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arXiv 2408.15328quant-phcond-mat.mes-hallcs.LG
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用于开放量子系统最优控制的人工智能麦克斯韦妖

Artificially intelligent Maxwell's demon for optimal control of open quantum systems

Freie Universität Berlin(柏林自由大学);University of Rochester(罗切斯特大学);Chapman University(查普曼大学);Microsoft Research AI4Science(微软研究院AI4Science);Rice University(莱斯大学);University of Pavia(帕维亚大学);INFN - Sezione di Pavia(国家核物理研究所帕维亚分所);Dahlem Center for Complex Quantum Systems(达勒姆复杂量子系统中心)

Paolo Andrea Erdman, Robert Czupryniak, Bibek Bhandari, Andrew N. Jordan, Frank Noé, Jens Eisert, Giacomo Guarnieri

AI总结:

本文利用强化学习让智能体充当量子麦克斯韦妖,在开放量子比特系统中自动发现最优反馈控制策略,以平衡测量驱动冷却与测量效率,并在不同时间尺度机制下找到了优于直觉策略的新方案。

摘要:

开放量子系统的反馈控制对于从量子计算到量子纠错和量子计量学等多种实际应用具有根本重要性。它在热力学背景下的应用进一步使人们能够研究信息与能量之间的相互作用。然而,推导最优反馈控制策略极具挑战性,因为它涉及开放量子系统的最优控制、量子测量的随机性质,以及纳入能够最大化长期时间和轨迹平均目标的策略。在这项工作中,我们采用强化学习方法来自动化并捕捉量子麦克斯韦妖的角色:智能体承担起字面意义上的角色,即在基于量子比特的系统中发现最优反馈控制策略,以最大化测量驱动的冷却与测量效率之间的权衡。考虑弱测量或投影量子测量,我们基于热化、测量和幺正反馈时间尺度之间的排序探索了不同的机制,发现了不同且高度非直观但可解释的策略。在热化主导的机制中,我们发现了以测量结果为条件的精细有限时间热化协议策略。在测量主导的机制中,我们发现最优策略涉及自适应地测量不同的量子比特可观测量以反映所获取的信息,并重复多次弱测量直到量子态“足够纯”,从而导致态空间中的随机行走。最后,我们研究了所有时间尺度相当的情况,发现了新的反馈控制策略,这些策略显著优于更直观的策略。我们讨论了一个双量子比特示例,在其中探索了纠缠的作用,并在结论中讨论了我们的结果向量子多体系统的扩展。

英文摘要:

Feedback control of open quantum systems is of fundamental importance for practical applications in various contexts, ranging from quantum computation to quantum error correction and quantum metrology. Its use in the context of thermodynamics further enables the study of the interplay between information and energy. However, deriving optimal feedback control strategies is highly challenging, as it involves the optimal control of open quantum systems, the stochastic nature of quantum measurement, and the inclusion of policies that maximize a long-term time- and trajectory-averaged goal. In this work, we employ a reinforcement learning approach to automate and capture the role of a quantum Maxwell's demon: the agent takes the literal role of discovering optimal feedback control strategies in qubit-based systems that maximize a trade-off between measurement-powered cooling and measurement efficiency. Considering weak or projective quantum measurements, we explore different regimes based on the ordering between the thermalization, the measurement, and the unitary feedback timescales, finding different and highly non-intuitive, yet interpretable, strategies. In the thermalization-dominated regime, we find strategies with elaborate finite-time thermalization protocols conditioned on measurement outcomes. In the measurement-dominated regime, we find that optimal strategies involve adaptively measuring different qubit observables reflecting the acquired information, and repeating multiple weak measurements until the quantum state is "sufficiently pure", leading to random walks in state space. Finally, we study the case when all timescales are comparable, finding new feedback control strategies that considerably outperform more intuitive ones. We discuss a two-qubit example where we explore the role of entanglement and conclude discussing the scaling of our results to quantum many-body systems.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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