1. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 Pflow in SNARK: the next steps Ties Behnke, SLAC and DESY; Vassilly Morgunov, DESY and ITEP, Moscow The Goal: Reconstruction of all 4-vectors in the event (charged and neutral) The Method: Use information from all available subdetectors (tracker, calorimeter, etc) Currently implemented in BRAHMS: Tracker ECAL, HCAL (tile option) Muon system still missing (under development) SNARK: a first attempt at Particle Flow reconstruction Status: What do we have Current system uses only reconstructed information, no cheat information

2. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 Packages used Framework: BRAHMS 306 (most recent version) Tracking: Pattern recognition TPC Graham Blair Pattern recognition VTX Richard Hawkings Pattern Recognition FCH Klaus Moenig Overall Track Recontruction Kristian Harder / Markus Elsing Calorimeter SNARK reconstruction package: Vasiliy Morgunov Nearly available (tile HCAL implementation missing) Reconstruction package tracking calorimeter merging etc etc. GEANT3 simulation (BRAHMS) GEANT4 simulation (MOKKA) Analysis

3. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 Calorimeter Reconstruction The Goal: Reconstruct the 4-momentum of all particles (charged and neutral) in the event tt event at 350 GeV, no ISR Particle / Energy Flow in this context does not deal with event properties but only with particles Event properties are part of the analysis

4. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 The Calorimeter Reconstruction Currently available in BRAHMS: SNARK package (author Vasiliy Morgunov) The philosophy behind SNARK: Assume tracks have been found and are “perfect” Start with tracks, associate hits in calo with the tracks Look for hits in a “tube” Iterate the size of the “tube” Use the information from the track to determine the tube parameters “remove” the hits associated to tracks Do cluster finding (conventional) Identify neutral objects Advantages: During “clustering” more information is availabel: charged/ neutral/.. Treatment of overlaps uses full information of the event Utilise the strong tracking system of the LC detector

5. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 The Algorithm 1. Collect hits in the calorimeter along the predicted track (track core) within a distance of +/- one electronic cell. 2. Make a first particle hypothesis (e.g. MIP,...) 3. Predict the transverse shower profile, collect more hits within the expected road 4. Iterate, until measurement and expectation agree best 5. Any hits which at the end of the procedure are not associated belong to a neutral particle. Run “conventional” clustering, determine properties of neutral particle The system depends on high granularity both in ECAL and HCAL excellent linking between Tracker – ECAL – HCAL extensive use of amplitude info (optimised for tile HCAL) Note: a similar program, but optimised for the digital HCAL, is also under development (Ecole Polytechnic)

6. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 Performance: Single Particles Efficiencies: 1 gamma 2 electron 3 muon 4 kaon + 5 kaon 0 6 pion + 7 kaon 0

7. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 Performance: Single particles Photons Electrons Pions

8. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 Single Particle Performance Decent single particle identification probabilities Based on simple selections intrinsic to the program More sophisticated algorithms can be applied “post mortem” The difference in neutral and charged particle treatment is visible in the single particle reconstruction performance Larger number of “fake” objects in charged particles Larger tail at high energies for charged objects Overall performance quite ok, though (of course) further imporvements are possible

9. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 Final Reconstructed Particle Objects Output of BRAHMS with SNARK: Reconstructed particle 4-vectors 3-momentum px, py, pz Energy E particle ID hypotheses link to track(s) used link to cluster(s) used 3-momentum px, py, pz Energy E particle ID hypotheses link to track(s) used link to cluster(s) used The user works with these objects: Build jets Find vertices Calculate event properties.... The system does work: (see Lcnotes by Vasiliy) Fully hadronic top decay (6 jets), full background

10. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 Known Problems Secondaries vs primaries treatment: Current system takes all tracks found at the IP, extrapolates them to the calorimeter No allowance made for decays, kinks, conversions, loopers,... Observation: see degradation (significant) in performance when going from “tree” tracks to real tracks Need second level of sophistication in “tracking” to identify such secondaries: See yesterdays discussions about the data format, reconstructed objects etc Current treatment of long lived particles is not correct: Decay of B-mesons, etc might happen inside the detector (particularly relevant for charged particles) Have to treat properly the interface between generator and simulation (GEANT) And of course tuning tuning tuning....

11. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 Summary SNARK is a first PFLOW implementation Results look rather promising Currently tuned to analogue detector, porting of the algorithm to other geometries planned Many detailed issues remain to be solved Goals of the next few month: Systematic study of the performance of the algorithm Systematic study of the dependence of the algorithm on some key parameters (granularity...) Tuning of the algorithm. Continuation of the physics studies (more channels, different channels) Start to port SNARK to the new data model (LCIO)

12. Ties Behnke, Vasiliy Morgunov 1SLAC simulation workshop, May 2003 A Pflow display