Muon detection in the CBM experiment at FAIR Andrey Lebedev 1,2 Claudia Höhne 1 Ivan Kisel 1 Anna Kiseleva 3 Gennady Ososkov 2 1 GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany 2 Laboratory of Information Technologies, Joint Institute for Nuclear Research, Dubna, Russia 3 Frankfurt University, Germany DPG 2010 March 15-19, 2010 Bonn
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Muon detection in the CBM experiment at FAIR Andrey Lebedev 1,2 Claudia Höhne 1 Ivan Kisel 1 Anna Kiseleva 3 Gennady Ososkov 2 1 GSI Helmholtzzentrum für.
3/10 A.Lebedev et al. Muon detection in the CBM Experiment at FAIR Challenges for μ identification Peculiarities for CBM: large track multiplicities ‒ up to 800 charged particles per reaction in +/- 25˚ high reaction rate ‒ up to 10 MHz reconstruction of low momentum muons (p> 1 GeV/c) measurement of rare probes fast and efficient trigger and tracking algorithms major background of muons from pion and kaon decay punch through of hadrons, track mismatches huge amount of data : foreseen are currently 1Gb/s archiving rate (600Tb/week) Central Au+Au collision at 25 AGeV (UrQMD + GEANT3) → clean μ identification → absorber-detector layers for continues tracking and variable μ ID for different momentum ranges → fast tracking algorithms are essential standard: muon identification by absorber technique
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Muon detection in the CBM experiment at FAIR
Andrey Lebedev1,2
Claudia Höhne1
Ivan Kisel1Anna Kiseleva3
Gennady Ososkov2
1 GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany2 Laboratory of Information Technologies, Joint Institute for Nuclear Research, Dubna, Russia3 Frankfurt University, Germany
DPG 2010March 15-19, 2010 Bonn
2/10 A.Lebedev et al. Muon detection in the CBM Experiment at FAIR
The CBM experiment at FAIR
• exploration of the QCD phase diagram in regions of high baryon densities and moderate temperatures• comprehensive measurement of hadron and lepton (vector mesons μ+μ-) production in pp, pA and AA collisions for 8-45 AGeV beam energy• fixed target experiment
beam
STS track, vertex and momentum reconstruction
MUCH muon identification
TRD in case of muons only tracking
TOF time of flight measurement
3/10 A.Lebedev et al. Muon detection in the CBM Experiment at FAIR
Challenges for μ identificationPeculiarities for CBM:• large track multiplicities
‒ up to 800 charged particles per reaction in +/- 25˚
• high reaction rate‒ up to 10 MHz
• reconstruction of low momentum muons (p> 1 GeV/c)• measurement of rare probes fast and efficient trigger and tracking algorithms• major background of muons from pion and kaon decay• punch through of hadrons, track mismatches• huge amount of data: foreseen are currently 1Gb/s archiving rate (600Tb/week) Central Au+Au collision at 25
AGeV (UrQMD + GEANT3)→ clean μ identification→ absorber-detector layers for continues tracking and
variable μ ID for different momentum ranges→ fast tracking algorithms are essential
standard: muon identification by absorber technique
4/10 A.Lebedev et al. Muon detection in the CBM Experiment at FAIR
The Muon detector (MUCH)
3 detector stations between the absorbers
Low mass vector mesons 5 Fe absorbers (125 cm)7.5 I, p> 1 GeV/cCharmonium 6 Fe absorbers (225 cm)13.5 I, p> 2.8 GeV/c
Measurements of:
Alternating detector-absorber layout for continuous tracking of muons through the absorber
Detector challenges:• High hit density (up to 1 hit per cm2 per event)• High event rates (up to 107 events/s)• Position resolution < 300 μm→ consider GEMs (minimum pad size 2.8x2.8 mm2) for first stations→ for the last stations straw tubes are under investigation
5/10 A.Lebedev et al. Muon detection in the CBM Experiment at FAIR
Track reconstruction algorithm
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Two main steps:– Tracking– Global track selection
Track propagation• Inhomogeneous magnetic field:
‒ solution of the equation of motion with the 4th order Runge-Kutta method• Large material budget: ‒ Energy loss (ionization: Bethe-Bloch, bremsstrahlung: Bethe-Heitler, pair production) ‒ Multiple scattering (Gaussian approximation)
Tracking is based on• Track following• Initial seeds are tracks reconstructed
in the STS (fast Cellular Automaton (CA), I.Kisel)
• Kalman Filter• Validation gate• Hit-to-track association techniques
‒ nearest neighbor: attaches the closest hit from the validation gate
Global track selection• aim: remove clone and ghost tracks• tracks are sorted by their quality,
obtained by chi-square and track length
• Check for shared hits
6/10 A.Lebedev et al. Muon detection in the CBM Experiment at FAIR
Optimization and parallelism
Parallel programming is mainstream!• SIMD: Single Instruction Multiple Data• Multithreading make use of many core CPUs
Algorithm optimization• Minimize access to global memory: approximation of the MF map• Simplification of the detector geometry• Computational optimization of the Kalman Filter• float precision