Bayesian Experimental Design – Studies for Fusion Diagnostics
نویسنده
چکیده
The design of fusion diagnostics is essential for the physics program of future fusion devices. The goal is to maximize the information gain of a future experiment with respect to various constraints. A measure of information gain is the mutual information between the posterior and the prior distribution. The Kullback-Leibler distance is used as a utility function to calculate the expected information gain marginalizing over data and parameter space. The expected utility function is maximized with respect to the design parameters of the experiment. The method will be applied to the design of a Thomson scattering experiment.
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