Multifractal structure of Barkhausen noise: A signature of collective dynamics at hysteresis loop
Bosiljka Tadic

TL;DR
This study uses multifractal analysis of Barkhausen noise to reveal how collective domain dynamics differ between weak and strong pinning regimes in disordered magnetic systems, with implications for memory device technologies.
Contribution
It introduces a multifractal analysis approach to distinguish between different pinning regimes and understand the underlying collective dynamics in magnetisation reversal processes.
Findings
Multifractal spectra differentiate weak and strong pinning regimes.
Increased driving rates affect small fluctuation segments and spectrum broadening.
Multifractal properties correlate with domain wall motion mechanisms.
Abstract
The field-driven magnetisation reversal processes in disordered systems exhibit a collective behaviour that is manifested in the scale-invariance of avalanches, closely related to underlying dynamical mechanisms. Using the multifractal time series analysis, we study the structure of fluctuations at different scales in the accompanying Barkhausen noise. The stochastic signal represents the magnetisation discontinuities along the hysteresis loop of a 3-dimensional random field Ising model simulated for varied disorder strength and driving rates. The analysis of the spectrum of the generalised Hurst exponents reveals that the segments of the signal with large fluctuations represent two distinct classes of stochastic processes in weak and strong pinning regimes. Furthermore, increased driving rates have a profound effect on the small fluctuation segments and broadening of the spectrum. The…
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Nonlinear Dynamics and Pattern Formation · Theoretical and Computational Physics
