Journal of Computational Physics

The Journal of Computational Physics (JCP) focuses on the computational aspects of physical problems. JCP encourages original scientific contributions in advanced mathematical and numerical modeling reflecting a combination of concepts, methods and principles which are often interdisciplinary in nature and span several areas of physics, mechanics, applied mathematics, statistics, applied geometry, computer science, chemistry and other scientific disciplines as well: the Journal's editors seek to emphasize methods that cross disciplinary boundaries.

JCP also encourages the submission of papers that develop innovative methods bridging mathematical, physical modeling and algorithmization, e.g. at the frontier between predictive simulation and machine learning. When addressing problems previously covered by other approaches, a comparison should be provided. As for any paper in JCP, the efficacy, robustness, computational complexity, as well as reproducibility should be addressed.

JCP also publishes short notes of 4 pages or less (including figures, tables, and references but excluding title pages). Letters to the Editor commenting on articles already published in this Journal will also be considered. Neither notes nor letters should have an abstract. Review articles providing a survey of particular fields are particularly encouraged. Full text articles have a recommended length of 25 pages for the initial submission. Submissions significantly exceeding this limit will not be considered. In order to estimate the page limit, please use our template.

Published conference papers are welcome provided the submitted manuscript is a significant enhancement of the conference paper with substantial additions.

Reproducibility, that is the ability to reproduce results obtained by others, is a core principle of the scientific method. As the impact of and knowledge discovery enabled by computational science and engineering continues to increase, it is imperative that reproducibility becomes a natural part of these activities. The journal strongly encourages authors to make available all software or data that would allow published results to be reproduced and that every effort is made to include sufficient information in manuscripts to enable this. This should not only include information used for setup but also details on post-processing to recover published results.