An implicit particle code with exact energy and charge conservation for electromagnetic studies of dense plasmas

Angus, J. R.; Farmer, W. A.; Friedman, A.; Ghosh, Debojyoti; Grote, D.P.; Larson, David J.; Link, A.

doi:10.1016/j.jcp.2023.112383

Cited by 2 publications

(2 citation statements)

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“…By removing these nonlinearities, we obtain a simpler, linear system, but we also introduce (small) energy errors. It is in principle possible to retain exact energy conservation by discarding our approximation and iterating on the field-particle equations up to exact nonlinear convergence; alternatively, a fixed amount of iterations could also help in improving energy conservation without reaching exact accuracy (see, e.g., Angus et al 2023). 2.…”

Section: Discussion and Summarymentioning

confidence: 99%

“…4 Implicit PIC codes essentially involve an implicit discretization of Maxwell's equations, together with a particle push that may or may not be nonlinearly coupled to the field-solver step. If this nonlinear coupling is retained, the resulting approach is usually labeled "fully implicit" Bacchini et al 2019;Chen et al 2020;Angus et al 2023) and may involve the solution of a very large, nonlinear system of equations, whose dimension can be on the order of the total number of particles in a simulation. Such extremely large systems are hard to handle in practice, because convergence of iterative solution methods is not guaranteed; even with advanced preconditioning, it is not straightforward to obtain acceptable scaling behavior on supercomputing infrastructures.…”

Section: Introduction and Review Of The Particle-in-cell Panoramamentioning

confidence: 99%

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RelSIM: A Relativistic Semi-implicit Method for Particle-in-cell Simulations

Bacchini

2023

ApJS

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We present a novel Relativistic Semi-Implicit Method (RelSIM) for particle-in-cell (PIC) simulations of astrophysical plasmas, implemented in a code framework ready for production runs. While explicit PIC methods have gained widespread recognition in the astrophysical community as a reliable tool to simulate plasma phenomena, implicit methods have been seldom explored. This is partly due to the lack of a reliable relativistic implicit PIC formulation that is applicable to state-of-the-art simulations. We propose the RelSIM to fill this gap: our new method is relatively simple, being free of nonlinear iterations and only requiring a global linear solve of the field equations. With a set of one- and two-dimensional tests, we demonstrate that the RelSIM produces more accurate results with much smaller numerical errors in the total energy than standard explicit PIC, in particular when characteristic plasma scales (skin depth and plasma frequency) are heavily underresolved on the numerical grid. By construction, the RelSIM also performs much better than the relativistic implicit-moment method, originally proposed for semi-implicit PIC simulations in the relativistic regime. Our results are promising to conduct large-scale (in terms of duration and domain size) PIC simulations of astrophysical plasmas, potentially reaching physical regimes inaccessible by standard explicit PIC codes.

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Section: Discussion and Summarymentioning

confidence: 99%

Section: Introduction and Review Of The Particle-in-cell Panoramamentioning

confidence: 99%