Randomness quantification in spontaneous emission

TL;DR

This paper develops a rigorous quantum information framework to quantify and analyze the security of spontaneous emission-based quantum random number generators, revealing their vulnerabilities and robustness against different eavesdropping strategies.

Contribution

It introduces a comprehensive adversarial model and quantifies intrinsic randomness, advancing the understanding of security in spontaneous emission QRNGs.

Findings

Single-photon detection QRNGs are vulnerable to direct atom access.

Spatial mode and phase fluctuation QRNGs are secure against both adversary types.

Quantitative bounds on intrinsic randomness are provided for different schemes.

Abstract

Quantum coherence serves as a fundamental resource for generating intrinsic randomness, yet the quantification of randomness in quantum random number generators (QRNGs) based on spontaneous emission has remained largely phenomenological. Existing randomness analysis lacks rigorous adversarial models and a clear characterization of the role of quantum coherence in these systems. In this work, we develop a comprehensive quantum information-theoretic framework for randomness generation in spontaneous emission processes. We characterize two distinct eavesdropping strategies: one where the adversary directly accesses the atom ensemble, and the other where the adversary accesses only its purification. Our analysis reveals that when randomness is generated through single-photon detection and temporal mode measurements, the QRNG is vulnerable to the first adversary scenario, though it still guarantees a lower bound on intrinsic randomness against the second adversary scenario even under maximal information leakage from the atoms. In contrast, QRNGs based on spatial mode detection and phase fluctuations demonstrate security against both types of adversaries, providing robust randomness generation. Furthermore, we provide a quantitative calculation of intrinsic randomness for these spontaneous-emission-based QRNG schemes.