Li Yuanhao, Fei Yangyang, Wang Weilong, Meng Xiangdong, Wang Hong, Duan Qianheng, Ma Zhi
State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, 450001, Henan, China.
Henan Key Laboratory of Network Cryptography Technology, Zhengzhou, 450001, Henan, China.
Sci Rep. 2021 Dec 13;11(1):23873. doi: 10.1038/s41598-021-03286-9.
Quantum random number generator (QRNG) relies on the intrinsic randomness of quantum mechanics to produce true random numbers which are important in information processing tasks. Due to the presence of the superposition state, a quantum computer can be used as a true random number generator. However, in practice, the implementation of the quantum computer is subject to various noise sources, which affects the randomness of the generated random numbers. To solve this problem, we propose a scheme based on the quantum computer which is motivated by the source-independent QRNG scheme in optics. By using a method to estimate the upper bound of the superposition state preparation error, the scheme can provide certified randomness in the presence of readout errors. To increase the generation rate of random bits, we also provide a parameter optimization method with a finite data size. In addition, we experimentally demonstrate our scheme on the cloud superconducting quantum computers of IBM.
量子随机数发生器（QRNG）依靠量子力学的固有随机性来产生真正的随机数，这些随机数在信息处理任务中很重要。由于叠加态的存在，量子计算机可以用作真正的随机数发生器。然而，在实际中，量子计算机的实现会受到各种噪声源的影响，这会影响所生成随机数的随机性。为了解决这个问题，我们提出了一种基于量子计算机的方案，该方案的灵感来自于光学中与源无关的QRNG方案。通过使用一种估计叠加态制备误差上限的方法，该方案可以在存在读出误差的情况下提供经过认证的随机性。为了提高随机比特的生成速率，我们还提供了一种针对有限数据大小的参数优化方法。此外，我们在IBM的云超导量子计算机上通过实验验证了我们的方案。
