Performance Optimization Method for Laser-Phase-Noise based Quantum Random Number Generation

Quantum Physics [Submitted on 16 Apr 2026] Performance Optimization Method for Laser-Phase-Noise based Quantum Random Number Generation Jinlu Liu, Jie Yang, Yu Gao, Guowei Zhang, Yan Pan, Heng Wang, Yuyang Ding, Yang Li, Wei Huang, Bingjie Xu, Wei Chen The quantum random number generation based on laser phase noise, which is featured with high generation rate and ease for photonic integration, has been extensively investigated and demonstrated. Despite these advancements, a theoretical model to achieve optimal performance in terms of maximizing the generation rate or entropy is still incomplete. In this work, a comprehensive physical model for this scheme is introduced to accurately predict the power spectrum and probability distribution of raw data, based on which the entropy source bandwidth and quantum min-entropy can be accordingly calculated and thus the system performance can be quantitatively evaluated. The model is sufficiently validated through both simulation and experiment with significant agreement under various setups. Furthermore, our proposal enables the priori configuration of experimental setups to achieve designed power spectrum and probability distribution of the raw data, thereby maximizing the generation rate or the min-entropy for system performance optimization. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2604.14511 [quant-ph]   (or arXiv:2604.14511v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2604.14511 Focus to learn more Submission history From: Yan Pan [view email] [v1] Thu, 16 Apr 2026 00:57:19 UTC (1,613 KB) Access Paper: view license Current browse context: quant-ph < prev   |   next > new | recent | 2026-04 References & Citations INSPIRE HEP NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)