From the 1 of 16 linked papers with an AI index.
9 papers · 1 filter
Preserving Heisenberg-Limited Metrological Information during Storage via Correlated-Noise Correction
Hang Xu, Xue-Ke Song, Jingzheng Huang +2
Quantum error correction has become an indispensable tool for restoring Heisenberg-limited precision in noisy quantum metrology. Existing protocols, however, almost exclusively foc…
Converting Quantum Sensing Noise into Erasures
Xingyu Liu, Zhaotong Cui, Binke Xia +4
The paper introduces a passive scheme that converts certain quantum sensing noise into erasures, enabling robust sensing without detailed noise knowledge, and demonstrates the meth…
Scaling Enhancement in Distributed Quantum Sensing via Bidirectional Causal Routing
Binke Xia, Zhaotong Cui, Jingzheng Huang +2
Sensing networks underpin applications ranging from fundamental physics to real-world engineering. Distributed quantum sensing (DQS) can improve measurement performance, but existi…
Learning to Restore Heisenberg Limit in Noisy Quantum Sensing via Quantum Digital Twin
Hang Xu, Tailong Xiao, Jingzheng Huang +2
Quantum sensors leverage nonclassical resources to achieve sensing precision at the Heisenberg limit, surpassing the standard quantum limit attainable through classical strategies.…
Scaling Enhancement in Quantum Metrology via Indefinite-Time-Direction Encoding
Binke Xia, Jingzheng Huang, Yuxiang Yang +1
The precision limit in quantum metrology, quantified by the root-mean-square error of parameter estimation, is conventionally expected to improve at most linearly with the total in…
Towards Heisenberg limit without critical slowing down via quantum reinforcement learning
Hang Xu, Tailong Xiao, Jingzheng Huang +3
Critical ground states of quantum many-body systems have emerged as vital resources for quantum-enhanced sensing. Traditional methods to prepare these states often rely on adiabati…