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This study presents a bus-based reconfigurable router for modular superconducting quantum processors, utilizing flux-tunable SQUID couplers to enable parallel entangling operations. Simulations indicate that this architecture significantly reduces SWAP gate counts and circuit depth compared to standard nearest-neighbor grids, offering a tangible path toward scaling qubit connectivity without excessive overhead. By treating enhanced connectivity as a compiler-visible resource, the work addresses critical bottlenecks in Hamiltonian simulation and resource-constrained scheduling for large-scale quantum systems.
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Reconfigurable bus-based quantum router for modular superconducting processors

arXiv2 min read

arXiv:2609.28881v1 Announce Type: new Abstract: Scaling superconducting quantum processors requires interconnects that provide both non-local connectivity and parallel entangling operations. Nearest-neighbour couplings require distant interactions to be routed through SWAP networks, increasing the native two-qubit-gate count and potentially extending the circuit critical path. Here we introduce a bus-based reconfigurable quantum router for modular superconducting processors. Flux-tunable SQUID couplers selectively connect interface qubits to two shared buses, allowing destructive interference to suppress idle interactions while supporting two disjoint controlled-$Z$ (CZ) gates in parallel. Full-system Hamiltonian simulations yield parallel-gate errors at the level of $10^{-3}$, and open-system analysis identifies the coherence requirements for high-fidelity operation. We further assess the circuit-level consequences using hardware-aware compilation and resource-constrained scheduling. For 36-qubit quantum Fourier transform (QFT), QAOA-MaxCut and random-pairing circuits, the router reduces the median SWAP count by up to $34\%$ and the native CZ count by up to $20\%$ relative to a matched two-dimensional grid. End-to-end depth reduction is circuit dependent, reaching $20\%$ for QAOA-MaxCut but remaining negligible for the QFT despite its lower gate count. These results show that enhanced connectivity and schedulable parallelism provide distinct benefits, establishing the router as a compiler-visible hardware resource for modular superconducting quantum processors.

Abstract:Scaling superconducting quantum processors requires interconnects that provide both non-local connectivity and parallel entangling operations. Nearest-neighbour couplings require distant interactions to be routed through SWAP networks, increasing the native two-qubit-gate count and potentially extending the circuit critical path. Here we introduce a bus-based reconfigurable quantum router for modular superconducting processors. Flux-tunable SQUID couplers selectively connect interface qubits to two shared buses, allowing destructive interference to suppress idle interactions while supporting two disjoint controlled-$Z$ (CZ) gates in parallel. Full-system Hamiltonian simulations yield parallel-gate errors at the level of $10^{-3}$, and open-system analysis identifies the coherence requirements for high-fidelity operation. We further assess the circuit-level consequences using hardware-aware compilation and resource-constrained scheduling. For 36-qubit quantum Fourier transform (QFT), QAOA-MaxCut and random-pairing circuits, the router reduces the median SWAP count by up to $34\%$ and the native CZ count by up to $20\%$ relative to a matched two-dimensional grid. End-to-end depth reduction is circuit dependent, reaching $20\%$ for QAOA-MaxCut but remaining negligible for the QFT despite its lower gate count. These results show that enhanced connectivity and schedulable parallelism provide distinct benefits, establishing the router as a compiler-visible hardware resource for modular superconducting quantum processors.

arXiv:2609.28881 [quant-ph]

(or arXiv:2609.28881v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2609.28881 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 283 words

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