We assess the predictive capabilities of various classes of avalanche models for solar flares. We demonstrate that avalanche models cannot generally be used to predict specific events due to their high sensitivity to their embedded stochastic process. We show that deterministically driven models can nevertheless alleviate this caveat and be efficiently used for large events predictions. Our res...

Observations over the past two solar cycles show a highly irregular pattern of occurrence for major solar flares, γ-ray events, and solar energetic particle (SEP) fluences. Such phenomena do not appear to follow the direct indices of solar magnetic activity, such as the sunspot number. I show that this results from non-Poisson occurrence for the most energetic events. This Letter also points ou...

Measurement of the evolution properties of solar flares through their complete cyclic development is crucial in the studies of Solar Physics. From the analysis of solar Hα images, we used Support Vector Machines (SVMs) to automatically detect flares and applied image segmentation techniques to compute their properties. We also present a solution for automatically tracking the apparent separatio...

of an M7.9 class flare on 13 March 2012. It is shown here in the 131 Å wavelength, which is particularly good for seeing solar flares and is typically colourized in teal. The flare was from the same active region, no. 1429, that produced flares and coronal mass ejections the entire week. The region had been moving across the face of the Sun since 2 March, then rotated out of Earth view. But per...

The existence of power law statistics in solar and stellar flares has prompted the suggestion that solar and stellar coronae are in a self-organized critical state, but the physical foundation of this theory is lacking. We present observational evidence from 107 flare events in 37 sun-like stars that solar and stellar coronae self-organize into a critical state set by a bifurcation in the dynam...

The focus of the automatic solar flare detection is on the development of efficient feature-based classifiers. The three principal techniques used in this work are Multi-Layer Perceptron (MLP), Radial Basis Function (RBF), and Support Vector Machine (SVM) classifiers. We have experimented and compared these three methods for solar flare detection on the solar Hα (Hydrogen-Alpha) images obtained...

Hard X-ray (HXR) spectroscopy is the most direct method of diagnosing energetic electrons in solar flares. Here we present a technique which allows us to use a single HXR spectrum to determine an effectively stereoscopic electron energy distribution. Considering the Sun’s surface to act as a ’Compton mirror’ allows us to look at emitting electrons also from behind the source, providing vital in...

We have developed a new type of cellular automaton (CA) model, the extended CA (X-CA), for the study of solar flares. The X-CA model is consistent with the MHD approach, in contrast to the previously proposed CA models (classical CAs), it consistently yields all the relevant physical variables, and it successfully reproduces the observed distributions of total energy, peak flux, and duration of...

A data mining system designed to associate previous solar flares with sunspot groups using databases from Nobeyama Radioheliograph and the National Geophysical Data Center, and associated data used for training verification, and comparison of several Neural Networks topologies which can be used with an automated solar activity prediction system in the future. The data mining system manages to a...

We treat in detail positron production from the decay of radioactive nuclei produced in nuclear reactions of accelerated 3He. Because of their large cross sections and low threshold energies, these reactions can significantly contribute to positron production in solar flares with accelerated-particle compositions enriched in 3He. The addition of these 3He reactions extends earlier calculations ...