2025/01/25 by Zhang, Ran, Wan, Caihua, Xu, Yingqian +15 · 1 citation
#Applied Physics (physics.app-ph) #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Electrical engineering #FOS: Physical sciences #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · doi:10.48550/arxiv.2501.15206
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 switching probability caused by thermal fluctuations, device aging, and environmental instability. This work presents an engineering-oriented, drift-resilient MTJ-based TRNG architecture, enabled by a hybrid control strategy that combines self-stabilizing feedback with pulse width modulation. A key component is the Downcalibration-2 scheme, which updates the control parameter every two steps using only integer-resolution timing, ensuring excellent statistical quality without requiring bit discarding, pre-characterization, or external calibration. Extensive experimental measurements and numerical simulations demonstrate that this approach maintains stable randomness under dynamic temperature drift, using only simple digital logic. The proposed architecture offers high throughput, robustness, and scalability, making it well-suited for secure hardware applications, embedded systems, and edge computing environments.