Related papers: Improved detection of farside solar active regions…
A solar active region can significantly disrupt the Sun Earth space environment, often leading to severe space weather events such as solar flares and coronal mass ejections. As a consequence, the automatic classification of active region…
Helioseismic techniques such as ring-diagram analysis have often been used to determine the subsurface structural differences between solar active and quiet regions. Results obtained by inverting the frequency differences between the…
This study addresses the prediction of geomagnetic disturbances by exploiting machine learning techniques. Specifically, the Long-Short Term Memory recurrent neural network, which is particularly suited for application over long time…
Solar magnetic fields play a key role in understanding the nature of the coronal phenomena. Global coronal magnetic fields are usually extrapolated from photospheric fields, for which farside data is taken when it was at the frontside,…
We use a publicly available numerical wave-propagation simulation of Hartlep et al. 2011 to test the ability of helioseismic holography to detect signatures of a compact, fully submerged, 5% sound-speed perturbation placed at a depth of 50…
The paper presents a reliable method using deep learning to recognize solar filaments in H-alpha full-disk solar images automatically. This method cannot only identify filaments accurately but also minimize the effects of noise points of…
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…
Reliable earthquake detection and seismic phase classification is often challenging especially in the circumstances of low magnitude events or poor signal-to-noise ratio. With improved seismometers and better global coverage, a sharp…
Accurate and reliable predictions of solar flares are essential due to their potentially significant impact on Earth and space-based infrastructure. Although deep learning models have shown notable predictive capabilities in this domain,…
Helioseismology is one of the most successful fields of astrophysics. The observation and characterization of solar oscillation has allowed solar seismologists to study the internal structure and dynamics of the Sun with unprecedented…
Context. Tracing wave activity from the photosphere to the corona has important implications for coronal heating and prediction of the solar wind. Despite extensive theory and simulations, the detection of waves in realistic MHD simulations…
Efficient prediction of solar flares relies on parameters that quantify the eruptive capability of solar active regions. Several such quantitative predictors have been proposed in the literature, inferred mostly from photospheric…
The solar tachocline at the bottom of the convection zone is an important region for the dynamics of the Sun and the solar dynamo. In this region, the sound speed inferred by global helioseismology exhibits a bump of approximately 0.4%…
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 using techniques such as deep learning, we are now in the…
Helioseismology, the study of global solar oscillations, has proved to be an extremely powerful tool for the investigation of the internal structure and dynamics of the Sun. Studies of time changes in frequency observations of solar…
Strong solar magnetic fields are the energy source of intense flares and energetic coronal mass ejections of space weather importance. The key issue is the difficulty in predicting the occurrence time and location of strong solar eruptions,…
Solar active regions are where sunspots are located and photospheric magnetic fluxes are concentrated, therefore being the sources of energetic eruptions in the solar atmosphere. The detection and statistics of solar active regions have…
Observations from the Solar Dynamics Observatory (SDO) have the potential for allowing the helioseismic study of the formation of hundreds of active regions, which would enable us to perform statistical analyses. Our goal is to collate a…
Sunspot regions often form complexes of activity that may live for several solar rotations, and represent a major component of the Sun's magnetic activity. It had been suggested that the close appearance of active regions in space and time…
Time-distance helioseismic measurements in surface- and deep-focus geometries for wave-paths that distinguish surface magnetic contributions from those due to deeper perturbations beneath a large sunspot are presented and analysed. Travel…