$\texttt{Aether.jl}$ : A High-Performance 3D MHD and Multifluid Dust Code Written in a Dynamic Language with an Interactive Human-AI Development Framework
We present $\texttt{Aether}$, a new finite-volume code for compressible hydrodynamics and magnetohydrodynamics, written in Julia and primarily designed for GPU systems. The code solves the MHD equations with constrained transport in Cartesian, cylindrical, and spherical-polar coordinates, using standard high-order Godunov methods. An arbitrary number of dust fluids can be coupled to the gas through stiff mutual drag. It was developed from scratch with interactive Human-coding agent workflow; the paper documents the framework of this workflow alongside the numerical methods. Performance-critical kernel is written through $\texttt{KernelAbstractions}$, and supports runs on CPUs and GPUs from multiple vendors. $\texttt{Aether}$ can be ran either from an interactive notebook or batch scripts, keeping prototyping, production runs, and analysis in a single language. We verify the implementation through a series of hydrodynamic, MHD, and dust tests. Although written in a dynamic language, $\texttt{Aether}$ achieves comparable or even higher single-GPU throughput than C++ code on the same hardware. In weak scaling on Frontier, parallel efficiency stays above $93\%$S on 4096 GCDs. These results show that a dynamic language now supports production astrophysical MHD simulations on exascale systems. $\texttt{Aether}$ and its Jupyter notebook example suite are publicly available.