Seminar: Bayesian inference for quantum sensors and open quantum systems

Last updated December 4, 2020 by Dermot Green

Wednesday 25 November 4pm
Location: MS Teams
Speaker: Dr Ricardo Puebla, CTAMOP, Queen’s University Belfast


Inference techniques built on the Bayes’ theorem provide powerful tools for hypothesis testing and/or parameter estimation. In spite of other inference techniques, Bayesian inference deals with a probabilistic description of the key quantities to be determined. This is done by updating any prior information or knowledge according to the likelihood between the given set of observations and the proposed model to explain them. Such Bayesian techniques are routinely employed in many branches of science, and have been proven very useful in situations with a reduced number of observations and/or complex underlying models.

In this seminar I will review the main ingredients of Bayesian analysis and how to apply these techniques to quantum mechanical systems. In particular, I will discuss two illustrative and practical examples to showcase the suitability of Bayesian inference in quantum systems, namely, (i) an atomic-size quantum sensor aiming at detecting electromagnetic fields, and (ii) the inference of the environment properties of an open quantum system.


We are a Research Cluster of the School of Mathematics and Physics at Queen’s University Belfast in Northern Ireland. Our research interests are focused primarily on computational and theoretical physics.

Old Physics Building

The Old Physics Building,
where CTAMOP is situated.