Quantum Algorithm Mapping Latency Estimation in Three-Dimensional Quantum Architectures

Quantum computing leverages the unique properties of qubits, such as superposition and entanglement, to address traditional computational efficiency issues and achieve exponential acceleration. However, the complexity of quantum architectures hinders the practical application of quantum algorithms, especially in three-dimensional architectures. Compared with one-dimensional and two-dimensional architectures, three-dimensional architectures offer superior scalability and fault tolerance but also introduce challenges like increased mapping latency. It requires Computer-Aided Design (CAD) software to optimize the design of quantum algorithms to reduce the latency overhead. However, existing Computer-Aided Design software contains methods for estimating latency, such as Quantum Scheduling, Placement, and Routing tool (QSPR) and Latency Estimation for Quantum Architectures (LEQA), that either require excessively long estimation times or are limited to two-dimensional architectures. This paper presents a novel method for estimating the mapping latency of quantum algorithms in 3D architectures, bridging the gap in current research. Additionally, we develop a simulator, LE3D-sim, to validate the method’s effectiveness and accuracy. Our contributions include providing the first latency estimation approach for 3D quantum architectures and significantly reducing runtime overhead, facilitating the efficient evaluation of large-scale quantum programs. Experimental results demonstrate that our method achieves an average absolute error of 2.3%-2.9% in latency estimation compared to actual latency, with runtime improvements of up to 1255.2 times. This advancement supports the optimization of quantum algorithm mapping and paves the way for the development of quantum computing in 3D architectures.