The role of noise in PIC and Vlasov simulations of the Buneman instability

TL;DR

This paper investigates how inherent noise in PIC simulations affects the growth rates of the Buneman instability, revealing discrepancies with Vlasov simulations and theoretical predictions, especially at low drift velocities.

Contribution

It demonstrates that PIC noise causes particle trapping and growth rate deviations, and evaluates the effectiveness of quiet-start methods in reducing these effects.

Findings

PIC simulations show higher growth rates than linear theory predicts.

Noise-induced particle trapping alters the electron velocity distribution.

Quiet-start methods improve accuracy only if initial perturbations are applied.

Abstract

The effects of noise in particle-in-cell (PIC) and Vlasov simulations of the Buneman instability in unmagnetized plasmas are studied. It is found that, in the regime of low drift velocity, the linear stage of the instability in PIC simulations differs significantly from the theoretical predictions, whereas in the Vlasov simulations it does not. A series of highly resolved PIC simulations with increasingly large numbers of macroparticles per cell is performed using a number of different PIC codes. All the simulations predict highly similar growth rates that are several times larger than those calculated from the linear theory. As a result, we find that the true convergence of the PIC simulations in the linear regime is elusive to achieve in practice and can easily be misidentified. The discrepancy between the theoretical and observed growth rates is attributed to the initial noise inherently present in PIC simulations, but not in Vlasov simulations, that causes particle trapping even though the fraction of trapped particles is low. We show analytically that even weak distortions of the electron velocity distribution function (such as flattening due to particle trapping) result in significant modifications of the growth rates. It is also found that the common quiet-start method for PIC simulations leads to more accurate growth rates but only if the maximum growth rate mode is perturbed initially. We demonstrate that the quiet-start method does not completely remedy the noise problem because the simulations generally exhibit inconsistencies with the linear theory.