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Exponential integrability properties of numerical approximations are a key tool for establishing positive rates of strong and numerically weak convergence for a large class of nonlinear stochastic differential equations. It turns out that…

Numerical Analysis · Mathematics 2020-08-10 Martin Hutzenthaler , Arnulf Jentzen , Xiaojie Wang

A parallel algorithm for computing the finite difference solution to the elliptic equations with non-separable variables is presented. The resultant matrix is symmetric positive definite, thus the preconditioning conjugate gradient or the…

Numerical Analysis · Mathematics 2015-03-13 Andrew V. Terekhov

The numerical methods for differential equation solution allow obtaining a discrete field that converges towards the solution if the method is applied to the correct problem. Nevertheless, the numerical methods have the restricted class of…

Numerical Analysis · Mathematics 2023-07-03 Alexander Hvatov , Tatiana Tikhonova

Classical algorithms in numerical analysis for numerical integration (quadrature/cubature) follow the principle of approximate and integrate: the integrand is approximated by a simple function (e.g. a polynomial), which is then integrated…

Numerical Analysis · Mathematics 2018-06-15 Yuji Nakatsukasa

Many nonlinear differential equations arising from practical problems may permit nontrivial multiple solutions relevant to applications, and these multiple solutions are helpful to deeply understand these practical problems and to improve…

Optimization and Control · Mathematics 2025-04-17 Lin Li , Yuheng Zhou , Pengcheng Xie , Huiyuan Li

We introduce tensor numerical techniques for solving optimal control problems constrained by elliptic operators in $\mathbb{R}^d$, $d=2,3$, with variable coefficients, which can be represented in a low rank separable form. We construct a…

Numerical Analysis · Mathematics 2021-05-28 Boris N. Khoromskij , Britta Schmitt , Volker Schulz

We show that integro-differential generalized Langevin and non-Markovian master equations can be transformed into larger sets of ordinary differential equations. .On the basis of this transformation we develop a numerical method for solving…

Quantum Physics · Physics 2009-11-10 Joshua Wilkie

This paper deals with fractional differential equations, with dependence on a Caputo fractional derivative of real order. The goal is to show, based on concrete examples and experimental data from several experiments, that fractional…

General Mathematics · Mathematics 2016-11-03 Ricardo Almeida , Nuno R. O. Bastos , M. Teresa T. Monteiro

We consider the numerical solution of the continuous algebraic Riccati equation $A^*X+XA-XFX+G=0$, with $F=F^*, G=G^*$ of low rank and $A$ large and sparse. We develop an algorithm for the low rank approximation of $X$ by means of an…

Numerical Analysis · Mathematics 2013-07-16 Yiding Lin , Valeria Simoncini

Solving large-scale continuous-time algebraic Riccati equations is a significant challenge in various control theory applications. This work demonstrates that when the matrix coefficients of the equation are quasiseparable, the solution…

Numerical Analysis · Mathematics 2026-01-30 Stefano Massei , Luca Saluzzi

The numerical solution of partial differential equations on high-dimensional domains gives rise to computationally challenging linear systems. When using standard discretization techniques, the size of the linear system grows exponentially…

Numerical Analysis · Mathematics 2015-08-13 Daniel Kressner , Michael Steinlechner , Bart Vandereycken

This paper proposes an effective low-rank alternating direction doubling algorithm (R-ADDA) for computing numerical low-rank solutions to large-scale sparse continuous-time algebraic Riccati matrix equations. The method is based on the…

Numerical Analysis · Mathematics 2024-04-23 Juan Zhang , Wenlu Xun

This study reexamines diffusive representations for fractional integrals with the goal of pioneering new variants of such representations. These variants aim to offer highly efficient numerical algorithms for the approximate computation of…

Numerical Analysis · Mathematics 2025-07-08 Renu Chaudhary , Kai Diethelm

Iterative gradient-based optimization algorithms are widely used to solve difficult or large-scale optimization problems. There are many algorithms to choose from, such as gradient descent and its accelerated variants such as Polyak's Heavy…

Optimization and Control · Mathematics 2023-09-21 Bryan Van Scoy , Laurent Lessard

Numerical solving differential equations with fractional derivatives requires elimination of the singularity which is inherent in the standard definition of fractional derivatives. The method of integration by parts to eliminate this…

Numerical Analysis · Mathematics 2022-01-26 Pavel B. Dubovski , Jeffrey A. Slepoi

We present a new class of numerical methods for solving stochastic differential equations with additive noise on general Riemannian manifolds with high weak order of accuracy. In opposition to the popular approach with projection methods,…

Numerical Analysis · Mathematics 2025-06-19 Eugen Bronasco , Adrien Busnot Laurent , Baptiste Huguet

A large toolbox of numerical schemes for dispersive equations has been established, based on different discretization techniques such as discretizing the variation-of-constants formula (e.g., exponential integrators) or splitting the full…

Numerical Analysis · Mathematics 2024-05-20 Frédéric Rousset , Katharina Schratz

We propose a hierarchical splitting approach to differential equations that provides a design principle for constructing splitting methods for $N$-split systems by iteratively applying splitting methods for two-split systems. We analyze the…

Numerical Analysis · Mathematics 2026-01-21 Kevin Schäfers , Michael Günther

This paper is devoted to the study of $L_p$ Lyapunov-type inequalities for linear systems of equations with Neumann boundary conditions and for any constant $p \geq 1$. We consider ordinary and elliptic problems. The results obtained in the…

Analysis of PDEs · Mathematics 2009-06-08 Antonio Canada , Salvador Villegas

Linearly implicit Runge-Kutta methods with approximate matrix factorization can solve efficiently large systems of differential equations that have a stiff linear part, e.g. reaction-diffusion systems. However, the use of approximate…

Numerical Analysis · Computer Science 2014-08-19 Hong Zhang , Adrian Sandu , Paul Tranquilli