Journal Article

IMPULSE-2025-00121

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png The use of artificial neural networks for the unfolding procedures in neutron activation measurements

Ilić, S. ; Jovančević, N. ; Knezevic, D.MLZ* ; Maletić, D. ; Stieghorst, C.MLZ* ; Nayak, A. ; Oberstedt, S. ; Hult, M. ; Boschmann, D. ; Kadri, L.MLZ* ; Ozden, Ö. ; Arsenić, I. ; Krmar, M.

2025
Springer Heidelberg

Please use a persistent id in citations: doi:10.1140/epja/s10050-025-01555-z

Abstract: 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.

Keyword(s): Instrument and Method Development (1st) ; Instrument and Method Development (2nd)

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Contributing Institute(s):

1. PGAA (PGAA)
2. DEVA (DEVA)

Research Program(s):

1. 05D23WO2 - Verbundprojekt 05D2022 - EvalSpek-ML: Entwicklung und Evaluierung von Machine-Learning-Algorithmen für die Analyse konvexkombinierter spektraler Daten. Teilprojekt 4. (BMBF-05D23WO2) (BMBF-05D23WO2)
2. 05D23XK1 - Verbundprojekt 05D2022 - EvalSpek-ML: Entwicklung und Evaluierung von Machine-Learning-Algorithmen für die Analyse konvexkombinierter spektraler Daten. Teilprojekt 2. (BMBF-05D23XK1) (BMBF-05D23XK1)
3. 05D23CG2 - Verbundprojekt 05D2022 - EvalSpek-ML: Entwicklung und Evaluierung von Machine-Learning-Algorithmen für die Analyse konvexkombinierter spektraler Daten. Teilprojekt 1. (BMBF-05D23CG2) (BMBF-05D23CG2)

Experiment(s):

1. Measurement at external facility

Appears in the scientific report 2025

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Database coverage:
; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; DEAL Springer ; DEAL Springer ; Ebsco Academic Search ; Essential Science Indicators ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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