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We propose a novel projection-based particle method for solving the McKean-Vlasov stochastic differential equations. Our approach is based on a projection-type estimation of the marginal density of the solution in each time step. The…

Numerical Analysis · Mathematics 2018-08-07 Denis Belomestny , John Schoenmakers

The combination of reduced basis and collocation methods enables efficient and accurate evaluation of the solutions to parameterized PDEs. In this paper, we study the stochastic collocation methods that can be combined with reduced basis…

Numerical Analysis · Mathematics 2022-04-19 Heyrim Cho , Howard C. Elman

Flow in variably saturated porous media is typically modelled by the Richards equation, a nonlinear elliptic-parabolic equation which is notoriously challenging to solve numerically. In this paper, we propose a robust and fast iterative…

Numerical Analysis · Mathematics 2023-01-06 Jakob S. Stokke , Koondanibha Mitra , Erlend Storvik , Jakub W. Both , Florin A. Radu

We propose a novel reformulation of the Vlasov-Amp{\`e}re equations for plasmas. This reformulation exposes discrete symmetries to achieve simultaneous conservation of mass, momentum, and energy; preservation of Gauss's law involution;…

Plasma Physics · Physics 2024-10-29 William T Taitano , Joshua W Burby , Alex Alekseenko

We consider finite element methods of multiscale type to approximate solutions for two-dimensional symmetric elliptic partial differential equations with heterogeneous $L^\infty$ coefficients. The methods are of Galerkin type and follow the…

Numerical Analysis · Mathematics 2025-05-20 Alexandre L. Madureira , Marcus Sarkis

Adaptive Partition-based Methods (APM) are numerical methods to solve two-stage stochastic linear problems (2SLP). The core idea is to iteratively construct an adapted partition of the space of alea in order to aggregate scenarios while…

Optimization and Control · Mathematics 2021-09-13 Maël Forcier , Vincent Leclère

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

N-body simulations are essential for understanding the formation and evolution of structure in the Universe. However, the discrete nature of these simulations affects their accuracy when modelling collisionless systems. We introduce a new…

Cosmology and Nongalactic Astrophysics · Physics 2015-11-18 Oliver Hahn , Raul E. Angulo

In this work we propose a Hybrid method with Deviational Particles (HDP) for a plasma modeled by the inhomogeneous Vlasov-Poisson-Landau system. We split the distribution into a Maxwellian part evolved by a grid based fluid solver and a…

Numerical Analysis · Mathematics 2016-02-17 Bokai Yan

This paper is devoted to the approximation of the linear Boltzmann equation by fractional diffusion equations. Most existing results address this question when there is no external acceleration field. The goal of this paper is to…

Analysis of PDEs · Mathematics 2016-06-06 Pedro Aceves-Sanchez , Antoine Mellet

A new method of solution to the local spin density approximation to the electronic Schr\"{o}dinger equation is presented. The method is based on an efficient, parallel, adaptive multigrid eigenvalue solver. It is shown that adaptivity is…

mtrl-th · Physics 2009-09-25 E. Bylaska , S. Khon , S. Baden , A. Edelman , R. Kawai , M. E. G. Ong , J. H. Weare

We introduce a high-order finite element method for approximating the Vlasov-Poisson equations. This approach employs continuous Lagrange polynomials in space and explicit Runge-Kutta schemes for time discretization. To stabilize the…

Numerical Analysis · Mathematics 2025-03-12 Junjie Wen , Murtazo Nazarov

We study smooth, global-in-time solutions of the Vlasov-Poisson system in the plasma physical case that possess arbitrarily large charge densities and electric fields. In particular, we construct two classes of solutions with this property.…

Analysis of PDEs · Mathematics 2017-08-09 Jonathan Ben-Artzi , Simone Calogero , Stephen Pankavich

The Grad method is generalized based on the Bogolyubov idea of the functional hypothesis for states at the end of relaxation processes in a system. The Grad problem (i.e., description of the Maxwell relaxation) for a completely ionized…

Statistical Mechanics · Physics 2017-06-23 V. N. Gorev , A. I. Sokolovsky

The kinetic analyses of many-particle soft matter often employ many simulation studies of various physical phenomena which supplement the experimental limitations or compliment the theoretical findings of the study. Such simulations are…

Plasma Physics · Physics 2024-05-28 Allen Lobo , Vinod Kumar Sayal

This work proposes a scheme for significantly reducing the computational complexity of discretized problems involving the non-smooth forward propagation of uncertainty by combining the adaptive hierarchical sparse grid stochastic…

Computational Physics · Physics 2015-09-07 Robert L. Gates , Maximilian R. Bittens

The Vlasov-Poisson-BGK (VPBGK) model is a kinetic model for describing the dynamics of collisional plasmas. Although various numerical schemes have been developed for it, a corresponding convergence theory has been absent. This paper fills…

Numerical Analysis · Mathematics 2026-05-11 Seung Yeon Cho , Sungsu Park , Seok-Bae Yun

We extend the semi-Lagrangian discontinuous Galerkin (SLDG) method of Einkemmer to velocity grids with adaptive mesh refinement (AMR) and to three-dimensional velocity space. The original SLDG formulation assumes uniform cell widths, which…

Numerical Analysis · Mathematics 2026-03-23 Mark F. Adams

The main objective of the paper is to determine asymptotic solutions to the initial-value conditions for Vlasov-Ampere/Gauss system of equations that is to find the "far field" solutions. Next, we determine dispersion relations for…

Plasma Physics · Physics 2007-05-23 A. J. Turski , B. Atamaniuk , E. Turska

Quantifying uncertainty in predictive simulations for real-world problems is of paramount importance - and far from trivial, mainly due to the large number of stochastic parameters and significant computational requirements. Adaptive sparse…

Computational Physics · Physics 2019-11-25 Ionut-Gabriel Farcas , Tobias Görler , Hans-Joachim Bungartz , Frank Jenko , Tobias Neckel