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The constrained transport (CT) method reflects the state of the art numerical technique for preserving the divergence-free condition of magnetic field to machine accuracy in multi-dimensional MHD simulations performed with Godunov-type, or…

Computational Physics · Physics 2020-12-02 Andrea Mignone , Luca Del Zanna

We present a modified Front Tracking (mFT) scheme for hyperbolic systems of conservation laws in one space dimension, in which we allow arbitrarily large nonlinear waves. We build the scheme by introducing and solving a ``generalized…

Analysis of PDEs · Mathematics 2025-04-30 Manas Bhatnagar , Robin Young

In this work, we propose and develop efficient and accurate numerical methods for solving the Kirchhoff-Love plate model in domains with complex geometries. The algorithms proposed here employ curvilinear finite-difference methods for…

Numerical Analysis · Mathematics 2021-05-13 Longfei Li , Hangjie Ji , Qi Tang

In this work we derive the general conditions for obtaining nonreciprocity in multi-mode parametrically-coupled systems. The results can be applied to a broad variety of optical, microwave, and hybrid systems including recent electro- and…

Superconductivity · Physics 2015-04-22 Leonardo Ranzani , José Aumentado

We combine the multigrid (MG) method with state-of-the-art concepts from the variational formulation of the numerical renormalization group. The resulting MG renormalization (MGR) method is a natural generalization of the MG method for…

Computational Physics · Physics 2018-07-17 Michael Lubasch , Pierre Moinier , Dieter Jaksch

On-chip optical interconnect has been widely accepted as a promising technology to realize future large-scale multiprocessors. Mode-division multiplexing (MDM) provides a new degree of freedom for optical interconnects to dramatically…

Optics · Physics 2020-04-07 Chunlei Sun , Yunhong Ding , Zhen Li , Wei Qi , Yu Yu , Xinliang Zhang

A collision-based hybrid method for the discrete ordinates approximation of the multigroup neutron transport equation is developed for two-dimensional time-dependent problems. At each time step, this algorithm splits the neutron transport…

Computational Physics · Physics 2025-02-17 Ben Whewell , Ryan G. McClarren

We are interested in numerical schemes for the simulation of large scale gas networks. Typical models are based on the isentropic Euler equations with realistic gas constant. The numerical scheme is based on transformation of conservative…

Numerical Analysis · Mathematics 2020-05-26 Sara Grundel , Michael Herty

We argue that the critical dynamical fluctuations predicted by the mode-coupling theory (MCT) of glasses provide a natural mechanism to explain the breakdown of the Stokes-Einstein relation. This breakdown, observed numerically and…

Statistical Mechanics · Physics 2015-06-25 Giulio Biroli , Jean-Philippe Bouchaud

It is known that the solution of a conservative steady-state two-sided fractional diffusion problem can exhibit singularities near the boundaries. As consequence of this, and due to the conservative nature of the problem, we adopt a finite…

Numerical Analysis · Mathematics 2022-09-20 Marco Donatelli , Rolf Krause , Mariarosa Mazza , Ken Trotti

We apply the mode coupling theory (MCT) which was recently worked out for molecular liquids to a liquid of diatomic, rigid molecules. Using the static correlators from a molecular dynamics simulation, we have solved the MCT-equations for…

Disordered Systems and Neural Networks · Physics 2009-10-31 Christoph Theis , Rolf Schilling

Geometric integration theory can be employed when numerically solving ODEs or PDEs with constraints. In this paper, we present several one-step algorithms of various orders for ODEs on a collection of spheres. To demonstrate the versatility…

Numerical Analysis · Mathematics 2011-12-05 Debra Lewis , Nilima Nigam

This work deals with the efficient numerical solution of the time-fractional heat equation discretized on non-uniform temporal meshes. Non-uniform grids are essential to capture the singularities of "typical" solutions of time-fractional…

Numerical Analysis · Mathematics 2020-05-08 Xiaozhe Hu , Carmen Rodrigo , Francisco J. Gaspar

We describe a short, reproducible workflow for applying finite differences on nonuniform grids determined by a positive weight function g. The grid is obtained by equidistribution, mapping uniform computational coordinates $\xi\in[0,1]$ to…

Numerical Analysis · Mathematics 2025-08-06 Mário B. Amaro

We introduce an algorithm to solve linear inverse problems regularized with the total (gradient) variation in a gridless manner. Contrary to most existing methods, that produce an approximate solution which is piecewise constant on a fixed…

Signal Processing · Electrical Eng. & Systems 2025-07-08 Yohann de Castro , Vincent Duval , Romain Petit

Magnetohydrodynamic (MHD) simulations are indispensable research infrastructure in astrophysics today. In order to satisfy the solenoidal constraint of the MHD equations on discretized grids, modern simulation codes often employ either…

Instrumentation and Methods for Astrophysics · Physics 2026-05-11 Kengo Tomida , Kenji Eric Sadanari , Shinsuke Takasao , Kazunari Iwasaki

This article shows the interfacial relation in electrodynamics shall be corrected in discrete grid form which can be seen as certain numerical dispersion beyond the usual bulk type. Furthermore we construct a lossy conductor model to…

Computational Physics · Physics 2011-11-22 Axman Fisher

In this work, we propose a generalized multiscale inversion algorithm for heterogeneous problems that aims at solving an inverse problem on a computational coarse grid. Previous inversion techniques for multiscale problems seek a…

Numerical Analysis · Mathematics 2017-07-27 Eric T. Chung , Yalchin Efendiev , Bangti Jin , Wing Tat Leung , Maria Vasilyeva

In this article we develop a numerical scheme to deal with interfaces between touching numerical grids when solving Schr\"o{}dinger equation. In order to pass the information among grids we use the values of the fields only at the contact…

Quantum Physics · Physics 2011-03-29 Oscar A. Reula

Conditional independence testing (CIT) is a common task in machine learning, e.g., for variable selection, and a main component of constraint-based causal discovery. While most current CIT approaches assume that all variables are numerical…

Machine Learning · Computer Science 2023-11-07 Oana-Iuliana Popescu , Andreas Gerhardus , Jakob Runge