Compensation of anisotropy in spin-Hall devices for neuromorphic applications

TL;DR

This paper demonstrates how compensating magnetic anisotropy in spin-Hall nano-oscillators reduces their non-linearity, enabling stable, fixed-frequency nano-neurons suitable for neuromorphic computing.

Contribution

It introduces a method to compensate anisotropy in spin-Hall nano-oscillators, resulting in low non-linearity and fixed-frequency operation for neuromorphic applications.

Findings

Reduced non-linearity in SHNOs through anisotropy compensation

Stable fixed frequency and linewidth in compensated SHNOs

Demonstration of a nano-neuron with low linewidth and fixed frequency

Abstract

Spintronic nano-oscillators with reduced non-linearity could offer key benefits for realizing neuromorphic applications such as spike-based neurons and frequency multiplexing in neural networks. Here, we experimentally demonstrate the reduction in non-linearity of a spin-Hall nano-oscillator (SHNO) by compensation of its effective magnetic anisotropy. The study involves optimization of Co/Ni multilayer growth to achieve the compensation, followed by spin diode measurements on patterned microstrips to quantify their anisotropy. The relation between the second ($H_{k2}$ = 0.47 mT) and the first order ($H_{k1}^{eff}$ = $-$0.8 mT) anisotropy fields reveals the existence of an easy cone, thereby validating the presence of compensation. Furthermore, we demonstrate a synapse based on the compensated spin diode which has a fixed frequency when the input power is varied. We then study the current-induced auto-oscillation properties of SHNOs on compensated films by patterning nano-constrictions of widths 200 and 100 nm. The invariance of the resonance frequency and linewidth of the compensated SHNO with applied dc current indicates the absence of non-linearity. This independence is maintained irrespective of the applied external fields and its orientations. The compensated SHNO obtained has a linewidth of 1.1 MHz and a peak output power of up to 1 pW/MHz emulating a nano-neuron with a low linewidth and a fixed frequency.