Benchmarking Optimization Algorithms for Automated Calibration of Quantum Devices

• URL: http://arxiv.org/abs/2509.08555v2
• Date: Wed, 01 Oct 2025 13:27:07 GMT
• Title: Benchmarking Optimization Algorithms for Automated Calibration of Quantum Devices
• Authors: Kevin Pack, Shai Machnes, Frank K. Wilhelm,
• Abstract summary: We present the results of a comprehensive study of optimization algorithms for the calibration of quantum devices.<n>Our benchmark includes widely used algorithms such as Nelder-Mead and the state-of-the-art Covariance Matrix Adaptation Evolution Strategy (CMA-ES)<n>Based on our findings, we recommend the CMA-ES algorithm and provide empirical evidence for its superior performance across all tested scenarios.
• Score: 0.0347577906896546
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present the results of a comprehensive study of optimization algorithms for the calibration of quantum devices. As part of our ongoing efforts to automate bring-up, tune-up, and system identification procedures, we investigate a broad range of optimizers within a simulated environment designed to closely mimic the challenges of real-world experimental conditions. Our benchmark includes widely used algorithms such as Nelder-Mead and the state-of-the-art Covariance Matrix Adaptation Evolution Strategy (CMA-ES). We evaluate performance in both low-dimensional settings, representing simple pulse shapes used in current optimal control protocols with a limited number of parameters, and high-dimensional regimes, which reflect the demands of complex control pulses with many parameters. Based on our findings, we recommend the CMA-ES algorithm and provide empirical evidence for its superior performance across all tested scenarios.

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