A quantum-inspired framework using effective Hamiltonians, Metropolis annealing and stochastic tensor-network compression is proposed for adaptive multi-demand routing in large-scale QKD networks.
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Quantum-Inspired Hamiltonian Optimization, Stochastic Tensor Networks and Adaptive Congestion Routing for Large-Scale QKD Networks
A quantum-inspired framework using effective Hamiltonians, Metropolis annealing and stochastic tensor-network compression is proposed for adaptive multi-demand routing in large-scale QKD networks.