Related papers: Application and interpretation of deep learning fo…

Geomagnetic disturbance forecasting is based on the identification of solar wind structures and accurate determination of their magnetic field orientation. For nowcasting activities, this is currently a tedious and manual process. Focusing…

This work presents a new approach for premixed turbulent combustion modeling based on convolutional neural networks (CNN). We first propose a framework to reformulate the problem of subgrid flame surface density estimation as a machine…

We developed a flare prediction model using machine learning, which is optimized to predict the maximum class of flares occurring in the following 24 h. Machine learning is used to devise algorithms that can learn from and make decisions on…

The interaction between emerging active regions and the pre-existing coronal magnetic field is important to understand better the mechanisms of storage and release of magnetic energy from the convection zone to the high corona. We are…

Detecting extreme events in large datasets is a major challenge in climate science research. Current algorithms for extreme event detection are build upon human expertise in defining events based on subjective thresholds of relevant…

Strong solar flares and coronal mass ejections (CMEs) are prone to originate within and near active regions (ARs) with a high magnetic complexity. Therefore, to better understand the generation mechanism of flares and the resultant CME…

Emergence, where complex behaviors develop from the interactions of simpler components within a network, plays a crucial role in enhancing neural network capabilities. We introduce a quantitative framework to measure emergence during the…

Machine learning models have been employed to perform either physics-free data-driven or hybrid dynamical downscaling of climate data. Most of these implementations operate over relatively small downscaling factors because of the challenge…

Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions of galaxies will have to be inspected to identify potential…

We study the evolution of electric currents during the emergence of magnetic flux in the solar photosphere and the differences exhibited between solar active regions of different Hale complexity classes. A sample of 59 active regions was…

We developed a reliable probabilistic solar flare forecasting model using a deep neural network, named Deep Flare Net-Reliable (DeFN-R). The model can predict the maximum classes of flares that occur in the following 24 h after observing…

Current models on Explainable Artificial Intelligence (XAI) have shown an evident and quantified lack of reliability for measuring feature-relevance when statistically entangled features are proposed for training deep classifiers. There has…

We use observations of line-of-sight magnetograms from Helioseismic and Magnetic Imager (HMI) on board of Solar Dynamics Observatory (SDO) to investigate polarity separation, magnetic flux, flux emergence rate, twist and tilt of solar…

Statistical properties of the Sun's photospheric turbulent magnetic field, especially those of the Active Regions (ARs), have been studied using the line-of-sight data from magnetograms taken by SOHO and several other instruments (see e.g.…

Neutrinos can interact in the atmosphere (downward-going {\nu}) or in the Earth crust (Earth-skimming {\nu}), producing air showers that can be observed with arrays of detectors at the ground. The surface detector array of the Pierre Auger…

The ability to recognize facial expressions automatically enables novel applications in human-computer interaction and other areas. Consequently, there has been active research in this field, with several recent works utilizing…

The tearing mode, a large-scale MHD instability in tokamak, typically disrupts the equilibrium magnetic surfaces, leads to the formation of magnetic islands, and reduces core electron temperature and density, thus resulting in significant…

We studied 101 flux emergence events ranging from small ephemeral regions to large emerging flux regions which were observed with Hinode Solar Optical Telescope filtergram. We investigated how the total magnetic flux of the emergence event…

We report a systematic strengthening of the local solar surface or fundamental $f$-mode $1$-$2$ days prior to the emergence of an active region (AR) in the same (corotating) location. Except for a possibly related increase in the kurtosis…

Craters are among the most studied geomorphic features in the Solar System because they yield important information about the past and present geological processes and provide information about the relative ages of observed geologic…