2 research outputs found
18.8 Gbps real-time quantum random number generator with a photonic integrated chip
Quantum random number generators (QRNGs) can produce true random numbers.
Yet, the two most important QRNG parameters highly desired for practical
applications, i.e., speed and size, have to be compromised during
implementations. Here, we present the fastest and miniaturized QRNG with a
record real-time output rate as high as 18.8 Gbps by combining a photonic
integrated chip and the technology of optimized randomness extraction. We
assemble the photonic integrated circuit designed for vacuum state QRNG
implementation, InGaAs homodyne detector and high-bandwidth transimpedance
amplifier into a single chip using hybrid packaging, which exhibits the
excellent characteristics of integration and high-frequency response. With a
sample rate of 2.5 GSa/s in a 10-bit analog-to-digital converter and subsequent
paralleled postprocessing in a field programmable gate array, the QRNG outputs
ultrafast random bitstreams via a fiber optic transceiver, whose real-time
speed is validated in a personal computer.Comment: 5 pages, 4 figures. Accepted for publication in Applied Physics
Letter
Performance Optimization on Practical Quantum Random Number Generators: Modification on Min-entropy Evaluation and Acceleration on Post Processing
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