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Influence of Post-Processing Techniques on Random Number Generation Using Chaotic Nanolasers
Influence of Post-Processing Techniques on Random Number Generation Using Chaotic Nanolasers
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Influence of Post-Processing Techniques on Random Number Generation Using Chaotic Nanolasers
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Influence of Post-Processing Techniques on Random Number Generation Using Chaotic Nanolasers
Influence of Post-Processing Techniques on Random Number Generation Using Chaotic Nanolasers

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Influence of Post-Processing Techniques on Random Number Generation Using Chaotic Nanolasers
Influence of Post-Processing Techniques on Random Number Generation Using Chaotic Nanolasers
Journal Article

Influence of Post-Processing Techniques on Random Number Generation Using Chaotic Nanolasers

2024
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Overview
In this paper, we propose using a chaotic system composed of nanolasers (NLs) as a physical entropy source. Combined with post-processing technologies, this system can produce high-quality physical random number sequences. We investigated the parameter range for achieving time-delay signature (TDS) concealment in the chaotic system. This study demonstrates that NLs exhibit noticeable TDS only under optical feedback. As mutual injection strength between the master NLs (MNLs) increases, the TDS of the MNLs is gradually suppressed until they are completely concealed. Compared to MNLs, the slave NL (SNL) exhibits better TDS suppression performance. Additionally, we investigated the chaotic and highly unpredictable regions of the SNL, demonstrating that high-quality chaotic signals can be produced over a wide range of parameters. Using TDS hidden and highly unpredictable chaotic signals as the source of random entropy, the effects of different post-processing techniques on random number extraction were compared. The results indicate that effective post-processing can enhance the unpredictability of the random sequence. This study successfully utilized NLs for random number generation, showcasing the potential and application prospects of NLs in the field of random numbers.