New Journal of Physics· 2026Q1
Model predictive quantum control: A modular approach for efficient and robust quantum optimal control
- 0citations
- Q1SCImago
- 2026year
Short summary
A new modular framework for quantum optimal control (QOC) uses model predictive control (MPC) to improve efficiency and robustness, demonstrated via numerical results benchmarking against competing approaches.
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Key points
- Develops a modular framework for quantum optimal control (QOC) using model predictive control (MPC).
- The framework aims to improve both the efficiency of open-loop QOC and the robustness of closed-loop quantum control.
- Multiple MPC schemes are presented, including those with stability guarantees.
- Numerical results demonstrate the benefits of the proposed methods compared to competing approaches.
AI-generated from the title and abstract; the full text is not read.
Abstract
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.
The authors' abstract, as published at the source. New Journal of Physics, 2026 · DOI ↗
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Field: Control and Systems Engineering
Control and Systems EngineeringEngineering