ScholarWorks@숙명여자대학교

초록

Quantum computing is quickly evolving from the era of quantum advantage to quantum utility, thereby enabling the formulation and implementation of large-scale, application-driven quantum algorithms. However, existing approaches often incur prohibitive sampling and reconstruction overheads due to their lack of sensitivity to application structure and device heterogeneity. DAScut proposes a Density-and-Structure-aware circuit cutting framework that exploits fidelity-aware circuit to device mapping and isomorphism awareness to reduce execution and reconstruction costs. Experimental results using selected benchmark quantum algorithms demonstrate that DAScut reduces redundant sub-circuit execution by up to 52% for heterogeneous workloads and speeds up execution by about 6 times relative to other scheduling methods. These results highlight DAScut as a scalable and practical step toward simulating sparse quantum circuit executions on classical resources.

키워드