Theoretical Models of Self-Organized Criticality (SOC) Systems

TL;DR

This chapter reviews classical and analytical models of self-organized criticality (SOC), discussing their universal features, applications, and related processes like turbulence and phase transitions, to understand SOC's observational signatures.

Contribution

It provides a comprehensive summary of classical cellular automaton models, analytical formulations of SOC, and explores related non-SOC processes, highlighting universal aspects and physical scaling laws.

Findings

Universal statistical aspects of SOC models

Analytical formulations applicable to various SOC systems

Shared observational properties among SOC and related processes

Abstract

In this chapter 2 of the e-book "Self-Organized Criticality Systems" we summarize the classical cellular automaton models, which consist of a statistical aspect that is universal to all SOC systems, and a physical aspect that depends on the physical definition of the observable. Then we derive some general analytical formulations of SOC processes, such as the exponential-growth SOC model and the fractal-diffusive SOC model, which also have universal validity for SOC processes, while specific applications to observations require additional physical scaling laws (e.g., for astrophysical or geophysical observations). Finally we discuss alternative SOC processes, SOC-related, or non-SOC processes, such as: self-organization (without criticality), forced SOC model, Brownian motion or classical diffusion, hyper-diffusion and Levy flight, nonextensive Tsallis entropy, turbulence, percolation, phase transitions, network systems, and chaotic systems. We synthesize a metrics that specifies which observational SOC properties are shared by these processes.