Bayesian estimation for collisional thermometry
- URL: http://arxiv.org/abs/2106.12072v2
- Date: Mon, 15 Nov 2021 11:18:49 GMT
- Title: Bayesian estimation for collisional thermometry
- Authors: Gabriel O. Alves, Gabriel T. Landi
- Abstract summary: Quantum thermometry exploits the high level of control in coherent devices to offer enhanced precision for temperature estimation.
We put forth a complete framework for analyzing collisional thermometry using Bayesian inference.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Quantum thermometry exploits the high level of control in coherent devices to
offer enhanced precision for temperature estimation. This highlights the need
for constructing concrete estimation strategies. Of particular importance is
collisional thermometry, where a series of ancillas are sent sequentially to
probe the system's temperature. In this paper we put forth a complete framework
for analyzing collisional thermometry using Bayesian inference. The approach is
easily implementable and experimentally friendly. Moreover, it is guaranteed to
always saturate the Cramer-Rao bound in the long-time limit. Subtleties
concerning the prior information about the system's temperature are also
discussed, and analyzed in terms of a modified Cramer-Rao bound associated to
Van Trees and Sch\"utzenberger.
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