TY - JOUR
T1 - Infrared safety of a neural-net top tagging algorithm
AU - Choi, Suyong
AU - Lee, Seung J.
AU - Perelstein, Maxim
N1 - Funding Information:
The authors are grateful for conversations with Mihailo Backovic, Steven Durr, and Jesse Thaler. MP acknowledges the support of the U.S. National Science Foundation through grant PHY-1719877. SC was supported by National Research Foundation of Korea (NRF) grant NRF-2018R1A2B6005043. SL was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education (NRF-2018R1D1A1B07049148), by the Korea government (MEST) (NRF-2015R1A2A1A15052408), and Samsung Science and Technology Foundation under Project Number SSTF-BA1601-07.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - Neural network-based algorithms provide a promising approach to jet classification problems, such as boosted top jet tagging. To date, NN-based top taggers demonstrated excellent performance in Monte Carlo studies. In this paper, we construct a top-jet tagger based on a Convolutional Neural Network (CNN), and apply it to parton-level boosted top samples, with and without an additional gluon in the final state. We show that the jet observable defined by the CNN obeys the canonical definition of infrared safety: it is unaffected by the presence of the extra gluon, as long as it is soft or collinear with one of the quarks. Our results indicate that the CNN tagger is robust with respect to possible mis-modeling of soft and collinear final-state radiation by Monte Carlo generators.
AB - Neural network-based algorithms provide a promising approach to jet classification problems, such as boosted top jet tagging. To date, NN-based top taggers demonstrated excellent performance in Monte Carlo studies. In this paper, we construct a top-jet tagger based on a Convolutional Neural Network (CNN), and apply it to parton-level boosted top samples, with and without an additional gluon in the final state. We show that the jet observable defined by the CNN obeys the canonical definition of infrared safety: it is unaffected by the presence of the extra gluon, as long as it is soft or collinear with one of the quarks. Our results indicate that the CNN tagger is robust with respect to possible mis-modeling of soft and collinear final-state radiation by Monte Carlo generators.
KW - Jets
KW - QCD Phenomenology
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U2 - 10.1007/JHEP02(2019)132
DO - 10.1007/JHEP02(2019)132
M3 - Article
AN - SCOPUS:85062030659
VL - 2019
JO - Journal of High Energy Physics
JF - Journal of High Energy Physics
SN - 1126-6708
IS - 2
M1 - 132
ER -