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Chinese Physics Letters

Optimal Control of Unknown Collective Spin Systems via a Neural Network Surrogate

Chen Yaofeng, Li You

Published Aug 15, 2025• 2 citations
Publisher

Abstract

Abstract Quantum optimal control (QOC) relies on accurately modeling system dynamics and is often challenged by unknown or inaccessible interactions in real systems. Taking an unknown collective spin system as an example, this work introduces a machine-learning-based, data-driven scheme to overcome the challenges encountered, with a trained neural network (NN) assuming the role of a surrogate model that captures the system’s dynamics and subsequently enables QOC to be performed on the NN instead of on the real system. The trained NN surrogate proves effective for practical QOC tasks and is further demonstrated to be adaptable to different experimental conditions, remaining robust across varying system sizes and pulse durations.

DOI
10.1088/0256-307x/42/10/100601

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Achieving precise preparation of quantum many-body states is crucial for the practical implementation of quantum computation and quantum simulation. However, the inherent challenges posed by unavoidable excitations at critical points during quench processes necessitate careful design of control fields. In this work, we introduce a promising and versatile dynamic control neural network tailored to optimize control fields. We address the problem of suppressing defect density and enhancing cat-state fidelity during the passage across the critical point in the quantum Ising model. Our method facilitates seamless transitions between different objective functions by adjusting the optimization strategy. In comparison to gradient-based power-law quench methods, our approach demonstrates significant advantages for both small system sizes and long-term evolutions. We provide a detailed analysis of the specific forms of control fields and summarize common features for experimental implementation. Furthermore, numerical simulations demonstrate the robustness of our proposal against random noise and spin number fluctuations. The optimized defect density and cat-state fidelity exhibit a transition at a critical ratio of the quench duration to the system size, coinciding with the quantum speed limit for quantum evolution.