True random number generator based on spin–orbit torque magnetic tunnel junctions
Xiaohan Li, Mingkun Zhao, Ran Zhang, Caihua Wan, Yizhan Wang, X. Luo, Shiqiang Liu, Jingkang Xia, Guoqiang Yu, Xiufeng Han
Abstract
True random number generators (TRNGs) play a pivotal role in solving NP-hard problems, neural network computing, and hardware accelerators for algorithms, such as the simulated annealing. In this work, we focus on TRNG based on high-barrier magnetic tunnel junctions (HB-MTJs) with identical stack structure and cell geometry, but employing different spin–orbit torque (SOT) switching schemes. We conducted a comparative study of their switching probability as a function of pulse amplitude and width of the applied voltage. Through experimental and theoretical investigations, we have observed that the Y-type SOT-MTJs exhibit the gentlest dependence of the switching probability on the external voltage. This characteristic indicates superior tunability in randomness and enhanced robustness against external disturbances when Y-type SOT-MTJs are employed as TRNGs. Furthermore, the random numbers generated by these Y-type SOT-MTJs, following XOR pretreatment, have passed the National Institute of Standards and Technology SP800-22 test. This comprehensive study demonstrates the high performance and immense potential of Y-type SOT-MTJs for the TRNG implementations.