HBT analysis in ALICE with ITS stand-alone and combined neural tracking (preliminary results)

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 large track density expected at ALICE. Results are shown for central Pb-Pb events at 5.5 ATeV in the center of mass system and the comparison with the Kalman filter results is included. Data coming from this tracking procedure are used for 1-dimensional HBT correlations and results are presented.