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:

TrackerECAL, 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 packagetrackingcalorimetermergingetc 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 ofall 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 particlesEvent 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 efficiencyin dd events, full backgroundsimulation

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 tracksLook 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 eventUtilise 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 HCALexcellent linking between Tracker – ECAL – HCALextensive 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 ParticlesPhoton Electron Muon

Kaon Kaon (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

Photon Electron H+ H0Photon 0.993 0.000 0.000 0.007Electron 0.000 0.884 0.089 0.000H+ 0.000 0.002 0.964 0.000H0 0.287 0.000 0.000 0.713

Efficiencies:

1 gamma2 electron3 muon4 kaon +5 kaon 06 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 programMore 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 particlesLarger 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, pzEnergy E

particle ID hypotheseslink to track(s) used link to cluster(s) used

The user works with these objects: Build jetsFind verticesCalculate 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 geometriesTracking 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 algorithmFirst results based on this full reconstruction do look promising

Further developments:

Tuning and improvements of the calorimeter reconstruction softwarePort 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