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Conventional computers operate deterministically using strings of zeros and ones called bits to represent information in binary code. Despite the evolution of conventional computers into sophisticated machines, there are many classes of problems that they cannot efficiently address, including inference, invertible logic, sampling and optimization, leading to considerable interest in alternative computing schemes. Quantum computing, which uses qubits to represent a superposition of 0 and 1, is expected to perform these tasks efficiently 1 – 3 . However, decoherence and the current requirement for cryogenic operation 4 , as well as the limited many-body interactions that can be implemented, pose considerable challenges. Probabilistic computing 1 , 5 – 7 is another unconventional computation scheme that shares similar concepts with quantum computing but is not limited by the above challenges. The key role is played by a probabilistic bit (a p-bit)—a robust, classical entity fluctuating in time between 0 and 1, which interacts with other p-bits in the same system using principles inspired by neural networks 8 . Here we present a proof-of-concept experiment for probabilistic computing using spintronics technology, and demonstrate integer factorization, an illustrative example of the optimization class of problems addressed by adiabatic 9 and gated 2 quantum computing. Nanoscale magnetic tunnel junctions showing stochastic behaviour are developed by modifying market-ready magnetoresistive random-access memory technology 10 , 11 and are used to implement three-terminal p-bits that operate at room temperature. The p-bits are electrically connected to form a functional asynchronous network, to which a modified adiabatic quantum computing algorithm that implements three- and four-body interactions is applied. Factorization of integers up to 945 is demonstrated with this rudimentary asynchronous probabilistic computer using eight correlated p-bits, and the results show good agreement with theoretical predictions, thus providing a potentially scalable hardware approach to the difficult problems of optimization and sampling. A probabilistic computer utilizing probabilistic bits, or p-bits, is implemented with stochastic nanomagnetic devices in a neural-network-inspired electrical circuit operating at room temperature and demonstrates integer factorization up to 945.

The existence of multiple ferroic orders in the same material and the coupling between them have been known for decades. However, these phenomena have mostly remained the theoretical domain owing to the fact that in single-phase materials such couplings are rare and weak. This situation has changed dramatically recently for at least two reasons: first, advances in materials fabrication have made it possible to manufacture these materials in structures of lower dimensionality, such as thin films or wires, or in compound structures such as laminates and epitaxial-layered heterostructures. In these designed materials, new degrees of freedom are accessible in which the coupling between ferroic orders can be greatly enhanced. Second, the miniaturization trend in conventional electronics is approaching the limits beyond which the reduction of the electronic element is becoming more and more difficult. One way to continue the current trends in computer power and storage increase, without further size reduction, is to use multi-functional materials that would enable new device capabilities. Here, we review the field of multi-ferroic (MF) and magnetoelectric (ME) materials, putting the emphasis on electronic effects at ME interfaces and MF tunnel junctions.

The field of spintronics has attracted tremendous attention recently owing to its ability to offer a solution for the present-day problem of increased power dissipation in electronic circuits while scaling down the technology. Spintronic-based structures utilize electron’s spin degree of freedom, which makes it unique with zero standby leakage, low power consumption, infinite endurance, a good read and write performance, nonvolatile nature, and easy 3D integration capability with the present-day electronic circuits based on CMOS technology. All these advantages have catapulted the aggressive research activities to employ spintronic devices in memory units and also revamped the concept of processing-in-memory architecture for the future. This review article explores the essential milestones in the evolutionary field of spintronics. It includes various physical phenomena such as the giant magnetoresistance effect, tunnel magnetoresistance effect, spin-transfer torque, spin Hall effect, voltage-controlled magnetic anisotropy effect, and current-induced domain wall/skyrmions motion. Further, various spintronic devices such as spin valves, magnetic tunnel junctions, domain wall-based race track memory, all spin logic devices, and recently buzzing skyrmions and hybrid magnetic/silicon-based devices are discussed. A detailed description of various switching mechanisms to write the information in these spintronic devices is also reviewed. An overview of hybrid magnetic /silicon-based devices that have the capability to be used for processing-in-memory (logic-in-memory) architecture in the immediate future is described in the end. In this article, we have attempted to introduce a brief history, current status, and future prospectus of the spintronics field for a novice.

