Neural network classification of eigenmodes in the magnetohydrodynamic spectroscopy code Legolas
Published in Neural Computing and Applications, 2024
Abstract. 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.
Preprint - arXiv:2312.08490
Data set - doi:10.34740/KAGGLE/DS/2750846
Recommended citation: De Jonghe, J. and Kuczyński, M. D. (2024). "Neural network classification of eigenmodes in the magnetohydrodynamic spectroscopy code Legolas." Neural Comput. Appl. 36, 5955–5964. http://doi.org/10.1007/s00521-023-09403-1