scholarly journals Do the solar flares originating from an individual active region follow a random process or a memory-dependent correlation?

2020 ◽  
Vol 494 (1) ◽  
pp. 975-982
Author(s):  
W H Lei ◽  
C Li ◽  
F Chen ◽  
S J Zhong ◽  
Z G Xu ◽  
...  
Keyword(s):  
Active Region ◽  
Random Process ◽  
Waiting Time ◽  
Solar Flares ◽  
Three Dimensional ◽  
Mhd Turbulence ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Cycle 24 ◽  
Non Linear System

ABSTRACT We investigate the waiting time statistics of solar flares both in a flare-productive active region (AR 12673) of the solar cycle 24 and in a three-dimensional magnetohydrodynamic (MHD) simulated AR. The statistical models of a discrete random process and a continuous memory-dependent process are applied to interpret the waiting time distributions (WTDs) of solar flares. Our results indicate that the occurrence of a solar flare in an individual AR maintains a certain amount of memory, and probably arises from MHD turbulence rather than from intermittent avalanches in a self-organized criticality system. It differs from the occurrence of ‘super flares’ when treating the star/Sun as a single non-linear system.

STATISTICAL PROPERTIES OF SOLAR FLARES AND COMPARISON TO OTHER IMPULSIVE ENERGY RELEASE EVENTS

2009 ◽  
Vol 23 (28n29) ◽  
pp. 5609-5618 ◽  
Author(s):  
FABIO LEPRETI ◽  
VLADIMIR G. KOSSOBOKOV ◽  
VINCENZO CARBONE
Keyword(s):  
Solar Flare ◽  
Energy Release ◽  
Solar Flares ◽  
Statistical Properties ◽  
Universal Curve ◽  
Mhd Turbulence ◽  
Natural Systems ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Impulsive Processes

Impulsive energy release events are observed in many natural systems. Solar flares are certainly among the most remarkable examples of such processes. In the last years the study of solar flare statistical properties has received considerable attention in the context of solar flare models based on different approaches, such as Self Organized Criticality (SOC) or magnetohydrodynamic (MHD) turbulence. In this talk the main statistical properties of solar flares will be presented and compared to those of other well known impulsive processes, such as earthquakes and soft γ-ray flashes occurring on neutron stars. It is shown that the these phenomena are characterized by different statistics that cannot be rescaled onto a single, universal curve and that this holds even for the same phenomenon, when observed in different periods or at different locations. Our results indicate apparent complexity of impulsive energy release processes, which neither follow a common behavior nor could be attributed to a universal physical mechanism.

Self‐organized Criticality from Separator Reconnection in Solar Flares

2000 ◽  
Vol 542 (2) ◽  
pp. 1088-1099 ◽  
Author(s):  
D. W. Longcope ◽  
E. J. Noonan
Keyword(s):  
Solar Flares ◽  
Self Organized ◽  
Self Organized Criticality

Three-Dimensional Magnetic and Velocity Structures of Active Region 12673

2020 ◽  
Author(s):  
Haimin Wang
Keyword(s):  
Active Region ◽  
Magnetic Fields ◽  
Thermal Structure ◽  
Transverse Velocity ◽  
Free Field ◽  
Three Dimensional ◽  
Velocity Fields ◽  
Height Range ◽  
Cycle 24 ◽  
Force Free Field

<p>We study the Solar Active Region (AR) 12673 in September 2017, which is the most flare productive AR in the solar cycle 24.  Observations from Goode Solar Telescope (GST) show the strong photospheric magnetic fields (nearly 6000 G) in polarity  inversion line (PIL) and apparent photospheric twist on September 6,  the day of X9.3 flare. Corresponding to the strong twist,   upflows are observed to last one day  at the center part of that section of PIL;  down flows are observed in two ends.  Transverse velocity fields are derived from flow tracking.   Both Non-Linear Force-Free Field (NLFFF) and Non-Force-Free Field (NFFF) extrapolations are carried out and compared to trace 3-D magnetic fields in corona. Combining with EOVSA, coronal magnetic fields between 1000 and 2000 gauss are found above the flaring PIL at the height range between 8 and 4Mm, outlining the structure of a fluxrope with sheared arcade.  The above magnetic and velocity fields, as well as thermal structure of corona, provide initial condition for further data-driven MHD simulation.</p>

scholarly journals Predicting large solar flares with data assimilation

2015 ◽  
Vol 11 (A29B) ◽  
pp. 734-734
Author(s):  
Antoine Strugarek ◽  
Paul Charbonneau
Keyword(s):  
Data Assimilation ◽  
Solar Flares ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Sandpile Models

AbstractWe propose to use a deterministically-driven class of self-organized criticality sandpile models to carry out predictions of the largest, most dangerous, and hardest to predict solar flares.

scholarly journals Self-organized criticality in solar flares: a cellular automata approach

2010 ◽  
Vol 17 (4) ◽  
pp. 339-344 ◽  
Author(s):  
L. F. Morales ◽  
P. Charbonneau
Keyword(s):  
Solar Flares ◽  
Electrical Current ◽  
Power Law Distribution ◽  
Additional Energy ◽  
Self Organized ◽  
Anisotropic Lattice ◽  
Self Organized Criticality ◽  
Released Energy ◽  
The Mean ◽  
Electrical Current Density

Abstract. We give an overview of a novel lattice-based avalanche model that reproduces well a number of observed statistical properties of solar flares. The anisotropic lattice is defined as a network of vertically-connected nodes subjected to horizontal random displacements mimicking the kinks introduced by random motions of the photospheric footpoints of magnetic fieldlines forming a coronal loop. We focus here on asymmetrical driving displacements, which under our geometrical interpretation of the lattice correspond to a net direction of twist of the magnetic fieldlines about the loop axis. We show that a net vertical electrical current density does build up in our lattice, as one would expect from systematic twisting of a loop-like magnetic structure, and that the presence of this net current has a profound impact on avalanche dynamics. The presence of an additional energy reservoir tends to increase the mean energy released by avalanches, and yield a probability distribution of released energy in better agreement with observational inferences than in its absence. Symmetrical driving displacements are in better conceptual agreement with a random shuffling of photospheric footpoint, and yield a power-law distribution of energy release with exponent larger than 2, as required in Parker's nanoflare model of coronal heating. On the other hand, moderate asymmetrical driving generate energy distribution exponents that are similar to those obtained from SOHO EUV observations.

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