Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-27T00:34:56.305Z Has data issue: false hasContentIssue false
  • English
  • Français

Comparison of Predictive Efficiency of Topological Descriptors and SHARP in Solar Flares Forecasting

Published online by Cambridge University Press:  24 July 2018

Irina Knyazeva ,
Fedor Urtiev  and
Nikolay Makarenko
Irina Knyazeva
Affiliation:
Pulkovo Observatory, Saint-Petersburg email: [email protected] Saint-Petersburg State University, Saint-Petersburg, Russia email: [email protected]
Fedor Urtiev
Affiliation:
Pulkovo Observatory, Saint-Petersburg email: [email protected]
Nikolay Makarenko
Affiliation:
Pulkovo Observatory, Saint-Petersburg email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In the current paper, we investigate topological invariants, calculated by HMI LOS magnetograms as complexity descriptors of solar magnetic fields. We compared them with the physical parameters provided by the Space-weather HMI Active Region Patches (SHARP). We have repeated forecasting experiment of Stanford Solar Observatories Group with the same positive and negative active region patches database, but replace SHARP parameters with topological invariants of corresponding LOS magnetograms. The classification results turned out practically identical to those obtained by the Stanford Solar Observatory group. This means that using LOS magnetograms retains enough complexity for magnetic field description.

Keywords

methods: numericalmethods: statisticalSun: magnetic fieldsSun: flares
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 13 , Symposium S335: Space Weather of the Heliosphere: Processes and Forecasts , July 2017 , pp. 291 - 293
Copyright
Copyright © International Astronomical Union 2018 

References

Bobra, M. G., Sun, X., Hoeksema, J. T., Turmon, M., Liu, Y., Hayashi, K., Barnes, G. & Leka, K. D., 2014, SoPh, 289, 3549Google Scholar
Makarenko, N. G., Malkova, D. B., Machin, M. L., Knyazeva, I. S. & Makarenko, I. N., 2014, Fundam. Prikl. Mat. (Russian), translation in J. Math. Sci., 203, 806Google Scholar
Edelsbrunner, H. & Harer, J. 2010, Computational topology: an introduction. AMSCrossRefGoogle Scholar
Adler, Robert J. 2010, The geometry of random fields, volume 62 of Classics in Applied Mathematics. SIAM, Philadelphia, PACrossRefGoogle Scholar
Juda, M. & Mrozek, M. 2014, ICMS 160–166CrossRefGoogle Scholar