simulations for cbm cbm-india meeting, jammu, 12 february 2008
DESCRIPTION
Simulations for CBM CBM-India Meeting, Jammu, 12 February 2008. V. Friese [email protected]. Planned experiment. Running experiment. Input (Signal, Background). Required performance (S/B, SNR, eff.). Detector description. Input (Signal, Background). Simulation. Simulation. - PowerPoint PPT PresentationTRANSCRIPT
V. Friese CBM-India, 12 February 2008 2
Simulations: Why?
Simulation
Detectordescription
Input(Signal,
Background)
Simulated signal
Performance(acceptance, efficiency)
Running experiment
Simulation
Input(Signal,
Background)
Required performance
(S/B, SNR, eff.)
Simulated signal
Detector design
Planned experiment
V. Friese CBM-India, 12 February 2008 3
Simulations for detector design
• Consequences:
– Many different detector designs / setups need being investigated
– The simulation framework must be flexible enough to enable an easy switch between geometries / digitisations
– Challenge in particular for reconstruction (data structures, ...)
V. Friese CBM-India, 12 February 2008 4
Simulation stepsC
BM
RO
OT
Mon
te-C
arl
oEvent generator
UrQMD, HSD, user defined, ...GEN Particles (type,
momentum, vertex)
MCTransport (MC)GEANT3, GEANT4, FLUKA, ...
MCPoint, MCTrack
RAWDetector response simulation
Digi
EDSReconstruction Hits, Tracks, Vertices
Analysis Histogram
Experiment DAQ
Step Data level Data structures
V. Friese CBM-India, 12 February 2008 5
CBMROOT
• CBMROOT is the CBM software framework for simulation, reconstruction and analysis
• It is based on (FAIR)ROOT and VMC
• Execution via ROOT macros
• Code is written in C++
• Documentation system is DOXYGEN
• The (current) build system is cmake, the distribution system is subversion
• Supported platforms are (almost) all Linux flavours
• External packages used:– GEANT3
– GEANT4
– ROOT
– CLHEP
– VMC
– PYTHIA
V. Friese CBM-India, 12 February 2008 6
CBMROOT and FAIRROOT
MVD STS RICH Tracking .... base geobase parbase
detector specific (geometry, digitisation, ...) core (run manager, I/O, ...)
MVD STS RICH Tracking ....
base geobase parbase
CBMROOT
FAIRROOT
CBMROOT
PANDAROOT
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Event generators
• Produces a list of particles, each with type, start vertex and momentum at start vertex, as input for the transport
• Available generator interfaces:– Standalone (outside of the framework, with intermediate file)
• UrqmdGenerator (UrQMD output ftn14, ASCII)
• PlutoGemerator (PLUTO output, ROOT)
• ShieldGenerator (SHIELD output, ASCII)
• AsciiGenerator (self-written ASCII, defined format)
– Integrated (inside the framework, on the fly, without intermediate file)• ParticleGenerator (single particles)
• BoxGenerator (particles with flat distribution in p, pt, y, φ)
• An arbitrary number of generators can be used at the same time
V. Friese CBM-India, 12 February 2008 8
MC transport
• FAIRROOT employs the concept of Virtual Monte Carlo (VMC): The user can choose between different transport engines
• Available engines:– GEANT3
– GEANT4
– (FLUKA in preparation)
• The simulation run is controlled by the manager class CbmRunSim
• The output is a ROOT tree. Branches are CbmMCTrack (input + secondary tracks) and objects derived from CbmMCPoint– CbmMvdPoint
– CbmStsPoint
– ....
