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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Veröffentlicht in:Physics of particles and nuclei letters 2021-09, Vol.18 (5), p.559-569
Hauptverfasser: Ososkov, G. A., Pyatkov, Yu. V., Rudenko, M. O.
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Rudenko, M. O.
description 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.
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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
title Simulation and Analysis of the Properties of Linear Structures in the Mass Distribution of Nuclear Reaction Products by Machine Learning Methods
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