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Title: Physics-based adaptivity of a spectral method for the Vlasov–Poisson equations based on the asymmetrically-weighted Hermite expansion in velocity space

Abstract

We propose a spectral method for the 1D-1V Vlasov–Poisson system where the discretization in velocity space is based on asymmetrically-weighted Hermite functions, dynamically adapted via a scaling α and shifting u of the velocity variable. Specifically, at each time instant an adaptivity criterion selects new values of α and u based on the numerical solution of the discrete Vlasov–Poisson system obtained at that time step. Once the new values of the Hermite parameters α and u are fixed, the Hermite expansion is updated and the discrete system is further evolved for the next time step. The procedure is applied iteratively over the desired temporal interval. The key aspects of the adaptive algorithm are: the map between approximation spaces associated with different values of the Hermite parameters that preserves total mass, momentum and energy; and the adaptivity criterion to update α and u based on physics considerations relating the Hermite parameters to the average velocity and temperature of each plasma species. For the discretization of the spatial coordinate, we rely on Fourier functions and use the implicit midpoint rule for time stepping. The resulting numerical method possesses intrinsically the property of fluid-kinetic coupling, where the low-order terms of the expansion aremore » akin to the fluid moments of a macroscopic description of the plasma, while kinetic physics is retained by adding more spectral terms. Moreover, the scheme features conservation of total mass, momentum and energy associated in the discrete, for periodic boundary conditions. A set of numerical experiments confirms that the adaptive method outperforms the non-adaptive one in terms of accuracy and stability of the numerical solution.« less

Authors:
 [1]; ORCiD logo [2];  [3]
  1. Eindhoven University of Technology (Netherlands)
  2. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
  3. KTH Royal Institute of Technology, Stockholm (Sweden)
Publication Date:
Research Org.:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1983856
Report Number(s):
LA-UR-22-28459
Journal ID: ISSN 0021-9991; TRN: US2402999
Grant/Contract Number:  
89233218CNA000001
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Computational Physics
Additional Journal Information:
Journal Volume: 488; Journal ID: ISSN 0021-9991
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; Vlasov–Poisson equations; spectral method; AW Hermite discretization; adaptive coefficients

Citation Formats

Pagliantini, Cecilia, Delzanno, Gian Luca, and Markidis, Stefano. Physics-based adaptivity of a spectral method for the Vlasov–Poisson equations based on the asymmetrically-weighted Hermite expansion in velocity space. United States: N. p., 2023. Web. doi:10.1016/j.jcp.2023.112252.
Pagliantini, Cecilia, Delzanno, Gian Luca, & Markidis, Stefano. Physics-based adaptivity of a spectral method for the Vlasov–Poisson equations based on the asymmetrically-weighted Hermite expansion in velocity space. United States. https://doi.org/10.1016/j.jcp.2023.112252
Pagliantini, Cecilia, Delzanno, Gian Luca, and Markidis, Stefano. Tue . "Physics-based adaptivity of a spectral method for the Vlasov–Poisson equations based on the asymmetrically-weighted Hermite expansion in velocity space". United States. https://doi.org/10.1016/j.jcp.2023.112252. https://www.osti.gov/servlets/purl/1983856.
@article{osti_1983856,
title = {Physics-based adaptivity of a spectral method for the Vlasov–Poisson equations based on the asymmetrically-weighted Hermite expansion in velocity space},
author = {Pagliantini, Cecilia and Delzanno, Gian Luca and Markidis, Stefano},
abstractNote = {We propose a spectral method for the 1D-1V Vlasov–Poisson system where the discretization in velocity space is based on asymmetrically-weighted Hermite functions, dynamically adapted via a scaling α and shifting u of the velocity variable. Specifically, at each time instant an adaptivity criterion selects new values of α and u based on the numerical solution of the discrete Vlasov–Poisson system obtained at that time step. Once the new values of the Hermite parameters α and u are fixed, the Hermite expansion is updated and the discrete system is further evolved for the next time step. The procedure is applied iteratively over the desired temporal interval. The key aspects of the adaptive algorithm are: the map between approximation spaces associated with different values of the Hermite parameters that preserves total mass, momentum and energy; and the adaptivity criterion to update α and u based on physics considerations relating the Hermite parameters to the average velocity and temperature of each plasma species. For the discretization of the spatial coordinate, we rely on Fourier functions and use the implicit midpoint rule for time stepping. The resulting numerical method possesses intrinsically the property of fluid-kinetic coupling, where the low-order terms of the expansion are akin to the fluid moments of a macroscopic description of the plasma, while kinetic physics is retained by adding more spectral terms. Moreover, the scheme features conservation of total mass, momentum and energy associated in the discrete, for periodic boundary conditions. A set of numerical experiments confirms that the adaptive method outperforms the non-adaptive one in terms of accuracy and stability of the numerical solution.},
doi = {10.1016/j.jcp.2023.112252},
journal = {Journal of Computational Physics},
number = ,
volume = 488,
place = {United States},
year = {Tue Jun 06 00:00:00 EDT 2023},
month = {Tue Jun 06 00:00:00 EDT 2023}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Figures / Tables:

Figure 1 Figure 1: Relative error between the analytic distribution function given by Eq. (10) (u0 variable and α0 = 1) and the distribution function given by expansion (6) with u = 0, α = 1 and 30 Hermite modes as a function of u0 (left); analytic and reconstructed distribution functions formore » u0 = 2.4 (right).« less

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