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

Florian Wechsung, Andrew Giuliani, Matt Landreman, Antoine Cerfon, Georg Stadler

Research output: Contribution to journalArticlepeer-review


It was recently shown in Wechsung et al (2022 Proc. Natl Acad. Sci. USA 119 e2202084119) that there exist electromagnetic coils that generate magnetic fields, which are excellent approximations to quasi-symmetric fields and have very good particle confinement properties. Using a Gaussian process-based model for coil perturbations, we investigate the impact of manufacturing errors on the performance of these coils. We show that even fairly small errors result in noticeable performance degradation. While stochastic optimization yields minor improvements, it is not possible to mitigate these errors significantly. As an alternative to stochastic optimization, we then formulate a new optimization problem for computing optimal adjustments of the coil positions and currents without changing the shapes of the coil. These a-posteriori adjustments are able to reduce the impact of coil errors by an order of magnitude, providing a new perspective for dealing with manufacturing tolerances in stellarator design.

Original languageEnglish (US)
Article number105021
JournalPlasma Physics and Controlled Fusion
Issue number10
StatePublished - Oct 2022


  • coil design
  • manufacturing errors
  • stellarator
  • stochastic optimization

ASJC Scopus subject areas

  • Nuclear Energy and Engineering
  • Condensed Matter Physics


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