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Kalanand Mishra University of Cincinnati

Kalanand Mishra University of Cincinnati. Branching Ratio Measurements of Decays D 0 π - π + π 0 , D 0 K - K + π 0 Relative to D 0 K -  +  0 decay. Initial Goal for this Analysis :.

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Kalanand Mishra University of Cincinnati

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  1. Kalanand MishraUniversity of Cincinnati Branching Ratio Measurements of Decays D0π-π+π0, D0K-K+π0 Relative to D0K-+0 decay Kalanand Mishra

  2. Initial Goal for this Analysis : Measuring the Relative Branching Fractions for the Cabibbo-suppressed modes (D0-+0 & D0K-K+0) relative to the Cabibbo-favored mode D0K-+0: (a) BR(D0π-π+π0) / BR(D0K-π+π0) (b) BR(D0K-K+π0) / BR(D0K-π+π0) using 230 fb-1 data collected by the BaBar detector at the PEP-II B Factory at SLAC during runs 1,2,3,4 (May 1999 - August 2004). Kalanand Mishra

  3. The Decay Chain We search for decays of type D*+D0s+ D0-+0 , D0K-K+0 , D0K-+0 0 • The D*+ is produced at interaction point from the ccbar continuum, and they have a negligible life-time. • “ s” is a “slow pion”, produced with very low momentum. • D0-+0, D0K-K+0 are Cabibbo-suppressed decay modes. • D0K-+0 is the Cabibbo-favored decay mode. We use this mode as normalization channel for the ratio of BRs measurement. • As usual (!), the CP conjugate mode is implied. Kalanand Mishra

  4. B-Factory at SLAC Record: L=9.2x1033 cm-2 s-1 ILER=2450 mA, IHER=1550 mA, 1588 bunches (1x1033 cm-2 s-1 ~ 1 B pair/s) 232M B pairs PEP-II accelerator schematic and tunnel view 9 GeV e- 3.1 GeV e+ Kalanand Mishra

  5. BaBar Detector Electromagnetic CalorimeterE/E = 3.0%, , = 4 mrad 1.5 T solenoid e+ (3.1 GeV) Cerenkov Detector(DIRC)c = 2.5 mrad e-(9 GeV) Drift Chamberpt/p = 0.5% Instrumented Flux Returnmuon and KL detector Silicon Vertex Tracker z=65m, d0=55m Kalanand Mishra

  6. Data Samples • Most ( ~ 90% ) data is taken at (4S) resonance • Integrated Luminosity ~ 230 fb -1(ON + OFF Resonance) • We use both on-resonance and off-resonance data for this analysis • For Background studies and cut optimization : Continuum Monte Carlo : ccbar ~ 179 million • For detection efficiency: Signal Monte Carlo : ~ 1.4 million for K-K+0 ~ 3.5 million for -+0 ~ 4.5 million for K-+0 Kalanand Mishra

  7. Track Selection • Kaon & pion tracks • Transverse momentum of the track > 0.10 GeV/c • Number of drift chamber hits ≥ 12 • ≥ 2 SVT r-phi (z) hits with at least 1 hit on inner 3 r-phi (z) layers • ≥ 6 total SVT hits • soft track • No requirement on drift chamber hits • ≥ 2 SVT r-phi (z) hits with at least 1 hit on inner 3 r-phi (z) layers • ≥ 6 total SVT hits • 0 Reconstruction •  Candidates with  Single calorimeter bumps not matched with any track  Energy of each photon > 100 MeV • 0 Energy > 0.350 GeV • 0.115 GeV/c2 < M  < 0.160 GeV/c2 Kalanand Mishra

  8. Particle Identification Charged particle Candidates are identified by means of measured energy-loss (dE/ dx) in drift chamber together with information from particle identification system (DIRC).For each particle hypothesis ( , K, p, , e ) a likelihood is calculated based on these informations. We use a strict likelihood for kaon and pion charged tracks.  Pion PID  Kaon PID Kalanand Mishra

