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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Dossett, D.
Languages: English
Types: Doctoral thesis
Subjects: QC
Measurements of the branching fractions of B0d,s→K*±h∓ (h = π,K) decays are performed, using pp collision data at the LHCb experiment. The data sample corresponds to an integrated luminosity of 1:0 fb-1, collected at a centre-of-mass energy of 7TeV. First observation of the B0s→K*±K∓ and evidence for the B0s→K*-π+ decay modes are reported. The following branching fraction measurements and limits of the B0d,s→K*±h∓ (h = π,K) decay modes, relative to the well measured B0→K*+π- decay, are obtained\ud \ud B (B0s→K*±K∓) / B (B0→K*+π-) = 1.49 ± 0.22 (stat.) ± 0.18 (syst.)\ud \ud B (B0→K*±K∓) / B (B0→K*+π-) < 0.06 at 95% CL.\ud \ud B (B0s→K*-π+) / B (B0→K*+π-) = 0.39 ± 0.13 (stat.) ± 0.05 (syst.)
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    • Chapter 1 Theory 3 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 The Standard Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 The fundamental particles . . . . . . . . . . . . . . . . . . . . . 4 The fundamental forces . . . . . . . . . . . . . . . . . . . . . . . 5 Form of the Standard Model . . . . . . . . . . . . . . . . . . . . 6 The electroweak theory . . . . . . . . . . . . . . . . . . . . . . . 7 Spontaneous symmetry breaking and massive vector bosons . . 10 1.3 Quark mixing and the CKM matrix . . . . . . . . . . . . . . . . . . 12 Yukawa coupling and quark masses . . . . . . . . . . . . . . . . 12 The CKM matrix . . . . . . . . . . . . . . . . . . . . . . . . . . 13 The Wolfenstein parameterisation . . . . . . . . . . . . . . . . . 14 1.4 CP-violation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Discrete symmetries . . . . . . . . . . . . . . . . . . . . . . . . . 15 A history of CP-violation . . . . . . . . . . . . . . . . . . . . . . 15 Unitarity triangles . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Direct CP-violation . . . . . . . . . . . . . . . . . . . . . . . . . 18 CP-violation in mixing . . . . . . . . . . . . . . . . . . . . . . . 19 CP-violation in interference between mixing and decay . . . . . 20 1.5 The Bs0 ! K K decay mode . . . . . . . . . . . . . . . . . . . . . . 21
    • Chapter 2 Experiment 26 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.2 The LHC machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 General design . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Accelerator chain . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2.3 The LHCb detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 General design . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Luminosity levelling . . . . . . . . . . . . . . . . . . . . . . . . . 30 The VELO sub-detector . . . . . . . . . . . . . . . . . . . . . . 32 Tracking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Ring imaging Cherenkov sub-detectors . . . . . . . . . . . . . . 37 Magnet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Calorimeters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Muon system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Reconstruction and analysis . . . . . . . . . . . . . . . . . . . . 43 Stripping lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
    • Chapter 3 Selection 45 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 3.2 Data sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.3 Initial selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 The B0d;s ! KS0h h0 stripping line . . . . . . . . . . . . . . . . . 46 Daughter track requirements . . . . . . . . . . . . . . . . . . . . 47 KS0 candidate requirements . . . . . . . . . . . . . . . . . . . . . 48 B candidate requirements . . . . . . . . . . . . . . . . . . . . . . 48 3.4 Trigger requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3.5 Charm vetoes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.6 Neural net . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 sPlots method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Training of neural nets . . . . . . . . . . . . . . . . . . . . . . . 52 Optimisation of neural net requirements . . . . . . . . . . . . . 59 3.7 Particle identi cation . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
    • Chapter 4 Backgrounds 67 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4.2 Decays containing a real K . . . . . . . . . . . . . . . . . . . . . . 68 The decay B0 ! K + . . . . . . . . . . . . . . . . . . . . . . . 68 The decay Bs0 ! K K . . . . . . . . . . . . . . . . . . . . . . 68 The decay b0 ! K p . . . . . . . . . . . . . . . . . . . . . . . . 71 Partially reconstructed decays . . . . . . . . . . . . . . . . . . . 72 4.3 Non-resonant KS0K decays . . . . . . . . . . . . . . . . . . . . . . 75 4.4 Charmed backgrounds . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Charmonium intermediate states . . . . . . . . . . . . . . . . . . 75 Baryonic charmed decays . . . . . . . . . . . . . . . . . . . . . . 78 Partially reconstructed decays . . . . . . . . . . . . . . . . . . . 79 4.5 Combinatorial background . . . . . . . . . . . . . . . . . . . . . . . . 79 4.6 Estimated yields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Signal yields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Background yields . . . . . . . . . . . . . . . . . . . . . . . . . . 84
