Applying machine learning method in neutrons and gamma-rays identification according to their pulse shapes
Main Article Content
Abstract
Neutrons and gamma-rays from a 152Cf source have been measured and separated based on the time of flight (TOF) technique. Their pulse shape characteristics measured by EJ-299-33 scintillator were used to train an artificial neural network (ANN) in a machine learning method. Afterward, the ANN was used to predict another set of pulse shape data to identify neutron and gamma-ray events. Comparing to the charge-comparison method, the ANN gave better identification. This result proves a potential application of machine learning method in the nuclear data analysis.
Article Details
Keywords
ANN, machine learning, neutrons, gamma-rays, time of flight
References
[2]. S.Gazula and J.W . Clark, and H. Bohr, Nuclear Physics A540, 1, 1992.
[3]. E. Ronchi et al., Nuclear Instruments and Methods in Physics Research A 610, 534, 2009.
[4]. S. Akkoyun, T. Bayram, S. O. Kara, and A. Sinan, Journal Physics G: Nuclear Particle Physics 40, 055106 (2013).
[5]. R. Utama, J. Piekarewicz, and H. B. Prosper, Physical Review C 93 (2016) 014311.
[6]. L. Neufcourt, Y. Cao, W. Nazarewicz, and F.Viens, Physical Review C 98 (2018) 034318.
[7]. G. A. Negoita et al., Physical Review C 99 (2019) 054308.
[8]. Long-Gang Pang, Nuclear Physics A 1005 (2021) 121972.
[9]. B. D, Linh, et al., “Investigation of the ground-state spin inversion in the neutron-rich 47,49Cl isotopes”, submitted to Physical Review C (2021).
[10]. V. H. Phong et al., Physical Review 100 (2019) 011302(R).
[11]. L. X. Chung et al., Nuclear Science and Technology 9, 48, 2019.
[12]. https://indico.cern.ch/event/737461/contributions/3730613/contribution.pdf
[13]. P.-A. Söderström and J. Nyberg, R. Wolters, Nuclear Instruments and Methods in Physics Research A 594 (2008) 79.
[14]. P.-A. Söderström et al., Nuclear Instruments and Methods in Physics Research A 916 (2019) 238.
[15]. S. Nyibule et al., Nuclear Instruments and Methods in Physics Research Section A 768 (2014) 141.
[16]. https://www.caen.it/download/?filter=CoMPASS
[17]. https://keras.io
[18]. https://www.tensorflow.org/
[19]. https://keras.io/api/layers/activations/