 Sigma 1.015 0.2642E-01 0 -4 -3 -2 -1 0 1 2 3 4 300 250 200 150 100 50 0 Entries Mean RMS 1000 4.417 1.764 0 2 4 6 8 10 12 upper limit on the KsKs yield in 1000 ToyMC events Figure 6-8. The pull distribution for the number of background events (left) and the upper limit distribution (right) in 1000 Ã Ë Ã Ë toy MC experiments with the � Ó× �Ë� cut value at ��. Table 6-4. Results of several Toy Monte Carlo experiments with different cuts. � Ó× �Ë� mean value of mean value of upper limit eff. upper limit on cut � bkg events distribution (on the yield) � � � �� 282 4.4 34.9 5.0 � �� 147 3.9 30.8 5.0 � �� 80 3.4 26.9 5.0 6.4 Counting analysis Along with the maximum likelihood fit, a counting analysis has been optimized in order to estimate the best upper limit on � � � Ã Ã we can extract with this technique from the Run1 data sample. The counting analysis consists of cutting and counting the events in a 2-dimensional signal box within the ¡�–Ñ�Ë plane defined with � � ¡� � � ��Î and �� Ñ�Ë � �� Î� (i.e. twice the Ñ�Ë resolution). The region where �� Ñ�Ë � �� Î� is called Ñ�Ë signal band and the one where �� Ñ�Ë � �� Î� is the already defined Ñ�Ë side-band. The optimization is done to choose the best cuts on the remaining discriminating variables used in two-body analysis: � Ó× �Ë� cut and Fisher cut. We define the best cuts for this analysis the ones which give the lowest upper limit on � � Ã Ã branching ratio. MEASUREMENT OF BRANCHING FRACTIONS FOR � � Ã Ë Ã Ë DECAYS
Page 1 and 2:
ÍÒ�Ú�Ö×�Ø��
Page 3 and 4:
Contents Introduction . ...........
Page 5 and 6:
4 Strategy and Tools for Charmless
Page 7 and 8:
7.2 Branching fraction � � �
Page 9 and 10:
Introduction The main goal of the B
Page 11 and 12:
1 �È Violation in the �� Sys
Page 13 and 14:
1.2 Neutral � Mesons 7 Note, howe
Page 15 and 16:
1.2 Neutral � Mesons 9 Applying t
Page 17 and 18:
1.2 Neutral � Mesons 11 �È �
Page 19 and 20:
1.2 Neutral � Mesons 13 ��
Page 21 and 22:
1.2 Neutral � Mesons 15 � ¡�
Page 23 and 24:
1.2 Neutral � Mesons 17 and � a
Page 25 and 26:
1.2 Neutral � Mesons 19 given tim
Page 27 and 28:
1.3 The Three Types of �È Violat
Page 29 and 30:
Page 31 and 32:
Page 33 and 34:
1.4 �È Violation in the Standard
Page 35 and 36:
Page 37 and 38:
Page 39 and 40:
Page 41 and 42:
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 and 86:
3.3 Studies on data 79 19.5° BINS
Page 87 and 88:
3.3 Studies on data 81 ¯ off-reson
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 93 and 94:
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 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 161: 6.3 The maximum likelihood analysis
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
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.
show all

Violation in Mixing

Create successful ePaper yourself

Delete template?

Save as template?