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BESIII dE/dx package: status and algorithm studies

BESIII dE/dx package: status and algorithm studies. WANG Dayong June 1,2005. Outline. dE/dx package:OO design and software development Calibration and systematic corrections Reconstruction algorithm studies: Different estimation of most prob Eloss Curve studies based on BESII data

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BESIII dE/dx package: status and algorithm studies

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  1. BESIII dE/dx package: status and algorithm studies WANG Dayong June 1,2005

  2. Outline • dE/dx package:OO design and software development • Calibration and systematic corrections • Reconstruction algorithm studies: • Different estimation of most prob Eloss • Curve studies based on BESII data • Resolution and residual bias correction

  3. dE/dx :Particle ID with energy loss measurements dE/dx~f(v) • Principle: P = · m Particle type info • Components: calibration and reconstruction • Implementation: C++ programming under BOSS framework • Design goal: Resolution 6—7%, good seperation MDC tracking

  4. Requirements and data flow MDC digits • AIM: to give the partID information from the list of pulse heights of hits on the MDC track, and store them into TDS • some corrections are performed to get unbiased dE/dx information. • Some proper dE/dx estimators are constructed MDC digits Transient Data Store (TDS) MDC Tracking Tracks Tracks MDC digits Tracks dE/dx Reconstruction Recon dE/dx Recon dE/dx Recon dE/dx Global Particle Identification partId info Apparent dataflow 。。。 Real dataflow physics analysis

  5. finally selected UML Class diagrams

  6. UML Sequence Diagram for dE/dx Reconstruction

  7. Some implementation features • Uniform interface: Alternative algorithms with the same interface • Uniform data I/O format: MDC recon data model: MdcRecEvent • Input from MC : MdcFakeData package

  8. Output:MdcDedx in MdcRecEvent • int m_id; • float m_dedx; // measured value of dE/dx • float m_dedx_exp[5]; // expected value of dE/dx for 5 particle hypotheses • float m_sigma_dedx[5]; // sigma value of dE/dx for 5 particle hypotheses • float m_pid_prob[5]; // probability for each of the 5 particle hypotheses • int m_stat; // status flag • SmartRef<MdcTrack> m_trk; // reference to the track

  9. Calibration issues • Systematic and run-by-run calibrations is important for dE/dx correction • Calibration consts ~7200 are designed • Calib consts stored in DataBase. They can be retrieved from DB in reconstruction now • In future, calib consts in ROOT format and DB only contains meta data

  10. dE/dx calibration and corrections • Gain variations among cells • Gas Gain variation within one cell • Sampling length corrections • Drift distance dependence • Longitude position(z) dependence • Dependence of the sense wire voltage • Space charge effect • Gas gain saturation : from electronics • Temperature,pressure and environmental effects • Corrections related to particle type • Variations of the pulse height run by run

  11. Algorithm studies: different estimation of most probable energy loss Landau distribution has no definite mean. The algorithm used must estimate the most probable energy loss • Truncated mean • Double truncated mean: truncate at both ends • Median • Geometric mean • Harmonic mean • Transformation: • Logorithm truncated mean: studies based on BESII data idea:these methods give less bias to large values,then the satured hits have less effect to give better shape and better seperation

  12. Different estimation of most probable energy loss: resolution(1) 5.51% 5.34% 0.05~0.75 truncation Truncation rate 0.7 6.06% 5.09% BOOST MC, MIP muon

  13. Different estimation of most probable energy loss: resolution(2) 5.44% 5.75% Truncation rate: 0.7 5.71% 2.61% BOOST MC, MIP muon

  14. Different estimation of most probable energy loss: seperation power(1) Pi/K Pi/P 0.7GeV 1.2GeV Pi/K Pi/P 0.7GeV 1.2GeV Pi/K Pi/P 0.6GeV 1.1GeV Pi/K Pi/P 0.75GeV 1.3GeV

  15. Different estimation of most probable energy loss: seperation power(2) Pi/K Pi/P 0.7GeV 1.2GeV Pi/K Pi/P 0.7GeV 1.3GeV Pi/K Pi/P 0.7GeV 1.3GeV Pi/K Pi/P 0.75GeV 1.3GeV

  16. Comparison of linear&logorithm TM • Logorithm TM(right figure),compared to plain TM(left figure): • Suppress high-end residual Landau tail • The distribution more Gaussian like BESII DATA, J/Psi hadrons shape is more Gaussian-like shape is more Gaussian-like Pull width: 1.020 0.9995 Pull width: 0.8477 0.9304 Cosmic rays Radiative Bhabha

  17. Study of truncated mean method • Well established method of dE/dx estimation • Simple and robust • Rejection of lower end hits to remove contributions from noise and background fluctuation • Truncation of higher tail to remove Landau tail due to hard collisions Just cooresponding to ~5% lower cut Landau tail After truncation, distribution just Gaussian-like BOOST MC, 1GeV electrons

  18. Resolution curve with different truncation rates • 70% truncation ratio is adopted for the algorthm • Number of good hits is required to no less than 10 for each track • Resolution from perfect MC consistent with empirical formula BOOST MC, 1GeV electrons

  19. Different most probable energy loss formulations(1) • Bethe-Bloch formula • Landau formula with density correction PAI: Photo-Absorption Ionization model Sternheimer correction : Cobb-Allison correction: A

  20. Different most probable energy loss formulations(2) B • Va’vra formulation • Other formulae

  21. dE/dx curve studies with BesII data • Purpose: • Comparison of different formula to find the best curve to calculate expectation in reconstruction • A test-bed for BESIII reconstruction • data samples used: Pion:J/Psirho+pi & J/PsiKKPiPi Kaon:J/PsiK*(892)+K(1430)KKPiPi Proton:J/psiPPbarPi0&J/PsiPPbarEta electron: (radiative) Bhabha muon: dimu +cosmic rays “Garbage” events: beam-gas protons, cosmic-rays, rad. Bhabha Example:Cuts for Bhabha • To get pure samples: • Use Tof and BSC information ONLY to identify particles • use relative probability only • Strict kinetic and invariant mass cut • The cuts are checked with GENBES

  22. Comparison between data and dE/dx curve • Sternheimer(A) is better at high momentum end • Va’vra(B) is relative better at low momentum end • Data need careful calibration • Practical global parameterization of curve is prefered Sternheimer B A Comparison of Sternheimer and Va’vra formula: A B

  23. Global 5-parameter fit for phmp_nml vs • binning with nearly the same statisticsat each point to reduce the error • Using garbage events in order to fastly calibrate this curve for BESIII in future • A uniform formula to avoid discrete expression for density effect • The curve fit the BESII data OK Beam-gas proton Radiative bb Cosmic rays

  24. Residual theta dependence before correction (Hadron events) After correction The correction is then parameterized and used in mass data process

  25. σdE/dx~hits number relationship Empirical formula : resolution resolution J/Psi dimuon events data of different momenta bins J/Psi radiative Bhabha events number of hits number of hits

  26. summary • OO designed BESIII dE/dx package now runs smothly under BOSS • Calibration algorithm are designed and many corrections considered • Different reconstruction algorithms are explored to get best performance • To reach design goals, there are still a long way to go

  27. Thank you谢谢！ Backed -up slides…

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