Spectral Detection of Correlated Errors on Superconducting Quantum Hardware via Parity-Circuit Canaries

Abstract

Standard device characterization protocols, such as Randomized Benchmarking (RB), typically report averaged, independent error rates per qubit. However, these methods are largely blind to correlated errors between neighbouring qubits: errors that fundamentally break the independent and identically distributed (i.i.d.) noise assumptions relied upon by most quantum error correction (QEC) decoders and error mitigation strategies. In this paper, we present a measurement approach using parity-circuit canaries to estimate pairwise error correlations on noisy intermediate-scale quantum (NISQ) devices. By applying spectral kernel analysis to the resulting correlation matrices, we can quantitatively assess the validity of the independent error assumption. We first validate our approach by emulating the canary protocol on publicly available surface code data from IBM Quantum hardware (ibm_fez). We then extend this proof-of-concept with directly measured, purpose-built canary circuits executed on the same backend, reproduced across independent sessions, controlled for physical adjacency and measurement batching, and shown to be inconsistent with pure estimation noise. The direct measurements confirm a significant, structural spectral violation that is not explained by neighbour-to-neighbour crosstalk alone, and reveal a previously unreported dependence of the excess correlation on the instantaneous marginal error rate, underscoring the need for correlation-aware, dynamically calibrated diagnostics in fault-tolerant quantum computing.