关联量子系统中的时序自由能：一种智能体方法
Time-ordered free energy in correlated quantum systems: An agentic approach
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中文总结 AI 辅助
本文针对关联量子系统，提出一种基于动态规划和计算力学的智能体方法，定义时序自由能（TOFE）为该系统中智能体可提取的最大功，其策略识别时间复杂度随序列长度线性缩放。
中文摘要 AI 辅助
当智能体只能在因果约束下在线操作（基于已观测到的信息决定采用哪种能量提取方法）时，它能从量子态的时间序列中提取多少功？本文在量子态序列可能非马尔可夫（由智能体无法观测的底层隐马尔可夫机生成）的背景下研究该问题。利用动态规划和计算力学技术，本文提出一种可证明最优智能体策略的识别方法，其时间复杂度随序列长度线性缩放。这促使本文引入此类智能体可提取的最大功——时序自由能（TOFE），作为考虑因果关系的时序关联量子系统中可用自由能的基本度量。
英文摘要
How much work can an agent extract from a temporal sequence of quantum states when it can only operate online under causal constraints---deciding which energy extraction method to use with knowledge of what it has observed before? Here, we study this problem in the context of quantum state sequences that are potentially non-Markovian---generated by some underlying hidden Markov machine that the agent cannot observe. Using techniques from dynamic programming and computational mechanics, we present a method to identify the provably optimal agent strategy, with time complexity that scales linearly with sequence length. This motivates us to introduce the maximum work such agents can extract---time-ordered free energy(TOFE)---as a fundamental measure of free energy available in a temporally correlated quantum system subject to causal considerations.
