Quantum random number generation

Random numbers are an essential resource in science and technology, with important applications in simulation, statistical sampling, and cryptography. There are two principal methods of generating random numbers. One method uses computational algorithms that produce sequences of apparently random results, which are in fact completely determined by a shorter initial value known as a seed. This type of random number generator (RNG) is therefore called a pseudo-random (or deterministic) RNG. The other method relies on physical phenomena, such as atmospheric or thermal noise, that are expected to be random. This type of RNG is called a true (or non-deterministic) RNG. A particular example of the latter, which relies on the inherent randomness of quantum mechanics, is the quantum random number generator (QRNG). Such a device can, for instance, be based on the detection of the “path choice” of a single polarized photon passing through a polarizing beam splitter or on the stochastic properties of quantum tunnelling. In this project, the output data from several pseudo-RNGs and QRNGs will be compared and subjected to statistical tests of randomness.

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