Energy landscape shaping for robust control of atoms in optical lattices

Weidner, C. A., O’Neil, S. P., Jonckheere, E. A., Langbein, F. C. ORCID: https://orcid.org/0000-0002-3379-0323 and Schirmer, S. G. 2025. Energy landscape shaping for robust control of atoms in optical lattices. New Journal of Physics 27 (6) , 064503. 10.1088/1367-2630/addc0d

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Abstract

Robust quantum control is crucial for realizing practical quantum technologies. Energy landscape shaping offers an alternative to conventional dynamic control, providing theoretically enhanced robustness and simplifying implementation for certain applications. This work demonstrates the feasibility of robust energy landscape control in a practical implementation with ultracold atoms. We leverage a digital mirror device (DMD) to shape optical potentials, creating complex energy landscapes. To achieve a desired objective, such as efficient quantum state transfer, we formulate a novel hybrid optimization approach that effectively handles both continuous (laser power) and discrete (DMD pixel activation) control parameters. This approach combines constrained quasi-Newton methods with surrogate models for efficient exploration of the vast parameter space. Furthermore, we introduce a framework for analyzing the robustness of the resulting control schemes against experimental uncertainties. By modeling uncertainties as structured perturbations, we systematically assess controller performance and identify robust solutions. We apply these techniques to maximize spin transfer in a chain of trapped atoms, achieving high-fidelity control while maintaining robustness. Our findings provide insights into the experimental viability of controlled spin transfer in cold atom systems. More broadly, the presented optimization and robustness analysis methods apply to a wide range of quantum control problems, offering a toolkit for designing and evaluating robust controllers in complex experimental settings.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Schools > Computer Science & Informatics
Additional Information:	License information from Publisher: LICENSE 1: URL: https://creativecommons.org/licenses/by/4.0/, Type: cc-by
Publisher:	IOP Publishing
Date of First Compliant Deposit:	11 June 2025
Date of Acceptance:	22 May 2025
Last Modified:	11 Jun 2025 09:00
URI:	https://orca.cardiff.ac.uk/id/eprint/178990

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