The conventional computing method based on the von Neumann architecture is limited by a series of problems such as high energy consumption, finite data exchange bandwidth between processors and storage media, etc., and it is difficult to achieve higher computing efficiency. A more efficient unconventional computing architecture is urgently needed to overcome these problems. Neuromorphic computing and stochastic computing have been considered to be two competitive candidates for unconventional computing, due to their extraordinary potential for energy-efficient and high-performance computing. Although conventional electronic devices can mimic the topology of the human brain, these require high power consumption and large area. Spintronic devices represented by magnetic tunnel junctions (MTJs) exhibit remarkable high-energy efficiency, non-volatility, and similarity to biological nervous systems, making them one of the promising candidates for unconventional computing. In this work, we review the fundamentals of MTJs as well as the development of MTJ-based neurons, synapses, and probabilistic-bit. In the section on neuromorphic computing, we review a variety of neural networks composed of MTJ-based neurons and synapses, including multilayer perceptrons, convolutional neural networks, recurrent neural networks, and spiking neural networks, which are the closest to the biological neural system. In the section on stochastic computing, we review the applications of MTJ-based p-bits, including Boltzmann machines, Ising machines, and Bayesian networks. Furthermore, the challenges to developing these novel technologies are briefly discussed at the end of each section.

This work proposes a novel three-terminal magnetic tunnel junction (MTJ) as a stochastic neuron. The neuron is probabilistically switched based on the voltage-controlled magnetic anisotropy (VCMA) effect with the assistance of Rashba effective field. We find that a restricted Boltzmann machine (RBM) implemented using our proposed neuron for handwritten character recognition can achieve synaptic weight sparsity, without sacrificing the network classification accuracy.Moreover, the RBM implemented by this novel neuron performs even better in the presence of device variations, implying that our device is highly suitable for the hardware implementation of RBM.

Previous research has demonstrated the spin-orbit torque (SOT) switching of $\mathrm{M}{\mathrm{n}}_3\mathrm{Sn}$ in configuration I, where the spin polarization σ resides within the kagome plane. However, this configuration has yielded several unexpected outcomes, giving rise to debates concerning the fundamental physics governing the switching process. Alternatively, in configuration II, σ is perpendicular to the kagome plane, which bears greater resemblance to the ferromagnetic system. In this study, we show successful SOT switching of $\mathrm{M}{\mathrm{n}}_3\mathrm{Sn}$ in configuration II, demonstrating behaviors more akin to ferromagnets, e.g., the critical switching current density ($J_{\mathrm{crit}}$) and external field ($H_{\mathrm{ext}}$) are in the order of ${10}^{10}\mathrm{A}/{\mathrm{m}}^2$ and tens of Oersted, respectively. The switching result is also independent of the initial state. We further show that the distinctive spin structure of $\mathrm{M}{\mathrm{n}}_3\mathrm{Sn}$ leads to unique switching characteristics, including $J_{\mathrm{crit}}$ increasing linearly with $H_{\mathrm{ext}}$ and the opposite switching polarity to ferromagnetism. A switching phase diagram is further provided as a guideline for experimental demonstrations, offering a clear physical picture for the observed phenomena.

Terahertz (THz) signals, mainly generated by photonic or electronic approaches, are being sought for various applications, whereas the development of magnetic source might be a necessary step to harness the magnetic nature of electromagnetic radiation. We show that the relativistic effect on the current-driven domain-wall motion induces THz spin-wave emission in ferrimagnets. The required current density increases dramatically in materials with strong exchange interaction and rapidly exceeds ${10}^{12}\mathrm{A}{\mathrm{m}}^{-2}$, leading to the device breakdown and thus the lack of experimental evidence. By translating the collective magnetization oscillations into voltage signals, we propose a three-terminal device for the electrical detection of THz spin wave. Through material engineering, a wide frequency range from 264 GHz to 1.1 THz and uniform continuous signals with improved output power can be obtained. As a reverse effect, the spin wave generated in this system is able to move the ferrimagnetic domain wall. Our work provides guidelines for the experimental verification of THz spin wave, and could stimulate the design of THz spintronic oscillators for wideband applications as well as the all-magnon spintronic devices.

Ferrimagnets, such as ${\mathrm{Gd}}_x\mathrm{Fe}{\mathrm{Co}}_{(1–x)}$, can produce ultrafast magnetic switching and oscillation due to the strong exchange field. The two-sublattice macrospin model has been widely used to explain the experimental results. However, it fails in describing the spatially nonuniform magnetic dynamics which gives rises to many important phenomena such as domain walls and skyrmions. Here we develop a two-dimensional atomistic model and provide a torque analysis method to study the ferrimagnetic oscillation. Under spin-transfer torque, the magnetization oscillates in the exchange mode or the flipped exchange mode. When the Gd composition is increased, the exchange mode first disappears, and then appears again as the magnetization compensation point is reached. We show that these results can only be explained by analyzing the spatial distribution of magnetization and effective fields. In particular, when the sample is small, a spatially nonuniform oscillation is also observed in the square film. Our work reveals the importance of spatial magnetic distributions in understanding the ferrimagnetic dynamics. The method developed in this paper provides an important tool to gain a deeper understanding of ferrimagnets and antiferromagnets. The observed ultrafast dynamics can also stimulate the development of THz oscillators.