50 citations · 201 across the 21 of their papers we have counts for
14 papers · 1 filter
Neural Differential Equations for the Solar Dynamo
E. Illarionov, R. Stepanov, K. M. Kuzanyan +1
Physical models aimed to reproduce basic features of the solar sunspot cycle are typically based on the solar dynamo mechanism. Usually qualitative arguments are used to define par…
Correlation of Coronal Hole Area Indices and Solar Wind Speed
Egor Illarionov, Andrey Tlatov, Ivan Berezin +1
Coronal holes (CHs) are widely considered as the main sources of high-speed solar wind streams. We validate this thesis comparing the smoothed time series of solar wind speed measu…
Sunspot positions from observations by Flaugergues in the Dalton Minimum
Egor Illarionov, Rainer Arlt
French astronomer Honoré Flaugergues compiled astronomical observations in a series of hand-written notebooks for 1782$\unicode{x2013}$1830, which are preserved at Paris Observator…
Statistical Study of the Correlation between Solar Energetic Particles and Properties of Active Regions
Russell D. Marroquin, Viacheslav Sadykov, Alexander Kosovichev +9
The flux of energetic particles originating from the Sun fluctuates during the solar cycles. It depends on the number and properties of Active Regions (ARs) present in a single day…
Predicting Solar Proton Events of Solar Cycles 22-24 using GOES Proton & soft X-Ray flux features
Aatiya Ali, Viacheslav Sadykov, Alexander Kosovichev +9
Solar Energetic Particle (SEP) events and their major subclass, Solar Proton Events (SPEs), can have unfavorable consequences on numerous aspects of life and technology, making the…
Reconstruction of the Solar Activity from the Catalogs of the Zurich Observatory
Egor Illarionov, Rainer Arlt
Catalogs of the Zurich Observatory contain positional information on sunspots, prominences and faculae in late 19th and early 20th centuries. This database is given in handwritten…
Parametrization of sunspot groups based on machine learning approach
Egor Illarionov, Andrey Tlatov
Sunspot groups observed in white-light appear as complex structures. Analysis of these structures is usually based on simple morphological descriptors which capture only generic pr…
Finite memory time and anisotropy effects for initial magnetic energy growth in random flow of conducting media
E. A. Illarionov, D. D. Sokoloff
The dynamo mechanism is a process of magnetic field self-excitation in a moving electrically conducting fluid. One of the most interesting applications of this mechanism related to…
Prediction of Solar Proton Events with Machine Learning: Comparison with Operational Forecasts and "All-Clear" Perspectives
Viacheslav Sadykov, Alexander Kosovichev, Irina Kitiashvili +7
Solar Energetic Particle events (SEPs) are among the most dangerous transient phenomena of solar activity. As hazardous radiation, SEPs may affect the health of astronauts in outer…
The Observational Uncertainty of Coronal Hole Boundaries in Automated Detection Schemes
Martin A. Reiss, Karin Muglach, Christian Möstl +16
Coronal holes are the observational manifestation of the solar magnetic field open to the heliosphere and are of pivotal importance for our understanding of the origin and accelera…
Compression of Solar Spectroscopic Observations: a Case Study of Mg II k Spectral Line Profiles Observed by NASA's IRIS Satellite
Viacheslav M Sadykov, Irina N Kitiashvili, Alberto Sainz Dalda +3
In this study we extract the deep features and investigate the compression of the Mg II k spectral line profiles observed in quiet Sun regions by NASA's IRIS satellite. The data se…
Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations
Gelu Nita, Manolis Georgoulis, Irina Kitiashvili +38
The authors of this white paper met on 16-17 January 2020 at the New Jersey Institute of Technology, Newark, NJ, for a 2-day workshop that brought together a group of heliophysicis…
Machine-learning approach to identification of coronal holes in solar disk images and synoptic maps
Egor Illarionov, Alexander Kosovichev, Andrey Tlatov
Identification of solar coronal holes (CHs) provides information both for operational space weather forecasting and long-term investigation of solar activity. Source data for the f…
Segmentation of coronal holes in solar disk images with a convolutional neural network
E. Illarionov, A. Tlatov
Current coronal holes segmentation methods typically rely on image thresholding and require non-trivial image pre- and post-processing. We have trained a neural network that accura…