Speaker
Description
The principle of Bayesian inference is used in many di?erent ?elds of science, e.g. medicine
and computer science. The foundation of Bayesian inference lies in Bayes' theorem, which o?ers
a powerful alternative method for data analysis. Nevertheless, Bayesian inference is still rather
unpopular in ?elds like nuclear structure physics, where very sensitive detector systems are needed.
In
-spectroscopy, one of the essential experimental tools of nuclear structure physics, the state-of-
the-art detector systems are highly segmented High-Purity Germanium detectors like the Advanced
GAmma Tracking Array AGATA. Due to AGATA's Germanium shell without any Compton-
shielding,
-ray tracking algorithms are needed. The mathematical problem these
-ray tracking
algorithms are based on, forms a perfect example case for the bene?ts of Bayesian inference over
standard statistical inference methods.
Using basic terms of probability theory, a short introduction into Bayesian inference is given and essential principles are presented. In addition, a how-to approach of Bayesian inference to the principle of -ray tracking is shown in the form of the Fuzzy Bayes Tracking algorithm. Possible di?culties, as well as bene?ts of Bayesian inference are elaborated in detail.
