6,092 research outputs found
Resonant-frequency-dependent flux noise of a high-T-C rf SQUID coupled to a substrate resonator
No full textIs there an ethnic difference in the prevalence of lupus cystitis? A report of six cases
No full text
Multifunctional design of high-transition-temperature directly coupled superconducting-quantum-interference-device magnetometers on a chip
No full textGöteborgs-Tidningen, Utkommer Kl.12 middagen
No full textGÖTEBORGS-TIDNINGEN, UTKOMMER KL.12 MIDDAGEN
Göteborgs-Tidningen, Utkommer Kl.12 middagen ( -
Search for KL decay to light pseudoscalar sgoldstino at E391a
No full text本論文尋找可能的中性K介子衰變至pi0介子以及輕準純量goldstino(代稱X粒子)。所使用數據來自日本國家高能加速器心質子加速器的E391a 偵測器，於九十四年二月至三月間取。由事例重建，我們針對四組可能的質量範圍搜尋，並無發顯著訊號，因此給予90%信心水準之衰變分率上限，分別為r(KL->pi0X(181.7 MeV)) < 2.26e-6r(KL->pi0X(198.0 MeV)) < 1.97e-6r(KL->pi0X(214.3 MeV)) < 1.81e-6r(KL->pi0X(230.6 MeV)) < 1.17e-6With mX = 214.3 MeV as hinted by a previous HyperCPxperiment, we report the first search of the decay KL->pi0X sing the Run2 data sample recorded with the E391a detector t KEK-PS. The particle X has a theoretical interpretation as he pseudoscalar sgoldstino. It is predicted to decay redominantly to two photons. As a result of this search, weet a 90% confidence-level upper limit for its branching atio at B(KL->pi0X)<1.81e-6. We also performed a search for he same mode assuming different mX: 181.7MeV, 198MeV, 30.6MeV and set respective 90% confidence-level upper imits: B(KL->pi0X181.7)<2.26e-6,(KL->pi0X198.0)<1.97e-6 and B(KL->pi0X230.6)<1.17e-6. TheL flux for the E391a Run2 data set is also measured to be (4.83+-0.21)e9 in the fiducial region.Introduction 1.1 The X particle - HyperCP experiment . . . . . . . . . . . . . 1.2 The sgoldstino interpretation . . . . . . . . . . . . . . . . . . 1.3 The Higgs boson interpretation . . . . . . . . . . . . . . . . . 4.4 Hints at decay K0L 0X(X ! - KTeV and NA48 experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 K mesons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Thesis outline . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 KEK E391a 8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 The Neutral Beam . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1 Particle Generation . . . . . . . . . . . . . . . . . . . . 8.2.2 The Pencil Beam . . . . . . . . . . . . . . . . . . . . . 9.3 The E391a Detector . . . . . . . . . . . . . . . . . . . . . . . 10.3.1 Electromagnetic Calorimeter . . . . . . . . . . . . . . . 11.3.2 Charged Veto . . . . . . . . . . . . . . . . . . . . . . . 14.3.3 Main Barrel . . . . . . . . . . . . . . . . . . . . . . . . 17.3.4 Front Barrel . . . . . . . . . . . . . . . . . . . . . . . . 21.3.5 Collar Counters . . . . . . . . . . . . . . . . . . . . . . 22.3.6 Back Anti . . . . . . . . . . . . . . . . . . . . . . . . . 24.3.7 Beam Hole Charged Veto . . . . . . . . . . . . . . . . . 25.4 Vacuum System . . . . . . . . . . . . . . . . . . . . . . . . . . 25.4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . 27.4.2 PMT operation in vacuum . . . . . . . . . . . . . . . . 27.5 Triggering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.5.1 AmpDiscri module . . . . . . . . . . . . . . . . . . . . 29.5.2 Physics trigger . . . . . . . . . . . . . . . . . . . . . . 