Roughness of time series in a critical interface model

TL;DR

This paper investigates the statistical distribution of signal roughness in a critical interface model related to Barkhausen noise, revealing a transition from Gaussian to double-Gaussian distributions as data collection windows shrink.

Contribution

It introduces a detailed analysis of roughness PDFs in a critical interface model, explaining the emergence of double-Gaussian structures with decreasing window size.

Findings

Initial Gaussian PDFs evolve into double-Gaussian structures with smaller windows.

The physical explanation aligns with numerical data.

Connections to experimental observations are proposed.

Abstract

We study roughness probability distribution functions (PDFs) of the time signal for a critical interface model, which is known to provide a good description of Barkhausen noise in soft ferromagnets. Starting with time ``windows'' of data collection much larger than the system's internal ``loading time'' (related to demagnetization effects), we show that the initial Gaussian shape of the PDF evolves into a double-Gaussian structure as window width decreases. We supply a physical explanation for such structure, which is compatible with the observed numerical data. Connections to experiment are suggested.