Presentation on theme: "June 9, 20041 Tetsuro Sekiguchi, KEK BNL-E949 Collaboration The E949 experiment The analysis The results Conclusions BNL, FNAL, UNM, Stony Brook Univ."— Presentation transcript:
June 9, 20041 Tetsuro Sekiguchi, KEK BNL-E949 Collaboration The E949 experiment The analysis The results Conclusions BNL, FNAL, UNM, Stony Brook Univ. (USA) Alberta, TRIUMF (Canada) IHEP, INR (Russia) Fukui, KEK, Kyoto, NDA, Osaka, Osaka RCNP (Japan)
June 9, 20042 BNL-E949 = Successor of E787 side viewend view Signal = Stopped + nothing Low energy beam and stop in the target (intensity = E787) Kinematics measurement momentum, energy and range in the stopping counter Photon veto hermetic detectors
June 9, 20043 Improved kinematics measurement Kinamatics measurement is sensitive to signal selection RS Layer 1-5 replacement more light output RS gain monitor system better energy calibration
June 9, 20044 Improved photon veto Rejection to background as a function of acceptance for E787 and E949. better rejection at 80% of nominal acceptance. New detectors in blue.
June 9, 20045 Data Taking Physics run in 2002 (12 weeks) Beam condition was not optimized Detector worked very well Smooth data taking
June 9, 20046 Analysis Signal region “the BOX” Background sources Analysis Strategy Blind Analysis Measure Background level with real data To avoid bias, 1/3 of data cut tuning 2/3 of data background measurement Characterize backgrounds using back- ground functions Likelihood Analysis
June 9, 20047 Background characterization Background can be characterized using background functions For muon backgrounds Neural net function for and but range is small due to interactions in RS. Changing cut position Acceptance & background level at each point of parameter Functions
June 9, 20048 Likelihood Analysis Branching ratio and Confidence level Both and are small Poisson statistic The ratio of two Poisson probabilities # of observed candidate events in the cell The signal region is divided into cells. C ell construction by binning the parameter space of each function. The signal and the background in the cell The cell is characterized by the signal to background ratio Likelihood ratio technique (T. Junk [NIM A434, 435 (1999)]) (BR) ( : Acceptance) Likelihood estimator of cells containing candidate events
June 9, 20049 For the likelihood analysis, important is the ratio in each cell NOT the total background level in signal region. Sensitivity and background Sensitivity Background Note: 10% larger acceptance by enlarging the signal region, resulting in more backgrounds All cuts are fixed and ready to open the BOX ! Total acceptance (%) Sensitivity (10 -10 ) N K (10 12 )
June 9, 200410 Opening the BOX Range (cm) and Energy (MeV) for E949 data after all other cuts applied. Solid line shows signal region. Single candidate found.
June 9, 200412 Branching ratio & Confidence level (68% CL) E949(02) = combined E787&E949. E949 projection with full running period. (~60 weeks) E949 result alone: Combine E787 and E949 results increase statistics
June 9, 200413 Conclusions Upgrades of E787 to E949 were successful. Likelihood analysis was performed to measure E949 has observed an additional candidate. (68% CL, PNN1 region) from the combined E787 and E949 result. We need more data. - Analysis of “ below(PNN2) region ” - Further E949 running?
June 9, 200419 Signal rate and background level for the candidate cell Signal S i Background b i
June 9, 200420 Acceptance calculation Cross check
June 9, 200421 Verify background prediction by loosening cuts Cut R = PV or TD: loosen by Cut K = KIN: loosen by more background event should be observed in loosened BOX. ( )
June 9, 200422 Branching ratio and confidence limits 2002 candidate event alone Branching ratio: Combined measurement (1995-2002) Combined BR:
June 9, 200423 Likelihood Analysis with T. Junk method The Poisson probability to observe d i with S i + b i or b i expected S i (BR) BR : signal BR: N K : # of Kaon decay A i : Acceptance b i : background d i : # of observed events
June 9, 200424 Likelihood Analysis with T. Junk method Summing all the set d i to satisfy Then obtain the confidence level