Quantum random number generation

TL;DR

Quantum random number generation leverages quantum physics to produce true randomness, with various device trust models enabling different balances of speed and trustworthiness, crucial for cryptography.

Contribution

This paper categorizes quantum random number generators into practical, self-testing, and semi-self-testing types, clarifying their trust assumptions and performance tradeoffs.

Findings

Quantum physics enables genuine randomness through measurement.

QRNGs are categorized based on device trustworthiness.

Different QRNG types balance speed and security.

Abstract

Quantum physics can be exploited to generate true random numbers, which play important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness --- coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. Based on the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at a high speed by properly modeling the devices. The second category is self-testing QRNG, where verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category which provides a tradeoff between the trustworthiness on the device and the random number generation speed.