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Application of neural networks in the ARGUS-experiment for the analysis of B- and Tau-physics

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Abstract

We present analyses of e{sup +}e{sup -} annihilation data taken with the ARGUS detector in the energy range of the Y resonances. The selection of Y(4s) decays and leptonic {tau} decays was studied with feed-forward multilayer networks using the backpropagation algorithm for the training. The correlated decay of {tau}{sup +}{tau}{sup -} pairs was analysed with a feed-forward network to determine a weak coupling constant. (orig.)
Authors:
Joswig, M; [1]  Kolanoski, H; [1]  Kublun, S; [1]  Thurn, H; [1]  Wegener, D; [1]  Westerhoff, S [1] 
  1. Dortmund Univ. (Germany). Inst. fuer Physik
Publication Date:
Nov 01, 1993
Product Type:
Conference
Report Number:
DESY-93-167; CONF-9310317-
Reference Number:
SCA: 440104; 990300; PA: DEN-94:0F7157; EDB-94:083255; ERA-19:019440; NTS-95:001328; SN: 94001207751
Resource Relation:
Conference: 3. international workshop on software engineering, artifical intelligence (AI) and expert systems for high energy and nuclear physics,Oberammergau (Germany),4-8 Oct 1993; Other Information: PBD: Nov 1993
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; DATA PROCESSING; PARTICLE TRACKS; DORIS STORAGE RING; ALGORITHMS; ANNIHILATION; COUPLING CONSTANTS; ELECTRON-POSITRON INTERACTIONS; GEV RANGE 10-100; LEPTONIC DECAY; PAIR PRODUCTION; TAU PARTICLES; WEINBERG LEPTON MODEL; NEURAL NETWORKS; HADRONIC PARTICLE DECAY; UPSILON-10575 MESONS; LEARNING; ENERGY DEPENDENCE; EFFICIENCY; SEMILEPTONIC DECAY; B MESONS; 440104; 990300; HIGH ENERGY PHYSICS INSTRUMENTATION; INFORMATION HANDLING
Sponsoring Organizations:
Bundesministerium fuer Forschung und Technologie, Bonn (Germany)
OSTI ID:
10153292
Research Organizations:
Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)
Country of Origin:
Germany
Language:
English
Other Identifying Numbers:
Journal ID: ISSN 0418-9833; Other: ON: DE94768956; CNN: Foerderkennzeichen BMFT 056DO57P; TRN: DE94F7157
Availability:
OSTI; NTIS (US Sales Only); INIS
Submitting Site:
DEN
Size:
7 p.
Announcement Date:
Jul 06, 2005

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Citation Formats

Joswig, M, Kolanoski, H, Kublun, S, Thurn, H, Wegener, D, and Westerhoff, S. Application of neural networks in the ARGUS-experiment for the analysis of B- and Tau-physics. Germany: N. p., 1993. Web.
Joswig, M, Kolanoski, H, Kublun, S, Thurn, H, Wegener, D, & Westerhoff, S. Application of neural networks in the ARGUS-experiment for the analysis of B- and Tau-physics. Germany.
Joswig, M, Kolanoski, H, Kublun, S, Thurn, H, Wegener, D, and Westerhoff, S. 1993. "Application of neural networks in the ARGUS-experiment for the analysis of B- and Tau-physics." Germany.
@misc{etde_10153292,
title = {Application of neural networks in the ARGUS-experiment for the analysis of B- and Tau-physics}
 author = {Joswig, M, Kolanoski, H, Kublun, S, Thurn, H, Wegener, D, and Westerhoff, S}
 abstractNote = {We present analyses of e{sup +}e{sup -} annihilation data taken with the ARGUS detector in the energy range of the Y resonances. The selection of Y(4s) decays and leptonic {tau} decays was studied with feed-forward multilayer networks using the backpropagation algorithm for the training. The correlated decay of {tau}{sup +}{tau}{sup -} pairs was analysed with a feed-forward network to determine a weak coupling constant. (orig.)}
 place = {Germany}
 year = {1993}
 month = {Nov}
 }