Related papers: Automatic Detection of Occulted Hard X-ray Flares …
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…
With machine learning entering into the awareness of the heliophysics community, solar flare prediction has become a topic of increased interest. Although machine learning models have advanced with each successive publication, the input…
This paper presents a post hoc analysis of a deep learning-based full-disk solar flare prediction model. We used hourly full-disk line-of-sight magnetogram images and selected binary prediction mode to predict the occurrence of…
We investigate the signature of the photospheric albedo contribution in solar flare hard X-ray spectra, the effect of low energy cutoffs in electron spectra, and the directivity of hard X-ray emission. Using Ramaty High Energy Solar…
We report the first science results from the newly completed Expanded Owens Valley Solar Array (EOVSA), which obtained excellent microwave imaging spectroscopy observations of SOL2017-09-10, a classic partially-occulted solar limb flare…
Solar flare forecasting mainly relies on photospheric magnetograms and associated physical features to predict forthcoming flares. However, it is believed that flare initiation mechanisms often originate in the chromosphere and the lower…
Exoplanet detection with precise radial velocity (RV) observations is currently limited by spurious RV signals introduced by stellar activity. We show that machine learning techniques such as linear regression and neural networks can…
We present X-ray imaging and spectral analysis of all microflares the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) observed between March 2002 and March 2007, a total of 25,705 events. These microflares are small flares,…
Stellar flares are an important aspect of magnetic activity -- both for stellar evolution and circumstellar habitability viewpoints - but automatically and accurately finding them is still a challenge to researchers in the Big Data era of…
RHESSI observations of elementary flare bursts are presented. These solar flare elements are distinct emission peaks of a duration of some tens of seconds present in the hard X-ray light curves. They are characterized by consistent…
Current post-processing techniques for the correction of atmospheric seeing in solar observations -- such as Speckle interferometry and Phase Diversity methods -- have limitations when it comes to their reconstructive capabilities of solar…
Hard X-rays and gamma-rays are the most direct signatures of energetic electrons and ions in the sun's atmosphere which is optically thin at these energies and their radiation involves no coherent processes. Being collisional they are…
Context: Solar flare hard X-rays (HXRs) are thought to be produced by nonthermal coronal electrons stopping in the chromosphere, or remaining trapped in the corona. The collisional thick target model (CTTM) predicts that sources produced by…
Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate classification of such data challenging for traditional machine…
A method for active learning of hyperspectral images (HSI) is proposed, which combines deep learning with diffusion processes on graphs. A deep variational autoencoder extracts smoothed, denoised features from a high-dimensional HSI, which…
Context. Hard X-ray (HXR) spikes refer to fine time structures on timescales of seconds to milliseconds in high-energy HXR emission profiles during solar flare eruptions. Aims. We present a preliminary statistical investigation of temporal…
We attempt to forecast M-and X-class solar flares using a machine-learning algorithm, called Support Vector Machine (SVM), and four years of data from the Solar Dynamics Observatory's Helioseismic and Magnetic Imager, the first instrument…
The study of nonstationary processes in the Sun is of great interest, and lately, multiwavelength observations and registration of magnetic fields are carried out by means of both ground-based telescopes and several specialized spacecraft…
We apply multi-algorithm machine learning models to TESS 2-minute survey data from Sectors 1-72 to identify stellar flares. Models trained with Deep Neural Network, Random Forest, and XGBoost algorithms, respectively, utilized four flare…
One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new Compressed Sensing-based algorithm named VIS_CS, which reconstructs the spatial distribution…