Title :
Heavy flavor discrimination by neural networks
Author_Institution :
Dept. of Phys., Bologna Univ., Italy
Abstract :
Recent work on neural network discrimination of heavy flavor jets and particle decays is surveyed. The feasibility of unearthing a top signal at hadron colliders with the top quark decaying into anything is discussed. Results obtained by several groups on identification of jets originated by bottom quarks in electron-positron annihilation are compared. A project for the development of a neural trigger for bottom events in a fixed target experiment at CERN is presented
Keywords :
elementary particle jets; neural nets; pattern recognition; physics computing; quark decay; quark production; CERN; bottom quarks; electron-positron annihilation; fixed target experiment; hadron colliders; heavy flavor jets; neural networks; neural trigger; particle decays; top quark decay; top signal; Coherence; Discrete event simulation; Input variables; Neural networks; Physics computing; Shape; Statistical analysis; Tagging; Testing; Vector quantization;
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference, 1992., Conference Record of the 1992 IEEE
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-0884-0
DOI :
10.1109/NSSMIC.1992.301439
