Online Pattern Recognition for the ALICE High Level Trigger (tracking and compression techniques)

• Main Authors: Lindenstruth, V, Loizides, C, Roehrich, D, Skaali, B, Steinbeck, T, Stock, R, Tilsner, H, Ullaland, K, Vestbo, A, Vik, T
• Format: Journal Article
• Language: English
• Published: 13-10-2003
• Subjects: Physics - Instrumentation and Detectors
• DOI: 10.48550/arxiv.physics/0310052

IEEE Trans.Nucl.Sci. 51 (2004) 3; IEEE Trans.Nucl.Sci. 51 (2004)
383-390 The ALICE High Level Trigger has to process data online, in order to select
interesting (sub)events, or to compress data efficiently by modeling
techniques. Focusing on the main data source, the Time Projection Chamber
(TPC), we present two pattern recognition methods under investigation: a
sequential approach (cluster finder and track follower) and an iterative
approach (track candidate finder and cluster deconvoluter). We show, that the
former is suited for pp and low multiplicity PbPb collisions, whereas the
latter might be applicable for high multiplicity PbPb collisions of dN/dy>3000.
Based on the developed tracking schemes we show that using modeling techniques
a compression factor of around 10 might be achievable.