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In partial differential equations-based (PDE-based) inverse problems with many measurements, many large-scale discretized PDEs must be solved for each evaluation of the misfit or objective function. In the nonlinear case, evaluating the…

Numerical Analysis · Mathematics 2018-07-18 Selin Aslan , Eric de Sturler , Misha E. Kilmer

While quantum computing provides an exponential advantage in solving linear differential equations, there are relatively few quantum algorithms for solving nonlinear differential equations. In our work, based on the homotopy perturbation…

Quantum Physics · Physics 2021-12-23 Cheng Xue , Yu-Chun Wu , Guo-Ping Guo

Two new approaches to solving first-order quasilinear elliptic systems of PDEs in many dimensions are proposed. The first method is based on an analysis of multimode solutions expressible in terms of Riemann invariants, based on links…

Mathematical Physics · Physics 2014-10-01 A. M. Grundland , V. Lamothe

This article generalizes a recently introduced procedure to solve nonlinear systems of equations, radically departing from the conventional Newton-Raphson scheme. The original nonlinear system is first unfolded into three simpler…

Numerical Analysis · Mathematics 2014-07-24 Antonio Gómez-Expósito

In numerical simulations of many charged systems at the micro/nano scale, a common theme is the repeated solution of the Poisson-Boltzmann equation. This task proves challenging, if not entirely infeasible, largely due to the nonlinearity…

Numerical Analysis · Mathematics 2018-08-29 Lijie Ji , Yanlai Chen , Zhenli Xu

Large scale optimization problems are ubiquitous in machine learning and data analysis and there is a plethora of algorithms for solving such problems. Many of these algorithms employ sub-sampling, as a way to either speed up the…

Optimization and Control · Mathematics 2016-02-29 Farbod Roosta-Khorasani , Michael W. Mahoney

This paper reports on a new algorithm to compute the asymptotic solutions of a linear differential system. A feature of the algorithm is the ability to accommodate periodic coefficients.

Spectral Theory · Mathematics 2025-10-20 B. M. Brown , M. S. P. Eastham , D. K. R. McCormack

We present a model reduction approach for the real-time solution of time-dependent nonlinear partial differential equations (PDEs) with parametric dependencies. The approach integrates several ingredients to develop efficient and accurate…

Numerical Analysis · Mathematics 2024-10-04 Ngoc Cuong Nguyen

A numerical method is proposed to compute a low-rank Galerkin approximation to the solution of a parametric or stochastic equation in a non-intrusive fashion. The considered nonlinear problems are associated with the minimization of a…

Numerical Analysis · Mathematics 2017-05-11 Loïc Giraldi , Dishi Liu , Hermann G. Matthies , Anthony Nouy

The nonlinear fractional Boussinesq equations are known as the fractional differential equation class that has an important place in mathematical physics. In this study, a method called (G'G^2)-extension method which works well and reveals…

Analysis of PDEs · Mathematics 2021-04-30 Erdogan Mehmet Ozkan

In this paper we consider splitting methods for the time integration of parabolic and certain classes of hyperbolic partial differential equations, where one partial flow can not be computed exactly. Instead, we use a numerical…

Numerical Analysis · Mathematics 2017-01-06 Lukas Einkemmer , Alexander Ostermann

A numerical method is developed leading to algebraic systems based on generalized Lyapunov-Sylvester operators to approximate the solution of two-dimensional Boussinesq equation. It consists of an order reduction method and a finite…

Numerical Analysis · Mathematics 2015-11-11 Abdelhamid Bezia , Anouar Ben Mabrouk , Kamel Betina

The numerical solution methods for partial differential equation (PDE) solution allow obtaining a discrete field that converges towards the solution if the method is applied to the correct problem. Nevertheless, the numerical methods…

Numerical Analysis · Mathematics 2021-03-04 Alexander Hvatov

We compute the nonlinearity of Boolean functions with Groebner basis techniques, providing two algorithms: one over the binary field and the other over the rationals. We also estimate their complexity. Then we show how to improve our…

Information Theory · Computer Science 2014-04-11 E. Bellini , I. Simonetti , M. Sala

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

We study the symmetry reduction of nonlinear partial differential equations with two independent variables. We propose new ans\"atze reducing nonlinear evolution equations to system of ordinary differential equations. The ans\"atze are…

Analysis of PDEs · Mathematics 2017-12-27 Ivan Tsyfra , Tomasz Czyżycki

In a recent work [1, 2] Sjoberg remarked that generalization of the double reduction theory to partial differential equations of higher dimensions is still an open problem. In this note we have attempted to provide this generalization to…

Analysis of PDEs · Mathematics 2009-09-28 Ashfaque H. Bokhari , Ahmad Y. Dweik , F. D. Zaman , A. H. Kara , F. M. Mahomed

An algorithm for sequential calculation of non-isotropic matrix elements of the collision integral which are necessary for the solution of the non-linear Boltzmann equation by moment method is proposed. Isotropic matrix elements that we…

Computational Physics · Physics 2017-04-20 I. A. Ender , L. A. Bakaleinikov , E. Yu. Flegontova , A. B. Gerasimenko

Algorithms for the symbolic computation of polynomial conservation laws, generalized symmetries, and recursion operators for systems of nonlinear differential-difference equations (DDEs) are presented. The algorithms can be used to test the…

Mathematical Physics · Physics 2011-04-26 Ünal Göktaş , Willy Hereman

We propose a numerical method for solving high dimensional fully nonlinear partial differential equations (PDEs). Our algorithm estimates simultaneously by backward time induction the solution and its gradient by multi-layer neural…

Optimization and Control · Mathematics 2021-01-27 Huyen Pham , Xavier Warin , Maximilien Germain
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