Related papers: Improvements on coronal hole detection in SDO/AIA …
Filaments are omnipresent features in the solar atmosphere. Their location, properties and time evolution can provide information about changes in solar activity and assist the operational space weather forecast. Therefore, filaments have…
Magnetic field diagnostics of the transition region from the chromosphere to the corona faces us with the problem that one has to apply extreme UV spectro-polarimetry. While for coronal diagnostic techniques already exist through infrared…
Coronal loops serve as the fundamental building blocks of the solar corona. Therefore, comprehending their properties is essential in unraveling the dynamics of the Sun's upper atmosphere. In this study, we conduct a comparative analysis of…
Magnetic fields are the primary driver of the plasma thermodynamics in the upper solar atmosphere, especially in the corona. However, magnetic field measurements in the solar corona are sporadic, thereby limiting us from the complete…
In order to address the growing need for more accurate space weather predictions, a new model named EUHFORIA (EUropean Heliospheric FORecasting Information Asset) was recently developed (Pomoell and Poedts, 2018). We present first results…
Extreme Ultraviolet images of the Sun are becoming an integral part of space weather prediction tasks. However, having different surveys requires the development of instrument-specific prediction algorithms. As an alternative, it is…
X-ray and EUV observations are an important diagnostic of various plasma parameters of the solar atmosphere during solar flares. Soft X-ray and EUV observations often show coronal sources near the top of flaring loops, while hard X-ray…
We developed an automated pattern recognition code that is particularly well suited to extract one-dimensional curvi-linear features from two-dimensional digital images. A former version of this {\sl Oriented Coronal CUrved Loop Tracing…
In order to utilize solar imagery for real-time feature identification and large-scale data science investigations of solar structures, we need maps of the Sun where phenomena, or themes, are labeled. Since solar imagers produce…
As the observational signature of the footprints of solar magnetic field lines open into the heliosphere, coronal holes provide a critical measure of the structure and evolution of these lines. Using a combination of Solar and Heliospheric…
We introduce a new method for the investigation of low-amplitude transverse oscillations of solar plasma non-uniformities, such as coronal loops, individual strands in coronal arcades, jets, prominence fibrils, polar plumes, and other…
With the advent of deep learning for computer vision tasks, the need for accurately labeled data in large volumes is vital for any application. The increasingly available large amounts of solar image data generated by the Solar Dynamic…
This study proposes an enhancement to the existing method for detecting Solar Active Regions (ARs). Our technique tracks ARs using images from the Atmospheric Imaging Assembly (AIA) of NASA's Solar Dynamics Observatory (SDO). It involves a…
Despite decades of studying the Sun, the coronal heating problem remains unsolved. One fundamental issue is that we do not know the spatial scale of the coronal heating mechanism. At a spatial resolution of 1000 km or more it is likely that…
We investigate the relationship between solar coronal holes and open-field regions using three-dimensional radiative magnetohydrodynamic (MHD) simulations combined with remote-sensing observations from the Solar Dynamics Observatory (SDO).…
The SDO/HMI instruments provide photospheric vector magnetograms with a high spatial and temporal resolution. Our intention is to model the coronal magnetic field above active regions with the help of a nonlinear force-free extrapolation…
We estimated the accuracy of coronal magnetic fields derived from radio observations by comparing them to potential field calculations and the DEM measurements using EUV observations. We derived line of sight component of the coronal…
Magnetic field extrapolation is an important tool to study the three-dimensional (3D) solar coronal magnetic field which is difficult to directly measure. Various analytic models and numerical codes exist but their results often drastically…
We propose and test a wavelet transform modulus maxima method for the au- tomated detection and extraction of coronal loops in extreme ultraviolet images of the solar corona. This method decomposes an image into a number of size scales and…
We present a novel method of classifying Type Ia supernovae using convolutional neural networks, a neural network framework typically used for image recognition. Our model is trained on photometric information only, eliminating the need for…