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True random number generators are of great interest in many computing applications such as cryptography, neuromorphic systems and Monte Carlo simulations. Here we investigate perpendicular magnetic tunnel junction nanopillars (pMTJs)…

Perpendicular magnetic tunnel junctions (pMTJs) actuated by nanosecond pulses are emerging as promising devices for true random number generation (TRNG) due to their intrinsic stochastic behavior and high throughput. In this work, we study…

Applied Physics · Physics 2025-06-23 Ahmed Sidi El Valli , Michael Tsao , J. Darby Smith , Shashank Misra , Andrew D. Kent

True random number generators (TRNGs) are fundamental building blocks for many applications, such as cryptography, Monte Carlo simulations, neuromorphic computing, and probabilistic computing. While perpendicular magnetic tunnel junctions…

Magnetic tunnel junctions (MTJs), which are the fundamental building blocks of spintronic devices, have been used to build true random number generators (TRNGs) with different trade-offs between throughput, power, and area requirements.…

This work investigates nanosecond superparamagnetic switching in 50 nm diameter in-plane magnetized magnetic tunnel junctions (MTJs). Due to the small in-plane uniaxial anisotropy, dwell times below 10 ns and auto-correlation times down to…

Mesoscale and Nanoscale Physics · Physics 2023-01-16 Leo Schnitzspan , Mathias Kläui , Gerhard Jakob

Large quantities of random numbers are crucial in a wide range of applications. We have recently demonstrated that perpendicular nanopillar magnetic tunnel junctions (pMTJs) can produce true random bits when actuated with short pulses.…

Mesoscale and Nanoscale Physics · Physics 2024-06-21 Andre Dubovskiy , Troy Criss , Ahmed Sidi El Valli , Laura Rehm , Andrew D. Kent , Andrew Haas

Perpendicular magnetic tunnel junction (pMTJ)-based true-random number generators (RNG) can consume orders of magnitude less energy per bit than CMOS pseudo-RNG. Here, we numerically investigate with a macrospin Landau-Lifshitz-Gilbert…

We review two magnetic tunnel junction (MTJ) approaches for compact, low-power, CMOS-integrated true random number generation (TRNG). The first employs passive-read, easy-plane superparamagnetic MTJs (sMTJs) that generate…

Mesoscale and Nanoscale Physics · Physics 2026-01-15 Jonathan Z. Sun , Christopher Safranski , Siyuranga Koswata , Pouya Hashemi , Andrew D. Kent

We demonstrate that thermally stable perpendicular magnetic tunnel junctions (pMTJs), widely used in spin-transfer torque magnetic random-access memory, can be actuated with nanosecond pulses to exhibit tunable stochastic behavior. This…

Mesoscale and Nanoscale Physics · Physics 2026-01-15 Ahmed Sidi El Valli , Michael Tsao , Dairong Chen , Andrew D. Kent

Magnetic Tunnel Junctions (MTJs) have shown great promise as hardware sources for true random number generation (TRNG) due to their intrinsic stochastic switching behavior. However, practical deployment remains challenged by drift in…

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

In recent years, true random number generators (TRNGs) based on magnetic tunnelling junction (MTJ) have become increasingly attractive. This is because MTJ-based TRNGs offer some advantages over traditional CMOS-based TRNGs, such as smaller…

Quantum Physics · Physics 2023-03-28 Hong Jie Ng , Shuhan Yang , Zhaoyang Yao , Hyunsoo Yang , Charles C. -W. Lim

Physical devices exhibiting stochastic functions with low energy consumption and high device density have the potential to enable complex probability-based computing algorithms, accelerate machine learning tasks, and enhance hardware…

Materials Science · Physics 2024-09-17 Dooyong Koh , Qiuyuan Wang , Brooke C. McGoldrick , Chung-Tao Chou , Luqiao Liu , Marc A. Baldo

Low-energy random number generation is critical for many emerging computing schemes proposed to complement or replace von Neumann architectures. However, current random number generators are always associated with an energy cost that is…

The emerging Spin Transfer Torque Magnetic Tunnel Junction (STT-MTJ) technology exhibits interesting stochastic behavior combined with small area and low operation energy. It is, therefore, a promising technology for security applications,…

Cryptography and Security · Computer Science 2023-07-28 Ben Perach , Shahar Kvatinsky

Recently there is considerable interest to realize efficient and low-cost true random number generators (RNGs) for practical applications. One important way is through the use of bistable magnetic tunnel junctions (MTJs). Here we study the…

Other Condensed Matter · Physics 2023-09-07 Chee Kwan Gan , Bingjin Chen , Minggang Zeng

The probability switching characteristics in spin transfer torque magnetic tunnel junctions (STT-MTJs) are simulated by considering thermal noise using a spin-circuit module. Thermal noise significantly affects the probability switching for…

Applied Physics · Physics 2025-05-02 Shaojie Hu , Fupeng Gao , Tengwei Huang , Zhizhong Wang , Hui Li , Dawei Wang

Naturally random devices that exploit ambient thermal noise have recently attracted attention as hardware primitives for accelerating probabilistic computing applications. One such approach is to use a low barrier nanomagnet as the free…

Mesoscale and Nanoscale Physics · Physics 2021-05-05 Kerem Y. Camsari , Mustafa Mert Torunbalci , William A. Borders , Hideo Ohno , Shunsuke Fukami

Magnetic tunnel junctions operating in the superparamagnetic regime are promising devices in the field of probabilistic computing, which is suitable for applications like high-dimensional optimization or sampling problems. Further, random…

Mesoscale and Nanoscale Physics · Physics 2021-03-24 Christopher Safranski , Jan Kaiser , Philip Trouilloud , Pouya Hashemi , Guohan Hu , Jonathan Z Sun

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
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