Speaker
Mr
Aatos Heikkinen
(Helsinki Institute of Physics)
Description
B tagging is an important tool for separating the LHC Higgs events with associated b
jets from the Drell-Yan background. We extend standard neural network (NN) approach
using multilayer perceptron in b tagging [1] to include self-organizing feature maps.
We demonstrate the use of the self-organizing maps (SOM_PAK program package) and the
learning vector quantization (LVQ_PAK). A background discriminating power of these NN
tools are compared with standard tagging algorithms.
[1] A. Heikkinen and S. Lehti, Tagging b jets associated with heavy neutral MSSM
Higgs bosons. Proceedings of ACAT 2005, May 22 - 27, DESY, Zeuthen, Germany.
Primary author
Mr
Aatos Heikkinen
(Helsinki Institute of Physics)
Co-author
Dr
Sami Lehti
(Helsinki Institute of Physics)
