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We investigate the integrability of Nonlinear Partial Differential Equations (NPDEs). The concepts are developed by firstly discussing the integrability of the KdV equation. We proceed by generalizing the ideas introduced for the KdV…

solv-int · Physics 2015-06-26 H. J. S. Dorren

This paper presents an optimized and scalable semi-Lagrangian solver for the Vlasov-Poisson system in six-dimensional phase space. Grid-based solvers of the Vlasov equation are known to give accurate results. At the same time, these solvers…

Computational Physics · Physics 2019-03-29 Katharina Kormann , Klaus Reuter , Markus Rampp

A new method has been presented of constructing a class of exact solutions of an infinite self-linking chain of the Vlasov equations for distribution functions of kinematic quantities of all orders. Using the characteristic transformation…

Mathematical Physics · Physics 2025-06-30 E. E. Perepelkin , B. I. Sadovnikov , N. G. Inozemtseva , A. S. Medvedev

In this note we provide dispersive estimates for Fourier integrals with parameter-dependent phase functions in terms of geometric quantities of associated families of Fresnel surfaces. The results are based on a multi-dimensional van der…

Analysis of PDEs · Mathematics 2012-03-20 Michael Ruzhansky , Jens Wirth

Under a precise nonlinearity-diffusivity condition we establish the decay of space-periodic entropy solutions of a multidimensional degenerate nonlinear parabolic equation.

Analysis of PDEs · Mathematics 2019-01-17 Evgeniy Yu. Panov

The aim of this article is to construct solutions to second order in time stochastic partial differential equations and to show hypocoercivity of the corresponding transition semigroups. More generally, we analyze non-linear…

Probability · Mathematics 2023-06-21 Benedikt Eisenhuth , Martin Grothaus

We introduce an aggregation framework to address multi-stage stochastic programs with mixed-integer state variables and continuous local variables (MSILPs). Our aggregation framework imposes additional structure to the integer state…

Optimization and Control · Mathematics 2023-05-11 Margarita P. Castro , Merve Bodur , Yongjia Song

In this work, we apply the finite element heterogeneous multiscale method to a class of dispersive first-order time-dependent Maxwell systems. For this purpose, we use an analytic homogenization result, which shows that the effective system…

Numerical Analysis · Mathematics 2022-07-19 Philip Freese

We consider continuous-space, discrete-time Markov chains on $\mathbb{R}^d$, that admit a finite number $N$ of metastable states. Our main motivation for investigating these processes is to analyse random Poincar\'e maps, which describe…

Probability · Mathematics 2025-08-19 Nils Berglund

The availability of data sets with large numbers of variables is rapidly increasing. The effective application of Bayesian variable selection methods for regression with these data sets has proved difficult since available Markov chain…

Computation · Statistics 2019-05-08 Jim Griffin , Krys Latuszynski , Mark Steel

Iterative methods based on matrix splittings are useful in solving large sparse linear systems. In this direction, proper splittings and its several extensions are used to deal with singular and rectangular linear systems. In this article,…

Numerical Analysis · Mathematics 2019-07-08 Ashish Kumar Nandi , Jajati Keshari Sahoo , Debasisha Mishra

In this paper a theory of reflective X-ray multilayer structures with a graded (slowly varying) period based on the coupled waves method and quasi-classical asymptotic expansions is reported. A number of exact solutions of the coupled wave…

Optics · Physics 2022-04-26 R. M. Feshchenko

We present a new algorithm for the discretization of the Vlasov-Maxwell system of equations for the study of plasmas in the kinetic regime. Using the discontinuous Galerkin finite element method for the spatial discretization, we obtain a…

Plasma Physics · Physics 2017-11-22 J. Juno , A. Hakim , J. TenBarge , E. Shi , W. Dorland

Highly heterogeneous, anisotropic coefficients, e.g. in the simulation of carbon-fibre composite components, can lead to extremely challenging finite element systems. Direct solvers for the resulting large and sparse linear systems suffer…

Numerical Analysis · Mathematics 2021-06-16 Peter Bastian , Robert Scheichl , Linus Seelinger , Arne Strehlow

We consider the 3D Mikhalev system, $$ u_t=w_x, \quad u_y= w_t-u w_x+w u_x, $$ which has first appeared in the context of KdV-type hierarchies. Under the reduction $w=f(u)$, one obtains a pair of commuting first-order equations, $$…

Exactly Solvable and Integrable Systems · Physics 2024-02-28 E. V. Ferapontov , V. Novikov , I. Roustemoglou

Problems of interest in hydrogeology and hydrocarbon resources involve complex heterogeneous geological formations. Such domains are most accurately represented in reservoir simulations by unstructured computational grids. Finite element…

Computational Physics · Physics 2016-05-04 Joachim Moortgat , Abbas Firoozabadi

In this paper we consider the classification of dispersive linearizable partial difference equations defined on a quad-graph by the multiple scale reduction around their harmonic solution. We show that the A_1, A_2 and A_3 linearizability…

Exactly Solvable and Integrable Systems · Physics 2015-05-20 R. Hernandez Heredero , D. Levi , C. Scimiterna

Nonlinear dispersionless equations arise as the dispersionless limit of well know integrable hierarchies of equations or by construction, such as the system of hydrodynamic type. Some of these equations are integrable in the Hamiltonian…

Exactly Solvable and Integrable Systems · Physics 2015-06-26 J. C. Brunelli

We consider the construction of semi-implicit linear multistep methods which can be applied to time dependent PDEs where the separation of scales in additive form, typically used in implicit-explicit (IMEX) methods, is not possible. As…

Numerical Analysis · Mathematics 2020-01-14 Giacomo Albi , Lorenzo Pareschi

We provide a novel method for sensitivity analysis of parametric robust Markov chains. These models incorporate parameters and sets of probability distributions to alleviate the often unrealistic assumption that precise probabilities are…

Machine Learning · Computer Science 2023-05-03 Thom Badings , Sebastian Junges , Ahmadreza Marandi , Ufuk Topcu , Nils Jansen