Physics, medicine, astronomy — these and other hard sciences share a common need for efficient algorithms, system software, and computer architecture to address large computational problems. And yet, useful advances in computational techniques that could benefit many researchers are rarely shared. To meet that need, Computing in Science & Engineering (CiSE) presents scientific and computational contributions in a clear and accessible format.

Please read our author guidelines and list of Frequently Asked Questions for information on how to submit an article.

CiSE is copublished by the IEEE Computer Society and the American Institute of Physics in technical cosponsorship with the IEEE Antennas and Propagation Society and the IEEE Signal Processing Society.

We want to hear from you. We invite reader comments on everything we cover and everything we don’t.

Scope

Authors for CiSE contribute articles on a broad range of topics, and our readers come from a variety of computational fields.

In addition to full-length articles, CiSE has departments that cover news and analysis, education, industrial applications, book reviews, scientific programming, grid computing, visualization, and conference reports.

CiSE magazine emphasizes articles that help define the field as the interface among the applications (in science and engineering), algorithms (numerical and symbolic), system software, and computer architecture. Such articles should also be readable by specialists from various disciplines; i.e., such articles should overcome the barriers usually created by discipline oriented vocabularies. Articles on topics across this spectrum are welcomed. Example topics include: Role of symbolic computing in computation; Survey of fast multipole methods: A revolution in computational electromagnetic field theory; Grid generation: State-of-the-art; Algorithms to overcome critical slowing down; Building the infrastructure for communications & networking & how to use it; Random number generation; Cellular automata & at-scale problems; Mathematical software: Future needs; Ab initio calculations (chemistry vs. physics approaches); Opinion pieces on trends; Protein polymer simulations & their use in other disciplines; Large-scope computation (combine simulation of fluid flow and structures, … ); Continuing surveys of computational biology, chemistry, physics, etc.; Computer science surveys/tutorials for computational scientists, e.g., what does RISC architecture mean to me?; Does computation complexity theory provide useful information: Now or ever?; Scientific computing in C; University programs in computational science & engineering; Industrial programs & approaches to computational science engineering; Computational plasma-aided manufacturing; Computational approaches to lithography; Software tools such as debuggers, pro filers, and performance evaluation tools; Standardization issues as they affect CS&E, e.g. FORTRAN and POSIX.