29.5.3 Other triggers . . . . . . . . . . . . . . . . . . . . . . . 32.5.4 Data Acquisition . . . . . . . . . . . . . . . . . . . . . 33.6 Data Sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33.6.1 Data taking shifts . . . . . . . . . . . . . . . . . . . . . 34 Monte Carlo Simulation 36.1 Particle generation . . . . . . . . . . . . . . . . . . . . . . . . 36.2 KL propagation and decay . . . . . . . . . . . . . . . . . . . . 37.3 Decay modes and statistics . . . . . . . . . . . . . . . . . . . . 37.3.1 Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . 38.4 Energy deposit . . . . . . . . . . . . . . . . . . . . . . . . . . 38.5 Accidental activity . . . . . . . . . . . . . . . . . . . . . . . . 40.6 Combination of modes . . . . . . . . . . . . . . . . . . . . . . 40 Analysis Method 41.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.2 Event Reconstruction . . . . . . . . . . . . . . . . . . . . . . . 42.2.1 Clustering routine . . . . . . . . . . . . . . . . . . . . . 42.2.2 Kinematic reconstruction . . . . . . . . . . . . . . . . . 43.2.3 Reconstruction results . . . . . . . . . . . . . . . . . . 52.3 Candidate Selection . . . . . . . . . . . . . . . . . . . . . . . . 52.3.1 Signal box . . . . . . . . . . . . . . . . . . . . . . . . . 52.3.2 0 region . . . . . . . . . . . . . . . . . . . . . . . . . . 53.4 Background Suppression . . . . . . . . . . . . . . . . . . . . . 53.4.1 Veto cuts . . . . . . . . . . . . . . . . . . . . . . . . . 54.4.2 Kinematic and MB cuts . . . . . . . . . . . . . . . . . 56.4.3 Cluster quality . . . . . . . . . . . . . . . . . . . . . . 60.4.4 0 tail . . . . . . . . . . . . . . . . . . . . . . . . . . . 63.4.5 KL radius at the exit of collimator 6 . . . . . . . . . . 63.4.6 Selection results . . . . . . . . . . . . . . . . . . . . . . 63 Signal Extraction 66.1 Likelihood Method . . . . . . . . . . . . . . . . . . . . . . . . 66.1.1 De nition . . . . . . . . . . . . . . . . . . . . . . . . . 66.1.2 Background PDF . . . . . . . . . . . . . . . . . . . . . 67.1.3 Background normalization . . . . . . . . . . . . . . . . 69.1.4 Signal PDF . . . . . . . . . . . . . . . . . . . . . . . . 70.1.5 Fit results . . . . . . . . . . . . . . . . . . . . . . . . . 70pper Limit Estimation . . . . . . . . . . . . . . . . . . . . . 71.2.1 Systematic error study . . . . . . . . . . . . . . . . . . 71.2.2 Implementation of systematic errors . . . . . . . . . . . 75.2.3 Final tting results . . . . . . . . . . . . . . . . . . . . 75.3Counting Method . . . . . . . . . . . . . . . . . . . . . . . . . 77.4KL Flux . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78onclusions and Prospects 81.1Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.2Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.2.1 Increased data statistics { Run3 data set . . . . . . . . 82.2.2 Increased MC statistics . . . . . . . . . . . . . . . . . . 83.2.3 Finer CsI crystals { E14 experiment . . . . . . . . . . . 84 0Monte Carlo 89inematic Fitting 9
Buchhandlung, Papier, E. Malsch, Berlin-Schöneberg, 8. Lektüre-Mietbücherei Kl.
No full textBUCHHANDLUNG, PAPIER, E. MALSCH, BERLIN-SCHÖNEBERG, 8. LEKTÜRE-MIETBÜCHEREI KL.
Buchhandlung, Papier, E. Malsch, Berlin-Schöneberg, 8. Lektüre-Mietbücherei Kl. ( -
- …
