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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Entanglement distribution in lossy quantum networks.

Leonardo Oleynik1, Junaid Ur Rehman2, Seid Koudia3

  • 1Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg, L-1855, Luxembourg. leonardo.oleynik@uni.lu.

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Summary
This summary is machine-generated.

Distributing entanglement in quantum networks is challenging due to signal loss. W states offer a more robust and advantageous method for establishing entanglement compared to GHZ-like states in lossy networks.

Keywords:
Entanglement distributionLossy quantum networksW states

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Area of Science:

  • Quantum Information Science
  • Quantum Communication Networks

Background:

  • Entanglement distribution is fundamental for distributed quantum information processing.
  • Quantum networks face challenges with entanglement distribution over lossy channels.

Purpose of the Study:

  • To develop a mathematical framework for assessing average bipartite entanglement in lossy networks.
  • To compare the effectiveness of different quantum states (W vs. GHZ-like) for entanglement distribution.

Main Methods:

  • Developed a general mathematical framework to quantify entanglement in lossy channels.
  • Introduced a lower bound by optimizing over single-parameter local operations and classical communication (LOCC).
  • Analyzed entanglement extraction from W states and GHZ-like states.

Main Results:

  • Probabilistic Bell pair extraction from W states is more advantageous than deterministic extraction from GHZ-like states in lossy networks.
  • The advantage of W states increases with network size.
  • W states are analytically proven to be more effective in large-scale quantum networks.

Conclusions:

  • W states provide a more robust strategy for entanglement distribution in lossy quantum networks.
  • A trade-off exists between the success probability of entanglement distribution protocols and their resilience to loss.
  • Findings offer insights for practical near-term quantum network deployment.