bayes_multi_metrology_jesus_jacob_accepted_version.pdf (514.65 kB)
Bayesian multiparameter quantum metrology with limited data
journal contribution
posted on 2023-06-09, 20:38 authored by Jesus Rubio, Jacob DunninghamJacob DunninghamA longstanding problem in quantum metrology is how to extract as much information as possible in realistic scenarios with not only multiple unknown parameters, but also limited measurement data and some degree of prior information. Here we present a practical solution to this: We derive a Bayesian multi-parameter quantum bound, construct the optimal measurement when our bound can be saturated for a single shot, and consider experiments involving a repeated sequence of these measurements. Our method properly accounts for the number of measurements and the degree of prior information, and we illustrate our ideas with a qubit sensing network and a model for phase imaging, clarifying the nonasymptotic role of local and global schemes. Crucially, our technique is a powerful way of implementing quantum protocols in a wide range of practical scenarios that tools such as the Helstrom and Holevo Cramér-Rao bounds cannot normally access.
Funding
UK Quantum Technology Hub: NQIT-Networked Quantum Information Technologies; G1503; EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCIL; EP/M013243/1
History
Publication status
- Published
File Version
- Accepted version
Journal
Physical Review A: Atomic, Molecular and Optical PhysicsISSN
1050-2947Publisher
American Physical SocietyExternal DOI
Issue
3Volume
101Article number
a032114Department affiliated with
- Physics and Astronomy Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2020-02-17First Open Access (FOA) Date
2020-02-17First Compliant Deposit (FCD) Date
2020-02-17Usage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC