Fidelity-Aware Frequency Allocation and Transpilation Co-Design for Tunable Coupler Quantum Systems

TL;DR

This paper introduces a physics-informed co-design framework for frequency allocation and transpilation in tunable-coupler quantum systems, improving gate fidelity and scalability.

Contribution

It presents a novel error-aware frequency allocation strategy and a noise-aware transpilation method called FINESSE for scalable quantum architectures.

Findings

Scalable frequency allocation minimizes spectator-induced errors.

FINESSE reduces log-infidelity cost by 8.9%.

FINESSE reduces circuit depth by 6.8%.

Abstract

Frequency crowding is a fundamental limitation in superconducting quantum architectures, particularly in tunable-coupler systems. We present a framework that explicitly models both coherent spectator-induced errors and incoherent lifetime effects through an error budgeting approach. Using this model, we analyze how frequency crowding impacts gate fidelity as module size and connectivity scale, and formulate a constrained optimization problem to assign qubit and coupler frequencies under realistic separation and hardware constraints. We demonstrate scalable frequency allocation strategies that minimize spectator-induced errors. We further show that increasing qubit count and coupling density within a module leads to a fidelity-connectivity tradeoff. To explore the benefits at the system scale, we have developed a noise-aware transpilation approach called FINESSE, which minimizes error by selecting high-fidelity paths that satisfy connectivity via SWAP insertion while jointly optimizing downstream gate execution. We demonstrate this physics-informed architecture-transpilation co-design approach for a SNAIL-based third-order coupler that natively realizes the $\sqrt{iSWAP}$ basis with frequency aware gate fidelities. On SNAIL architectures, FINESSE achieves an average 8.9% reduction in log-infidelity cost and 6.8% reduction in circuit depth vs. SABRE. We also compare results on IBM Brisbane's architecture.