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AIHENP-99 Momentum Reconstruction of Particles...1 Momentum Reconstruction of Particles in the Forward Muon Trigger System of the ATLAS Detector Gideon.

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Presentation on theme: "AIHENP-99 Momentum Reconstruction of Particles...1 Momentum Reconstruction of Particles in the Forward Muon Trigger System of the ATLAS Detector Gideon."— Presentation transcript:

1 AIHENP-99 Momentum Reconstruction of Particles...1 Momentum Reconstruction of Particles in the Forward Muon Trigger System of the ATLAS Detector Gideon Dror 1, Erez Etzion 2, David Horn 2 1. The Academic College of Tel-Aviv-Yaffo, Tel Aviv, Israel. 2. Tel-Aviv University, Tel Aviv, Israel.

2 AIHENP-99 Momentum Reconstruction of Particles...2 ATLAS S.C Solenoid Hadron Calorimeter Muon Detectors EM Calorimeters Inner Detector S.C Air core Toroids

3 AIHENP-99 Momentum Reconstruction of Particles...3 Typical ATLAS collision 4*10 7 bunch crossing per second 23 events per bunch crossing 1Mbyte per event Data rate ~ 10 16 Byte/second

4 AIHENP-99 Momentum Reconstruction of Particles...4 Experimental setup TGC calorimeter beam pipe

5 AIHENP-99 Momentum Reconstruction of Particles...5 Network architecture PTPT Q   sigmoid hidden layers linear output input parameters of straight track of muon PxPx QPzPz PyPy

6 AIHENP-99 Momentum Reconstruction of Particles...6 Testing network performance Test set of 1829 events. Distribution of network errors - approximately gaussian. compatible with stochasticity of the data. charge is discrete!!! 95.8% correct sign.

7 AIHENP-99 Momentum Reconstruction of Particles...7 Relative error of P T vs. pseudorapidity Small pseudorapidity - larger widths. The effect is due to smaller magnetic field and larger inhomogeneities

8 AIHENP-99 Momentum Reconstruction of Particles...8 Network mean charge error Larger erros in charge at high momentum. (with infinite momentum tracks do not curve - no resolution!!!)

9 AIHENP-99 Momentum Reconstruction of Particles...9 Summary & discussion The network can successfully estimate the charge and transverse momentum of the muon. The data is intrinsically stochastic giving rise to approximately gaussian errors. The simplicity of the network enables very fast hardware realization.

10 AIHENP-99 Momentum Reconstruction of Particles...10 Future work Further optimize the architecture. Calculate the lower bound for network errors based on data stochasticity. Calculate triggering efficiencies in realistic environments. Realize in hardware.

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