English

Global Stellarator Coil Optimization with Quadratic Constraints and Objectives

Plasma Physics 2025-06-11 v6

Abstract

Most present stellarator designs are produced by costly two-stage optimization: the first for an optimized equilibrium, and the second for a coil design reproducing its magnetic configuration. Few proxies for coil complexity and forces exist at the equilibrium stage. Rapid initial state finding for both stages is a topic of active research. Most present convex coil optimization codes use the least square winding surface method by Merkel (NESCOIL), with recent improvement in conditioning, regularization , sparsity and physics objectives. While elegant, the method is limited to modeling the norms of linear functions in coil current. We present QUADCOIL, a fast, global coil optimization method that targets combinations of linear and quadratic functions of the current. It can directly constrain and/or minimize a wide range of physics objectives unavailable in NESCOIL and REGCOIL, including the Lorentz force, magnetic energy, curvature, field-current alignment, and the maximum density of a dipole array. QUADCOIL requires no initial guess and runs nearly 102×10^2\times faster than filament optimization. Integrating it in the equilibrium optimization stage can potentially exclude equilibria with difficult-to-design coils, without significantly increasing the computation time per iteration. QUADCOIL finds the exact, global minimum in a large parameter space when possible, and otherwise finds a well-performing approximate global minimum. It supports most regularization techniques developed for NESCOIL and REGCOIL. We demonstrate QUADCOIL's effectiveness in coil topology control, minimizing non-convex penalties, and predicting filament coil complexity with three numerical examples.

Keywords

Cite

@article{arxiv.2408.08267,
  title  = {Global Stellarator Coil Optimization with Quadratic Constraints and Objectives},
  author = {Lanke Fu and Elizabeth J. Paul and Alan A. Kaptanoglu and Amitava Bhattacharjee},
  journal= {arXiv preprint arXiv:2408.08267},
  year   = {2025}
}
R2 v1 2026-06-28T18:13:58.792Z