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Imposing quasineutrality on electrostatic plasmas via the Dirac theory of constraints

Published online by Cambridge University Press:  26 February 2026

Dimitrios Kaltsas*
Affiliation:
Department of Physics, University of Ioannina, Ioannina 451 10, Greece Department of Informatics, Democritus University of Thrace, Kavala 654 04, Greece
Joshua W. Burby
Affiliation:
Department of Physics and Institute for Fusion Studies, The University of Texas at Austin, Austin, TX 78712, USA
Philip J. Morrison
Affiliation:
Department of Physics and Institute for Fusion Studies, The University of Texas at Austin, Austin, TX 78712, USA
Emanuele Tassi
Affiliation:
CNRS, Observatoire de la Côte d’Azur, Laboratoire J. L. Lagrange, Boulevard de l’Observatoire, Université Côte d’Azur, CS 34229, 06304 Nice CEDEX 4, France
George Throumoulopoulos
Affiliation:
Department of Physics, University of Ioannina, Ioannina 451 10, Greece
*
Corresponding author: Dimitrios Kaltsas, d.kaltsas@uoi.gr

Abstract

We present a method for imposing quasineutrality and, more generally, charge density conservation in the Vlasov–Poisson (VP) and Vlasov–Ampère (VA) systems, which describe electrostatic plasma dynamics, by applying the Dirac theory of constraints. Leveraging the Hamiltonian field formulations of the VP and VA models, we construct generalised Dirac brackets using the Dirac algorithm. The resulting constrained systems enforce charge density conservation, and consequently quasineutrality, given that the initial charge density is zero, through new advection terms in the Vlasov equations involving generalised-force terms, while the electric field is eliminated from the constrained Vlasov dynamics. To verify charge density conservation we conduct one-dimensional numerical experiments using a semi-Lagrangian method, demonstrating that the enforcement of the quasineutrality constraint significantly modifies the dynamics. This approach enables us to identify the forces required to enforce quasineutrality, offering a systematic way to assess the validity of the quasineutral approximation across different kinetic scales.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press
Figure 0

Figure 1. Initial conditions of the distribution functions $f_e$ and $f_i$ in phase space. The electron distribution forms two separated beams since $V_e$ is large enough in (4.21), whereas the two ion beams are so close to each other that they effectively form a single beam with zero macroscopic velocity. This broad, centralised ion beam was found to favour numerical stability over longer simulation times.

Figure 1

Figure 2. Snapshots of the electron and ion distribution functions in phase space $(x,v)$ at different times. The left-hand column corresponds to the VP case and the right-hand column to the QN case. A distinct evolution of $f_e$ is observed between the two scenarios, especially during the nonlinear phase.

Figure 2

Figure 3. Left: Evolution of the average charge density modulus $\langle |\rho |\rangle$ in the standard VP scenario (solid red line) versus the Dirac-constrained QN scenario (dashed blue line). The QN charge density, although non-zero, remains consistently three orders of magnitude smaller than in the VP case, even in the vortex saturation stage (right).

Figure 3

Figure 4. Left: Evolution of $\langle |\partial _x J|\rangle$ in the standard VP scenario (solid red line) versus the Dirac-constrained QN scenario (dashed blue line). Although non-zero, this quantity remains consistently at least three orders of magnitude smaller than in the VP case, even in the vortex saturation stage (right).

Figure 4

Figure 5. Relative energy error (left) and relative particle error (right) in the VP simulation. The particle number and energy are not conserved with high precision due to the non-conservative nature of the simulation algorithm, interpolation errors and the applied filtering method.

Figure 5

Figure 6. Snapshots of the electron and positron distribution functions in phase space $(x,v)$ at different times. The left column corresponds to the VP case and the right column to the QN case. We observe distinct evolution for both $f_e$ and $f_i$.

Figure 6

Figure 7. Left: Evolution of the average charge density modulus $\langle |\rho |\rangle$ in the standard VP scenario (solid red line) versus the Dirac-constrained QN scenario (dashed blue line). We see that $\rho _{_{QN}}$ stays constant while $\rho _{_{VP}}$ shows significant change during the evolution. Right: The corresponding plots for the quantity $\langle |\partial _x J|\rangle$ showing that in the QN case the current incompressibility constraint is satisfied with acceptable accuracy.

Figure 7

Figure 8. Left: The evolution of the ratio (4.27) of the Dirac forces over the fluid forces for a simulation with steady ion distribution. In all four cases $L=25$, $L=50$, $L=100$ and $L=250$, this ratio increases with time and becomes progressively smaller for larger length scales. Right: The time-averaged ratio versus the length scale $L$.