Software plenary, 16 February 2000 David Rousseau (LAL, Orsay) ID reconstruction plans ztrack reconstruction is well understood zseveral packages (2 C++) have been used znow: yadapt to new framework ymodularization yconvergence yimprove algorithms

Software plenary, 16 February 2000 David Rousseau (LAL, Orsay) ID reconstruction plans Track Track finding Track extrapolating Track fitting Roads Bad Channels Geometry (hits) Magnetic field Raw data Clustering Geometry (material) Calibrations

Software plenary, 16 February 2000 David Rousseau (LAL, Orsay) ID reconstruction plans Raw data and up zRaw data to be defined more precisely, in offline and event filter environment zDetector description: ydetector identifier is being exercised (iPatRec in PASO) ygeometry (nominal+alignments) handling to be done (CPU optimization …) yadditional information handling to be done: calibrations noisy/dead channels/modules...

Software plenary, 16 February 2000 David Rousseau (LAL, Orsay) ID reconstruction plans External seeds handling zRegion where track finding is done defined by other detectors and trigger (jet,lepton,LVL2 ROI…) zinterface to evolve constantly when output of other reconstruction is defined zconvergence required

Software plenary, 16 February 2000 David Rousseau (LAL, Orsay) ID reconstruction plans Track finding (I) zWealth of algorithms available yGeneral purposes (iPatrec(C++),xKalman/xKalman++) yMore specialized: Pixlrec,ASTRA,Xhourec yLVL2 algorithms (SCT-Kalman…) shall be run in offline framework

Software plenary, 16 February 2000 David Rousseau (LAL, Orsay) ID reconstruction plans Track finding (ii) zAlgorithms are sometimes quite different zbut using same utilities rewritten n times yconvergence on utilities yconvergence on algorithms not desirable ynew algorithms (or improvement to existing one) needed for: xnon-pointing tracks xvery low p T tracks (<0.5 GeV)

Software plenary, 16 February 2000 David Rousseau (LAL, Orsay) ID reconstruction plans Track extrapolation  extrapolating track parameters and (possibly) covariance matrix from a point to a piece of the detector, taking into account non-homogeneous magnetic field, energy loss, in a minimum amount of time zwell defined, but difficult task zconvergence on one or two tools

Software plenary, 16 February 2000 David Rousseau (LAL, Orsay) ID reconstruction plans Track fitting  Two classes of algorithms exist: Kalman filter/smoother and numerical  2 fit zConvergence on two algorithms should be possible but careful with couplings to track finding methods

Software plenary, 16 February 2000 David Rousseau (LAL, Orsay) ID reconstruction plans Track output class zBroad agreement with content zchoice of design is more general than just track zneed library of utilities to be used later on: yextrapolation yrefit with one hit less or more ykinematical fit/vertexing y...

Software plenary, 16 February 2000 David Rousseau (LAL, Orsay) ID reconstruction plans Other ID perf items zVertexing, kinematic fitting (CDF fortran package use so far) zconversion/K0s/primary vertex/hadronic interactions zbrem fitting strategies  e/K/  separation zalignment zvisualization

Software plenary, 16 February 2000 David Rousseau (LAL, Orsay) ID reconstruction plans Conclusion zMain tracking algorithms in PASO, then new framework, reading GEANT3 data to be expected by autumn 2000 (modularization and convergence not complete) zGEANT4 data and full use of databases and detector description by autumn 2001