Title :
Online pattern recognition for the ALICE high level trigger
Author :
Lindenstruth, V. ; Loizides, C. ; Röhrich, D. ; Skaali, B. ; Steinbeck, T. ; Stock, R. ; Tilsner, H. ; Ullaland, K. ; Vestb, A. ; Vik, T.
Author_Institution :
Kirchhoff Inst. fur Phys., Heidelberg, Germany
fDate :
6/1/2004 12:00:00 AM
Abstract :
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.
Keywords :
Hough transforms; data compression; deconvolution; heavy ion-nucleus reactions; high energy physics instrumentation computing; iterative methods; particle tracks; pattern recognition; position sensitive particle detectors; proton-proton interactions; time projection chambers; trigger circuits; ALICE high level trigger; Hough transforms; Pb(Pb,X); cluster deconvoluter; cluster finder; data compression; high multiplicity collisions; iterative approach; online data processing; online pattern recognition; particle tracking; proton+proton; time projection chamber; track candidate finder; Bandwidth; Cost function; Detectors; Event detection; Helium; Iterative methods; Parallel processing; Particle tracking; Pattern recognition; Physics; Data compression; hough transforms; particle tracking; pattern recognition;
Journal_Title :
Nuclear Science, IEEE Transactions on
DOI :
10.1109/TNS.2004.829384
