AI summaryⓘ
The authors address a problem in quantum networks where creating connections over long distances is random and slow, which conflicts with how quickly quantum information loses its quality. They suggest a new method that makes decisions locally and quickly, reducing delays to almost constant time, which helps keep quantum information reliable. They tested this method using a specific type of quantum hardware and found it uses resources efficiently and works within practical time limits. The authors also identify that the biggest challenge is accurately reading quantum states, but propose ways to reduce errors to keep the network working well. This approach could help build reliable building blocks needed for future large-scale quantum computers.
quantum networksentanglement generationcoherence timerouting protocolslocal measurementclassical feedforwarddual-species trapped-ionnoise suppressionstar subgraphsfault-tolerant quantum computing
Authors
Xiaoyi Zheng, Chan-Tong Lam, Lin Chen, Zheng Xing
Abstract
The development of quantum networks faces a key challenge: the contradiction between probabilistic long-range entanglement generation and finite coherence time. Existing routing protocols typically focus on global state computation or path optimization. As the network scales up, classical delays accumulate and exacerbate decoherence, leading to a decrease in entanglement fidelity. To reduce routing decision delays to levels far below the coherence time of qubits, we propose a protocol based on local measurement and classical feedforward. This protocol reduces the local decision complexity to amortized O(1) level, ensuring that the decision delay is always much smaller than the coherence time of qubits. We map this protocol onto a dual-species trapped-ion platform and perform hybrid simulations. The results show that the proposed protocol performs well in terms of both resource efficiency and time feasibility. Noise analysis indicates that readout fidelity is the main bottleneck of this protocol, but noise suppression can be achieved by employing an erasure transformation in the dual-species architecture, combined with spatial multiplexing and branch independence, thereby ensuring the generation of high-fidelity star subgraphs. This protocol provides a clear path to achieving high-fidelity star subgraphs. These subgraphs can serve as general modules, merging to construct arbitrary subgraphs, providing a feasible solution for future fault-tolerant distributed quantum computing.