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The modeling of electric machines and power transformers typically involves systems of nonlinear magnetostatics or -quasistatics, and their efficient and accurate simulation is required for the reliable design, control, and optimization of…

Numerical Analysis · Mathematics 2024-08-23 Herbert Egger , Felix Engertsberger , Bogdan Radu

We present a quantum algorithm for computational fluid dynamics based on the Lattice-Boltzmann method. Our approach involves a novel encoding strategy and a modified collision operator, assuming full relaxation to the local equilibrium…

Over the last two decades, several fast, robust, and high-order accurate methods have been developed for solving the Poisson equation in complicated geometry using potential theory. In this approach, rather than discretizing the partial…

Numerical Analysis · Mathematics 2024-09-19 Fredrik Fryklund , Leslie Greengard , Shidong Jiang , Samuel Potter

We develop a numerical method for solving a system of nonlinear integral equations involving two integral terms: at the current time t, one integral is taken from 0 to t, and a different integral is taken from t to infinity. We prove the…

Numerical Analysis · Mathematics 2008-09-15 S. A. Belbas

This paper presents a novel framework for high-dimensional nonlinear quantum computation that exploits tensor products of amplified vector and matrix encodings to efficiently evaluate multivariate polynomials. The approach enables the…

Quantum Physics · Physics 2025-10-01 Matthias Deiml , Daniel Peterseim

Ion transport, often described by the Poisson--Nernst--Planck (PNP) equations, is ubiquitous in electrochemical devices and many biological processes of significance. In this work, we develop conservative, positivity-preserving, energy…

Numerical Analysis · Mathematics 2020-07-15 Jie Ding , Zhongming Wang , Shenggao Zhou

Efficient and fast predictor-corrector methods are proposed to deal with nonlinear Caputo-Fabrizio fractional differential equations, where Caputo-Fabrizio operator is a new proposed fractional derivative with a smooth kernel. The proposed…

Numerical Analysis · Mathematics 2020-10-07 Seyeon Lee , Junseo Lee , Hyunju Kim , Bongsoo Jang

We introduce a novel kernel-based framework for learning differential equations and their solution maps that is efficient in data requirements, in terms of solution examples and amount of measurements from each example, and computational…

Machine Learning · Statistics 2025-04-07 Yasamin Jalalian , Juan Felipe Osorio Ramirez , Alexander Hsu , Bamdad Hosseini , Houman Owhadi

A new method for generating analytical expression of quantum Hamiltonian from non-linear differential equation with stationary energy level has been formulated.Further calculation of energy levels have been carried out analytically using…

Quantum Physics · Physics 2014-12-30 Biswanath Rath , P. Mallick

Discretization of non-linear Poisson-Boltzmann Equation equations results in a system of non-linear equations with symmetric Jacobian. The Newton algorithm is the most useful tool for solving non-linear equations. It consists of solving a…

Mathematical Physics · Physics 2007-05-23 Sanjay Kumar Khattri

In this paper, we consider the problem of solving a constrained system of nonlinear equations. We propose an algorithm based on a combination of the Newton and conditional gradient methods, and establish its local convergence analysis. Our…

Optimization and Control · Mathematics 2016-08-25 Max L. N. Goncalves , Jefferson G. Melo

We propose a novel method to compute multi-loop master integrals by constructing and numerically solving a system of ordinary differential equations, with almost trivial boundary conditions. Thus it can be systematically applied to problems…

High Energy Physics - Phenomenology · Physics 2018-02-28 Xiao Liu , Yan-Qing Ma , Chen-Yu Wang

We develop a novel iterative solution method for the incompressible Navier-Stokes equations with boundary conditions coupled with reduced models. The iterative algorithm is designed based on the variational multiscale formulation and the…

Numerical Analysis · Mathematics 2020-06-24 Ju Liu , Weiguang Yang , Melody Dong , Alison L. Marsden

In this work, we propose a numerical approach for simulations of large deformations of interfaces in a level set framework. To obtain a fast and viable numerical solution in both time and space, temporal discretization is based on the…

General Mathematics · Mathematics 2023-05-30 Aymen Laadhari , Ahmad Deeb

We develop a randomized Newton's method for solving differential equations, based on a fully connected neural network discretization. In particular, the randomized Newton's method randomly chooses equations from the overdetermined nonlinear…

Numerical Analysis · Mathematics 2019-12-09 Qipin Chen , Wenrui Hao

With the aim of efficiently simulating three-dimensional multiphase turbulent flows with a phase-field method, we propose a new discretization scheme for the biharmonic term (the 4th-order derivative term) of the Cahn-Hilliard equation.…

Fluid Dynamics · Physics 2022-05-24 Hao-Ran Liu , Chong Shen Ng , Kai Leong Chong , Detlef Lohse , Roberto Verzicco

We present a quantum algorithm for systems of (possibly inhomogeneous) linear ordinary differential equations with constant coefficients. The algorithm produces a quantum state that is proportional to the solution at a desired final time.…

Quantum Physics · Physics 2017-11-07 Dominic W. Berry , Andrew M. Childs , Aaron Ostrander , Guoming Wang

On an example of the open nonlinear electrodynamic system - transverse non-homogeneous, isotropic, nonlinear (a Kerr-like dielectric nonlinearity) dielectric layer, the algorithms of solution of the diffraction problem of a plane wave on…

Computational Physics · Physics 2007-05-23 V. V. Yatsyk

Finite difference method was extended to unstructured meshes to solve Euler equations. The spatial discretization is made of two steps. First, numerical fluxes are computed at the middle point of each edge with high order accuracy. In this…

Computational Physics · Physics 2021-02-26 Meiyuan Zhen , Kun Qu , Jinsheng Cai

We investigate the use of piecewise linear systems, whose coefficient matrix is a piecewise constant function of the solution itself. Such systems arise, for example, from the numerical solution of linear complementarity problems and in the…

Numerical Analysis · Mathematics 2012-06-21 Luigi Brugnano , Alessandra Sestini
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