Multiferroic tunnel junctions (MFTJs) own significant potential application in non-volatile memory devices due to their multifunctional characteristics, which has attracted widespread attention. The recent advancements in van der Waals (vdW) multiferroic materials have successfully combined ferromagnetism and ferroelectricity, providing an ideal platform for studying MFTJs at the atomic scale. In this study, we theoretically investigate the spin-dependent transport properties of vdW MFTJs based on sliding ferroelectric barrier layers of PtTe2 using first principles based on density functional theory. Our research shows that multiple non-volatile resistance states can be achieved by controlling the polarization direction of the ferroelectric barrier in Fe3GaTe2/PtTe2/Fe3GeTe2 vdW MFTJs and the magnetization direction of the ferromagnetic electrodes. Specifically, as the ferroelectric material undergoes slippage, the polarization of the ferroelectric barrier shifts from left-oriented (P←) to right-oriented (P→), which induces the tunneling magnetoresistance ratio at the Fermi level increasing from 2.7×107% to 5.7×107%. As the magnetization direction of the ferromagnetic electrodes changes from parallel (M↑↑) to antiparallel (M↑↓), the tunneling electroresistance ratio significantly rises from 9.52% to 155%. Moreover, a nearly 100% spin-filtering efficiency is observed in the four states of MFTJs and the resistance area (RA) product is very small, with the minimum RA product at the Fermi level 0.033 Ω⋅μm2. This research highlights the potential use of the sliding ferroelectricity in bilayer PtTe2 in constructing multistate non-volatile memory and spin filter, and can be used for the development of multifunctional electronic devices.

Multiferroic van der Waals (vdW) heterostructures hold great potential for next-generation spin-based memory and logic devices, offering versatile control over electron spins and electric polarization in atomically thin platforms. However, achieving exceptionally large tunnel magnetoresistance (TMR), stable multi-resistance states, and low resistance-area (RA) products remains a challenge. Here, using first-principles calculations, we address these issues by designing a Fe 3 GaTe 2 /α-In 2 Se 3 /Fe 3 GaTe 2 multiferroic tunnel junction (MFTJ). We demonstrate large TMR values exceeding 10 5 %, nonvolatile multistate and RA product below 1 Ω µm 2 , which matched the requirements for high-density memory cells. The remarkably low RA products from the ultrathin ferroelectric barrier’s narrow bandgap, while the exceptionally high TMR and nearly perfect spin polarization originate from enhanced momentum-selective tunneling at the Fe 3 GaTe 2 /α-In 2 Se 3 interface. Moreover, the low energy barrier for ferroelectric switching enables efficient voltage-driven polarization control. These findings establish a clear pathway for integrating low-RA, high-TMR, and multistate MFTJs into spintronic architectures, accelerating the development of high-density, energy-efficient data storage and processing technologies.

In this study, nanoscale MgO magnetic tunnel junctions (MTJs) with an orthogonal magnetization structure between the free and pinned layers and various junction sizes were fabricated, and their tunnel magnetoresistance (TMR) ratio, resistance-area (RA) product, and low-frequency noise (LFN) behavior were experimentally investigated thoroughly. The circular MTJs with various diameters (80–400 nm) show high TMR ratios of greater than 100% at room temperature (RT) with relatively low RA in the range of 2.8–4.4 Ωµm 2 . We found that the noise power spectral density (PSD) as a function of d.c. bias voltage ( V bias ) and perpendicular d.c. bias magnetic field ( H DC ) in all junction sizes exhibits 1/ f -noise behavior within a wide investigated frequency range from 5 Hz up to 10 kHz. The bias voltage and magnetic field-dependent LFN indicated that the 1/ f noise of the MTJs has both electric and magnetic origins. The results show that though the TMR ratio and RA product are size-independent, the Hooge parameter for the parallel (P) state ( α P ) is strongly dependent on the MTJ size, and its values decrease with decreasing MTJ size, suggesting the reduction of electronic 1/ f noise as the MTJ size shrinks. This is the first experimental report on the size dependency of electronic 1/ f noise in nano-sized MTJs. The results may open a new approach for reducing not only magnetic but also electronic 1/ f noises in MTJs by downscaling, thereby increasing the sensitivity of MTJ nanosensors.

