Status of BESIII Event Reconstruction System

BESIII offline software group 2006.10.31

BESIII ExperimentMuon Chamber (MUC)RPC based TOF SystemT = 90 ps barrel 110 ps endcapMain Drift Chamber (MDC) xy = 130 mP/P = 0.5 %@1 GeVdE/dx = 6-7 %

EM Calorimeter (EMC)E/E = 2.5 % @ 1 GeV z, = 0.6 cm @ 1 GeV Super-conducting Magnet1.0 Tesla

Offline software BOSS BES Offline Software Systembased on Gaudi.

Reconstruction

Calibration & Database

Framework Core Software

Simulaton

Physics AnalysisSoftware

BES III Software

CalibrationRecon. and simulation algorithms retrieve calibration data from calibration data storeCalibration constants are stored in ROOT files

The BESIII Event Reconstruction Modules and General FlowEventStartTime(Fast-tracking, PID,EST )MDC Tracking EventStartTimeTrack Fitting (Kalman Filter) dE/dx Rec.(Particle ID) Track Ext.TOF Rec.EMC Rec.MuC Rec. Veefind EvtvertTrack Matching

MDC Fast Tracking ModuleTrack parameters: d0 , 0, , dz , tg

MDC Fast Tracking Module(based on Belle Lib. developed by xiaomei zhang)

x160 mz 6mmp 10MeVTrk Eff 99%

x160m

z6mm

p10MeV

data unpacking

axial segments finding

stereo segments finding

2D track finding

2D track fitting

3D track finding

S_Z track fitting

TEST (Event Start Time) ModuletevTDCM(TOF)TOFTestTrigger Clock (24ns)Bunch(8ns)REF(2ns)TDCM(MDC)MDCThe TEST is important for the momentum Res., spatial Res. of the charged particles, but it is uncertain in the online system due to: 1) The BESIII trigger system cant separate every event up to beam bunch.2) The start time of charged event is determined by TOF_T, but the TOF reach time is different for different particle and different momentum. TEST should be calculated by offline system.

TEST (Event Start Time) Flow

Have TOFInformation ?2.Calculate Test by TOF Inf. And MDC Fast tracking Inf.3. Calculate Test by MDC Inf.And Fast tracking Inf. TOFNoTOFMDC Fast Rec.Information?4. Calculate Test Only by MDC Inf.YesNoYesMDC Fast ReconstructionNoYesCalculate Test by straight line segments fitPID

TOF: 96.78%MDC: 3.22% Segment FitTest Eff. : 100%Preliminary Result of TESTMuon ,Test=0ns,8ns,16ns, 5000 eventsTOF: 97.2%MDC: 2.6% Segment Fit:0.2%Test Eff. : 96.4%error0.63%e+e-hadrons ,Test=0ns,8ns,16ns, 5000 events

Mdc Tracking AlgorithmTwo algorithms for MDC track reconstruction: TrkReco & MdcPatRec

MDC Tracking Module(1) (based on Belle Lib.)Init: Geometry-Survice., Cal.-Const., Adjust-constant Get Hit Information R- Tracking: segment finding by conformal transformation and histogram methodZ Finding 3D Helix FitConformal transformationS-Z calculation in Z finding

Segment Finding Algorithm

Conformal transformation. A circle which passes through the origin is transformed into a line.Segments found by histogram of hit wires azimuthal angle Track linking from the outmost to the innermost layer with the directions of segments and apply the circle fit.

MDC Tracking Module(2) (based on Babar Lib. )Init: Geometry-Survice., Cal.-Const., Adjust-constant Get Hit Information Segment finding: Search segments in each super-layer using a pattern look-up tableTracking: Link segments to 2D tracks, add stereo segments3D Helix FitSequence of segment Finder

For every superlayer,every wire in 2nd Layer form a group of 8 wires

For every groupSet massage of segment list(1) Try 4 hit pattern for group(2) Try 3 hit pattern for groupWires No. 0-7 Set one word for a group of 8 wire, each bit for a wire. Set 1 for a hit wire, others 0 This octal value used for its group No.

- at pt = 1GeVMomentum resolutionp = 0.40%Preliminary Result of MDC tracking- at Pt = 1GeVspatial resolution ~= 110mSpatial resolution Momentum resolution

Preliminary Result of MDC trackingEfficiency vs Pt (e-,-,,p)Efficiency > 95% for single track Pt > 200MeVd0: signed distance from the pivot to track in x-y planez0: signed distance from the pivot to track in z direction 0.1 mm 0.8 mm

Parameters of a track before KalFit & after KalFit(proton 300Mev)Kalman filter tracking fitting ModuleThe MDC reconstruction results are not very good, have to do KalFit: multiple scatteringenergy lossesnon-uniform magnetic fields

dE/dx ModulePrinciple: P = mdE/dx codes developed successfully, released for physics study.

Particle ID is tested with MC samples, dE/dx resolution, distributions, PID efficiency is reasonable. MDC trackingdE/dx~f(v)

Particle type info

Overview of the software

MdcDedxRecon

DedxCalibAlg

Calibration const

CalibDataSvc

DedxCorrecSvc

EventDataSvc

Transient Data Store

Transient Calib Data Store

DST

converter

MdcGeomSvc

converter

Pre. Performance of dE/dxdE/dx seperation for 5 particles(MC) seperation power with dE/dxGood particle seperation in a wide range for different particlesThe /K seperation(3 ) reach about 800 MeV/cParticle identification efficiency is more than 90% with MC samples

Track Extrapolation Module Function: Extrapolate MDC tracks to Outer detectors: TOF, EMC and MUC Algorithm: based on GEANT4, Energy loss and Magnetic field. Multiple scattering effect put into error matrix.

TOF Reconstruction ModuleInitialize()finalize()execute()TofGeomSvcTofCalibSvcGet DataGet TracksMake HitsMatch Hits and TracksReconstructed Tof TracksData baseTDSTDSTof TracksMDC TracksTof DigitsCalibration constants Geometry data

Primary TOF Recon. Result beta vs momentumtime resolution:113ps Reconstruction Efficiency : 99.82% (1 GeV electron data)

EMC Reconstruction ModuledigithitclustershowerEMC is used to measure energy and position of electrons and photons, and to provide neutral energy trigger

Pre. Performances of EMC single gamma with 0.5MeV noiseE/E2.2%@1GeVthetaphiRecon Effi. of 0

Muc Reconstruction Module Use Ext Track from Mdc as seed; Compare with Mc truth;

Pre. Performances of Muc / IdentifcationRatio %p (GeV/c)9070With different 504030

SummaryBased on Gaudi, the BESIII offline software system (Boss) has developedSimulationReconstructionCalibration systemPhysics analysisAll sub-system work well on the Boss 6.1.0, got the Pre. Performance by the simple data sample, and passed the checking by typical physics channel.More works need to do to make each code work in the best status by closely the data to real data case step by step, such as: noise study, NUMF and low momentum tracking and S-T relation in MDC etc. Data challenge and software performance optimization are the major task in the next step.