  9. D0h-h+0 Reconstruction • Multi-hadron events with at least three charged tracks • h- and h+ tracks are fit to a vertex • Mass of 0 candidate is constrained to m0 at h-h+ vertex • Unconverged fits are rejected • 1.70 GeV/c2 < M ( h-h+0 ) < 2.0 GeV/c2 • PCM ( D0 ) > 2.77 GeV/c D* Reconstruction: • D*+ candidate is made by fitting the D0 and the s+ to a vertex constrained in x and y to the measured beam-spot for the run. • |mD* - mD0 - 0.1455| < 0.001 GeV/c2 • D*+ vertex 2 < 20.0 • Unconverged fits are rejected Kalanand Mishra

  10. -+0 mass plot -+0 mass plot from real data showing the signal (yellow color) and side band (red color) regions. Kalanand Mishra

  11. Multiple Candidates • We observed multiple D0h-h+0 candidates per event with multiplicity ~ 7 - 8 % (ie, average 1.07 - 1.08 candidates/event). • With tighter (< 1 MeV) mD* - mD0 cut, the multiple candidates decrease to ~ 3% level. • Multiplicity due to following reasons : • Right D0 combined with a fake soft+ to make a D*+ . • Charged track combinatorics. • More than one 0 candidates with or without a shared photon. • Fake / mis-constructed 0 • Select the D0 candidate which has the smallest 2 at D* vertex. • By looking at Monte Carlo we see that ~ 60 % of the time we choose the correct candidate. Kalanand Mishra

  12. Mass plots for the three modes K-+0 -+0 K-K+0 Data Ccbar Signal MC Kalanand Mishra

  13. K-+0 yield K-+0 mass distribution (dots) and the result of the fit (blue line) with three Gaussians for the signal and a second order polynomial term for the background (broken red line). Kalanand Mishra

  14. -+0 yield -+0 mass distribution (dots) and the result of the fit (blue line) with two Gaussians for the signal and an exponential term for the background (red broken line). No specific fit for the reflection peak in the plot on left. I take the yield from the fit on right. I am still trying to understand and include in fit the reflection peak in the lower side band. Kalanand Mishra

  15. Reflection Study K-+0 reflection in -+0 sample. We get the shape of the reflection from Monte Carlo (left) and the number of reflection events from data (right). Kalanand Mishra

  16. K-K+0 yield K-K+0 mass distribution (dots) and the result of the fit (blue line) with two Gaussians for the signal and an exponential term for the background (yellow color/ broken red line). No specific fit for the reflection peak in the plot on left. I take the yield from the fit on right. I am still trying to understand and include in fit the reflection peak in the upper side band. Kalanand Mishra

  17. Efficiency Calculation Left: K-+0 mass distribution (dots) and the result of the fit (blue line) with three Gaussians for the signal and a second order polynomial term for the background (yellow color). 282068 signals selected out of 4672000 generated. Efficiency ~ 6.0% Middle: -+0 mass distribution (dots) and the result of the fit (blue line) with two Gaussians for the signal and an exponential term for the background (red broken line). 234435 signals selected out of 3466000 generated. Efficiency ~ 6.8% Right: K-K+0 mass distribution (dots) and the result of the fit (blue line) with two Gaussians for the signal and an exponential term for the background (yellow color). 66235 signals selected out of 1362000 generated. Efficiency ~ 4.9% Kalanand Mishra

  18. Dalitz plot for -+0 (Monte Carlo) Kalanand Mishra

  19. Systematic Studies • Systematic checks fall into two categories: • “sanity” checks • systematic variations which include lack of knowledge/ understanding and biases in the fit model • First class demonstrates reasonableness of result • Latter class determines quantitative estimation of the systematic error Reasonableness Checks I plan to: • Separate analysis in different momentum bins. • Separate analysis by charge (ie, D*+ and D*- ) • Systematic Errors • I have studied difference in yield due to different fits • I plan to calculate efficiency as function of position on Dalitz plot. • PID corrections for efficiencies. Kalanand Mishra

