Optimization of Nonlinear Turbulence in Stellarators

TL;DR

This paper introduces a new optimization approach for stellarator equilibria that reduces turbulent transport by integrating fast nonlinear gyrokinetic simulations with equilibrium and optimization codes, employing SPSA for efficient gradient estimation.

Contribution

It presents a novel optimization framework coupling gyrokinetic simulations with stellarator design to directly minimize turbulent heat fluxes, incorporating noise-tolerant gradient estimation techniques.

Findings

Optimized stellarator configurations with reduced turbulent heat flux.

Demonstrated effectiveness of SPSA in noisy simulation environments.

Full transport simulations confirm improved macroscopic profiles.

Abstract

We present new stellarator equilibria that have been optimized for reduced turbulent transport using nonlinear gyrokinetic simulations within the optimization loop. The optimization routine involves coupling the pseudo-spectral GPU-native gyrokinetic code GX with the stellarator equilibrium and optimization code DESC. Since using GX allows for fast nonlinear simulations, we directly optimize for reduced nonlinear heat fluxes. To handle the noisy heat flux traces returned by these simulations, we employ the simultaneous perturbation stochastic approximation (SPSA) method that only uses two objective function evaluations for a simple estimate of the gradient. We show several examples that optimize for both reduced heat fluxes and good quasisymmetry as a proxy for low neoclassical transport. Finally, we run full transport simulations using the T3D stellarator transport code to evaluate the changes in the macroscopic profiles.