Česky
English
Committee for collaboration of Czech Republic

with Joint Institute for Nuclear Research in Dubna Login
Muon Identification using Neural Networks With the Muon Telescope Detector at STAR

Author
Adamczyk L. AGH University of Science and Technology, Poland
Lednický Richard, promovaný fyzik DrSc. dr. h. c. Institute of physics of the ASCR, JINR Dubna
et al.  different institutions

Year
2019

Scientific journal
NUCLEAR PHYSICS A 982 192-194

Web


Abstract
The installation of the Muon Telescope Detector (MTD) at STAR allows a measurement of the dimuon (mu(+)mu(-)) production in heavy-ion collisions over a large invariant mass range for the first time. Data has been collected with the MTD from Au+Au collisions at root S-NN = 200 GeV and from p+p collisions at root S = 200 GeV. These two datasets allow for new opportunities to measure the dimuon invariant mass spectra at STAR. Before any dimuon measurements can be made, muons must be identified. This contribution presents muon identification employing deep neural networks (DNN) and compares it with other multi-variate techniques. Applications of the DNN technique for data-driven purity measurements are discussed.

Cite article as:
L. Adamczyk, R. Lednický, . et al., "Muon Identification using Neural Networks With the Muon Telescope Detector at STAR", NUCLEAR PHYSICS A 982 192-194 (2019)