A Statistical Fractal-Diffusive Avalanche Model of a Slowly-Driven Self-Organized Criticality System

TL;DR

This paper introduces a fractal-diffusive analytical model for avalanches in slowly-driven self-organized criticality systems, predicting power-law distributions and correlations that align with simulations, and has implications for understanding energy release in solar flares.

Contribution

The paper presents a novel statistical fractal-diffusive SOC model that analytically predicts avalanche distributions and correlations in three-dimensional systems, validated by simulations.

Findings

Power-law distributions for avalanche parameters with specific slopes.

Agreement between model predictions and cellular automaton simulations within 10%.

Energy distribution slopes suggest large events dominate energy release, impacting solar flare theories.

Abstract

We develop a statistical analytical model that predicts the occurrence frequency distributions and parameter correlations of avalanches in nonlinear dissipative systems in the state of a slowly-driven self-organized criticality (SOC) system. This model, called the fractal-diffusive SOC model, is based on the following four assumptions: (i) The avalanche size $L$ grows as a diffusive random walk with time $T$, following $L \propto T^{1/2}$; (ii) The instantaneous energy dissipation rate $f(t)$ occupies a fractal volume with dimension $D_S$, which predicts the relationships $F = f(t=T) \propto L^{D_S} \propto T^{D_S/2}$, $P \propto L^{S} \propto T^{S/2}$ for the peak energy dissipation rate, and $E \propto F T \propto T^{1+D_S/2}$ for the total dissipated energy; (iii) The mean fractal dimension of avalanches in Euclidean space $S=1,2,3$ is $D_S \approx (1+S)/2$; and (iv) The occurrence frequency distributions $N(x) \propto x^{-\alpha_x}$ based on spatially uniform probabilities in a SOC system are given by $N(L) \propto L^{-S}$, which predicts powerlaw distributions for all parameters, with the slopes $\alpha_T=(1+S)/2$, $\alpha_F=1+(S-1)/D_S$, $\alpha_P=2-1/S$, and $\alpha_E=1+(S-1)/(D_S+2)$. We test the predicted fractal dimensions, occurrence frequency distributions, and correlations with numerical simulations of cellular automaton models in three dimensions $S=1,2,3$ and find satisfactory agreement within $\approx 10%$. One profound prediction of this universal SOC model is that the energy distribution has a powerlaw slope in the range of $\alpha_E=1.40-1.67$, and the peak energy distribution has a slope of $\alpha_P=1.67$ (for any fractal dimension $D_S=1,...,3$ in Euclidean space S=3), and thus predicts that the bulk energy is always contained in the largest events, which rules out significant nanoflare heating in the case of solar flares.