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arXiv:2510.20735 · Journal of Applied Physics

Magnetic tunnel junction as a real-time entropy source: Field-Programmable Gate Array based random bit generation without post-processing

Troy Criss, Ahmed Sidi El Valli, Naomi Li, A. Haas, Andrew D. Kent

Published Jan 6, 2026• 4 citations
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Abstract

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 50% and apply an XOR operation, both on the FPGA, to suppress short-term correlations, together mitigating long-term drift and bias in the bitstream. This combined approach passes the NIST Statistical Test Suite for random bit generation at 5 Mb/s without post-processing, providing a practical hardware solution for fast and reliable true random number generation. Beyond cryptographic applications, these capabilities open opportunities for stochastic hardware accelerators, probabilistic computing, and large-scale modeling where real-time access to unbiased randomness is essential.

DOI
10.1063/5.0308636

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Applied Physics Express•Jul 25, 2014•236 citations
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 50% and apply an XOR operation, both on the FPGA, to suppress short-term correlations, together mitigating long-term drift and bias in the bitstream. This combined approach passes the NIST Statistical Test Suite for random bit generation at 5 Mb/s without post-processing, providing a practical hardware solution for fast and reliable true random number generation. Beyond cryptographic applications, these capabilities open opportunities for stochastic hardware accelerators, probabilistic computing, and large-scale modeling where real-time access to unbiased randomness is essential.
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. However, our implementation used high-end and expensive electronics, such as a high-bandwidth arbitrary waveform generator and analog-to-digital converter, and was limited to relatively low data rates. Here, we significantly increase the speed of true random-number generation of our stochastic actuated pMTJs (SMART-pMTJs) using field-programmable gate arrays (FPGAs), demonstrating the generation of over1012{\text{10}}^{\text{12}}1012bits at rates exceeding 10 Mb/s. The resulting bitstreams pass the NIST Statistical Test Suite for randomness with only onexoroperation. In addition to a hundred-fold reduction in the setup cost and a thousand-fold increase in bitrate, the advancement includes simplifying and optimizing random bit generation with a custom-designed analog daughterboard to interface an FPGA and SMART-pMTJ. The resulting setup further enables FPGA at-speed processing of MTJ data for stochastic modeling and cryptography.
Magnetic tunnel junction (MTJ)-based true random number generators (TRNG), which are promisingly utilized as hardware accelerators for probabilistic computing, may suffer intrinsic performance drifting and fluctuation in the probability space and performance variations in device arrays. In order to preventively avoid these concerns, it is necessary to develop strategies that can help MTJ-based TRNG to be self-stabilized and calibration-free. Here, we derived a simple and easily handleable strategy that only depends on the current sampled state of an MTJ device without any historical or statistic information or a pre-calibrated probabilistic switching property to dynamically tune its sampling probability for the next sampling operation. In this way, the long-term sampling probability of the MTJ can be proved to automatically converge into a desired probability with little fluctuation and drifting. We further experimentally demonstrate such a self-stabilized MTJ-based TRNG. Our results show that the TRNG can generate binary random numbers with any destined probability regardless of its initial state. Furthermore, the TRNG also displays the desired capability of excellently hedging against performance drifting and fluctuations. All these combined allow the self-stabilized TRNG without calibration to be more viable for high-quality entropy source applications.
True random number generation is a critical capability for fault-tolerant quantum computing at millikelvin temperatures. Yet existing Josephson-junction-based TRNGs all rest on a widely accepted but untested assumption: that reliable entropy extraction requires precisely controlled device parameters. Here we show that this assumption does not always hold. We demonstrate a counterintuitive finding: a single current-biased Josephson junction, regardless of its parameter quality, can serve as a cryptographic-grade true random number generator. To establish the universality of this conclusion, we deliberately selected the most extremely deviated devices from fabrication, with critical currents three orders of magnitude away from theoretical predictions and IcRI_cRIc​R products an order of magnitude above conventional values, as the ultimate stress test. Even under these extreme conditions, the raw Shannon entropy reaches 0.9981~bit (99.8\% of the theoretical maximum), with a min-entropy of 0.9271~bit. Using a square-wave pulsed-bias scheme, we tune the switching probability to P≈0.5P\approx0.5P≈0.5. After SHA-256 post-processing, the bitstreams pass all 15 NIST SP 800-22 tests under a conservative m=3m=3m=3 criterion that is more demanding than the standard recommendation, and this certification holds across the entire 100-700~mK operating window of a dilution refrigerator.
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 demonstrate the tunability and quality of random number distributions generated by pMTJs operating at a frequency of 104 MHz. First, changing the pulse amplitude is used to systematically vary the probability bias. The variance of the resulting bitstreams closely matches the expected binomial distribution, demonstrating consistency with an underlying sequence of Bernoulli trials. Second, the quality of uniform distributions of 8-bit random numbers generated with a probability bias of 0.5 is considered. A reduced chi-square analysis of these data shows that only two XOR operations are sufficient to achieve this distribution with p-values greater than 0.05. Finally, we show that there is a correlation between long-term probability bias variations and pMTJ resistance. These findings suggest that variations in the characteristics of the pMTJ underlie the observed variation of probability bias. Our results highlight the potential of stochastically actuated pMTJs for high-speed, tunable TRNG applications, showing the importance of the stability of pMTJ device characteristics in achieving reliable, long-term performance.
High-speed true random number generator is a building block in the modern information security system. We propose and demonstrate an efficient high-speed true random number generator based on multiple parallel self-timed rings (STRs). To improve the security, we evaluate the randomness of the entropy source by min-entropy and exploit the information-theoretically provable Toeplitz-hashing extractor. To minimize the consumption of hardware resources of a field programmable gate array at a predetermined high throughput and maximize the throughput with the limited hardware resources, we systematically derive and investigate the dependence of the data throughput and the total consumed resources of the random number generator on the system parameters. On this basis, we make a joint optimization for the degree of parallelism of the STRs and the extraction efficiency of the extractor. A 10-Gbps true random number generator is implemented efficiently, so that the output random bits can pass all the National Institute of Standards and Technology (NIST) and Dieharder test suites.
Generation of practical random numbers (RNs) by a spintronics-based, scalable truly RN generator called "spin dice" was demonstrated.The generator utilizes the stochastic nature of spin-torque switching in a magnetic tunnel junction (MTJ) to generate RNs.We fabricated eight perpendicularly magnetized MTJs on a single-board circuit and generated eight sequences of RNs simultaneously.The sequences of RNs of different MTJs were not correlated with each other, and performing an exclusive OR (XOR) operation among them improved the quality of the RNs.The RNs obtained by performing a nested XOR operation passed the statistical test of NIST SP-800 with the appropriate pass rate.