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arXiv · 2509.05167

Model predictive quantum control: A modular approach for efficient and robust quantum optimal control

Eya Guizani·Julian Berberich
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Abstract

Model predictive control (MPC) is one of the most successful modern control methods. It relies on repeatedly solving a finite-horizon optimal control problem and applying the beginning piece of the optimal input. In this paper, we develop a modular framework for improving efficiency and robustness of quantum optimal control (QOC) via MPC. We first provide a tutorial introduction to basic concepts of MPC from a QOC perspective. We then present multiple MPC schemes, ranging from simple approaches to more sophisticated schemes which admit stability guarantees. This yields a modular framework which can be used 1) to improve efficiency of open-loop QOC and 2) to improve robustness of closed-loop quantum control by incorporating feedback. We demonstrate these benefits with numerical results, where we benchmark the proposed methods against competing approaches.

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Eya Guizani, Julian Berberich. 2025-09-05. Model predictive quantum control: A modular approach for efficient and robust quantum optimal control. https://arxiv.org/abs/2509.05167

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