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05:30
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
Published on: September 8, 2023
509
Optimal routing and end-to-end entanglement distribution in quantum networks
Joy Halder1, Akhmadjon Rajabov2,3, Riccardo Bassoli4,5,6
1Vodafone Chair Mobile Communications Systems, Technische Universität Dresden, 01067, Dresden, Germany. joy.halder@tu-dresden.de.
Scientific Reports
|August 20, 2024
Summary
This study optimizes resource allocation in quantum networks by minimizing entangled qubit pairs. A heuristic algorithm achieves near-optimal performance, crucial for efficient quantum communication.
Area of Science:
- Quantum Information Science
- Network Engineering
- Computer Science
Background:
- Quantum networks utilize quantum bits (qubits) for advanced applications.
- Entanglement distribution and swapping are key but probabilistic operations, impacting network performance.
- Resource allocation is critical for efficient quantum network operation.
Purpose of the Study:
- To address the engineering challenge of resource allocation in quantum networks.
- To minimize the number of entangled qubit pairs (Bell pairs) required between adjacent nodes.
- To investigate the impact of entanglement probability and quantum memory on network performance.
Main Methods:
- Formulation of an integer linear programming (ILP) optimization model.
- Development of a heuristic algorithm for resource allocation.
- Extensive simulations to compare ILP and heuristic performance.
Main Results:
- The heuristic algorithm yields solutions comparable to the optimal ILP solution.
- Maximum utilized Bell pairs depend significantly on entanglement establishment probability.
- Quantum memory time and incoming request volume influence Bell pair utilization.
Conclusions:
- The proposed heuristic algorithm is an effective method for resource allocation in quantum networks.
- Optimizing resource allocation is vital for mitigating performance degradation caused by probabilistic entanglement operations.
- Network performance is sensitive to entanglement fidelity, memory, and request load.
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