About the Journal

Journal of Approximation Theory and Numerical Analysis (JATNA) is an international, peer-reviewed, open-access journal that publishes high-quality research in approximation theory and numerical analysis. The journal focuses on the development, analysis, and implementation of approximation techniques and numerical methods for solving continuous and discrete problems arising in science, engineering, and applied mathematics. JATNA welcomes original research articles, review papers, and short communications that provide rigorous theoretical results, efficient algorithms, or insightful computational experiments related to function approximation, numerical linear algebra, numerical solutions of differential equations, and approximation-based methods in applications.

Scope

JATNA invites original contributions in, but not limited to, the following areas:

Approximation Theory

Polynomial and rational approximation
Orthogonal polynomials and special functions
Splines, wavelets, and multiresolution methods
Best approximation, interpolation, and extrapolation
Approximation in Banach and Hilbert spaces

Numerical Linear Algebra

Iterative methods for large linear systems
Eigenvalue problems and matrix factorization
Preconditioning and Krylov subspace methods
Low-rank approximation and matrix decomposition

Numerical Methods for Differential Equations

Finite difference, finite element, and finite volume methods
Spectral and pseudospectral methods
Numerical methods for ODEs and PDEs
Stability, convergence, and error estimates

Computational Methods in Approximation

Numerical quadrature and cubature
Function approximation, interpolation, and data fitting
Approximation in high dimensions and sparse grids

Approximation and Numerical Methods in Applications

Computational physics, engineering, and mechanics
Numerical methods in optimization and control
Approximation techniques in data science and machine learning
Inverse problems and regularization methods

Related Topics

Operator-theoretic approaches related to approximation
Functional analytic methods in numerical analysis
Hybrid analytical–numerical methods