Related papers: Application and interpretation of deep learning fo…
Solar flares are explosions in the solar atmosphere that release intense bursts of short-wavelength radiation and are capable of producing severe space-weather consequences. Flares release free energy built up in coronal fields, which are…
Solar active regions (ARs) are the primary drivers of space weather events, making their early prediction crucial for operational forecasting systems. We develop machine learning models capable of predicting the evolution of magnetic flux…
Magnetic active regions on the Sun are harbingers of space weather events. Understanding the physics of how they form and evolve will improve space weather forecasting. Our aim is to characterise the surface magnetic field and flows for a…
Machine learning (ML) is becoming a critical tool for interrogation of large complex data. Labeling, defined as the process of adding meaningful annotations, is a crucial step of supervised ML. However, labeling datasets is time consuming.…
Solar flares - bursts of high-energy radiation responsible for severe space-weather effects - are a consequence of the occasional destabilization of magnetic fields rooted in active regions (ARs). The complexity of AR evolution is a barrier…
To create early warning capabilities for upcoming Space Weather disturbances, we have selected a dataset of 61 emerging active regions, which allows us to identify characteristic features in the evolution of acoustic power density to…
Solar flares and coronal mass ejections are among the most prominent manifestations of the magnetic activity of the Sun. The strongest events of them tend to occur in active regions (ARs) that are large, complex, and dynamically evolving.…
We developed Long Short-Term Memory (LSTM) models to predict the formation of active regions (ARs) on the solar surface. Using the Doppler shift velocity, the continuum intensity, and the magnetic field observations from the Solar Dynamics…
Using the data on magnetic field maps and continuum intensity for Solar Cycles 23 and 24, we explored 100 active regions (ARs) that produced M5.0 or stronger flares. We focus on the presence/absence of the emergence of magnetic flux in…
Magnetic flux emergence from the convection zone into the photosphere and beyond is a critical component of the behaviour of large-scale solar magnetism. Flux rarely emerges amid field-free areas at the surface, but when it does, the…
Solar eruptions, including flares and coronal mass ejections (CMEs), have a significant impact on Earth. Some flares are associated with CMEs, and some flares are not. The association between flares and CMEs is not always obvious. In this…
Solar flare prediction is a central problem in space weather forecasting and recent developments in machine learning and deep learning accelerated the adoption of complex models for data-driven solar flare forecasting. In this work, we…
Solar flares are defined as outbursts on the surface of the Sun. They occur when energy accumulated in magnetic fields enclosing solar active regions (ARs) is abruptly expelled. Solar flares and associated coronal mass ejections are sources…
Solar flares are explosions on the Sun. They happen when energy stored in magnetic fields around solar active regions (ARs) is suddenly released. In this paper, we present a transformer-based framework, named SolarFlareNet, for predicting…
Flux emergence is crucial for the formation of solar active regions and triggering of various eruptions. However, the detailed mechanisms by which flux emergence drives these eruptions remain unclear and require numerical investigation.…
Strong solar flares and coronal mass ejections, here defined not only as the bursts of electromagnetic radiation but as the entire process in which magnetic energy is released through magnetic reconnection and plasma instability, emanate…
We developed a solar flare prediction model using a deep neural network (DNN), named Deep Flare Net (DeFN). The model can calculate the probability of flares occurring in the following 24 h in each active region, which is used to determine…
We study the effect of newly emerged solar active regions (ARs) on the large-scale magnetic environment of pre-existing ARs (PEARs). We first present a theoretical approach to quantify the "interaction energy" between new ARs and PEARs as…
Current operational forecasts of solar eruptions are made by human experts using a combination of qualitative shape-based classification systems and historical data about flaring frequencies. In the past decade, there has been a great deal…
Solar active regions (ARs) are areas on the Sun with very strong magnetic fields where various activities take place. Prominences are one of the typical solar features in the solar atmosphere, whose eruptions often lead to solar flares and…