Isolating Recurring Execution-Dependent Abnormal Patterns on NISQ Quantum Devices

Abstract

Quantum devices increasingly expose a fundamental gap between compiler-modeled noise and hardware execution. Today's compilers approximate noise as calibration-derived costs over gates, qubits, and coupling edges, yet semantically equivalent circuits with identical compiler-visible costs can still produce unexpected hardware noise on real devices. The missing factor is execution context: short ordered gate sequences on specific qubit neighborhoods can induce excess error beyond current quantum noise models. Isolating these execution-dependent abnormal patterns is naturally reminiscent of delta debugging, but direct reduction is unsound in this setting: the failure signal is stochastic and drifting across calibration windows. To address this problem, we propose QRisk, a delta-debugging framework for isolating recurring abnormal gate patterns on quantum hardware. The key idea is to turn hardware-model discrepancy into a size-normalized stochastic fault signal: QRisk compares real-device error against calibration-based error from current quantum noise model, so reductions are judged by excess discrepancy rather than raw error decrease. It then performs segment-level reduction to localize compact gate fragments and validates candidates through independent rediscovery across calibration windows, retaining only recurring backend-specific gate patterns. On three IBM Heron r2 backends across 30 qubit layouts, QRisk finds 25 recurring abnormal gate patterns. Controlled experiments show that eliminating these gate patterns in compiled circuits reduces excess hardware noise by 24% on ibm_fez (Spearman \r{ho} = 0.515, p = 0.0007) and by 45% on ibm_marrakesh (\r{ho} = 0.711, p < 0.0001).