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Superparamagnetic tunnel junctions (SMTJs) are promising sources for the randomness required by some compact and energy-efficient computing schemes. Coupling SMTJs gives rise to collective behavior that could be useful for cognitive…

Ising computer is a powerful computation scheme to deal with NP-hard optimization problems that cannot be efficiently addressed by conventional computers. A robust probabilistic bit (P-Bit) which is realized by a hardware entity fluctuating…

Mesoscale and Nanoscale Physics · Physics 2022-02-23 Bolin Zhang , Yu Liu , Tianqi Gao , Deming Zhang , Weisheng Zhao , Lang Zeng

The tunnel magnetoresistance (TMR) in the magnetic tunnel junction (MTJ) with embedded nanoparticles (NPs) was calculated in range of the quantum-ballistic model. The simulation was performed for electron tunneling through the insulating…

Mesoscale and Nanoscale Physics · Physics 2016-03-25 Arthur Useinov , Lin-Xiu Ye , Niazbeck Useinov , Te-Ho Wu , Chih-Huang Lai

Energy-efficient methods are addressed for leveraging low energy barrier nanomagnetic devices within neuromorphic architectures. Using a Magnetoresistive Random Access Memory (MRAM) probabilistic device (p-bit) as the basis of neuronal…

Emerging Technologies · Computer Science 2020-05-06 Hossein Pourmeidani , Punyashloka Debashis , Zhihong Chen , Ronald F. DeMara , Ramtin Zand

Graphical probabilistic circuit models of stochastic computing are more powerful than the predominant deep learning models, but also have more demanding requirements. For example, they require "programmable stochasticity", e.g. generating…

Mesoscale and Nanoscale Physics · Physics 2023-01-24 M. T. McCray , Md Ahsanul Abeed , Supriyo Bandyopadhyay

The figures-of-merit for reservoir computing (RC), using spintronics devices called magnetic tunnel junctions (MTJs), are evaluated. RC is a type of recurrent neural network. The input information is stored in certain parts of the…

GaMnAs-based magnetic tunnel junction (MTJ) devices are characterized by in-plane and perpendicular-toplane magnetotransport at low temperatures. Perpendicular-to-plane transport reveals the typical tunneling magnetotransport (TMR) signal.…

Mesoscale and Nanoscale Physics · Physics 2015-06-11 Aymen Ben Hamida , Florian Bergmann , Klaus Pierz , Hans Werner Schumacher

We study whether a direct measurement of the absolute temperature of a Magnetic Tunnel Junction (MTJ) can be performed using the high frequency electrical noise that it delivers under a finite voltage bias. Our method includes quasi-static…

Materials Science · Physics 2016-08-03 Adrien Le Goff , Vladimir Nikitin , Thibaut Devolder

We have fabricated nanoscale magnetic tunnel junctions (MTJs) with an additional fixed magnetic layer added above the magnetic free layer of a standard MTJ structure. This acts as a second source of spin-polarized electrons that, depending…

The writing energy for reversing the magnetization of the free layer in a magnetic tunnel junction (MTJ) is a key figure of merit for comparing the performances of magnetic random access memories with competing technologies. Magnetization…

The true random number generators (TRNGs) have received extensive attention because of their wide applications in information transmission and encryption. The true random numbers generated by TRNG are typically applied to the encryption…

Applied Physics · Physics 2020-06-24 Yong Yao , Xing Chen , Wang Kang , Youguang Zhang , Weisheng Zhao

Spin filtering and its back-action spin transfer torque (STT) are key ingredients of latest spintronic devices based on magnetic tunnel junctions (MTJs). Resonant tunneling (RT), implemented by design or occurring as parasitic effects, is…

Mesoscale and Nanoscale Physics · Physics 2025-10-27 Maciej Bazarnik , Anika Schlenhoff

Superparamagnetic tunnel junctions (SMTJs) are promising sources of randomness for compact and energy efficient implementations of probabilistic computing techniques. Augmenting an SMTJ with electronic circuits, to convert the random…

The slowing down of Moore's Law has led to a crisis as the computing workloads of Artificial Intelligence (AI) algorithms continue skyrocketing. There is an urgent need for scalable and energy-efficient hardware catering to the unique…

Emerging Technologies · Computer Science 2023-10-11 Shuvro Chowdhury , Kerem Y. Camsari

We demonstrate a method to generate application-ready truly random bits from a magnetic tunnel junction driven by a Field-Programmable Gate Array (FPGA). We implement a real-time feedback loop that stabilizes the switching probability near…

Applied Physics · Physics 2026-01-13 Troy Criss , Ahmed Sidi El Valli , Naomi Li , Andrew Haas , Andrew D. Kent

Spin-transfer magnetic random access memory is of significant interest for cryogenic applications where a persistent, fast, low-energy consumption and high device density is needed. Here we report the low-temperature nanosecond duration…

Applied Physics · Physics 2019-10-31 Laura Rehm , Georg Wolf , Bartek Kardasz , Mustafa Pinarbasi , Andrew D. Kent

Perpendicular MgO-based Magnetic Tunnel Junctions are optimal candidates as building block of Spin Transfer Torque (STT) magnetoresistive memories. However, up to now, the only STT is not enough to achieve switching current density below…

Materials Science · Physics 2015-03-13 M. Carpentieri , R. Tomasello , M. Ricci , P. Burrascano , G. Finocchio

Probabilistic Ising machines (PIMs) provide a path to solving many computationally hard problems more efficiently than deterministic algorithms on von Neumann computers. Stochastic magnetic tunnel junctions (S-MTJs), which are engineered to…

Magnetic tunnel junctions (MTJs) interconnected via a continuous ferromagnetic free layer were fabricated for Spin Torque Majority Gate (STMG) logic. The MTJs are biased independently and show magnetoelectric response under spin transfer…

The spatiotemporal nature of neuronal behavior in spiking neural networks (SNNs) make SNNs promising for edge applications that require high energy efficiency. To realize SNNs in hardware, spintronic neuron implementations can bring…

Neural and Evolutionary Computing · Computer Science 2023-07-12 Thomas Leonard , Samuel Liu , Harrison Jin , Jean Anne C. Incorvia