V. Friese CBM-India, 12 February 2008 9
MC Transport step by step
1. Choose engine and create run CbmRunSim* fRun = new CbmRunSim(); fRun->SetName("TGeant3"); // Transport engine fRun->SetOutputFile(outFile); // Output file CbmRuntimeDb* rtdb = fRun->GetRuntimeDb(); fRun->SetMaterials/"media.geo");
2. Define detector geometry CbmDetector* sts = new CbmSts("STS", kTRUE); sts->SetGeometryFileName(stsGeom); fRun->AddModule(sts);
3. Define magnetic field CbmFieldMap* magField = new CbmFieldMapSym3(fieldMap); magField->SetPosition(0., 0., fieldZ); magField->SetScale(fieldScale); fRun->SetField(magField);
4. Define inputCbmPrimaryGenerator* primGen = new CbmPrimaryGenerator();CbmUrqmdGenerator* urqmdGen = new CbmUrqmdGenerator(inFile);primGen->AddGenerator(urqmdGen);
fRun->SetGenerator(primGen);
5. ... and runfRun->Run(nEvents);
V. Friese CBM-India, 12 February 2008 10
Detector simulation (digitisation)
• describes the detector response to the simulated MCTracks
• to be defined according to knowledge on the detector
• output: CbmDigi for each active channel
• workaround: HitProducer (e.g. Gaussian smearing of point)
CbmStsPoint
CbmStsDigi
CbmStsHit
CbmStsDigitize
CbmStsFindHits
CbmStsPoint
CbmStsHit
CbmStsHitProducer
V. Friese CBM-India, 12 February 2008 11
The CBM setup: electrons
magnet
RICH
TRD
TOF
STS + MVD
ECAL
V. Friese CBM-India, 12 February 2008 12
The CBM setup: muons
STS + MVD
magnet
TRD
ECAL
V. Friese CBM-India, 12 February 2008 13
Status of detector description
Detector Geometry (MC) Digitisation
MVD Monolithic stations HitProducer
STSSegmented (sectors), support, cables
Projective strip geometry, hit finder
RICH Monolithic (PM plane) HitProducer
MUCH Monolithic stationsProjective pad geometry, avalanche simulation, cluster reconstruction
TRD Segmented (sectors) HitProducer
TOF Segmented HitProducer
ECAL Over-segmented Shower parameterisation
V. Friese CBM-India, 12 February 2008 14
Example: STS
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Example: MUCH
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Event reconstruction
• is currently done in one step with digitisation (macro)
• manager class is CbmRunAna
• input is MC data (output of transport simulation)
• The user defines tasks which are
– initialised at the beginning of the run
– executed for each event
– finalised after the last event
• output is a ROOT tree with branches for all data structures registered to the run manager by the class
V. Friese CBM-India, 12 February 2008 17
Reconstruction step by step
1. Create runCbmRunAna *run= new CbmRunAna();run->SetInputFile(inFile);run->SetOutputFile(outFile);
2. Register task(s)CbmTask* stsDigitize = new CbmStsDigitize(iVerbose);run->AddTask(stsDigitize);
3. Initialise and start run run->LoadGeometry(); run->Init(); run->Run(0,nEvents);
V. Friese CBM-India, 12 February 2008 18
Available reconstruction algorithms
Task Algorithms Output
Local STS trackingCellular Automaton
Hough TransformCbmStsTrack
Local TRD trackingCellular Automaton
Track followingCbmTrdTrack
Local MUCH tracking Track following CbmMuchTrack
RICH ring findingHough Transform
Elastic NetCbmRichRing
Global tracking Global Tracker CbmGlobalTrack
Main vertex finding Kalman Filter CbmVertex
V. Friese CBM-India, 12 February 2008 19
Some results
Track reconstruction efficiency in MVD+STS, CA algorithm
Mom$ntum [G$V/c]0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
All S
$t
Eff
ici$
nc
y [
%]
0
10
20
30
40
50
60
70
80
90
100
V. Friese CBM-India, 12 February 2008 20
Some more results
RICH ring reconstruction with Hough transform
V. Friese CBM-India, 12 February 2008 21
Electron identification capabilities
Composition of identified electrons Pion suppression
V. Friese CBM-India, 12 February 2008 22
Performance of di-electron measurements
Low-mass vector mesons Acceptance for ρ meson
V. Friese CBM-India, 12 February 2008 23
Performance of di-electron measurements (2)
Charmonia Acceptance for J/ψ meson
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Open charm results
D0, cτ=127 μm
K-
π+
V. Friese CBM-India, 12 February 2008 25
Open charm results (2)
c+ pK-+
D0 ->K- - ++
D+ ->K- ++