# An adjoint method for neoclassical stellarator optimization

## TL;DR

This paper introduces an adjoint method that significantly reduces the computational cost of gradient calculations in neoclassical stellarator optimization, enabling more efficient magnetic geometry design.

## Contribution

The paper presents a novel adjoint approach for computing derivatives of neoclassical fluxes, drastically decreasing the cost of gradient evaluations in stellarator optimization.

## Key findings

- Up to 200-fold reduction in gradient computation cost.
- Successful optimization of magnetic field strength for minimal bootstrap current.
- Accelerated solution of the ambipolar electric field using adjoint-derived derivatives.

## Abstract

Stellarators are a promising route to steady-state fusion power. However, to achieve the required confinement, the magnetic geometry must be highly optimized. This optimization requires navigating high-dimensional spaces, often necessitating the use of gradient-based methods. The gradient of the neoclassical fluxes is expensive to compute with classical methods, requiring $O(N)$ flux computations, where $N$ is the number of parameters. To reduce the cost of the gradient computation, we present an adjoint method for computing the derivatives of moments of the neoclassical distribution function for stellarator optimization. The linear adjoint method allows derivatives of quantities which depend on solutions of a linear system, such as moments of the distribution function, to be computed with respect to many parameters from the solution of only two linear systems. This reduces the cost of computing the gradient to the point that the finite-collisionality neoclassical fluxes can be used within an optimization loop. With the neoclassical adjoint method, we compute solutions of the drift kinetic equation and an adjoint drift kinetic equation to obtain derivatives of neoclassical quantities with respect to geometric parameters. When the number of parameters in the derivative is large ($\mathcal{O}(10^2)$), this adjoint method provides up to a factor of 200 reduction in cost. We demonstrate adjoint-based optimization of the field strength to obtain minimal bootstrap current on a surface. With adjoint-based derivatives, we also compute the local sensitivity to magnetic perturbations on a flux surface and identify regions where tight tolerances on error fields are required for control of the bootstrap current or radial transport. Furthermore, the solve for the ambipolar electric field is accelerated using a Newton method with derivatives obtained from the adjoint method.