Advanced Maxwell Solver Algorithms in Particle-in-Cell Simulations of Relativistic Magnetic Reconnection

Relativistic magnetic reconnection is a source of non-thermal particle acceleration in many high-energy astrophysical systems. Particle-in-cell (PIC) methods are commonly used for simulating reconnection from first principles. While much progress has been made in understanding the physics of reconnection, especially in 2D, the adoption of advanced algorithms and numerical techniques for efficiently modeling such systems has been limited. With the GPU-accelerated PIC code WarpX, we explore the accuracy and potential performance benefits of two advanced Maxwell solver algorithms: a non-standard finite difference scheme (CKC) and an ultrahigh-order pseudo-spectral method (PSATD). We find that for the relativistic reconnection problem, CKC and PSATD qualitatively and quantitatively match the standard Yee-grid finite-difference method. Both methods have a ~40% faster time to solution than Yee, largely because they admit longer time steps. These performance gains will make 3D simulations of reconnection more tractable, and complement other efforts to improve simulation efficiency, such as the use of mesh refinement.