Violation in Mixing

More documents

Recommendations

Info

126 Measurement of Branching Fractions for � ¦ � Ã � ¦ decays statistical significance (in 20 fb -1 ) 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 optimization with continuum MC 0 0.43 0.435 0.44 0.445 0.45 0.455 0.46 0.465 0.47 0.475 0.48 efficiency on signal statistical significance (in 20 fb -1 ) 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 optimization with offresonance data 0 0.43 0.435 0.44 0.445 0.45 0.455 0.46 0.465 0.47 0.475 0.48 efficiency on signal Figure 5-6. Significance as a function of a cut on Ø ÃË ��Ø ÃË resonance (center) and on-resonance (right) side-band. statistical significance (in 20 fb -1 ) optimization on onresonance upper and lower side bands 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 0.43 0.435 0.44 0.445 0.45 0.455 0.46 0.465 0.47 0.475 0.48 efficiency on signal for continuum Monte Carlo (left), off- isolate samples of events that are consistent with the Ã Ë � and Ã Ë Ã hypotheses, and signal yields are then obtained from an unbinned maximum likelihood fit (Sec. 5.5). 5.4 Background Suppression and PDF Parameterization 5.4.1 ¡� PDF and Definition of Signal and Side-band Regions Signal events are Gaussianly distributed in ¡� with a mean near zero as one can see from the distribution of Monte Carlo signal events (Fig 5-7), while the continuum background events fall quadratically over the signal region (Fig 5-8). For this analysis, since the pion mass is assigned to all tracks, the Ã Ë Ã decays have ¡�� shifted from zero by an amount depending on the momentum of the tracks. From Monte Carlo simulation we find an average shift of � Å�Î for the Ã Ë Ã decays (Fig 5-7). In the global likelihood fit we take into account the shift depending on the momentum of the tracks using a ¡� PDF for � � Ã Ë Ã decays that consists of a Gaussian with a mean given by the analytical form in 4.13. The ¡�� distribution was fitted with a Gaussian width of ��Å�Î for Ã Ë Ã and �� Å�Î for Ã Ë � Monte Carlo. A comparison of � � � � decays in data and Monte Carlo indicates that the Monte Carlo resolution should be scaled by a factor � � ¦ � � to agree with data (see study in Sec. 4.2.2.1). As a consequence, in case of Ã Ë � decays, we have estimated the resolution on ¡� in real data to be �¦�Å�Î. Monte Carlo shows that the mean in ¡� for Ã Ë � signal events is around ��Å�Î 1 . The estimated mean of ¡� in data is therefore taken from the � � � � control sample ( � ¦ �Å�Î, see Sec. 4.2.2.1). 1 This effect in MC is not understood yet, but goes in the same direction as the shift seen in MC in the reconstructed ÃË mass. The reconstructed value in MC is higher than the PDG value, while in data the Ã Ë mass is in perfect agreement with the PDG (see Sec. 2). MARCELLA BONA
5.4 Background Suppression and PDF Parameterization 127 number of MC signal events / 0.0095 GeV 1000 number of events / 0.0095 GeV 800 600 400 200 MC B-to-KsK signal events ALLCHAN 6313. 247.4 / 53 P1 6066. 77.88 P2 -0.4137E-01 0.2914E-03 P3 0.2264E-01 0.2445E-03 0 -0.3 -0.2 -0.1 0 0.1 0.2 Delta E (GeV) number of MC signal events / 0.0095 GeV 1000 800 600 400 200 MC B-to-KsPi signal events ALLCHAN 4966. 234.3 / 52 P1 4732. 68.79 P2 0.3528E-02 0.2832E-03 P3 0.1933E-01 0.2395E-03 0 -0.3 -0.2 -0.1 0 0.1 0.2 Delta E (GeV) Figure 5-7. Distributions of ¡� in � � Ã Ë Ã (left) and � � Ã Ë � Monte Carlo (right). The resolution is �� ¦ � Å�Îfor the former and �� ¦ � Å�Îfor the latter. Delta E distribution in offresonance grand side band 40 ALLCHAN 1264. 35 A0 59.90 / 57 19.03 0.8475 A1 -29.44 3.459 30 A2 16.18 23.51 25 20 15 10 5 0 -0.3 -0.2 -0.1 0 0.1 0.2 Delta E (GeV) 0.03 0.025 0.02 0.015 0.01 0.005 0 -0.3 -0.2 -0.1 0 0.1 0.2 Delta E (GeV) number of events / 0.0095 GeV 0.03 0.025 0.02 0.015 0.01 0.005 ALLCHAN 1395. 0 -0.3 -0.2 -0.1 0 0.1 0.2 Delta E (GeV) Figure 5-8. Distributions of ¡� in off-resonance data (left), comparison of continuum Monte Carlo and off-resonance data (center) and comparison of on-resonance side-bands and off-resonance data (right). MEASUREMENT OF BRANCHING FRACTIONS FOR � ¦ � Ã � ¦ 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 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: 5.3 Analysis Strategy 125 0.35 0.3
Page 135 and 136: 5.4 Background Suppression and PDF
Page 137 and 138: 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 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 183 and 184:
7.7 The maximum likelihood analysis
Page 185 and 186:
Page 187 and 188:
Page 189 and 190:
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?