Simulation and Analysis of the Properties of Linear Structures in the Mass Distribution of Nuclear Reaction Products by Machine Learning Methods

This paper is devoted to the analysis of manifestations of clustering in rare multibody decays of heavy nuclei. A computer model of the fine structure was developed jointly with the physicists of FLNR JINR; it was found based on experiments with the transuranium element Californium. To test the hypo...

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Bibliographic Details
Published inPhysics of particles and nuclei letters Vol. 18; no. 5; pp. 559 - 569
Main Authors Ososkov, G. A., Pyatkov, Yu. V., Rudenko, M. O.
Format Journal Article
LanguageEnglish
Published Moscow Pleiades Publishing 01.09.2021
Springer Nature B.V
Subjects
Californium
Clustering
Fine structure
Heavy nuclei
Machine learning
Mass distribution
Nuclear reactions
Particle and Nuclear Physics
Physicists
Physics
Physics and Astronomy
Physics of Elementary Particles and Atomic Nuclei. Experiment
Reaction products
Transuranium elements
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Summary:This paper is devoted to the analysis of manifestations of clustering in rare multibody decays of heavy nuclei. A computer model of the fine structure was developed jointly with the physicists of FLNR JINR; it was found based on experiments with the transuranium element Californium. To test the hypothesis that the structure really exists and is not a noise artifact, it was proposed to use a deep convolution network as a binary classifier trained on a large sample of model and noise images. Preliminary results of using the developed neuroclassifier show the prospects for this approach.
ISSN:1547-4771
1531-8567
DOI:10.1134/S1547477121050083