2024/07/25 by Travis Hurant, Hurant, Travis, Ke Sun +7 · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · #Advanced Electron Microscopy Techniques and Applications #FOS: Physical sciences #Integrated Circuits and Semiconductor Failure Analysis #Quantum Information and Cryptography #Quantum Physics (quant-ph)
paper · pdf · doi:10.48550/arxiv.2407.18339
openalex publication_date 2024/07/25 · openalex created_date 2024/09/30 · openalex updated_date 2026/07/28
Accurate calibration of control parameters in quantum gates is crucial for high-fidelity operations, yet it represents a significant time and resource challenge, necessitating periods of downtime for quantum computers. Robust Phase Estimation (RPE) has emerged as a practical and effective calibration technique aimed at tackling this challenge. It combines a provably efficient number of control pulses with a classical post-processing algorithm to estimate the phase accumulated by a quantum gate. We introduce Bayesian Robust Phase Estimation (BRPE), an innovative approach that integrates Bayesian parameter estimation into the classical post-processing phase to reduce the sampling overhead. Our numerical analysis shows that BRPE markedly reduces phase estimation errors, requiring approximately 50% fewer samples than standard RPE. Specifically, in an ideal, noise-free setting, it achieves up to a 96% reduction in average absolute estimation error for a fixed sample cost of 88 shots when compared to RPE. Under a depolarizing noise model, it attains up to a 47% reduction for a fixed cost of 176 shots. Additionally, we adapt BRPE for Ramsey spectroscopy applications and successfully implement it experimentally in a trapped ion system.