Scalable Transpilation for Overcoming Restricted Connectivity in Distributed Superconducting Quantum Architectures

Abstract:Distributed Quantum Computing (DQC) offers a promising pathway to scale superconducting quantum hardware, but restricted inter- and intra-module connectivity creates a major transpilation bottleneck. Current DQC transpilation methods often assume idealized hardware connectivity, ignore subsequent intra-module routing, or suffer from substantial computational overheads that limit their applicability at scale. To address this, we introduce a scalable transpilation method tailored for the restricted connectivity of distributed superconducting quantum architectures. Specifically, our quantum interaction graph (QIG) approach couples a graph-partitioning mapping step with a fast SABRE-inspired routing heuristic. On a 48-qubit (3 QPUs $\times$ 16 qubits) architecture with all-to-all inter-core connectivity, our method reduces average aggregated costs by up to 24.72% (unstructured) and 24.01% (structured), while delivering >250$\times$ speed-ups for structured workloads compared to the state-of-the-art DMapS algorithm. On the 399-qubit (3$\times$133) IBM Flamingo, where DMapS times out on dense circuits, our approach maintains practical runtimes. Against a DQC-adapted SABRE baseline, it reduces structured circuit routing costs by up to 51.94% (all-to-all inter-core topology) and 51.96% (restricted line topology). Ultimately, this work delivers a practical transpilation method for DQC at scale.

11 pages, 3 figures. Accepted at the 2026 IEEE International Conference on Quantum Computing and Engineering (QCE)

Quantum Physics (quant-ph); Emerging Technologies (cs.ET)

arXiv:2611.07175 [quant-ph]

(or arXiv:2611.07175v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2611.07175 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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