通过局部测量的信息能力统一 U(1)对称量子电路中的电荷可学习性转变
Unifying Charge-Learnability Transitions in U(1)-Symmetric Quantum Circuits through Informational Power of Local Measurement
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中文总结 AI 辅助
研究通过局部测量信息能力统一U(1)对称量子电路电荷可学习性转变，将其扩展到概率性弱测量，引入交叉熵区分解码器变体，精确记录-标签互信息提供基准，确立局部测量信息能力为统一原则。
中文摘要 AI 辅助
受监测的对称量子电路中的电荷可学习性转变揭示了局部测量记录如何获取足够信息来推断守恒电荷。本文将电荷可学习性扩展到概率性弱测量，其测量概率和测量强度可独立调节。发现可学习性相边界由局部测量的信息能力组织。还引入交叉熵作为区分无偏、有偏和反偏解码器变体的标签敏感诊断。最后，精确的记录-标签互信息为电荷推断的基本可用信息提供了与解码器无关的基准。结果确立了局部测量的信息能力作为一般监测协议下电荷可学习性的统一原则。
英文摘要
Charge-learnability transitions in monitored symmetric quantum circuits reveal how local measurement records acquire sufficient information to infer a conserved charge. Here we extend charge learnability to probabilistic weak measurements, for which the measurement probability and measurement strength are independently tunable. We find that the learnability phase boundary is organized by the informational power of local measurement. We further introduce cross entropy as a label-sensitive diagnostic that distinguishes unbiased, biased, and antibiased decoder variants. Finally, the exact record--label mutual information provides a decoder-independent benchmark for the information fundamentally available for charge inference. Our results establish informational power of local measurement as a unifying principle for charge learnability under general monitoring protocols.
