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

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,...

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Bibliographic Details
Published in:arXiv.org 2021-12
Main Authors: Tavassoli, Arash, Chapurin, Oleksandr, Jimenez, Marilyn, Zadeh, Mina Papahn, Zinte, Trevor, Sengupta, Meghraj, Couëdel, Lénaïc, Spiteri, Raymond J, Shoucri, Magdi, Smolyakov, Andrei
Format: Article
Language:English
Subjects:
Distribution functions
Electron velocity distribution
Noise
Particle in cell technique
Plasmas (physics)
Simulation
Stability
Trapped particles
Trapping
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Summary: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.
ISSN:2331-8422
DOI:10.48550/arxiv.2112.12697