BESIII offline software group Status of BESIII Event Reconstruction System

BESIII Experiment Muon Chamber (MUC) ： RPC based TOF System ：  T = 90 ps barrel 110 ps endcap Main Drift Chamber (MDC) ：  xy = 130  m  P/P = 0.5 GeV  dE/dx = 6-7 % EM Calorimeter (EMC) ：  E/E = GeV  z,  = GeV Super-conducting Magnet ： 1.0 Tesla

Offline software BOSS – BES Offline Software System based on Gaudi.

 Recon. and simulation algorithms retrieve calibration data from calibration data store  Calibration constants are stored in ROOT files Calibration constants (ROOT) MySQL database CalibFunc Svc Calibration Data Service Reconstruction algorithm CalibRoot CnvSvc Simulation algorithm GUI Client Calibration Algorithm

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

Track parameters: d 0, Ф 0, Κ, d z, tgλ MDC Fast Tracking Module

T EST (Event Start Time) Module t ev TDCM(TOF) TOF T est Trigger Clock (24ns) Bunch (8ns) REF (2ns) TDCM(MDC) MDC The T EST 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 can’t 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. T EST should be calculated by offline system.

T EST (Event Start Time) Flow Have TOF Information ? 2.Calculate T est by TOF Inf. And MDC Fast tracking Inf. 3. Calculate T est by MDC Inf. And Fast tracking Inf. TOFNoTOF MDC Fast Rec. Information? 4. Calculate T est Only by MDC Inf. Yes No Yes MDC Fast Reconstruction No Yes 1.Calculate T est by straight line segments fit PID

TOF: 96.78%MDC: 3.22% Segment Fit T est Eff. : 100% Preliminary Result of T EST Muon,T est =0ns,8ns,16ns, 5000 events TOF: 97.2% MDC: 2.6% Segment Fit: 0.2% T est Eff. : 96.4% error ： 0.63% e+e-  hadrons,T est =0ns,8ns,16ns, 5000 events

Mdc Tracking Algorithm TrkRecoMdcPatRec PersonpowerZang S. L.(IHEP)Zhang X. Y.(SDU) Zhang Y.(SDU) Based onBelle reco. algorithmBaBar reco. algorithm Segment findingConformal transformPattern matching Track fittingLeast square method Two 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 method  Z Finding  3D Helix Fit Conformal transformation S-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 table  Tracking: Link segments to 2D tracks, add stereo segments  3D Helix Fit Sequence of segment Finder For every superlayer, every wire in 2 nd Layer form a group of 8 wires For every group Set massage of segment list (1) Try 4 hit pattern for group (2) Try 3 hit pattern for group Wires 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.

μ - at p t = 1GeV Momentum resolution σ p = 0.40% Preliminary Result of MDC tracking μ - at Pt = 1GeV spatial resolution σ ~= 110μm Spatial resolution Momentum resolution

Preliminary Result of MDC tracking Efficiency vs Pt (e -,μ -,π,p) Efficiency > 95% for single track Pt > 200MeV d 0 : signed distance from the pivot to track in x-y plane z 0 : 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 Module The MDC reconstruction results are not very good, have to do KalFit:  multiple scattering  energy losses  non-uniform magnetic fields ……

dE/dx Module  dE/dx codes developed successfully, released for physics study.  Particle ID is tested with MC samples, dE/dx resolution, distributions, PID efficiency is reasonable.  Principle: P =βγ · m MDC trackin g dE/dx~f(v) Particle type info

dE/dx seperation for 5 particles(MC) seperation power with dE/dx Pre. Performance of dE/dx Good particle seperation in a wide range for different particles The π/K seperation(3 σ ) reach about 800 MeV/c Particle 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 Module Initialize() finalize() execute() TofGeomSvc TofCalibSvc Get Data Get Tracks Make Hits Match Hits and Tracks Reconstructed Tof Tracks Data base TDS Tof Tracks MDC Tracks Tof Digits Calibration constants Geometry data

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

digithit cluster shower EMC Reconstruction Module EMC 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 noise σ E /E theta phi Recon Effi. of π0

Muc Reconstruction Module Use Ext Track from Mdc as seed; Searching hits gap by gap; Searching on Barrel first, then EndCap; Also Searching on neighboring segments; Line Fit with hits on track; Ext track Fired strips Window Barrel End Cap Compare with Mc truth;

Pre. Performances of Muc μ/π Identifcation μ efficiency π (fake μ ) Ratio % p (GeV/c) With different θ

Summary  Based on Gaudi, the BESIII offline software system (Boss) has developed  Simulation  Reconstruction  Calibration system  Physics analysis  All 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.