RT Journal Article
T1 Principal Component Analysis Applied to Digital Pulse Shape Analysis for Isotope Discrimination
A1 Guerrero Morejón, Katherine
A1 Hinojo Montero, José María
A1 Muñoz Chavero, Fernando
A1 Flores Garrido, Juan Luis
A1 Gómez Galán, Juan Antonio
A1 González Carvajal, Ramón
AB Digital pulse shape analysis (DPSA) techniques are becoming increasingly important forthe study of nuclear reactions since the development of fast digitizers. These techniques allow us toobtain the (A, Z) values of the reaction products impinging on the new generation solid-state detectors.In this paper, we present a computationally efficient method to discriminate isotopes with similarenergy levels, with the aim of enabling the edge-computing paradigm in future field-programmablegate-array-based acquisition systems. The discrimination of isotope pairs with analogous energylevels has been a topic of interest in the literature, leading to various solutions based on statisticalfeatures or convolutional neural networks. Leveraging a valuable dataset obtained from experimentsconducted by researchers in the FAZIA Collaboration at the CIME cyclotron in GANIL laboratories,we aim to establish a comparative analysis regarding selectivity and computational efficiency, as thisdataset has been employed in several prior publications. Specifically, this work presents an approachto discriminate between pairs of isotopes with similar energies, namely, 12,13C, 36,40Ar, and 80,84Kr,using principal component analysis (PCA) for data preprocessing. Consequently, a linear and cubicmachine learning (ML) support vector machine (SVM) classification model was trained and tested,achieving a high identification capability, especially in the cubic one. These results offer improvedcomputational efficiency compared to the previously reported methodologies.
PB MDPI
SN 1424-8220 (electrónico)
YR 2023
FD 2023-11-26
LK https://hdl.handle.net/10272/22712
UL https://hdl.handle.net/10272/22712
LA eng
NO Guerrero-Morejón, K., Hinojo-Montero, J. M., Muñoz-Chavero, F., Flores-Garrido, J. L., Gómez-Galán, J. A., & González-Carvajal, R. (2023). Principal Component Analysis Applied to Digital Pulse Shape Analysis for Isotope Discrimination. In Sensors (Vol. 23, Issue 23, p. 9418). MDPI AG. https://doi.org/10.3390/s23239418
NO Grant TED2021-131075B-I00 funded byMCIN/AEI/10.13039/501100011033. Grant PID2021-127711NB-I00 funded by MCIN/AEI/10.13039/501100011033.
DS Repositorio Institucional de la Universidad de Huelva
RD 30 may 2026