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We propose a second order exponential scheme suitable for two-component coupled systems of stiff evolutionary advection--diffusion--reaction equations in two and three space dimensions. It is based on a directional splitting of the involved…

Numerical Analysis · Mathematics 2023-11-27 Marco Caliari , Fabio Cassini

In this paper, we propose and analyse a novel class of exponential collocation methods for solving conservative or dissipative systems based on exponential integrators and collocation methods. It is shown that these novel methods can be of…

Numerical Analysis · Mathematics 2018-09-18 Bin Wang , Xinyuan Wu

In this paper, a novel class of exponential Fourier collocation methods (EFCMs) is presented for solving systems of first-order ordinary differential equations. These so-called exponential Fourier collocation methods are based on the…

Numerical Analysis · Mathematics 2018-02-22 Bin Wang , Xinyuan Wu , Fanwei Meng , Yonglei Fang

The exponential trapezoidal rule is proposed and analyzed for the numerical integration of semilinear integro-differential equations. Although the method is implicit, the numerical solution is easily obtained by standard fixed-point…

Numerical Analysis · Mathematics 2024-03-12 Alexander Ostermann , Nasrin Vaisi

We present a number of new contributions to the topic of constructing efficient higher-order splitting methods for the numerical integration of evolution equations. Particular schemes are constructed via setup and solution of polynomial…

Numerical Analysis · Mathematics 2016-04-06 Winfried Auzinger , Harald Hofstätter , David Ketcheson , Othmar Koch

On the basis of additive schemes (splitting schemes) we construct efficient numerical algorithms to solve approximately the initial-boundary value problems for systems of time-dependent partial differential equations (PDEs). In many applied…

Numerical Analysis · Computer Science 2011-12-07 Petr N. Vabishchevich

Exponential family extensions of principal component analysis (EPCA) have received a considerable amount of attention in recent years, demonstrating the growing need for basic modeling tools that do not assume the squared loss or Gaussian…

Machine Learning · Computer Science 2012-03-19 Arto Klami , Seppo Virtanen , Samuel Kaski

In the probabilistic approach to quantum many-body systems, the ground-state energy is the solution of a nonlinear scalar equation written either as a cumulant expansion or as an expectation with respect to a probability distribution of the…

Statistical Mechanics · Physics 2013-04-04 Andrea Di Stefano , Massimo Ostilli , Carlo Presilla

In this manuscript, we propose newly-derived exponential quadrature rules for stiff linear differential equations with time-dependent fractional sources in the form $h(t^r)$, with $0<r<1$ and $h$ a sufficiently smooth function. To construct…

Numerical Analysis · Mathematics 2025-06-26 Marco Caliari , Fabio Cassini

In this paper, we consider the composition of two independent processes : one process corresponds to position and the other one to time. Such processes will be called iterated processes. We first propose an algorithm based on the Euler…

Probability · Mathematics 2017-05-03 Michèle Thieullen , Alexis Vigot

This paper deals with the problem of simulating dense dispersed systems composed by large numbers of particles undergoing ballistic aggregation. The most classical approaches for dealing with such problems are represented by the so-called…

Computational Physics · Physics 2024-09-25 Pierre Degond , Giacomo Dimarco , Marina Ferreira , Sophie Hecht

Differentiable physics provides a new approach for modeling and understanding the physical systems by pairing the new technology of differentiable programming with classical numerical methods for physical simulation. We survey the rapidly…

Machine Learning · Computer Science 2021-09-17 Bharath Ramsundar , Dilip Krishnamurthy , Venkatasubramanian Viswanathan

Symplectic integration methods based on operator splitting are well established in many branches of science. For Hamiltonian systems which split in more than two parts, symplectic methods of higher order have been studied in detail only for…

The machine learning explosion has created a prominent trend in modern computer hardware towards low precision floating-point operations. In response, there have been growing efforts to use low and mixed precision in general scientific…

Numerical Analysis · Mathematics 2024-03-19 Cody J. Balos , Steven Roberts , David J. Gardner

Exponential integrators have been introduced as an efficient alternative to explicit and implicit methods for integrating large stiff systems of differential equations. Over the past decades these methods have been studied theoretically and…

Numerical Analysis · Mathematics 2018-04-03 Lukas Einkemmer , Mayya Tokman , John Loffeld

In this work, we consider the coupled systems of linear unsteady partial differential equations, which arise in the modeling of poroelasticity processes. Stability estimates of weighted difference schemes for the coupled system of equations…

Numerical Analysis · Computer Science 2013-11-18 A. E. Kolesov , P. N. Vabishchevich , M. V. Vasilyeva

Compartmentalised biochemical reactions are a ubiquitous building block of biological systems. The interplay between chemical and compartmental dynamics can drive rich and complex dynamical behaviors that are difficult to analyse…

Molecular Networks · Quantitative Biology 2023-06-16 Tommaso Bianucci , Christoph Zechner

For quantum systems with competing potentials, the conventional perturbation theory often yields an asymptotic series and the subsequent numerical outcome becomes uncertain. To tackle such kind of problems, we develop a general solution…

Quantum Physics · Physics 2015-06-05 H. Mineo , Sheng D. Chao

The splitting method is a powerful method for solving partial differential equations. Various splitting methods have been designed to separate different physics, nonlinearities, and so on. Recently, a new splitting approach has been…

Numerical Analysis · Mathematics 2023-03-22 Yalchin Efendiev , Wing Tat Leung , Wenyuan Li , Zecheng Zhang

In this paper, we combine deterministic splitting methods with a polynomial chaos expansion method for solving stochastic parabolic evolution problems. The stochastic differential equation is reduced to a system of deterministic equations…

Numerical Analysis · Mathematics 2021-07-02 Andreas Kofler , Tijana Levajković , Hermann Mena , Alexander Ostermann