Adaptive, Continuous Entanglement Generation for Quantum Networks

Quantum networks rely on entanglement between qubits at distant nodes to transmit information; however, creation of these links is not dependent on the information to be transmitted. Researchers have thus explored schemes for continuous generation of entanglement, where network nodes may generate entanglement links before receiving user requests. In this work, we present a scheme for continuous generation of entanglement utilizing an adaptive method to better tailor generated entanglement links to incoming requests and reduce latency. This method selects links to generate randomly according to some distribution and updates this distribution upon receiving requests. We first construct a simple simulator to test the scheme and derive parameter spaces where latency improvement is likely. For these spaces, we observe improvements in latency versus networks with no pre-generated entanglement and networks with a static distribution for pre-generated links. We then move our simulation to the more realistic Simulator of Quantum Network Communication (SeQUeNCe) and observe the performance of our scheme for varying hardware parameters, request structures, and network topologies.