SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© Thomson Reuters Journal Citation Reports 2015
To calculate the five year Impact Factor, citations are counted in 2014 to the previous five years and divided by the source items published in the previous five years.
© Journal Citation Reports 2015, Published by Thomson Reuters
The Journal of Computational Physics focuses on the computational aspects of physical problems. The scope of the Journal is the presentation of new of significantly improved techniques for the numerical solution of problems in all areas of physics. This is typically accomplished through advanced mathematical and numerical modeling reflecting a combination of concepts, methods and principles are often interdisciplinary in nature and span several areas of physics, mechanics, mathematics, statistics, applied geometry, computer science and other scientific disciplines as well: the Journal seeks to emphasize methods that cross disciplinary boundaries.
The Journal of Computational Physics 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.
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 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.
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