2011/03/27 by B. M. Escher, R. L. de Matos Filho, L. Davidovich · 5 citations
Computer Science · Mathematics · Physics and Astronomy · #Algorithm #Artificial intelligence #Computer science #Dephasing #Interferometry #Limit (mathematics) #Lossy compression #Mathematics #Metrology #Open quantum system #Physics #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Mechanics and Applications #Quantum limit #Quantum mechanics #Quantum metrology #Quantum sensor #Quantum technology #Statistical physics #Upper and lower bounds #quant-ph
paper · pdf · doi:10.1038/nphys1958
published as Nature Physics 7, 406-411 (2011) · Published in Nature Physics. This is the revised submitted version. The supplementary material can be found at http://www.nature.com/nphys/journal/v7/n5/extref/nphys1958-s1.pdf
openalex publication_date 2011/03/27 · arxiv created 2012/01/09 · arxiv updated 2012/01/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The estimation of parameters characterizing dynamical processes is central to science and technology. The estimation error changes with the number N of resources employed in the experiment (which could quantify, for instance, the number of probes or the probing energy). Typically, it scales as 1/N^(1/2). Quantum strategies may improve the precision, for noiseless processes, by an extra factor 1/N^(1/2). For noisy processes, it is not known in general if and when this improvement can be achieved. Here we propose a general framework for obtaining attainable and useful lower bounds for the ultimate limit of precision in noisy systems. We apply this bound to lossy optical interferometry and atomic spectroscopy in the presence of dephasing, showing that it captures the main features of the transition from the 1/N to the 1/N^(1/2) behaviour as N increases, independently of the initial state of the probes, and even with use of adaptive feedback.