Machine learning in solar physics
A Asensio Ramos, MCM Cheung, I Chifu… - Living Reviews in Solar …, 2023 - Springer
The application of machine learning in solar physics has the potential to greatly enhance our
understanding of the complex processes that take place in the atmosphere of the Sun. By …
understanding of the complex processes that take place in the atmosphere of the Sun. By …
[HTML][HTML] Prediction of solar energetic events impacting space weather conditions
Aiming to assess the progress and current challenges on the formidable problem of the
prediction of solar energetic events since the COSPAR/International Living With a Star …
prediction of solar energetic events since the COSPAR/International Living With a Star …
Modelling solar coronal magnetic fields with physics-informed neural networks
H Baty, V Vigon - Monthly Notices of the Royal Astronomical …, 2024 - academic.oup.com
We present a novel numerical approach aiming at computing equilibria and dynamics
structures of magnetized plasmas in coronal environments. A technique based on the use of …
structures of magnetized plasmas in coronal environments. A technique based on the use of …
Machine learning in solar physics
The application of machine learning in solar physics has the potential to greatly enhance our
understanding of the complex processes that take place in the atmosphere of the Sun. By …
understanding of the complex processes that take place in the atmosphere of the Sun. By …
Solving the Orszag–Tang vortex magnetohydrodynamics problem with physics-constrained convolutional neural networks
A Bormanis, CA Leon, A Scheinker - Physics of Plasmas, 2024 - pubs.aip.org
We study the 2D Orszag–Tang vortex magnetohydrodynamics (MHD) problem through the
use of physics-constrained convolutional neural networks (PCNNs) for forecasting the …
use of physics-constrained convolutional neural networks (PCNNs) for forecasting the …
Advancing solar magnetic field extrapolations through multiheight magnetic field measurements
R Jarolim, B Tremblay, M Rempel… - The Astrophysical …, 2024 - iopscience.iop.org
Nonlinear force-free extrapolations are a common approach to estimate the 3D topology of
coronal magnetic fields based on photospheric vector magnetograms. The force-free …
coronal magnetic fields based on photospheric vector magnetograms. The force-free …
Spectropolarimetric Inversion in Four Dimensions with Deep Learning (SPIn4D). I. Overview, Magnetohydrodynamic Modeling, and Stokes Profile Synthesis
Abstract The National Science Foundation's Daniel K. Inouye Solar Telescope (DKIST) will
provide high-resolution, multiline spectropolarimetric observations that are poised to …
provide high-resolution, multiline spectropolarimetric observations that are poised to …
[HTML][HTML] Multipoint study of the rapid filament evolution during a confined C2 flare on 28 March 2022, leading to eruption
Aims. This study focuses on the rapid evolution of the solar filament in active region 12975
during a confined C2 flare on 28 March 2022, which finally led to an eruptive M4 flare 1.5 h …
during a confined C2 flare on 28 March 2022, which finally led to an eruptive M4 flare 1.5 h …
Photospheric signatures of CME onset
OPM Aslam, D MacTaggart, T Williams… - Monthly Notices of …, 2024 - academic.oup.com
Coronal mass ejections (CMEs) are solar eruptions that involve large-scale changes to the
magnetic topology of an active region. There exists a range of models for CME onset which …
magnetic topology of an active region. There exists a range of models for CME onset which …
First Insights into the Applicability and Importance of Different 3D Magnetic Field Extrapolation Approaches for Studying the Preeruptive Conditions of Solar Active …
Abstract The three-dimensional (3D) coronal magnetic field has not yet been directly
observed. However, for a better understanding and prediction of magnetically driven solar …
observed. However, for a better understanding and prediction of magnetically driven solar …