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This research advances fundamental quantum computing theory by establishing the informational power of local measurements as a unifying principle for inferring conserved charges in monitored circuits. The study extends these learnability transitions to probabilistic weak measurements and introduces cross-entropy diagnostics to benchmark information availability across various decoder variants. These findings provide critical theoretical benchmarks for understanding how measurement records extract fundamental properties from quantum systems under general monitoring protocols.
Unifying Charge-Learnability Transitions in U(1)-Symmetric Quantum Circuits through Informational Power of Local Measurement
arXiv:2607.17886v1 Announce Type: new Abstract: 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.
Abstract: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.
10 pages, 7 figures. Comments are welcome
arXiv:2607.17886 [quant-ph]
(or arXiv:2607.17886v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2607.17886 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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