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It was recently shown in [Wechsung et. al., Proc. Natl. Acad. Sci. USA, 2022]that there exist electromagnetic coils that generate magnetic fields which areexcellent approximations to quasi-symmetric fields and have very good particleconfinement properties. Using a Gaussian process based model for coilperturbations, we investigate the impact of manufacturing errors on theperformance of these coils. We show that even fairly small errors result innoticeable performance degradation. While stochastic optimization yields minorimprovements, it is not able to mitigate these errors significantly. As analternative to stochastic optimization, we then formulate a new optimizationproblem for computing optimal adjustments of the coil positions and currentswithout changing the shapes of the coil. These a-posteriori adjustments areable to reduce the impact of coil errors by an order of magnitude, providing anew perspective for dealing with manufacturing tolerances in stellaratordesign.

Stochastic and a posteriori optimization to mitigate coil manufacturing errors in stellarator design