We investigate the limits of thermometry using quantum probes at thermal equilibrium within the Bayesian (global) approach. Firstly, an ultimate bound on thermometry precision in the Bayesian setting is obtained, which lower bounds the error with a quadratic (Heisenberg) scaling. The bound is very versatile, and both adaptive and non-adaptive protocols should respect it. Secondly, a no-go theorem is obtained for non-adaptive protocols that does not allow for better than shot-noise-scaling in thermometry even if one has unlimited control in designing the probe, namely access to many-body interactions. Finally, a simple adaptive scheme is proposed that beats the non-adaptive no-go, and can reach the Heisenberg scaling. This is illustrated through an example.

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Seminar, July 21, 2021, 15:00. Online (Zoom)

Hosted by Prof Antonio Acin