English
Related papers

Related papers: An algorithm of computing inhomogeneous differenti…

200 papers

We present several new algorithms for computing factorization invariant values over affine semigroups. In particular, we give (i) the first known algorithm to compute the delta set of any affine semigroup, (ii) an improved method of…

Number Theory · Mathematics 2017-01-04 Pedro A. García-Sánchez , Christopher O'Neill , Gautam Webb

Differential equations with constant and variable coefficients over octonions are investigated. It is found that different types of differential equations over octonions can be resolved. For this purpose non-commutative line integration is…

Complex Variables · Mathematics 2018-12-18 Sergey V. Ludkovsky

Here we present an algorithm to find elementary first integrals of rational second order ordinary differential equations (SOODEs). In \cite{PS2}, we have presented the first algorithmic way to deal with SOODEs, introducing the basis for the…

Mathematical Physics · Physics 2008-10-02 J. Avellar , L. G. S. Duarte , S. E. S. Duarte , L. A. C. P. da Mota

Deep learning has become a popular tool across many scientific fields, including the study of differential equations, particularly partial differential equations. This work introduces the basic principles of deep learning and the Deep…

Machine Learning · Computer Science 2026-01-09 Georgios Is. Detorakis

In this paper, modulating functions-based method is proposed for estimating space-time dependent unknowns in one-dimensional partial differential equations. The proposed method simplified the problem into a system of algebraic equations…

Numerical Analysis · Mathematics 2016-01-13 Sharefa Asiri , Taous-Meriem Laleg-Kirati

We propose an algorithm to find a solution to an integro-differential equation of the DGLAP type for all the orders in the running coupling $\alpha$ with splitting functions given at a fixed order in $\alpha.$ Complex analysis is…

High Energy Physics - Phenomenology · Physics 2026-04-10 Igor Kondrashuk

Physics-informed neural networks have emerged as a prominent new method for solving differential equations. While conceptually straightforward, they often suffer training difficulties that lead to relatively large discretization errors or…

Mathematical Physics · Physics 2024-03-13 Shivam Arora , Alex Bihlo , Francis Valiquette

In this paper, the tropical differential Gr\"obner basis is studied, which is a natural generalization of the tropical Gr\"obner basis to the recently introduced tropical differential algebra. Like the differential Gr\"obner basis, the…

Symbolic Computation · Computer Science 2019-04-05 Youren Hu , Xiao-Shan Gao

In this paper, we give an overview of the differential algebra approach to identifiability, and then note a very simple observation about input-output equivalence and identifiability, that describes the identifiability equivalence between…

Quantitative Methods · Quantitative Biology 2019-08-20 Marisa Eisenberg

The identification of a mathematical dynamics model is a crucial step in the designing process of a controller. However, it is often very difficult to identify the system's governing equations, especially in complex environments that…

Systems and Control · Electrical Eng. & Systems 2024-07-01 Tobias Nagel , Marco F. Huber

The result after $N$ steps of an implicit Runge-Kutta time discretization of an inhomogeneous linear parabolic differential equation is computed, up to accuracy $\epsilon$, by solving only $$O\Big(\log N \log \frac1\epsilon \Big) $$ linear…

Numerical Analysis · Mathematics 2011-11-10 María López-Fernández , Christian Lubich , Cesar Palencia , Achim Schädle

This paper studies the expressive and computational power of discrete Ordinary Differential Equations (ODEs), a.k.a. (Ordinary) Difference Equations. It presents a new framework using these equations as a central tool for computation and…

Logic in Computer Science · Computer Science 2022-09-27 Olivier Bournez , Arnaud Durand

Quantum algorithms for Hamiltonian simulation and linear differential equations more generally have provided promising exponential speed-ups over classical computers on a set of problems with high real-world interest. However, extending…

Quantum Physics · Physics 2025-05-14 Noah Brüstle , Nathan Wiebe

We study a numerical approximation for a nonlinear variable-order fractional differential equation via an integral equation method. Due to the lack of the monotonicity of the discretization coefficients of the variable-order fractional…

Numerical Analysis · Mathematics 2021-10-12 Xiangcheng Zheng

The theme of this paper is to `solve' an absolutely irreducible differential module explicitly in terms of modules of lower dimension and finite extensions of the differential field $K$. Representations of semi-simple Lie algebras and…

Classical Analysis and ODEs · Mathematics 2008-10-23 K. A. Nguyen , M. van der Put

In this paper, we present a numerical homogenization scheme for indefinite, time-harmonic Maxwell's equations involving potentially rough (rapidly oscillating) coefficients. The method involves an $\mathbf{H}(\mathrm{curl})$-stable,…

Numerical Analysis · Mathematics 2017-12-01 Barbara Verfürth

We give algorithms for the computation of the algebraic de Rham cohomology of open and closed algebraic sets inside projective space or other smooth complex toric varieties. The methods, which are based on Gr\"obner basis computations in…

Algebraic Geometry · Mathematics 2009-09-25 Uli Walther

The correct computation of orbits of discrete dynamical systems on the interval is considered. Therefore, an arbitrary-precision floating-point approach based on automatic error analysis is chosen and a general algorithm is presented. The…

Numerical Analysis · Computer Science 2015-03-13 Christoph Spandl

By a high-order numerical homogenization method, a heterogeneous multiscale scheme was developed in Jin & Li (2022) for evolving differential equations containing two time scales. In this paper, we further explore the technique to propose…

Numerical Analysis · Mathematics 2025-09-25 Bojin Chen , Zeyu Jin , Ruo Li

This paper presents a novel algorithm to obtain the closed-form anti-derivative of a function using Deep Neural Network architecture. In the past, mathematicians have developed several numerical techniques to approximate the values of…

Numerical Analysis · Mathematics 2022-09-20 D. Chakraborty , S. Gopalakrishnan
‹ Prev 1 8 9 10 Next ›