identification in CBM will be performed by a RICH and TRD detectors. In this contribution, methods which have been developed for electron identification in.
ELECTRON IDENTIFICATION IN THE CBM EXPERIMENT AT FAIR S. Lebedev1,2, C. Hoehne2 and G.Ososkov1 for the CBM Collaboration 1 2
Joint Institute for Nuclear Research, Laboratory of Information Technologies GSI Helmholtzzentrum fur Schwerionenforschung GmbH, Darmstadt, Germany
The Compressed Baryonic Matter (CBM) experiment at the future FAIR facility at Darmstadt will measure dileptons emitted from the hot and dense phase in heavy-ion collisions. In case of an electron measurement, a high purity of identified electrons is required in order to suppress the background. Electron identification in CBM will be performed by a RICH and TRD detectors. In this contribution, methods which have been developed for electron identification in CBM are presented. A fast and efficient RICH ring recognition algorithm based on the Hough Transform has been implemented. An ellipse fitting algorithm has been elaborated because most of the CBM RICH rings have elliptic shapes. An Artificial Neural Network can be used in order to suppress fake rings. The electron identification in RICH is substantially improved by the use of TRD information for which several different algorithms for electron identification are implemented. Results of electron identification and pion suppression are presented.
Reconstruction in CBM RICH
Physics topics Exploration of the QCD phase diagram in regions of high baryon densities and moderate temperatures
a)
Sketch of the STS and the RICH detector, track extrapolation and track projection onto the photodetector plane; b) sketch of RICH hits and found rings; c) RICH ring and STS track matching.
CBM experiment TOF
1) Ring recognition Many overlapping rings -> algorithm based
ECAL
on Hough Transform was implemented.
TRD RICH
2) Ring fitting Simple procedure: circular fit.
STS
Improved description: non-linear ellipse fit, as the rings in the photodetector plane have a slight elliptic shape.
PSD
3) Parameters correction The values of major and minor half axes strongly depend on the position on the PMT plane. A parameter correction algorithm was implemented. About 800 charged particles for central Au+Au collision at a beam energy of 25 AGeV for the CBM acceptance
Micro-Vertex Detector (MVD) and Silicon Tracking System (STS) in dipole magnet track reconstruction and momentum determination, primary and secondary vertices reconstruction
Ring Imaging Cherenkov (RICH)
and Transition Radiation Detectors (TRDs) electron identification
Time-of-flight (TOF) system hadron identification Electromagnetic Calorimeter (ECAL) measurement of photon and neutral particles Projectile Spectator Detector (PSD) determination of the collision centrality
4) Ring-track matching Ring-track matching is based on combining pairs with the smallest distance between ring center and track extrapolation on the PMT plane.
5) Fake ring rejection The ring finder not only finds "true" rings but also "fake" rings by random combinations of hits in the PMT plane. To reject fake rings an Artificial Neural Network (ANN) is used.
6) Electron identification Finally, electrons are chosen by a 3σ cut around the mean electron radius (minor half axes). As an alternative we investigate a possibility to use an ANN.
Electron Identification in TRD The CBM TRD is intended for tracking and improved electron identification for p > 1.5 GeV/c. Electron identification is based on the energy loss measurements. Tracking procedure: Kalman filter and track following methods. Electrons Eloss = dE/dx+TR
Pions Eloss = dE/dx
The CBM RICH detector The RICH detector in CBM will serve for electron identification from lowest momenta up to 10 GeV/c needed for the study of the dielectronic decay channel of vector mesons and J/Psi.
Energy loss spectra. Comparison simulation (red and blue) with experimental data (black)
Using only cut on sum of energy losses is not enough -> advanced algorithms were implemented, which allow one to reach a pion suppression factor of 200 – 500 for 90% electron efficiency. Several methods of electron identification in TRD: • Artificial Neural Network (ANN) • Likelihood Ratio Function • Boosted decision tree and others
Results Sketch of the RICH setup as used in simulations and part of typical event
Electrons
Pions
Radius versus momentum for reconstructed rings in central Au+Au collisions at 25 AGeV beam energy for UrQMD events. A 3σ band around the mean radius is indicated by solid lines
Electron identification efficiency (left) and pion suppression factor (right) for simulations of central Au+Au collisions at 25 AGeV beam energy (UrQMD)
Conclusion The RICH detector alone yields a pion suppression factor of 500-1000 at an electron identification efficiency of 82%, while in combination with TRD and TOF a factor 104 is reached at 72% efficiency. References 1) C. Hohne, S. Lebedev, G. Ososkov et al. Nucl. Instrum. Meth. A595:187-189,2008 2) S. Lebedev, C. Hoehne, G. Ososkov, Proceedings on International Conference on Computing in High Energy and Nuclear Physics, 21 - 27 March 2009 Prague, “Ring Recognition and Electron Identification in the RICH detector of the CBM Experiment at FAIR”, to be published in Journal of Phisics: Conference Series. 3) S. Lebedev, G. Ososkov, “Fast Algorithms for Ring Recognition and Electron Identification in the CBM RICH Detector”, PEPAN Letters, 2009, Vol. 6, No 2(151), pp. 260-284.
