Related papers: Identifying Flux Rope Signatures Using a Deep Neur…
The identification of local modules in dynamic networks with known topology has recently been addressed by formulating conditions for arriving at consistent estimates of the module dynamics, typically under the assumption of having…
Context. In the scope of space weather forecasting, it is crucial to be able to more reliably predict the arrival time, speed, and magnetic field configuration of coronal mass ejections (CMEs). From the time a CME is launched, the dominant…
Disruption prediction has made rapid progress in recent years, especially in machine learning (ML)-based methods. Understanding why a predictor makes a certain prediction can be as crucial as the prediction's accuracy for future tokamak…
Coronal mass ejections (CME) occur when long-lived magnetic flux ropes (MFR) anchored to the solar surface destabilize and erupt away from the Sun. This destabilization is often described in terms of an ideal magnetohydrodynamic (MHD)…
Magnetic flux rope (MFR) is the core structure of the greatest eruptions, i.e., the coronal mass ejections (CMEs), on the Sun, and magnetic clouds are post-eruption MFRs in interplanetary space. There is a strong debate about whether or not…
Many large scale problems in computational fluid dynamics such as uncertainty quantification, Bayesian inversion, data assimilation and PDE constrained optimization are considered very challenging computationally as they require a large…
We present a 2.5D MHD simulation of a magnetic flux rope (FR) propagating in the heliosphere and investigate the cause of the observed sharp plasma beta transition. Specifically, we consider a strong internal magnetic field and an explosive…
One of the very common in situ signatures of interplanetary coronal mass ejections (ICMEs), as well as other interplanetary transients, are Forbush decreases (FDs), i.e. short-term reductions in the galactic cosmic ray (GCR) flux. A…
We present a catalogue of 35 interplanetary coronal mass ejections (ICMEs) observed by the Juno spacecraft and at least one other spacecraft during its cruise phase to Jupiter. We identify events observed by MESSENGER, Venus Express, Wind,…
Currently, achieving a balance between computational efficiency, accuracy, and numerical stability in CME simulations, particularly in the sub-Alfv{'e}nic coronal region, remains a significant challenge. This paper aims to address the…
Extreme ultraviolet (EUV) images from the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamic Observatory (SDO) are providing new insights into the early phase of CME evolution. Observations now show the ejection of magnetic flux…
In this study, we analyze nine CMEs from the Sun to Earth as observed in both the remote sensing and in situ data sets. To date, this is the largest study of Earth impacting CMEs using the multi-view point remote sensing and in situ data.…
We study the so-called neural network flow of spin configurations in the 2-d Ising ferromagnet. This flow is generated by successive reconstructions of spin configurations, obtained by an artificial neural network like a restricted…
Deep learning has been employed to identify flow characteristics from Computational Fluid Dynamics (CFD) databases to assist the researcher to better understand the flow field, to optimize the geometry design and to select the correct CFD…
We systematically search for magnetic flux rope structures in the solar wind to within the closest distance to the Sun of 0.13 AU, using data from the third and fourth orbits of the Parker Solar Probe. We extend our previous magnetic…
The identification of local modules in dynamic networks with known topology has recently been addressed by formulating conditions for arriving at consistent estimates of the module dynamics, under the assumption of having disturbances that…
This paper describes a study based on computational fluid dynamics (CFD) and deep neural networks that focusing on predicting the flow field in differently distorted U-shaped pipes. The main motivation of this work was to get an insight…
Interplanetary coronal mass ejections (ICMEs) are magnetic structures propagating from the Sun's corona to the interplanetary medium. With over 20 years of observations at the L1 libration point, ACE offers hundreds of ICMEs detected at…
The characterization of an exoplanet's interior is an inverse problem, which requires statistical methods such as Bayesian inference in order to be solved. Current methods employ Markov Chain Monte Carlo (MCMC) sampling to infer the…
Coronal mass ejections (CMEs) are magnetized plasma systems with highly complex magnetic topology and evolution. Methods developed to assess their magnetic configuration have primarily focused on reconstructing three-dimensional…