Simulations for CBM CBM-India Meeting, Jammu, 12 February 2008

Simulations for CBM

CBM-India Meeting, Jammu, 12 February 2008

V. Friese

v.friese@gsi.de

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

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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, ...)

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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

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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

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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

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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

– ....

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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);

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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

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The CBM setup: electrons

magnet

RICH

TRD

TOF

STS + MVD

ECAL

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The CBM setup: muons

STS + MVD

magnet

TRD

ECAL

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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

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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

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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);

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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

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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

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Some more results

RICH ring reconstruction with Hough transform

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Electron identification capabilities

Composition of identified electrons Pion suppression

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Performance of di-electron measurements

Low-mass vector mesons Acceptance for ρ meson

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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+

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Open charm results (2)

c+ pK-+

D0 ->K- - ++

D+ ->K- ++