Predicting the Temporal Variability of Error Rates in Superconducting Quantum Processors: Mitigating Error Accuracy Loss in Queue-Based Quantum Computing Platforms [Focus: Quantum Software and its Engineering]

• Published in: IEEE software Vol. 42; no. 5; pp. 90 - 97
• Main Authors: Rodriguez-Soriano, Laura, Garcia-Herrero, Francisco, Almudever, Carmen G.
• Format: Journal Article
• Language: English
• Published: Los Alamitos IEEE 01.09.2025; IEEE Computer Society
• Subjects: Accuracy; Calibration; Computational modeling; Error analysis; Errors; Integrated circuit modeling; Logic gates; Machine learning; Noise measurement; Predictive models; Program processors; Quantum computing; Quantum theory; Qubit; Qubits (quantum computing)

Multiple layers of the quantum system full-stack require data on temporal variations in error rates of physical elements. This article proposes using five machine learning and time-series models to predict error rate variability for two-qubit gates based on calibration data.