The superconductor–insulator–normal metal–insulator–superconductor (SINIS) tunnel junction structure is the basic building block for various cryogenic devices. Microwave detectors, electron coolers, primary thermometers, and Aharonov–Bohm interferometers have been fabricated by various methods and measured at temperatures down to 100 mK. The manufacturing methods included Dolan-type shadow evaporation, Manhattan-type shadow evaporation, and magnetron sputtering with selective etching of superconducting and normal metal electrodes. Improvement in ultimate sensitivity is achieved by suspending the absorber above the substrate. Best responsivity of up to 30 electrons per photon at a frequency of 350 GHz, or 72000 A/W, and voltage responsivity up to 3.9 × 10 9 V/W were obtained with a black body radiation source and series of band-pass filters. The specially designed SINIS arrays are intended to detect 90 GHz radiation at the “Big Telescope Alt-azimuthal” (romanized Russian: “Bolshoi Teleskop Alt-azimutalnyi”, BTA) with noise equivalent power of less than 10 −16 W·Hz −1/2 . The receiver in a 3 He cryostat with an optical window was mounted at the Nasmyth focus of the BTA and tested at a temperature of 260 mK with a IMPATT diode radiation source.

Ferroelectric Tunnel Junctions (FTJs) are a candidate for the hardware realization of synapses in artificial neural networks. The fabrication process for a 784 × 100 crossbar array of 500 nm large FTJs, exhibiting effective On/Off currents ratio in the range 50–100, is presented. First, the epitaxial 4 nm-BiFeO 3 /Ca 0.96 Ce 0.04 MnO 3 //YAlO 3 is combined with Ni electrodes. The oxidation of Ni during the processing affects the polarity of the FTJ and the On/Off ratio, which becomes comparable to that of CMOS-compatible HfZrO 4 junctions. The latter have a wider coercive field distribution: consequently, in test crossbar arrays, BiFeO 3 exhibits a smaller cross-talk than HfZrO 4 . Furthermore, the relatively larger threshold for ferroelectric switching in BiFeO 3 allows the use application of half-programming schemes for supervised and unsupervised learning. Second, the heterostructure is combined with W and Pt electrodes. The design is optimized for the controlled collapse chip connection to neuromorphic circuits. Graphical abstract

The BeEST experiment is a precision laboratory search for physics beyond the standard model that measures the electron capture decay of 7 Be implanted into superconducting tunnel junction (STJ) detectors. For Phase-III of the experiment, we constructed a continuously sampling data acquisition system to extract pulse shape and timing information from 16 STJ pixels offline. Four additional pixels are read out with a fast list-mode digitizer, and one with a nuclear MCA already used in the earlier limit-setting phases of the experiment. We present the performance of the data acquisition system and discuss the relative advantages of the different digitizers.

With its unique computer paradigm, the Ising annealing machine has become an emerging research direction. The Ising annealing system is highly effective at addressing combinatorial optimization (CO) problems that are difficult for conventional computers to tackle. However, Ising spins, which comprise the Ising system, are difficult to implement in high-performance physical circuits. We propose a novel type of Ising spin based on an electrically-controlled magnetic tunnel junction (MTJ). Electrical operation imparts true randomness, great stability, precise control, compact size, and easy integration to the MTJ-based spin. In addition, simulations demonstrate that the frequency of electrically-controlled stochastic Ising spin (E-spin) is 50 times that of the thermal disturbance MTJ-based spin (p-bit). To develop a large-scale Ising annealing system, up to 64 E-spins are implemented. Our Ising annealing system demonstrates factorization of integers up to 264 with a temporal complexity of around O(n). The proposed E-spin shows superiority in constructing large-scale Ising annealing systems and solving CO problems.