no code implementations • 11 Apr 2022 • P. Žugec, M. Barbagallo, J. Andrzejewski, J. Perkowski, N. Colonna, D. Bosnar, A. Gawlik, M. Sabate-Gilarte, M. Bacak, F. Mingrone, E. Chiaveri
The paper explores the feasibility of using machine learning techniques, in particular neural networks, for classification of the experimental data from the joint $^\text{nat}$C(n, p) and $^\text{nat}$C(n, d) reaction cross section measurement from the neutron time of flight facility n_TOF at CERN.
