Sensitivity of the Power Spectra of Magnetization Fluctuations in Low Barrier Nanomagnets to Barrier Height Modulation and Defects

Abstract

Nanomagnets with small shape anisotropy energy barriers on the order of the thermal energy have unstable magnetization that fluctuates randomly in time. They have recently emerged as promising hardware platforms for stochastic computing and machine learning because the random magnetization states can be harnessed for probabilistic bits. Here, we have studied how the statistics of the magnetization fluctuations (e.g. the power spectral density) is affected by (i) moderate variations in the barrier height of the nanomagnet and (ii) the presence of structural defects, in order to assess how robust the computing platform is. We found that the power spectral density is relatively insensitive to moderate barrier height change and also relatively insensitive to the presence of small localized defects. However, extended (delocalized) defects, such as thickness variations over a significant fraction of the nanomagnet, affect the power spectral density very noticeably. As a result, small variations in the shape (causing small variations in the barrier height), or small localized defects, are relatively innocuous and tolerable, but significant variation of the nanomagnet thickness is not. Consequently, tight control over the nanomagnet thickness must be maintained for stochastic computing applications.