Nuclear Fusion
Ekin Öztürk¹ Rob Akers² Stanislas Pamela² The MAST Team² Pieter Peers³ Abhijeet Ghosh¹
¹Imperial College London, ²Culham Centre For Fusion Energy, ³College of William & Mary
Fig. 1: Overarching pipeline for the differentiable optimisation routine for estimating the plasma composition.
Abstract: In this work, we develop a differentiable rendering pipeline for visualising plasma emission within tokamaks, and estimating the gradients of the emission and estimating other physical quantities. Unlike prior work, we are able to leverage arbitrary representations of plasma quantities and easily incorporate them into a non-linear optimisation framework. The efficiency of our method enables not only estimation of a physically plausible image of plasma, but also recovery of the neutral Deuterium distribution from imaging and midplane measurements alone. We demonstrate our method with three different levels of complexity showing first that a poloidal neutrals density distribution can be recovered from imaging alone, second that the distributions of neutral Deuterium, electron density and electron temperature can be recovered jointly, and finally, that this can be done in the presence of realistic imaging systems that incorporate sensor cropping and quantisation.
Publication: Inverse rendering of fusion plasmas: Inferring plasma composition from imaging systems, Ekin Öztürk, Robert James Akers, Stanislas Pamela, The MAST Team, Pieter Peers, and Abhijeet Ghosh. In: Nuclear Fusion 65 026020, Jan 2025. ISSN: 1741-4326. DOI: 10.1088/1741-4326/ad9ab5
