To simulate plasma phenomena, large-scale computational resources have been employed in developing high-precision and high-resolution plasma simulations. One of the main obstacles in plasma
simulations is the requirement of computational resources that scale polynomially with the number of spatial grids, which poses a significant challenge for large-scale modeling. To address this issue,
this study presents a quantum algorithm for simulating the nonlinear electromagnetic fluid dynamics that govern space plasmas. We map it, by applying Koopman-von Neumann linearization, to the Schrodinger equation and evolve the system using Hamiltonian simulation via quantum singular value transformation. Our algorithm scales O(sNx polylog (Nx) T ) in time complexity with s, Nx, and T being the spatial dimension, the number of spatial grid points per dimension, and the evolution time, respectively. Comparing the scaling O(sNx^s (T^(5/4)+T Nx)) for the classical method with the finite volume scheme, this algorithm achieves polynomial speedup in Nx. The space complexity of this algorithm is exponentially reduced from O(s Nx^s) to O(s polylog(Nx)). Numerical experiments validate that accurate solutions are attainable with smaller m than theoretically anticipated and with practical values of m and R, underscoring the feasibility of the approach. As a practical demonstration, the method accurately reproduces the Kelvin-Helmholtz instability, underscoring its capability to tackle more intricate nonlinear dynamics. These results suggest that quantum computing can offer a viable pathway to overcome the computational barriers of multiscale plasma modeling.