Influence of statistical distribution properties on ultrafast random-number generation using chaotic semiconductor lasers

We study the influence of statistical distribution properties on ultrafast random-number generators (RNGs) using chaotic laser system consisting of a semiconductor laser subject to dual-chaotic optical injections. Two completely different distributions are considered in this paper: one is a long-tailed distribution, and the other is a well-fitted Gaussian distribution. The numerical results show that, using minimum post-processing, symmetric distribution allows for the extraction of 4 least significant bits (LSBs) per sample; while for the asymmetric distribution the produced sequence based on the last LSB still exhibits certain bias. In other words, the important role of symmetric distribution in fast generation of random bits using multi-bit extraction scheme is demonstrated in numerical simulations.