arXiv · 2108.05932
Fundamental limits in Bayesian thermometry and attainability via adaptive strategies
Abstract
We investigate the limits of thermometry using quantum probes at thermal equilibrium within the Bayesian approach. We consider the possibility of engineering interactions between the probes in order to enhance their sensitivity, as well as feedback during the measurement process, i.e., adaptive protocols. On the one hand, we obtain an ultimate bound on thermometry precision in the Bayesian setting, valid for arbitrary interactions and measurement schemes, which lower bounds the error with a quadratic (Heisenberg-like) scaling with the number of probes. We develop a simple adaptive strategy that can saturate this limit. On the other hand, we derive a no-go theorem for non-adaptive protocols that does not allow for better than linear (shot-noise-like) scaling even if one has unlimited control over the probes, namely access to arbitrary many-body interactions.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Mohammad Mehboudi, Mathias R. Jørgensen, Stella Seah, Jonatan B. Brask, Jan Kołodyński, Martí Perarnau-Llobet. 2021-08-12. Fundamental limits in Bayesian thermometry and attainability via adaptive strategies. https://doi.org/10.1103/physrevlett.128.130502
Cite the original work for its findings. Save a collection to share your selection of sources.