3 papers
physics.plasm-ph2026
Bayesian optimization of stellarator alpha-particle confinement using data-informed parameter spaces and dimensionality reduction
Matt Landreman, Michael Czekanski, Andrew Giuliani +2
Modern stellarators are typically designed by optimizing the shape of the plasma boundary surface, with the parameters taken to be Fourier amplitudes. Many promising optimization a…
physics.plasm-ph2026
Deflation Techniques for Stellarator Equilibrium and Optimization
Dario Panici, Byoungchan Jang, Rory Conlin +3
Stellarator optimization is a multi-objective, non-convex problem characterized by a complex objective landscape containing many local minima. The solution resulting from a single…
physics.plasm-ph2025
Exponential Spectral Scaling: Robust and Efficient Stellarator Boundary Optimization via Mode-Dependent Scaling
Byoungchan Jang, Rory Conlin, Matt Landreman
Stellarator boundary optimization faces a fundamental numerical challenge: the extreme disparity between low- and high-mode amplitudes creates an optimization landscape in which di…