An Adaptive Fourier Spectral Method for the Vlasov-Poisson system

Numerical simulation of the Vlasov-Poisson system faces fundamental challenges due to phase-space filamentation.

Standard spectral methods rely on artificial filtering to suppress errors, which inadvertently degrades physical structures and accuracy over time.

This paper proposes a dynamically adaptive Fourier spectral method combined with high-order time splitting to overcome these limitations.

To prevent filamentation-induced aliasing, we dynamically expand the wavenumber domain via adaptive zero-padding whenever spectral tail monitoring detects emerging fine-scale structures.

Acting as an exact trigonometric interpolation, it inherently avoids the artificial smoothing of traditional filters, preserving mass and effectively maintaining the $L^2$-norm within the dynamically resolved scales.

Numerical experiments on Landau damping and various instability problems validate the robustness of our scheme.