Fully‐Optimized Quantum Metrology: Framework, Tools, and Applications
Year: 2024
Type: article
Abstract: This tutorial introduces a systematic approach for addressing the key question of quantum metrology: For a generic task of sensing an unknown parameter, what is the ultimate precision given a constrained set of admissible strategies. The approach outputs the maximal attainable precision (in terms of the maximum of quantum Fisher information) as a semidefinite program and optimal strategies as feasible solutions thereof. Remarkably, the approach can identify the optimal precision for different sets of strategies, including parallel, sequential, quantum SWITCH‐enhanced, causally superposed, and generic indefinite‐causal‐order strategies. The tutorial consists of a pedagogic introduction to the background and mathematical tools of optimal quantum metrology, a detailed derivation of the main approach, and various concrete examples. As shown in the tutorial, applications of the approach include, but are not limited to, strict hierarchy of strategies in noisy quantum metrology, memory effect in non‐Markovian metrology, and designing optimal strategies. Compared with traditional approaches, the approach here yields the exact value of the optimal precision, offering more accurate criteria for experiments and practical applications. It also allows for the comparison between conventional strategies and the recently discovered causally‐indefinite strategies, serving as a powerful tool for exploring this new area of quantum metrology.
Source: Advanced Quantum Technologies
Authors: Qiushi Liu, Zihao Hu, Haidong Yuan, Yuxiang Yang
Institutions: University of Hong Kong, Chinese University of Hong Kong
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,220
Funders: National Natural Science Foundation of China, University Grants Committee, Ministry of Science and Technology of the People's Republic of China, Guangdong Science and Technology Department, National Outstanding Youth Science Fund Project of National Natural Science Foundation of China, University Research Committee, University of Hong Kong, Young Scientists Fund, Basic and Applied Basic Research Foundation of Guangdong Province
OpenAlex ID: W4402424703