Power Spectral Density of Magnetization Dynamics Driven by a Jump-Noise Process

TL;DR

This paper develops a method to analyze the power spectral density of magnetization dynamics influenced by jump-noise, using graph-based stochastic energy analysis and eigenvalue techniques, supported by numerical results.

Contribution

It introduces a novel approach to analyze stochastic magnetic energy dynamics on graphs and provides an eigenvalue method for calculating power spectral density.

Findings

Effective analysis of magnetization dynamics using graph-based stochastic methods.

Eigenvalue technique accurately computes power spectral density in specific cases.

Numerical results validate the proposed analytical approach.

Abstract

Random magnetization dynamics driven by a jump-noise process is reduced to stochastic magnetic energy dynamics on specific graphs using an averaging technique. An approach to analyzing stochastic energy dynamics on graphs is presented and applied to the calculation of power spectral density of random magnetization dynamics. An eigenvalue technique for computing the power spectral density under specific cases is also presented and illustrated by numerical results.