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Data from: Plasma refilling of the lunar wake: Plasma-vacuum interactions, electrostatic shocks, and electromagnetic instabilities

An, Xin1; Angelopoulos, Vassilis1; Liu, Terry Z.1; Artemyev, Anton1; Poppe, Andrew2; Ma, Donglai1

Published Jul 07, 2025 on Dryad. https://doi.org/10.5061/dryad.8w9ghx3zv

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Jul 07, 2025 version files 160.46 GB

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Abstract

A plasma void forms downstream of the Moon when the solar wind impacts the lunar surface. This void gradually refills as the solar wind passes by, forming the lunar wake. We investigate this refilling process using a fully kinetic particle-in-cell (PIC) simulation. The early stage of refilling follows plasma-vacuum interaction theory, characterized by exponential decay of plasma density into the wake, along with ion acceleration and cooling in the expansion direction. Our PIC simulation confirms these theoretical predictions. In the next stage of the refilling process, the counter-streaming supersonic ion beams collide, generating Debye-scale electrostatic shocks at the wake's center. These shocks decelerate and thermalize the ion beams while heating electrons into flat-top velocity distributions along magnetic field lines. Additionally, fast magnetosonic waves undergo convective growth via anomalous cyclotron resonance as they co-propagate with temperature-anisotropic ion beams toward the wake's center. Electromagnetic ion cyclotron waves may also be excited through normal cyclotron resonance, counter-propagating with these anisotropic ion beams. Our findings provide new insights into the kinetic aspects of lunar wake refilling and may enhance interpretation of spacecraft observations. The accompanying dataset comprises PIC simulation results organized into raw data files and analysis scripts. Field data on spatial grids are archived as .gda files, while particle data on phase space grids are stored as .bin files in the "data" directory. Jupyter notebooks in the "scripts" directory provide analysis pipelines for reproducing all figures in our study. Each notebook demonstrates complete workflows for data processing and visualization, with detailed notebook-to-data correspondence documented in the README file to ensure full reproducibility.