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We study the convergence of the new family of mimetic finite difference schemes for linear diffusion problems recently proposed in [38]. In contrast to the conventional approach, the diffusion coefficient enters both the primary mimetic…

Numerical Analysis · Mathematics 2016-12-07 G. Manzini , K. Lipnikov , J. D. Moulton , M. Shashkov

To precondition a large and sparse linear system, two direct methods for approximate factoring of the inverse are devised. The algorithms are fully parallelizable and appear to be more robust than the iterative methods suggested for the…

Numerical Analysis · Mathematics 2012-08-20 Mikko Byckling , Marko Huhtanen

We study a fully discrete finite element approximation of a model for unsteady flows of rate-type viscoelastic fluids with stress diffusion in two and three dimensions. The model consists of the incompressible Navier--Stokes equation for…

Numerical Analysis · Mathematics 2024-06-21 Dennis Trautwein

We study a conservative 5-point cell-centered finite volume discretization of the high-contrast diffusion equation. We aim to construct preconditioners that are robust with respect to the magnitude of the coefficient contrast and the mesh…

Numerical Analysis · Mathematics 2009-04-14 Burak Aksoylu , Zuhal Yeter

We present a stationary iteration based upon a block splitting for a class of indefinite least squares problem. Convergence of the proposed method is investigated and optimal value of the involving parameter is used. The induced…

Numerical Analysis · Mathematics 2025-12-15 Davod Khojasteh Salkuyeh

In this paper, using a pseudospectral approach, we develop operational matrices based on the shifted Chebyshev polynomials to approximate numerically Caputo fractional derivatives and Riemann-Liouville fractional integrals. In order to make…

Numerical Analysis · Mathematics 2025-11-17 Francisco de la Hoz , Peru Muniain

We present a simple discretization scheme for the hypersingular integral representation of the fractional Laplace operator and solver for the corresponding fractional Laplacian problem. Through singularity subtraction, we obtain a…

Numerical Analysis · Mathematics 2020-01-29 Victor Minden , Lexing Ying

The paper introduces the sweeping preconditioner, which is highly efficient for iterative solutions of the variable coefficient Helmholtz equation including very high frequency problems. The first central idea of this novel approach is to…

Numerical Analysis · Mathematics 2010-08-04 Björn Engquist , Lexing Ying

Diffusion models over discrete spaces have recently shown striking empirical success, yet their theoretical foundations remain incomplete. In this paper, we study the sampling efficiency of score-based discrete diffusion models under a…

Machine Learning · Computer Science 2026-02-17 Daniil Dmitriev , Zhihan Huang , Yuting Wei

We consider a system of semilinear partial differential equations (PDEs) with a nonlinearity depending on both the solution and its gradient. The Neumann boundary condition depends on the solution in a nonlinear manner. The uniform…

Probability · Mathematics 2022-01-14 Khaled Bahlali , Brahim Boufoussi , Soufiane Mouchtabih

We develop efficient hierarchical preconditioners for optimal control problems governed by partial differential equations with uncertain coefficients. Adopting a discretize-then-optimize framework that integrates finite element…

Optimization and Control · Mathematics 2026-02-24 Zhendong Li , Akwum Onwunta , Bedřich Sousedík

The fractional wave equation governs the propagation of mechanical diffusive waves in viscoelastic media which exhibits a power-law creep, and consequently provided a physical interpretation of this equation in the framework of dynamic…

Numerical Analysis · Mathematics 2020-07-21 Minghua Chen , Wenshan Yu

Many scientific and engineering challenges can be formulated as optimization problems which are constrained by partial differential equations (PDEs). These include inverse problems, control problems, and design problems. As a major…

Optimization and Control · Mathematics 2017-12-25 Lasse Hjuler Christiansen , John Bagterp Jørgensen

We study solution techniques for an evolution equation involving second order derivative in time and the spectral fractional powers, of order $s \in (0,1)$, of symmetric, coercive, linear, elliptic, second-order operators in bounded domains…

Numerical Analysis · Mathematics 2018-06-18 Lehel Banjai , Enrique Otarola

In this paper, we study numerical methods for the homogenization of linear second-order elliptic equations in nondivergence-form with periodic diffusion coefficients and large drift terms. Upon noting that the effective diffusion matrix can…

Numerical Analysis · Mathematics 2025-06-18 Timo Sprekeler , Han Wu , Zhiwen Zhang

We construct deterministic particle solutions for linear and fast diffusion equations using a nonlocal approximation. We exploit the $2$-Wasserstein gradient flow structure of the equations in order to obtain the nonlocal approximating PDEs…

Analysis of PDEs · Mathematics 2024-08-06 José Antonio Carrillo , Antonio Esposito , Jakub Skrzeczkowski , Jeremy Sheung-Him Wu

We consider the reaction diffusion problem and present efficient ways to discretize and precondition in the singular perturbed case when the reaction term dominates the equation. Using the concepts of optimal test norm and saddle point…

Numerical Analysis · Mathematics 2021-04-26 Constantin Bacuta , Daniel Hayes , Jacob Jacavage

The boundary integral method is an efficient approach for solving time-harmonic obstacle scattering problems by a bounded scatterer. This paper presents the directional preconditioner for the iterative solution of linear systems of the…

Numerical Analysis · Mathematics 2014-09-17 Lexing Ying

In this article, we systematically explain how to apply the analytical technique called the invariant subspace method to find various types of analytical solutions for a coupled nonlinear time-fractional system of partial differential…

Analysis of PDEs · Mathematics 2024-06-17 K. S. Priyendhu , P. Prakash , M. Lakshmanan

We present a Bayesian non-parametric way of inferring stochastic differential equations for both regression tasks and continuous-time dynamical modelling. The work has high emphasis on the stochastic part of the differential equation, also…

Machine Learning · Statistics 2020-06-29 Martin Jørgensen , Marc Peter Deisenroth , Hugh Salimbeni