Comparison of Preconditioning Strategies in Energy Conserving Implicit Particle in Cell Methods
DOI10.4208/cicp.OA-2017-0171zbMath1475.82026arXiv1806.04454OpenAlexW2963323579WikidataQ128538351 ScholiaQ128538351MaRDI QIDQ5160478
Lorenzo Siddi, Giovanni Lapenta, Emanuele Cazzola
Publication date: 29 October 2021
Published in: Communications in Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1806.04454
Statistical mechanics of polymers (82D60) Ionized gas flow in electromagnetic fields; plasmic flow (76X05) Finite volume methods for initial value and initial-boundary value problems involving PDEs (65M08) Finite volume methods applied to problems in statistical mechanics (82M12)
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Fluid preconditioning for Newton-Krylov-based, fully implicit, electrostatic particle-in-cell simulations
- Particle simulations of space weather
- An energy- and charge-conserving, implicit, electrostatic particle-in-cell algorithm
- The energy conserving particle-in-cell method
- Multi-scale simulations of plasma with iPIC3D
- Direct implicit large time-step particle simulation of plasmas
- An implicit method for electromagnetic plasma simulation in two dimensions
- Jacobian-free Newton-Krylov methods: a survey of approaches and applications.
- Exactly energy conserving semi-implicit particle in cell formulation
- A multi-dimensional, energy- and charge-conserving, nonlinearly implicit, electromagnetic Vlasov-Darwin particle-in-cell algorithm
- Development of a Consistent and Stable Fully Implicit Moment Method for Vlasov--Ampère Particle in Cell (PIC) System
- GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems
- Parallel Newton--Krylov--Schwarz Algorithms for the Transonic Full Potential Equation
This page was built for publication: Comparison of Preconditioning Strategies in Energy Conserving Implicit Particle in Cell Methods
