Neural network classification of eigenmodes in the magnetohydrodynamic spectroscopy code Legolas

التفاصيل البيبلوغرافية
العنوان: Neural network classification of eigenmodes in the magnetohydrodynamic spectroscopy code Legolas
المؤلفون: De Jonghe, Jordi, Kuczyński, Michał D.
سنة النشر: 2023
المجموعة: Physics (Other)
مصطلحات موضوعية: Physics - Plasma Physics
الوصف: To predict the immediate evolution of a plasma system, one needs to identify the nature of the dominant instability. In this work, a neural network is employed to address a non-binary classification problem of instabilities in astrophysical jets, whose natural oscillations and instabilities are quantified with the magnetohydrodynamic spectroscopy code Legolas. The trained models exhibit reliable performance in the identification of the two instability types supported by these jets. To improve the neural network aided classification process, techniques for training data augmentation and refinement of predictions for general eigenproblems are discussed.
Comment: 16 pages, 6 figures, 4 tables. Accepted for publication in Neural Computing and Applications
نوع الوثيقة: Working Paper
DOI: 10.1007/s00521-023-09403-1
الوصول الحر: http://arxiv.org/abs/2312.08490Test
رقم الانضمام: edsarx.2312.08490
قاعدة البيانات: arXiv