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Time Synchronization in Communication Networks: A Comparative Study of Quantum Technologies

Swaraj Shekhar Nande, Andrea Garbugli, Riccardo Bassoli, Frank H. P. Fitzek

202411 citationsDOI

Abstract

Time synchronization is crucial in the architecture of modern communication networks, supporting numerous high-stakes applications like financial transactions, autonomous vehicle control, and data center operations. While traditional time synchronization protocols, specifically the Network Time Protocol (NTP) and Precision Time Protocol (PTP), are reliable for various applications, they fall short in scenarios requiring ultra-high precision and resilience. To address these limitations, this paper provides a comprehensive comparative analysis of two emerging quantum technologies, namely Time-Correlated Entangled Photons (TCEP) and Optical Lattice Clocks (OLC). Using Monte Carlo simulations, we examined the synchronization in terms of the accuracy of these technologies under various noise conditions, revealing that while TCEP works perfectly in low-noise environments, its efficacy diminishes significantly with increasing noise levels. On the contrary, OLCs demonstrate consistent performance across various noise levels, making them more versatile for diverse application scenarios. This study is foundational for integrating quantum technologies in time synchronization for communication networks and sheds light on their merits and challenges. Our findings open new avenues for research in scalability, environmental resilience, and the development of hybrid quantum-classical timekeeping systems. Integrating quantum-enhanced time synchronization into a communication network will be the key step for achieving full-fledged Quantum Internet and quantum-enhanced communication networks.

Topics & Concepts

Computer scienceSynchronization (alternating current)Computer networkQuantumDistributed computingPhysicsChannel (broadcasting)Quantum mechanicsNetwork Time Synchronization TechnologiesMolecular Communication and NanonetworksEEG and Brain-Computer Interfaces