Experimentally Probing the Algorithmic Randomness and Incomputability of Quantum Randomness
Alastair A. Abbott, Cristian S. Calude, Michael J. Dinneen, Nan Huang

TL;DR
This paper explores the fundamental differences between quantum and pseudo-random sequences, focusing on their algorithmic complexity and incomputability, and proposes indirect testing methods to evaluate these properties in practice.
Contribution
It introduces methods to test the incomputability of QRNGs and compares quantum and pseudo-random sequences using these novel approaches.
Findings
Tests did not show a clear advantage of QRNGs in algorithmic properties.
Some test results were ambiguous, indicating the need for further research.
The study highlights challenges in certifying quantum randomness through algorithmic complexity.
Abstract
The advantages of quantum random number generators (QRNGs) over pseudo-random number generators (PRNGs) are normally attributed to the nature of quantum measurements. This is often seen as implying the superiority of the sequences of bits themselves generated by QRNGs, despite the absence of empirical tests supporting this. Nonetheless, one may expect sequences of bits generated by QRNGs to have properties that pseudo-random sequences do not; indeed, pseudo-random sequences are necessarily computable, a highly nontypical property of sequences. In this paper, we discuss the differences between QRNGs and PRNGs and the challenges involved in certifying the quality of QRNGs theoretically and testing their output experimentally. While QRNGs are often tested with standard suites of statistical tests, such tests are designed for PRNGs and only verify statistical properties of a QRNG, but are…
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