Theoretical Motivation Analysis Procedure Systematics Results David Doll
- Slides: 12
Theoretical Motivation Analysis Procedure Systematics Results David Doll, on behalf of the Ba. Bar Collaboration 1 APS 04/12/08
Theoretical Motivation Standard Model BF *535 M Experimental Limit on BF (90% CL)* ar. Xiv: 0708. 4089 v 2 [hep-ex], PRL 99, 221802 (2007) pairs at Belle • Highly suppressed Flavor Changing Neutral Current • Not well constrained experimentally • Several models enhance BF(Unparticle Model, MSSM at large tan β, …) Ba. Bar’s previous best upper limit is 7. 8 x 10 -5 for semileptonic tags with 81. 9 fb-1 Current analysis at 319 fb-1 2 APS 04/12/08
Analysis Procedure, Tagging Perform a ‘semileptonic’ tagged analysis ◦ Fully reconstruct the ‘tag B’ in the decay ◦ Look at the rest of the event for our signal Tag B B+ Signal B B- 3 APS 04/12/08
Random Forest (RF) Use a multivariate analysis tool from Stat. Pattern. Recognition (ar. Xiv: physics/0507143 v 1) Sampling with replacement of both the training data and the input variables (bagging) Optimize the ‘Punzi’ Figure of Merit The important input variables: number of charged tracks in the signal B (opposite the ‘tag B’) the missing energy in the event the signal Kaon candidate’s momentum the unmatched neutral energy in the event 4 APS B->Knunu 04/12/08
Final Predictions, Continuum Use sideband region in the continuum data in the signal region from amount of data in sideband RF continuum est. Estimate sideband 5 APS B->Knunu 04/12/08
Final Predictions, Peaking estimate from RF output, separated into sideband/signal regions Subtract sideband from signal region in both Data and MC and take the ratio MC: Data Extrapolate a line into the signal region trendline signal region 6 APS B->Knunu 04/12/08
Background Systematics Continuum systematic from difference between MC and data Peaking background systematic from difference between the a trendline fit to all the MC: Data, vs. a trendline fit to just the peaking component (above) We also take a systematic based on our MC weighting procedure. MC Background prediction Statistical Uncertainty Systematic uncertainty 7 APS B->Knunu 04/12/08
Control Sample • Both Bs decay semileptonicly requiring: • no remaining charged tracks in the event • momentum of each lepton>1. 24 Ge. V/c • Resolved differences between signal MC and double tag data: • particle substitutions • kinematic corrections • brute force variable redistribution. • Serves as control sample for evaluating systematics for the multivariate analysis. B+ B 8 APS B->Knunu 04/12/08
Signal Systematics Tagging Efficiency: Taken from ratio below in which both tags are Kaon Momentum: Evaluated by comparing phase space theory with SM-predicted theory 9 APS B->Knunu 04/12/08
Signal Systematics Correlations Variables: btwn. ◦ 1 -D distributions already resolved ◦ Need to account for correlations in order use the control sample to evaluate signal box efficiency in signal MC 10 APS B->Knunu 04/12/08
Signal Systematics Signal Box Eff. : ◦ Retrain RF with double tag MC control sample substituted for signal MC ◦ Evaluate systematic by comparing efficiency of the RF cut on double tag MC to double tag data Ntrkleft=1: ◦ The control sample identified with this cut, not present in signal MC ◦ Evaluate systematic from separate rectangular cut based investigation 11 APS B->Knunu 04/12/08
Results Upper limit at the 90% confidence level Expect 30. 7 +/- 10. 7 events, corresponding to an upper limit of 2. 9 x 10 -5 Inside the RF box, we saw 38 events, which gives an upper limit: 12 APS B->Knunu 04/12/08
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