    • Chapter 5 Fit model 87 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.2 Fitting techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Maximum likelihood ts . . . . . . . . . . . . . . . . . . . . . . 88 Extended ts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 Pull distributions . . . . . . . . . . . . . . . . . . . . . . . . . . 89 5.3 B0d;s ! K K Signal model . . . . . . . . . . . . . . . . . . . . . . . 89 5.4 B0d;s ! K K Background models . . . . . . . . . . . . . . . . . . . 94 5.5 Simulation studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 5.6 B0d;s ! K model . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Signal PDFs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Background PDFs . . . . . . . . . . . . . . . . . . . . . . . . . . 100 5.7 Fit results on data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
    • Chapter 6 E ciencies 106 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Master formula of branching ratio . . . . . . . . . . . . . . . . . 106 6.2 Detector acceptance . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 6.3 Reconstruction and selection . . . . . . . . . . . . . . . . . . . . . . 108
    • Chapter 7 Systematics 114 7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 7.2 Trigger requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 7.3 PID requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 7.4 Fit model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Linear approximation of non-resonant shapes . . . . . . . . . . . 116 S-wave interference . . . . . . . . . . . . . . . . . . . . . . . . . 117 Shape parameters . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Fit bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 7.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
    • Chapter 8 Results 124 8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 8.2 Observation signi cances . . . . . . . . . . . . . . . . . . . . . . . . . 124 Likelihood ratio test . . . . . . . . . . . . . . . . . . . . . . . . . 125 Signi cances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 8.3 Relative branching fraction limits . . . . . . . . . . . . . . . . . . . . 128 8.4 Relative branching fractions . . . . . . . . . . . . . . . . . . . . . . . 129
    • Chapter 9 Conclusion 132 9.1 Summary of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 9.2 Comparison with predictions . . . . . . . . . . . . . . . . . . . . . . 135 9.3 Future analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
    • Chapter A Dalitz plots 137 A.1 Three-body kinematics . . . . . . . . . . . . . . . . . . . . . . . . . . 137 A.2 Dalitz plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
    • 3.1 Total selection requirements for the charged pion and kaon tracks. . 47
    • 3.2 Selection requirements for the Long-Long and Down-Down KS0 candidates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
    • 3.3 Selection requirements for the B candidates after four-momentum combination. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
    • 3.4 Selection requirements for the B candidates after the full vertex t. . 49
    • 3.5 Extra selection requirements for candidate decays containing DownDown KS0, added from later stripping versions. . . . . . . . . . . . . . 50
    • 3.6 Trigger selection requirements after reconstruction of decays. . . . . 51
    • 3.7 Charm vetoes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
    • 3.8 Signal yields for B0 ! KS0 + MC, Bs0 ! KS0K MC and B0 ! KS0 + Collision data . . . . . . . . . . . . . . . . . . . . . . . . . . 54
    • 3.9 p-values of simulation and Data comparisons for neural net variables for Down-Down KS0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
    • 3.10 p-values of simulation and Data comparisons for neural net variables for Long-Long KS0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
    • 3.11 Neural net cuts applied to the di erent KS0 types. . . . . . . . . . . . 62
    • 3.12 PID cuts applied to the particle hypothesis of a kaon or pion for the KS0 + and KS0K nal states. . . . . . . . . . . . . . . . . . . . 65
    • 3.13 Fitting ranges of the mB and mK0S variables. . . . . . . . . . . . . . 66
    • 4.1 Average b-hadron production fractions. . . . . . . . . . . . . . . . . 84
    • 4.2 Theoretical predictions for CP averaged branching fractions of K K signal decay modes. . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
    • 2.1 Layout of the LHC . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
    • 2.2 LHCb integrated and instantaneous luminosities. . . . . . . . . . . . 28
    • 2.3 Diagram of the LHC complex. . . . . . . . . . . . . . . . . . . . . . . 29
    • 2.4 Vertical cross section of the LHCb detector. . . . . . . . . . . . . . . 29
    • 2.5 Simulated bb production angles at LHCb. . . . . . . . . . . . . . . . 30
    • 2.6 Luminosity levelling . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
    • 2.7 VELO (x,z) cross section showing sensor plane positions. . . . . . . . 33
    • 2.8 The VELO R and sensor planes. . . . . . . . . . . . . . . . . . . . 34
    • 2.9 Summary of the material budget of the VELO. . . . . . . . . . . . . 35
    • 2.10 Material scan of VELO upstream sensors and RF foil . . . . . . . . . 36
    • 2.11 The relative layout of the TT, IT and OT . . . . . . . . . . . . . . . 36
    • 2.12 RICH Cherenkov angles vs. momentum, and a typical LHCb event in RICH1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
    • 2.13 Sketch of the LHCb magnet . . . . . . . . . . . . . . . . . . . . . . . 38
    • 2.14 Channel density of the LHCb calorimeters . . . . . . . . . . . . . . . 39
    • 2.15 Side view of the LHCb muon system . . . . . . . . . . . . . . . . . . 41
    • 2.16 Flow chart of the LHCb trigger system. . . . . . . . . . . . . . . . . 42
    • 3.1 Simulation and collision data for B0 ! KS0 + MC, Bs0 ! KS0K MC and KS0 + tted. . . . . . . . . . . . . . . . . . . . . . . . . . 54
    • 3.2 sPlots of B impact parameter 2 distributions . . . . . . . . . . . . 56
    • 3.3 sPlots of B end vertex 2 distributions . . . . . . . . . . . . . . . . . 56
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