Author/Authors :
Badalà، نويسنده , , A. La Barbera، نويسنده , , R. and Lo Re، نويسنده , , G. and Palmeri، نويسنده , , A. and Pappalardo، نويسنده , , G.S. and Pulvirenti، نويسنده , , A. and Riggi، نويسنده , , F.، نويسنده ,
Abstract :
A neural network based algorithm to perform track recognition in the ALICE Inner Tracking System (ITS) for high transverse momentum particles (pt>1 GeV/c) is presented,. The model is based on the Denby-Peterson scheme, with some original improvements which are necessary to cope with the very high track density expected in ALICE. Results are shown for a central Pb–Pb event at 5.5 A TeV in the center of mass system and the comparison with the Kalman Filter results is included.
Keywords :
ALICE experiment , Pattern recognition , Track reconstruction , NEURAL NETWORKS
