Avalanche prediction in Self-organized systems

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.

4 pages, 4 figures, submitted to PRL

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Cited by in corpus (9)

• Controlling self-organized criticality in sandpile models
• Self-Organization of Dragon Kings
• Some Properties of Sandpile Models as Prototype of Self-Organized Critical Systems
• Fine Structure of Avalanches in the Abelian Sandpile Model
• Reorganization of a granular medium around a localized transformation
• Estimating predictability of depinning dynamics by machine learning
• Fluctuations of particle motion in granular avalanches - from the microscopic to the macroscopic scales
• Force and geometric signatures of the creep-to-failure transition in a granular pile
• Avalanches on a conical bead pile: scaling with tuning parameters