Avalanche prediction in Self-organized systems

TL;DR

This paper demonstrates that, contrary to common belief, avalanches in self-organized critical systems like sandpiles can be predicted by monitoring internal structural variations, challenging the idea of inherent unpredictability.

Contribution

It provides experimental evidence that avalanche prediction is possible in classical SOC systems by analyzing internal structural changes.

Findings

Avalanches follow a power-law distribution.

Precursor signals can predict large avalanches.

Internal structural variations precede avalanches.

Abstract

It is a common belief that power-law distributed avalanches are inherently unpredictable. This idea affects phenomena as diverse as evolution, earthquakes, superconducting vortices, stock markets, etc; from atomic to social scales. It mainly comes from the concept of ``Self-organized criticality" (SOC), where criticality is interpreted in the way that at any moment, any small avalanche can eventually cascade into a large event. Nevertheless, this work demonstrates experimentally the possibility of avalanche prediction in the classical paradigm of SOC: a sandpile. By knowing the position of every grain in a two-dimensional pile, avalanches of moving grains follow a distinct power-law distribution. Large avalanches, although uncorrelated, are preceded by continuous, detectable variations in the internal structure of the pile that are monitored in order to achieve prediction.