  20. Very Preliminary Result BR(D0ppp)/BR(D0pp) = (6.51 ± 0.04) X 10-2 BR(D0K-K+p)/BR(D0pp) = (2.31 ± 0.03) X 10-2 • Investigate systematics associated with the analysis. Uniform efficiency across Dalitz plot is an approximation. I need to calculate efficiency as function of position on Dalitz plot and correctly account for contributions from other side of charm decay in Signal Monte Carlo when calculating the efficiencies. • Finish this analysis (new version of Babar Analysis Document 841) without delay. • Extension of present analysis to a full Dalitz plot analysis of Cabibbo-suppressed decays D0h-h+0to include these results in the study of B-D(*)0 K-with the same D0 decay as this analysis, which will be useful to constrain the third angle of unitarity triangle g • Final analysis with double the present data size ~ 450 fb-1 (which we hope to accumulate by summer 2006 ). Kalanand Mishra

  21. What is Next ? Dalitz analysis for CP phase g s K- u bc b c B- D0 u u g b u bu D0 c B- s K- u u p0p+p- Final production amplitude Kalanand Mishra

  22. Backup slides Kalanand Mishra

  23. Service Work • As our commitment towards smooth running of BaBar detector, we are required to undertake service works in the area of our expertise. • University of Cincinnati group has always been very active in BaBar collaboration - providing leadership role in DIRC, Particle ID, and and Data Quality groups. • At present I am BaBar DIRC operations manager (March - December, ‘05). I was earlier a DIRC commissioner ( December ‘04 - March ‘05). • I am one of the members of BaBar Particle ID team and very recently completed a major project for the group. Kalanand Mishra

  24. DIRC is FineTM ! Nicolas & Kalanand Nicolas & Kalanand Breaking News! DRC-mon migrated to new version of EPICS Kalanand Mishra

  25. BaBar PID: Automated fast PID-table production (ROOT-based) • New BaBar Particle ID tables successfully made entirely using ROOT -based procedure (major part of code written by me). • One unified procedure to make PID tables, manage the PID-tables inventory, produce efficiency plots for each selector within a few hours for each run of a release. • This major project has been characterized as “The Hall Of Fame - Successfully completed Project” by BaBar PID group on their web page: http://www.slac.stanford.edu/BFROOT/www/Physics/Tools/Pid/tasks.html Kalanand Mishra

  26. Fit Strategy We perform an extended maximum likelihood fit on the data to determine the number of signal and background events. • From the selected events in the mD0 - m window, determine • signal and background levels in mass plots by fitting with the • following distribution: • Fitted with three gaussians signal & a 2nd order polynomial background • The mean’s and the σ 's of the three gaussians are allowed to be different Kalanand Mishra

  27. Background Sources • Combinatoric • Real D0, fake s • Fake / mis-constructed p0 • Kpp0 reflection in ppp0 and KKp0 modes Bottom line: Our analysis is dominated by systematics and NOT by Statistics Kalanand Mishra

  28. BaBar Detector • The BABAR detector is located at Stanford Linear Accelerator Center (SLAC) • Taking data since May 1999 • We use 228.8 fb-1 of data taken till now for this analysis • PEPII is an asymmetric collider • Electron beam is 9.0 GeV (High Energy Ring), positron beam is 3.1 GeV (Low Energy Ring ) • Most data is taken at (4S) resonance • We use both on-resonance and off-resonance data Kalanand Mishra

  29. Detectors used in this analysis The Silicon Vertex Tracker (SVT) provides vertexing information and stand-alone tracking for low momentum particles. The Drift Chamber provides momentum information and dE/dx information to identify particles with transverse momentum < 0.7 GeV/c. The Particle Identification System (DIRC) uses Cerenkov Radiation to identify particles with transverse momentum > 0.7 GeV/c Kalanand Mishra

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