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We develop a finite volume method for Maxwell's equations in materials whose electromagnetic properties vary in space and time. We investigate both conservative and non-conservative numerical formulations. High-order methods accurately…

Computational Physics · Physics 2023-07-25 Damian P. San Roman Alerigi , David I. Ketcheson , Boon S. Ooi

Recently, a class of efficient spectral Monte-Carlo methods was developed in \cite{Feng2025ExponentiallyAS} for solving fractional Poisson equations. These methods fully consider the low regularity of the solution near boundaries and…

Numerical Analysis · Mathematics 2025-10-07 Lisen Ding , Mingyi Wang , Dongling Wang

We explain when and why symmetries enhance in fermionic rational conformal field theories. In order to achieve the goal, we first clarify invariants under renormalization group flows. In particular, we find the Ocneanu rigidity is not…

High Energy Physics - Theory · Physics 2022-10-05 Ken Kikuchi

We propose a multiscale approach for an elliptic multiscale setting with general unstructured diffusion coefficients that is able to achieve high-order convergence rates with respect to the mesh parameter and the polynomial degree. The…

Numerical Analysis · Mathematics 2020-09-03 Roland Maier

In this work, we propose a novel formulation for the solution of partial differential equations using finite element methods on unfitted meshes. The proposed formulation relies on the discrete extension operator proposed in the aggregated…

Numerical Analysis · Mathematics 2022-08-15 Santiago Badia , Eric Neiva , Francesc Verdugo

Optimal block designs for additive models achieve their efficiency by dividing experimental units among relatively homogenous blocks and allocating treatments equally to blocks. Responses in many modern experiments, however, are drawn from…

Methodology · Statistics 2016-01-05 Stephen Bush , Katya Ruggiero

Fully connected multilayer perceptrons are used for obtaining numerical solutions of partial differential equations in various dimensions. Independent variables are fed into the input layer, and the output is considered as solution's value.…

Neural and Evolutionary Computing · Computer Science 2020-01-28 V. I. Avrutskiy

We consider model-based derivative-free optimization (DFO) for large-scale problems, based on iterative minimization in random subspaces. We provide the first worst-case complexity bound for such methods for convergence to approximate…

Optimization and Control · Mathematics 2024-12-20 Coralia Cartis , Lindon Roberts

Many high-dimensional uncertainty quantification problems are solved by polynomial dimensional decomposition (PDD), which represents Fourier-like series expansion in terms of random orthonormal polynomials with increasing dimensions. This…

Numerical Analysis · Mathematics 2018-04-06 Sharif Rahman

This paper generalizes the non-conforming FEM of Crouzeix and Raviart and its fundamental projection property by a novel mixed formulation for the Poisson problem based on the Helmholtz decomposition. The new formulation allows for ansatz…

Numerical Analysis · Mathematics 2016-01-25 Mira Schedensack

While pseudospectral (PS) methods can feature very high accuracy, they tend to be severely limited in terms of geometric flexibility. Application of global radial basis functions overcomes this, however at the expense of problematic…

Numerical Analysis · Mathematics 2017-05-09 Pankaj K Mishra , Sankar K Nath , Gregor Kosec , Mrinal K Sen

In this paper, we examine a number of additive and multiplicative multilevel iterative methods and preconditioners in the setting of two-dimensional local mesh refinement. While standard multilevel methods are effective for uniform…

Numerical Analysis · Mathematics 2010-01-12 Burak Aksoylu , Stephen Bond , Michael Holst

We consider within a finite element approach the usage of different adaptively refined meshes for different variables in systems of nonlinear, time-depended PDEs. To resolve different solution behaviours of these variables, the meshes can…

Numerical Analysis · Mathematics 2010-05-27 Thomas Witkowski , Axel Voigt

Bayesian optimization is widely employed for optimizing complex black-box functions but struggles with the curse of dimensionality. Random embedding, as a dimension reduction strategy, simplifies tasks that possess the effective dimension…

Machine Learning · Computer Science 2026-05-26 Hong Qian , Xiang Shu , Xiang Xia , Xuhui Liu , Yangde Fu , Bei Liang , Huibin Wang , Liang Dou

The Poisson-Boltzmann equation (PBE) is a nonlinear elliptic PDE that arises in biomolecular modeling and is a fundamental tool for structural biology. It is used to calculate electrostatic potentials around an ensemble of fixed charges…

Numerical Analysis · Mathematics 2017-10-12 Cleophas Kweyu , Lihong Feng , Matthias Stein , Peter Benner

Recovered finite element methods (R-FEM) have been recently introduced for meshes consisting of simplicial and/or box-type meshes. Here, utilising the flexibility of R-FEM framework, we extend their definition on polygonal and polyhedral…

Numerical Analysis · Mathematics 2018-04-24 Zhaonan Dong , Emmanuil H. Georgoulis , Tristan Pryer

An efficient solver for the three dimensional free-space Poisson equation is presented. The underlying numerical method is based on finite Fourier series approximation. While the error of all involved approximations can be fully controlled,…

Computational Physics · Physics 2017-10-18 Lukas Exl

A method is described to solve the Poisson problem for a three dimensional source distribution that is periodic into one direction. Perpendicular to the direction of periodicity a free space (or open) boundary is realized. In beam physics,…

Accelerator Physics · Physics 2016-03-23 M. Dohlus , Ch. Henning

This paper is part of a series developing $C^0$ finite element methods for fourth-order elliptic equations on polygonal domains. Here, we investigate how boundary conditions influence the design of effective $C^0$ schemes, specifically…

Numerical Analysis · Mathematics 2026-02-05 Xihao Zhang , Hengguang Li , Nianyu Yi , Peimeng Yin

In many practical applications, heuristic or approximation algorithms are used to efficiently solve the task at hand. However their solutions frequently do not satisfy natural monotonicity properties of optimal solutions. In this work we…

Machine Learning · Computer Science 2020-03-24 Evangelia Gergatsouli , Brendan Lucier , Christos Tzamos
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