Minisymposium Presentation

The simulation of turbulence in the boundary region of a tokamak is crucial for understanding and optimizing the performance of fusion reactors. However, these simulations pose significant computational challenges due to the complex plasma dynamics at the boundary. In this talk, we explore how low-rank linear algebra techniques can enhance the efficiency of boundary simulations, specifically by accelerating the computation of neutral particle dynamics. When modeled deterministically, this problem leads to the solution of integral equations, which typically result in dense linear systems upon discretization. We employ hierarchical matrix approximations to significantly reduce the computational cost of assembling and solving linear systems, leading to substantial savings in both time and memory. Our method is implemented and tested within the GBS framework, achieving over 90% reduction in computation time and memory and enabling simulations with unprecedented spatial resolution for neutral particles. The scalability of this approach represents a critical step towards simulating turbulence in larger fusion reactors, facilitating high-resolution studies of plasma-neutral interactions and enhancing the safety and operational efficiency of fusion devices.