An Unbiased Quantum Random Number Generator Based on Boson Sampling
Jinjing Shi, Tongge Zhao, Yizhi Wang, Chunlin Yu, Yuhu Lu, Ronghua, Shi, Shichao Zhang, Junjie Wu

TL;DR
This paper introduces a novel quantum random number generator leveraging Boson sampling's inherent quantum randomness, implemented on a silicon photonic processor, producing unbiased, high-quality random sequences suitable for practical applications.
Contribution
It is the first to utilize Boson sampling randomness for a practical QRNG prototype, overcoming limitations of existing methods and demonstrating successful statistical testing.
Findings
The QRNG prototype passes 15 NIST statistical tests.
Boson sampling provides a reliable entropy source for randomness.
The system overcomes previous detector and speed limitations.
Abstract
It has been proven that Boson sampling is a much promising model of optical quantum computation, which has been applied to designing quantum computer successfully, such as "Jiuzhang". However, the meaningful randomness of Boson sampling results, whose correctness and significance were proved from a specific quantum mechanical distribution, has not been utilized or exploited. In this research, Boson sampling is applied to design a novel Quantum Random Number Generator (QRNG) by fully exploiting the randomness of Boson sampling results, and its prototype system is constructed with the programmable silicon photonic processor, which can generate uniform and unbiased random sequences and overcome the shortcomings of the existing discrete QRNGs such as source-related, high demand for the photon number resolution capability of the detector and slow self-detection generator speed. Boson…
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Taxonomy
TopicsQuantum Information and Cryptography · Chaos-based Image/Signal Encryption · Neural Networks and Reservoir Computing
