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Single-qubit gates are essential components of a universal quantum computer. Without selective addressing of individual qubits, scalable implementation of quantum algorithms is extremely challenging. When the qubits are discrete points or regions on a lattice, selectively addressing magnetic spin qubits at the nanoscale remains a challenge due to the difficulty of localizing and confining a classical divergence-free field to a small volume of space. Herein we propose a technique for addressing spin qubits using voltage-control of nanoscale magnetism, exemplified by the use of voltage control of magnetic anisotropy. We show that by tuning the frequency of the nanomagnet’s electric field drive to the Larmor frequency of the spins confined to a nanoscale volume, and by modulating the phase of the drive, single-qubit quantum gates with fidelities approaching those for fault-tolerant quantum computing can be implemented. Such single-qubit gate operations require only tens of femto-Joules per gate operation and have lossless, purely magnetic field control. Their physical realization is also straightforward using foundry manufacturing techniques.

 

We demonstrate using micromagnetic simulations that a nanomagnet array excited by surface acoustic waves (SAWs) can work as a reservoir. An input nanomagnet is excited with focused SAW and coupled to several nanomagnets, seven of which serve as output nanomagnets. To evaluate memory effect and computing capability, we study the short-term memory (STM) and parity check (PC) capacities, respectively. The SAW (4 GHz carrier frequency) amplitude is modulated to provide a sequence of sine and square waves of 100 MHz frequency. The responses of the selected output nanomagnets are processed by reading the envelope of their magnetization states, which is used to train the output weights using the regression method. For classification, a random sequence of 100 square and sine wave samples is used, of which 80% are used for training, and the rest are used for testing. We achieve 100% training and 100% testing accuracy. The average STM and PC are calculated to be ∼4.69 and ∼5.39 bits, respectively, which is indicative of the proposed acoustically driven nanomagnet oscillator array being well suited for physical reservoir computing applications. The energy dissipation is ∼2.5 times lower than a CMOS-based echo-state network. Furthermore, the reservoir is able to accurately predict Mackey-Glass time series up to several time steps ahead. Finally, the ability to use high frequency SAW makes the nanomagnet reservoir scalable to small dimensions, and the ability to modulate the envelope at a lower frequency (100 MHz) adds flexibility to encode different signals beyond the sine/square waves classification and Mackey-Glass predication tasks demonstrated here. 

Abstract In Part I of this topical review, we discussed dynamical phenomena in nanomagnets, focusing primarily on magnetization reversal with an eye to digital applications. In this part, we address mostly wave-like phenomena in nanomagnets, with emphasis on spin waves in myriad nanomagnetic systems and methods of controlling magnetization dynamics in nanomagnet arrays which may have analog applications. We conclude with a discussion of some interesting spintronic phenomena that undergird the rich physics exhibited by nanomagnet assemblies. 

Abstract When magnets are fashioned into nanoscale elements, they exhibit a wide variety of phenomena replete with rich physics and the lure of tantalizing applications. In this topical review, we discuss some of these phenomena, especially those that have come to light recently, and highlight their potential applications. We emphasize what drives a phenomenon, what undergirds the dynamics of the system that exhibits the phenomenon, how the dynamics can be manipulated, and what specific features can be harnessed for technological advances. For the sake of balance, we point out both advantages and shortcomings of nanomagnet based devices and systems predicated on the phenomena we discuss. Where possible, we chart out paths for future investigations that can shed new light on an intriguing phenomenon and/or facilitate both traditional and non-traditional applications. 

We propose energy-efficient voltage-induced strain control of a domain wall (DW) in a perpendicularly magnetized nanoscale racetrack on a piezoelectric substrate that can implement a multistate synapse to be utilized in neuromorphic computing platforms. Here, strain generated in the piezoelectric is mechanically transferred to the racetrack and modulates the perpendicular magnetic anisotropy (PMA) in a system that has significant interfacial Dzyaloshinskii-Moriya interaction (DMI). When different voltages are applied (i.e., different strains are generated) in conjunction with spin-orbit torque (SOT) due to a fixed current flowing in the heavy metal layer for a fixed time, DWs are translated to different distances and implement different synaptic weights. We have shown using micromagnetic simulations that five-state and three-state synapses can be implemented in a racetrack that is modeled with the inclusion of natural edge roughness and room temperature thermal noise. These simulations show interesting dynamics of DWs due to interaction with roughness-induced pinning sites. Thus, notches need not be fabricated to implement multistate nonvolatile synapses. Such a strain-controlled synapse has an energy consumption of ~1 fJ and could thus be very attractive to implement energy-efficient quantized neural networks, which has been shown recently to achieve near equivalent classification accuracy to the full-precision neural networks. 

Using time-resolved magneto-optical Kerr effect (TR-MOKE) microscopy, we demonstrate surface-acoustic-wave (SAW) induced resonant amplification of intrinsic spin-wave (SW) modes, as well as generation of new extrinsic or driven modes at the SAW frequency, in a densely packed two-dimensional array of elliptical Co nanomagnets fabricated on a piezoelectric LiNbO 3 substrate. This system can efficiently serve as a magnonic crystal (MC), where the intrinsic shape anisotropy and the strong inter-element magnetostatic interaction trigger the incoherent precession of the nanomagnets' magnetization in the absence of any bias magnetic field, giving rise to the ‘intrinsic’ SW modes. The magnetoelastic coupling leads to a rich variety of SW phenomena when the SAW is launched along the major axis of the nanomagnets, such as 4–7 times amplification of intrinsic modes (at 3, 4, 7 and 10 GHz) when the applied SAW frequencies are resonant with these frequencies, and the generation of new extrinsic modes at non-resonant SAW frequencies. However, when the SAW is launched along the minor axis, a dominant driven mode appears at the applied SAW frequency. This reveals that the magnetoelastic coupling between SW and SAW is anisotropic in nature. Micromagnetic simulation results are in qualitative agreement with the experimental observations and elucidate the underlying dynamics. Our findings lay the groundwork for bias-field free magnonics, where the SW behavior is efficiently tuned by SAWs. It has important applications in the design of energy efficient on-chip microwave devices, SW logic, and extreme sub-wavelength ultra-miniaturized microwave antennas for embedded applications.