Energy Landscape Shaping for Robust Control of Atoms in Optical Lattices

TL;DR

This paper demonstrates a practical approach to robust quantum control in cold atom systems by shaping energy landscapes using a digital mirror device and a hybrid optimization method, enhancing control robustness and efficiency.

Contribution

It introduces a novel hybrid optimization framework combining quasi-Newton methods and surrogate models for energy landscape shaping in quantum control.

Findings

High-fidelity spin transfer achieved in cold atom chains.

Robust control schemes maintain performance under experimental uncertainties.

Framework applicable to various quantum control problems.

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.