Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 2003 Event Reconstruction Event Reconstruction in the BRAHMS simulation framework: The BRAHMS framework Tracking Reconstruction (a brief reminder) Calorimeter Reconstruction Ties Behnke, SLAC and DESY 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)

Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 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

Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 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

Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 2003 The tracking package A very brief reminder: Patrec done separately in VTX, TPC, FCH Merging done for the complete event simultaneously Performance: measured in tracking efficiency in dd events, full background simulation

Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 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

Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 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)

Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 2003 Performance: Single Particles PhotonElectronMuon KaonKaon (neutral)Pion PiZero Particle identification as given by the SNARK algorithm

Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 2003 Performance: Single Particles Efficiencies: 1 gamma 2 electron 3 muon 4 kaon + 5 kaon 0 6 pion + 7 kaon 0

Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 2003 Performance: Single particles Photons Electrons Pions

Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 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

Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 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 talk (V. Morgunov) in top session on top reconstruction: Under development: common data model for all simulation and reconstruction systems (US, EU, J(?),...) Fully hadronic top decay (6 jets), full background

Ties Behnke: Event Reconstruction 1Arlington LC workshop, Jan 9-11, 2003 Conclusion BRAHMS offers a complete simulation and reconstruction framework for a LC detector Tracking implemented for a complicated geometry, easily adaptable to other geometries Tracking interface to MOKKA (Geant4) does exist One version of calorimeter reconstruction software is included: Optimised for SI-W ECAL and tile type HCAL Port to other systems is (at the moment) not easy Full implementation of the energy flow algorithm First results based on this full reconstruction do look promising Further developments: Tuning and improvements of the calorimeter reconstruction software Port of simulation part to GEANT4 (MOKKA) Implementation of the new LCIO standard for persistency and data model to easy portability of software between systems and regions