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PPubMed1 Nov 2024Cited 9×

Harnessing Physical Entropy Noise in Structurally Metastable 1T′ Molybdenum Ditelluride for True Random Number Generation

Yang Liu, Pengyu Liu, Yingyi Wen, Zihan Liang, Songwei Liu, Lekai Song, Jingfang Pei, Xiaoyue Fan, Teng Ma, Gang Wang, Shuo Gao, Kong-Pang Pun, Xiaolong Chen, Guohua Hu

Abstract

Physical Entropy Noise in Structurally Metastable 1T′ Molybdenum Ditelluride for True Random Number Generation Authors: ['Yang Liu' 'Pengyu Liu' 'Yingyi Wen' 'Zihan Liang' 'Songwei Liu' 'Lekai Song' 'Jingfang Pei' 'Xiaoyue Fan' 'Teng Ma' 'Gang Wang' 'Shuo Gao' 'Kong-Pang Pun' 'Xiaolong Chen' 'Guohua Hu'] True random numbers are crucial for various research and engineering problems. Their generation depends upon a robust physical entropy noise. Here, we present true random number generation from the conductance noise probed in structurally metastable 1T′ molybdenum ditelluride (MoTe2). The noise, fitting a Poisson process, is proved to be a robust physical entropy noise at low and even cryogenic temperatures. Noise characteristic analyses suggest the noise may originate from the polarization variations of the underlying ferroelectric dipoles in 1T′ MoTe2. We demonstrate the noise allows for true random number generation, and this facilitates their use as the seed for generating high-throughput secure random numbers exceeding 1 Mbit/s, appealing for practical applications in, for instance, cryptography where data security is now critical. As an example, we show biometric information safeguarding in neural networks by using the random numbers as the mask, proving a promising data security measure in big data and artificial intelligence.

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