New Laser-Based Random Number Generator Is 100 Times Quicker Than Its Predecessors
If you could throw multiple dice at the same time, you would get many sequences of random numbers. These values could then be used for encryption, scrambling private data so that information can travel securely over the internet. They could also be used for complex computer simulations such as those of the stock market. Now, a new study is revealing an improved faster way of generating these numbers.
"Human-made physical random number generators (RNGs) can be traced back 5000 years or more. Early examples such as knucklebones, two-sided throw sticks, and dice have been found in the Middle East, India, and China. RNGs were used for fortune-telling and games of chance, with the oldest known board games of similar age as those of the number generators," wrote Daniel Gauthier, a physicist at Ohio State University, in a commentary of the study.
"Today, RNGs are vital for services and state-of-the-art technologies such as cryptographically secured communication, blockchain technologies, and quantum key distribution. Moreover, RNGs are needed in machine learning and scientific applications such as Monte Carlo numerical methods."
Now, physicist Hui Cao of Yale University and his colleagues have come up with a new approach to generating these random numbers that is 100 times quicker than previously existing generators. This new approach is the result of the use of lasers.
Lasers have tiny, naturally occurring fluctuations in the light’s frequency over time. It is this quality that generators use to come up with their random numbers.
In order to create this RNG, Cao and his fellow researchers had to engineer a very particular device. The team "designed a chip-scale laser diode that generates random bits at an ultrahigh rate," states the study.
"By tailoring the geometry of the cavity, they were able to exploit the spatiotemporal interference of many lasing modes to generate picosecond-scale emission intensity fluctuations in space and time, producing ultrafast random bitstreams in parallel."