Communications in Applied Mathematics and Computational Science publishes high-quality and original research at the intersection of applied mathematics and computational science. Contributions that demonstrate fundamental advances in mathematics, numerics, algorithms and computing are particularly encouraged. The journal also welcomes submissions reporting on highly specialized numerical methods, algorithms or tools, provided such work is worthy of a tailored discussion and represents a cogent stepping stone toward broader objectives in advancing the state-of-the-art.

The journal welcomes papers in a variety of forms, including research articles, communications, short notes, and longer-length detailed studies, as appropriate. In all cases, contributions should be anchored by compelling computational experiments, e.g., to demonstrate the characteristics or utility of any developed methods. Results from any particular scientific applications are welcome, however the focus should be on the ideas and methods rather than any physical conclusions.

CAMCoS welcomes research across the full gamut of applied mathematics and computational sciences, both traditional and contemporary. Areas include

mathematical and numerical frameworks for multi-scale and/or multi-physics coupling;
analysis, discretization, optimization, and/or numerical algorithms for ordinary, partial, and stochastic differential equations;
scalable solvers and high-performance computing methods;
advances in randomized and deterministic numerical linear algebra, optimization, and computational harmonic analysis;
mathematically rigorous and computationally efficient methods for the analysis of scientific data;
mathematical analysis of computational machine learning (ML) / artificial intelligence (AI) methods;
the use of ML and AI methodologies to advance mathematical modeling and numerical algorithm development;
analysis and algorithms for dimension reduction, reduced order modeling, uncertainty quantification, or approximation theory;
mathematical and algorithmic approaches for solving inverse problems;
mathematical models and numerical methods for quantum mechanics, statistical mechanics, and quantum computing.