Two-level noise and stochastic resonance in individual permalloy nanoscale magnets
2015-08
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Two-level noise and stochastic resonance in individual permalloy nanoscale magnets
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2015-08
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We present the results of a study on stochastic resonance in individual magnetic random telegraph oscillators. We have fabricated sub-micron magnetic samples, which have multiple stable magnetic states. We are able to observe random telegraph switching between magnetic states and tune the energetics by varying the temperature and applied external field. If a small AC field is applied to the system, it will modulate the energy well depth for the two states and the system shows stochastic resonance near the matching condition 2f[A] = ?[D], where ?[D] is the drive frequency and f is the characteristic frequency of magnetic transitions. We fit our measured data for the resonance amplitude and phase of the particle as a function of temperature to a linear-response model and obtain good agreement. At low temperatures we observe a peak in the phase lag of the returned signal, which is consistent with linear-response theories. At higher temperatures, our fitted model parameters suggest that the particle has an energy surface that is not sinusoidal. This contradicts our initial approximation for the energy surface, but it is consistent with a model for magnetic energy that takes into account the magnetization dynamics near the conditions for random telegraph switching. Our work is the first clear observation of stochastic resonance in a single superparamagnetic particle where the energetics are modulated by an applied field. In addition, our work is the first physical system where stochastic resonance has been characterized with sufficient detail to allow for comparison to linear-response models.
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University of Minnesota Ph.D. dissertation. August 2015. Major: Physics. Advisor: Earl Dahlberg. 1 computer file (PDF); viii, 98 pages.
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Youngblood, Bern. (2015). Two-level noise and stochastic resonance in individual permalloy nanoscale magnets. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/175382.
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