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Stochastic model of hysteresis

Pal1

  • 1KFKI Atomic Energy Research Institute, P.O. Box 49, 1525 Budapest, Hungary.

Physical Review. E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
|November 23, 2000
PubMed
Summary

This study introduces a novel probability theory model for hysteresis, differing from the Preisach model. It explains hysteresis curves and the accommodation process, offering a new approach to analyzing magnetic field transitions.

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Area of Science:

  • Statistical Physics
  • Probability Theory
  • Materials Science

Background:

  • Hysteresis is a critical phenomenon in various physical systems, often modeled by the Preisach model.
  • Understanding the underlying stochastic processes governing transitions is essential for accurate hysteresis modeling.
  • Existing models may not fully capture the nuances of accommodation and memory effects in hysteresis loops.

Purpose of the Study:

  • To develop a new probability theory-based model for hysteresis, distinct from the Preisach model.
  • To analyze the stochastic evolution of systems with two-state particles under external parameter variations.
  • To explain the accommodation process and memory properties of hysteresis loops.

Main Methods:

  • Modeling hysteresis using probability theory and abstract particles with two states (+1 and -1).
  • Defining transitions between states using random variables for 'up' and 'down' switching.
  • Analyzing the probability distribution and expectation values to determine hysteresis curves.

Main Results:

  • Reversal points act as Markov points governing stochastic evolution.
  • Hysteresis loop branches converge to limit curves, explaining the accommodation process.
  • The model shows non-zero reversal point susceptibilities and approximates the Rayleigh law for small parameter variations.

Conclusions:

  • The proposed stochastic model provides a new framework for understanding and calculating hysteresis.
  • It offers a clear explanation for the accommodation process and return-point memory effects.
  • The model aligns well with experimental observations and aids in estimating switching field distributions.

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