Observing Particle Energization above the Nyquist Frequency: An Application of the Field-Particle Correlation Technique

TL;DR

This study demonstrates that the field-particle correlation technique can detect particle energization signatures, like Landau damping, even in undersampled spacecraft data, supported by gyrokinetic simulations.

Contribution

The paper validates that field-particle correlations can recover velocity-space signatures from low-resolution data, extending their applicability to real spacecraft measurements.

Findings

Signatures of electron Landau damping are detectable in high-resolution simulations.

Reduced data resolution can still preserve key energization signatures.

A practical rule of thumb is proposed for applying the technique to spacecraft data.

Abstract

The field-particle correlation technique utilizes single-point measurements to uncover signatures of various particle energization mechanisms in turbulent space plasmas. The signature of Landau damping by electrons has been found in both simulations and observations from Earth's magnetosheath using this technique, but instrumental limitations of spacecraft sampling rates present a challenge to discovering the full extent of the presence of Landau damping in the solar wind. Theory predicts that field-particle correlations can recover velocity-space energization signatures even from data that is undersampled with respect to the characteristic frequencies at which the wave damping occurs. To test this hypothesis, we perform a high-resoluation gyrokinetic simulation of space plasma turbulence, confirm that it contains signatures of electron Landau damping, and then systematically reduce the time resolution of the data to identify the point at which the signatures become impossible to recover. We find results in support of our theoretical prediction and look for a rule of thumb that can be compared with the measurement capabilities of spacecraft missions to inform the process of applying field-particle correlations to low time resolution data.