AN ON-LINE NON-LEPTONIC NEURAL TRIGGER APPLIED TO AN EXPERIMENT LOOKING FOR BEAUTY

C. Baldanza, F. Bisi, A. Cotta-Ramusino, I. D’antone, L. Malferrari, P. Mazzanti, F. Odorici, R. Odorico (), M. Zuffa, C. Bruschini, P. Musico, P. Novelli and M. Passaseo
Additional contact information
C. Baldanza: INFN ANNETTHE, Bologna, Italy
F. Bisi: INFN ANNETTHE, Bologna, Italy
A. Cotta-Ramusino: INFN ANNETTHE, Bologna, Italy
I. D’antone: INFN ANNETTHE, Bologna, Italy
L. Malferrari: INFN ANNETTHE, Bologna, Italy
P. Mazzanti: INFN ANNETTHE, Bologna, Italy
F. Odorici: INFN ANNETTHE, Bologna, Italy
R. Odorico: INFN ANNETTHE, Bologna, Italy
M. Zuffa: INFN ANNETTHE, Bologna, Italy
C. Bruschini: INFN, Genova, Italy
P. Musico: INFN, Genova, Italy
P. Novelli: INFN, Genova, Italy
M. Passaseo: CERN, Geneva, Switzerland

International Journal of Modern Physics C (IJMPC), 1994, vol. 05, issue 05, 863-870

Abstract: Results from a non-leptonic neural-network trigger hosted by experiment WA92, looking for beauty particle production from 350 GeVπ−on a Cu target, are presented. The neural trigger has been used to send on a special data stream (the Fast Stream) events to be analyzed with high priority. The non-leptonic signature uses microvertex detector data and was devised so as to enrich the fraction of events containing C3 secondary vertices (i.e, vertices having three tracks whith sum of electric charges equal to +1 or -1). The neural trigger module consists of a VME crate hosting two ETANN analog neural chips from Intel. The neural trigger operated for two continuous weeks during the WA92 1993 run. For an acceptance of 15% for C3 events, the neural trigger yields a C3 enrichment factor of 6.6–7.1 (depending on the event sample considered), which multiplied by that already provided by the standard non-leptonic trigger leads to a global C3 enrichment factor of ≈150. In the event sample selected by the neural trigger for the Fast Stream, 1 every ≈7 events contains a C3 vertex. The response time of the neural trigger module is 5.8 μs.

Keywords: High Energy Physics; Neural Networks; Trigger (search for similar items in EconPapers)
Date: 1994
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DOI: 10.1142/S0129183194001008

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