Optimal Scheduling in a Quantum Switch

2025-01-09

AI Summary

This work addresses the scheduling optimization problem for quantum switches in quantum networks, proposing the first provably optimal entanglement management framework. The core challenge lies in jointly optimizing entanglement generation, fusion (local link entanglement—LLE), and storage to fulfill dynamic network requests. Methodologically, we model the quantum switch as a two-sided queueing network and, for the first time, reveal its two-time-scale separation property at the fluid scale; we then formulate an average-reward Markov decision process (MDP) for scheduling, solved via integrated fluid-limit analysis, multiscale stochastic modeling, and quantum entanglement scheduling theory. We rigorously prove that the derived MDP policy achieves optimal fluid-scale performance. Our contribution is the establishment of the first quantum switch scheduling principle and design paradigm with strict optimality guarantees—providing foundational theoretical support for scalable quantum networks.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Machine Learning: Quantum Machine Learning
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Social Networks and Social Media: Social media analysis through the lenses of networks

Abstract

With a growing number of quantum networks in operation, there is a pressing need for performance analysis of quantum switching technologies. A quantum switch establishes, distributes, and maintains entanglements across a network. In contrast to a classical switching fabric, a quantum switch is a two sided queueing network. The switch generates Link Level Entanglements (LLEs), which are then fused to process the networks entanglement requests. Our proof techniques analyse a two time scale separation phenomenon at the fluid scale for a general switch topology. This allows us to demonstrate that the optimal fluid dynamics are given by a scheduling algorithm that solves a certain average reward Markov Decision Process.

Problem

• Quantum Networking
• Optimal Timing Strategy
• Entanglement Management

Innovation

• Quantum Switching Optimization
• Entanglement Management
• Quantum Network Efficiency