Data-Driven Generation of Compact Quasi-Isodynamic Stellarators
This paper presents a data-driven method that extends conditional boundary generation to four-field-period quasi-isodynamic stellarators in the low-aspect-ratio regime, successfully adapting to a compact high-fidelity dataset to produce converged candidates with favorable confinement properties that serve as effective seeds for further optimization.