Effect of thresholding on avalanches and their clustering for interfaces with long-range elasticity

TL;DR

This study investigates how thresholding affects avalanche detection and clustering in long-range elastic interfaces, revealing that higher thresholds lead to steeper distributions and increased clustering, with implications for experimental analysis.

Contribution

It demonstrates how threshold choice influences avalanche size, duration, and clustering, bridging theoretical models with experimental observations.

Findings

Higher thresholds produce steeper size and duration distributions.

Avalanches tend to cluster temporally with power-law event frequency decay.

Event size can predict subsequent avalanche activity.

Abstract

Avalanches are often defined as signals higher than some detection level in bursty systems. The choice of the detection threshold affects the number of avalanches, but it can also affect their temporal correlations. We simulated the depinning of a long-range elastic interface and applied different thresholds including a zero one on the data to see how the sizes and durations of events change and how this affects temporal avalanche clustering. Higher thresholds result in steeper size and duration distributions and cause the avalanches to cluster temporally. Using methods from seismology, the frequency of the events in the clusters was found to decrease as a power-law of time, and the size of an event in a cluster was found to help predict how many events it is followed by. The results bring closer theoretical studies of this class of models to real experiments, but also highlight how different phenomena can be obtained from the same set of data.