Neural network classification of eigenmodes in the magnetohydrodynamic spectroscopy code Legolas
Date
04/2024Metadata
Show full item recordAbstract
A neural network is employed to address a non-binary classification problem of plasma instabilities in astrophysical jets, calculated with the Legolas code. The trained models exhibit reliable performance in the identification of the two instability types supported by these jets. We also discuss the generation of artificial data and refinement of predictions in general eigenfunction classification problems.
Citation
De Jonghe , J & Kuczyński , M D 2024 , ' Neural network classification of eigenmodes in the magnetohydrodynamic spectroscopy code Legolas ' , Neural Computing and Applications , vol. 36 , pp. 5955–5964 . https://doi.org/10.1007/s00521-023-09403-1
Publication
Neural Computing and Applications
Status
Peer reviewed
ISSN
1433-3058Type
Journal article
Description
JDJ was supported by funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme, Grant agreement No. 833251 PROMINENT ERC-ADG 2018.Collections
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