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The multigrid algorithm is a multilevel approach to accelerate the numerical solution of discretized differential equations in physical problems involving long-range interactions. Multiresolution analysis of wavelet theory provides an…

Computational Physics · Physics 2007-05-23 D. Yesilleten , T. A. Arias

Reduced rank extrapolation (RRE) is an acceleration method typically used to accelerate the iterative solution of nonlinear systems of equations using a fixed-point process. In this context, the iterates are vectors generated from a…

This work concerns the exponential stabilization of underactuated linear homogeneous systems of m parabolic partial differential equations (PDEs) in cascade (reaction-diffusion systems), where only the first state is controlled either…

Optimization and Control · Mathematics 2023-10-19 Constantinos Kitsos , Emilia Fridman

Probabilistic solvers for ordinary differential equations (ODEs) provide efficient quantification of numerical uncertainty associated with simulation of dynamical systems. Their convergence rates have been established by a growing body of…

Machine Learning · Statistics 2020-12-21 Nicholas Krämer , Philipp Hennig

Many problems in science and engineering require an efficient numerical approximation of integrals or solutions to differential equations. For systems with rapidly changing dynamics, an equidistant discretization is often inadvisable as it…

Time integration of ODEs or time-dependent PDEs with required resolution of the fastest time scales of the system, can be very costly if the system exhibits multiple time scales of different magnitudes. If the different time scales are…

Numerical Analysis · Mathematics 2012-05-15 Anders Logg

In the fields of statistics, machine learning, image science, and related areas, there is an increasing demand for decentralized collection or storage of large-scale datasets, as well as distributed solution methods. To tackle this…

Optimization and Control · Mathematics 2024-01-17 Bowen Li , Bin Shi

Pulay's Direct Inversion in the Iterative Subspace (DIIS) method is one of the most widely used mixing schemes for accelerating the self-consistent solution of electronic structure problems. In this work, we propose a simple generalization…

Computational Physics · Physics 2016-03-08 Amartya S. Banerjee , Phanish Suryanarayana , John E. Pask

Fractional Differential Equations (FDEs) are essential tools for modelling complex systems in science and engineering. They extend the traditional concepts of differentiation and integration to non-integer orders, enabling a more precise…

Machine Learning · Computer Science 2025-03-27 C. Coelho , M. Fernanda P. Costa , L. L. Ferrás

We present a new class of iterative schemes for solving initial value problems (IVP) based on discontinuous Galerkin (DG) methods. Starting from the weak DG formulation of an IVP, we derive a new iterative method based on a preconditioned…

Numerical Analysis · Mathematics 2016-10-06 Xiaozhou Li , Pietro Benedusi , Rolf Krause

The fast Ewald methods are widely used to compute the point-charge electrostatic interactions in molecular simulations. The key step that introduces errors in the computation is the particle-mesh interpolation. In this work, the optimal…

Chemical Physics · Physics 2017-10-25 Han Wang , Jun Fang , Xingyu Gao

We propose new linear combinations of compositions of a basic second-order scheme with appropriately chosen coefficients to construct higher order numerical integrators for differential equations. They can be considered as a generalization…

Numerical Analysis · Mathematics 2024-04-25 Sergio Blanes , Fernando Casas , Luke Shaw

Extrapolation remains a grand challenge in deep neural networks across all application domains. We propose an operator learning method to solve time-dependent partial differential equations (PDEs) continuously and with extrapolation in time…

Machine Learning · Computer Science 2023-12-12 Oded Ovadia , Vivek Oommen , Adar Kahana , Ahmad Peyvan , Eli Turkel , George Em Karniadakis

The discrete-dipole approximation (DDA) is a flexible technique for computing scattering and absorption by targets of arbitrary geometry. In this paper we perform systematic study of various non-stationary iterative (conjugate gradient)…

Atmospheric and Oceanic Physics · Physics 2007-05-23 Piotr J. Flatau

Mathematical models for flow and reactive transport in porous media often involve non-linear, degenerate parabolic equations. Their solutions have low regularity, and therefore lower order schemes are used for the numerical approximation.…

Numerical Analysis · Mathematics 2021-05-24 Jakub W. Both , Kundan Kumar , Jan M. Nordbotten , Iuliu Sorin Pop , Florin A. Radu

Purpose -- RF circuits often possess a multi-rate behavior. Slow changing baseband signals and fast oscillating carrier signals often occur in the same circuit. Frequency modulated signals pose a particular challenge.…

Numerical Analysis · Mathematics 2016-04-26 Kai Bittner , Hans Georg Brachtendorf

Neural ordinary differential equations (ODEs) have attracted much attention as continuous-time counterparts of deep residual neural networks (NNs), and numerous extensions for recurrent NNs have been proposed. Since the 1980s, ODEs have…

Machine Learning · Computer Science 2022-10-17 Kazuki Irie , Francesco Faccio , Jürgen Schmidhuber

This paper presents the novel Droop-e grid-forming inverter control strategy, which establishes an active power-frequency relationship based on an exponential function of the inverter power dispatch. The advantages of this control strategy…

Systems and Control · Electrical Eng. & Systems 2022-07-11 Rick Wallace Kenyon , Amirhossein Sajadi , Bri-Mathias Hodge

A genetic algorithm procedure is demonstrated that refines the selection of interpolation points of the discrete empirical interpolation method (DEIM) when used for constructing reduced order models for time dependent and/or parametrized…

Numerical Analysis · Mathematics 2016-07-27 Syuzanna Sargsyan , Steven L. Brunton , J. Nathan Kutz

Discrete Differential Equations (DDEs) are functional equations that relate polynomially a power series $F(t,u)$ in $t$ with polynomial coefficients in a "catalytic" variable $u$ and the specializations, say at $u=1$, of $F(t,u)$ and of…

Symbolic Computation · Computer Science 2023-05-01 Alin Bostan , Hadrien Notarantonio , Mohab Safey El Din