https://doi.org/10.1140/epja/s10050-025-01555-z
Regular Article - Experimental Physics
The use of artificial neural networks for the unfolding procedures in neutron activation measurements
1
Faculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovića 6, 21000, Novi Sad, Serbia
2
Department of Physics, Faculty of Science, University of Novi Sad, Trg Dositeja Obradovića 4, 21000, Novi Sad, Serbia
3
Institute of Physics, University of Belgrade, Pregrevica 118, 11080, Belgrade, Serbia
4
Heinz Maier Leibnitz Zentrum (MLZ), Technische Universität München, Lichtenbergstr 1, 85748, Garching, Germany
5
European Commission, Joint Research Centre (JRC), Geel, Belgium
6
Lehrstuhl für Informatik im Maschinenbau, Institut für Automatisierungstechnik, Helmut-Schmidt-Universität, Holstenhofweg 85, 22043, Hamburg, Germany
7
German Engineering Materials Science Centre (GEMS), Heinz Maier-Leibnitz Zentrum (MLZ), Lichtenbergstr. 1, 85748, Garching bei München, Germany
8
AiNT GmbH, Research and Development Department, 52222, Stolberg, Germany
9
Faculty of Agriculture, University of Novi Sad, Novi Sad, Serbia
a
nikola.jovancevic@df.uns.ac.rs
Received:
21
November
2024
Accepted:
28
March
2025
Published online:
17
April
2025
The MAXED and GRAVEL unfolding algorithms have been used to determine cross-sections, with the NAXSUN method developed at JRC-Geel. This study explores the potential of a particular type of artificial neural network, the multilayer perceptron (MLP), as an alternative to traditional unfolding algorithms. By generating a training dataset using the TALYS 2.0 code and testing the MLP model on real experimental data, we compared the effectiveness of MLP in unfolding neutron-induced reactions cross sections involving indium and rhenium isotopes. The results were benchmarked against those obtained using standard unfolding algorithms and TALYS 2.0 simulations, demonstrating the advantages and limitations of the ANN approach. The obtained results show a much-reduced corridor of uncertainty in the derived cross-section curves compared to previous work using traditional unfolding techniques.
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© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
