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Solar flares originate from magnetically active regions but not all solar active regions give rise to a flare. Therefore, the challenge of solar flare prediction benefits by an intelligent computational analysis of physics-based properties…

太阳与恒星天体物理 · 物理学 2019-10-09 Cristina Campi , Federico Benvenuto , Anna Maria Massone , D Shaun Bloomfield , Manolis K Georgoulis , Michele Piana

Whilst the most dynamic solar active regions (ARs) are known to flare frequently, predicting the occurrence of individual flares and their magnitude, is very much a developing field with strong potentials for machine learning applications.…

太阳与恒星天体物理 · 物理学 2020-12-16 M. B. Korsos , R. Erdelyi , J. Liu , H. Morgan

Intermittent magnetohydrodynamical turbulence is most likely at work in the magnetized solar atmosphere. As a result, an array of scaling and multi-scaling image-processing techniques can be used to measure the expected self-organization of…

天体物理学 · 物理学 2007-05-23 Manolis K. Georgoulis

Large scale solar eruptions significantly impact space weather and damages space-based human infrastructures. It is necessary to predict large scale solar eruptions, which will enable us to protect our vulnerable infrastructures of modern…

太阳与恒星天体物理 · 物理学 2020-07-08 Soumitra Hazra , Gopal Sardar , Partha Choudhuri

Based on several magnetic nonpotentiality parameters obtained from the vector photospheric active region magnetograms obtained with the Solar Magnetic Field Telescope at the Huairou Solar Observing Station over two solar cycles, a machine…

太阳与恒星天体物理 · 物理学 2013-08-29 Xiao Yang , GangHua Lin , HongQi Zhang , XinJie Mao

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…

太阳与恒星天体物理 · 物理学 2020-03-11 Brandon Panos , Lucia Kleint

The precise physical process that triggers solar flares is not currently understood. Here we attempt to capture the signature of this mechanism in solar image data of various wavelengths and use these signatures to predict flaring activity.…

太阳与恒星天体物理 · 物理学 2018-03-14 Eric Jonas , Monica G. Bobra , Vaishaal Shankar , J. Todd Hoeksema , Benjamin Recht

The prediction of solar flares is of practical and scientific interest; however, many machine learning methods used for this prediction task do not provide the physical explanations behind a model's performance. We made use of two recently…

太阳与恒星天体物理 · 物理学 2023-03-08 Brandon Panos , Lucia Kleint , Jonas Zbinden

Solar flares create adverse space weather impacting space and Earth-based technologies. However, the difficulty of forecasting flares, and by extension severe space weather, is accentuated by the lack of any unique flare trigger or a single…

Solar flares emanate from solar active regions hosting complex and strong bipolar magnetic fluxes. Estimating the probability of an active region to flare and defining reliable precursors of intense flares is an extremely challenging task…

We study the photospheric magnetic field of ~2000 active regions in solar cycle 23 to search for parameters indicative of energy build-up and subsequent release as a solar flare. We extract three sets of parameters: snapshots in space and…

太阳与恒星天体物理 · 物理学 2015-07-01 Amani Al-Ghraibah , Laura. E. Boucheron , R. T. James McAteer

Solar flares are extremely energetic phenomena in our Solar System. Their impulsive, often drastic radiative increases, in particular at short wavelengths, bring immediate impacts that motivate solar physics and space weather research to…

Solar active regions and the processes that occur in them have been extensively studied and analyzed and many types of models and characterizations have been proposed for the occurrence of different eruptive events that take place in the…

太阳与恒星天体物理 · 物理学 2020-12-09 N. Granados Hernández , S. Vargas Domínguez

We study the predictive capabilities of magnetic feature properties (MF) generated by Solar Monitor Active Region Tracker (SMART) for solar flare forecasting from two datasets: the full dataset of SMART detections from 1996 to 2010 that has…

太阳与恒星天体物理 · 物理学 2018-12-07 Katarina Domijan , D. Shaun Bloomfield , Francois Pitie

We propose a forecasting approach for solar flares based on data from Solar Cycle 24, taken by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) mission. In particular, we use the Space-weather HMI…

Solar flares are among the most severe space weather phenomena, and they have the capacity to generate radiation storms and radio disruptions on Earth. The accurate prediction of solar flare events remains a significant challenge, requiring…

太阳与恒星天体物理 · 物理学 2023-10-31 Vysakh P. A. , Prateek Mayank

Solar flares, especially the M- and X-class flares, are often associated with coronal mass ejections (CMEs). They are the most important sources of space weather effects, that can severely impact the near-Earth environment. Thus it is…

太阳与恒星天体物理 · 物理学 2022-12-02 Hewei Zhang , Qin Li , Yanxing Yang , Ju Jing , Jason T. L. Wang , Haimin Wang , Zuofeng Shang

Current operational forecasts of solar eruptions are made by human experts using a combination of qualitative shape-based classification systems and historical data about flaring frequencies. In the past decade, there has been a great deal…

太阳与恒星天体物理 · 物理学 2020-06-02 V. Deshmukh , T. E. Berger , E. Bradley , J. D. Meiss

In this dataset we provide a comprehensive collection of magnetograms (images quantifying the strength of the magnetic field) from the National Aeronautics and Space Administration's (NASA's) Solar Dynamics Observatory (SDO). The dataset…

太阳与恒星天体物理 · 物理学 2024-02-13 Laura E. Boucheron , Ty Vincent , Jeremy A. Grajeda , Ellery Wuest

Photospheric vector magnetograms from Helioseismic and Magnetic Imager on board the Solar Dynamic Observatory are utilized as the boundary conditions to extrapolate both non-linear force-free and potential magnetic fields in solar corona.…

太阳与恒星天体物理 · 物理学 2015-06-19 J. T. Su , J. Jing , S. Wang , T. Wiegelmann , H. M. Wang
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