论文标题
实用量子随机数生成器的性能优化：对后期处理的最小渗透评估和加速度的修改
Performance Optimization on Practical Quantum Random Number Generators: Modification on Min-entropy Evaluation and Acceleration on Post Processing
论文作者
论文摘要
量子随机数生成是一种通过从特定量子过程中提取随机性来生成随机数的技术。至于实际的随机数生成器，它们不仅需要没有信息泄漏，而且还需要高速生成随机序列。在本文中，我们考虑了基于激光相噪声的发电机，并提出了一种修改最小透镜估计的方法，该方法不能保证对窃听器的信息泄漏。我们还基于toeplitz矩阵加速后处理，并以快速的傅立叶变换，将其时间复杂性降低到O（nlogn）。此外，我们讨论了按块长度对后处理速度的影响，并找到适当的块长度来处理固定长度的原始序列。
Quantum random number generation is a technique to generate random numbers by extracting randomness from specific quantum processes. As for practical random number generators, they are required not only to have no information leakage but also have a high speed at generating random sequences. In this paper, we consider the generators based on laser phase noise and propose a method to modify the estimation of min-entropy, which can guarantee no information leakage to the eavesdropper. We also accelerate post processing based on Toeplitz matrix with Fast Fourier Transformation, reducing its time complexity to O(nlogn). Furthermore, we discuss the influence on post processing speed by block length and find a proper block length to process a fixed-length raw sequence.
