发电机(电路理论)
控制(管理)
计算机科学
材料科学
电气工程
电子工程
工程类
物理
人工智能
量子力学
功率(物理)
作者
Ran Zhang,Caihua Wan,Yingqian Xu,Xiaohan Li,Raik Hoffmann,Meike Hindenberg,Shiqiang Liu,Dehao Kong,Shilong Xiong,Shikun He,Alptekin Vardar,Qiang Dai,Junlu Gong,Yihui Sun,Zejie Zheng,Thomas Kämpfe,Guoqiang Yu,Xiufeng Han
标识
DOI:10.1103/physrevapplied.23.054073
摘要
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 the drift in the 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, precharacterization, 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.
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