Title of article
Neural tracking in the ALICE Inner Tracking System
Author/Authors
Pulvirenti، نويسنده , , A. and Badalà، نويسنده , , A. La Barbera، نويسنده , , R. and Lo Re، نويسنده , , G. and Palmeri، نويسنده , , A. and Pappalardo، نويسنده , , G.S. and Riggi، نويسنده , , F.، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2004
Pages
17
From page
543
To page
559
Abstract
A neural network-based algorithm to perform track recognition in the ALICE Inner Tracking System (ITS) for high transverse momentum particles ( p t > 1 GeV / c ) is presented. The model is based on the Denby–Peterson scheme, especially improved to cope with the very high track density expected in ALICE. Results are shown for central and mid-central Pb–Pb collisions at the CERN Large Hadron Collider energy.
Keywords
Track finding , Pattern recognition , ALICE experiment , NEURAL NETWORKS
Journal title
Nuclear Instruments and Methods in Physics Research Section A
Serial Year
2004
Journal title
Nuclear Instruments and Methods in Physics Research Section A
Record number
2198489
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