We introduce Quantum Tree Networks, a k-ary tree topology for scalable, error-corrected entanglement routing. Using sublinear qubit overhead and network-level simulations, we demonstrate efficient routing and congestion avoidance.

Small interconnected quantum processors can collaborate to tackle quantum computational problems that typically demand more capable devices. These linked processors, referred to as quantum nodes, can use shared entangled states to execute nonlocal operations. As a consequence, understanding how to distribute entangled states among nodes is essential for developing hardware and software. We analyze a protocol where entanglement is continuously distributed among nodes that are physically arranged in a regular pattern: a chain, a honeycomb lattice, a square grid, and a triangular lattice. These regular patterns allow for the modular expansion of networks for large-scale distributed quantum computing. Within the distribution protocol, we investigate how nodes can optimize the frequency of attempting entanglement swaps, trading off multiple entangled states shared with neighboring nodes for fewer states shared with non-neighboring nodes. We evaluate the protocol's performance using the virtual neighborhood size - a metric indicating the number of other nodes with which a given node shares entangled states. Employing numerical methods, we find that nodes must perform more swaps to maximize the virtual neighborhood size when coherence times are short. In a chain network, the virtual neighborhood size's dependence on swap attempt frequency differs for each node based on its distance from the end of the chain. Conversely, all nodes in the square grid exhibit a qualitatively similar dependence of the virtual neighborhood size on the swap frequency.

Entangled states shared among distant nodes are frequently used in quantum network applications. When quantum resources are abundant, entangled states can be continuously distributed across the network, allowing nodes to consume them whenever necessary. This continuous distribution of entanglement enables quantum network applications to operate continuously while being regularly supplied with entangled states. Here, we focus on the steady-state performance analysis of protocols for continuous distribution of entanglement. We propose the virtual neighborhood size and the virtual node degree as performance metrics. We utilize the concept of Pareto optimality to formulate a multiobjective optimization problem to maximize the performance. As an example, we solve the problem for a quantum network with a tree topology. One of the main conclusions from our analysis is that the entanglement consumption rate has a greater impact on the protocol performance than the fidelity requirements. The metrics that we establish in this paper can be utilized to assess the feasibility of entanglement distribution protocols for large-scale quantum networks.