Public articles linked to the same research event.
arXiv The authors introduce Quantum Utility Routing (QUR), a weighted routing framework for continuous-variable quantum key distribution networks that embeds transition-level composable finite-size secret key rates directly into the route search, with a graph-optimized mode (QURgo) and a machine-learned fixed-weight mode (QURfw); at the default configuration on Waxman graphs, QURgo increases mean path SKR by 193.2% relative to A* while using 78.4% fewer nodes than Max–Min, and maintains 100.0% routing success when 76.3% of nodes are untrusted.
The authors introduce Quantum Utility Routing (QUR), a weighted routing framework for continuous-variable quantum key distribution networks that embeds transition-level composable finite-size secret key rates directly into the route search, with a graph-optimized mode (QURgo) and a machine-learned fixed-weight mode (QURfw); at the default configuration on Waxman graphs, QURgo increases mean path SKR by 193.2% relative to A* while using 78.4% fewer nodes than Max–Min, and maintains 100.0% routing success when 76.3% of nodes are untrusted.
The authors introduce Quantum Utility Routing (QUR), a weighted routing framework for continuous-variable quantum key distribution networks that embeds transition-level composable finite-size secret key rates directly into the route search, with a graph-optimized mode (QURgo) and a machine-learned fixed-weight mode (QURfw); at the default configuration on Waxman graphs, QURgo increases mean path SKR by 193.2% relative to A* while using 78.4% fewer nodes than Max–Min, and maintains 100.0% routing success when 76.3% of nodes are untrusted.
The authors introduce Quantum Utility Routing (QUR), a weighted routing framework for continuous-variable quantum key distribution networks that embeds transition-level composable finite-size secret key rates directly into the route search, with a graph-optimized mode (QURgo) and a machine-learned fixed-weight mode (QURfw); at the default configuration on Waxman graphs, QURgo increases mean path SKR by 193.2% relative to A* while using 78.4% fewer nodes than Max–Min, and maintains 100.0% routing success when 76.3% of nodes are untrusted.