Maximum likelihood bolometric tomography for DTT diagnostic design

Abstract

On both the Joint European Torus (JET) and the ASDEX-Upgrade (AUG) tokamaks, an Expectation Maximization algorithm has been adapted to implement a Maximum Likelihood (ML) approach to derive tomograms from bolometers data. The main feature of such an approach is the ability to estimate the variance associated with the reconstructed tomograms and hence the uncertainties in the derived quantities. It has therefore been selected to support the design of the bolometric diagnostics for the Divertor Tokamak Test Facility (DTT). A reliable reconstruction of the emissivity profile is indeed relevant for the scientific exploitation of the device. As any tomographic inversion method is an ill-conditioned problem, two milestones should be achieved: ensuring the reconstruction of specific features and minimizing the risk of producing artefacts. The design strategy for the bolometric diagnostic on DTT involves testing various possible layouts to ensure that they meet the above requirements and are compatible with the engineering and machine constraints. This contribution focuses on showing how the conceptual bolometric layout can handle different phantoms mimicking typical emissivities observed on JET and AUG. A methodology has been developed to further optimize the layout within the constraints of the machine design. For the initial phase of DTT, a reduced layout is proposed, utilizing half of the conceptual lines of sight. The ability to reconstruct specific emissivity features while minimizing the risk of producing artefacts has been tested. The current ML implementation uses an anisotropic diffusion technique and is already significantly faster than the JET implementation for each reconstruction.