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| SIAM Journal on Scientific Computing | |
|---|---|
| Title | SIAM Journal on Scientific Computing |
| Discipline | Computational science |
| Publisher | Society for Industrial and Applied Mathematics |
| Country | United States |
| Frequency | Monthly |
| History | 1979–present |
| Issn | 0895-4798 |
SIAM Journal on Scientific Computing is a peer-reviewed scholarly journal focusing on numerical methods, algorithms, and software for scientific computing. It publishes research articles that advance computational techniques applicable to problems in physics, engineering, and data-driven modeling. The journal serves as a nexus among research communities linked to applied mathematics, numerical linear algebra, high-performance computing, and domain scientists.
The journal was established in 1979 by the Society for Industrial and Applied Mathematics to provide a venue bridging Stanford University-adjacent numerical analysis groups and practitioners from national laboratories such as Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Oak Ridge National Laboratory. Early editorial leadership included figures associated with Courant Institute of Mathematical Sciences, Massachusetts Institute of Technology, and University of California, Berkeley, and the journal quickly became associated with milestones in iterative methods and multigrid that intersected work by researchers at Argonne National Laboratory and Sandia National Laboratories. Throughout the 1980s and 1990s the journal chronicled algorithmic advances tied to the rise of vector supercomputers from companies like Cray Research and massively parallel efforts supported by Department of Energy (United States). In the 2000s the journal adapted to developments in multicore architectures connected to projects at Intel Corporation, IBM, and academic centers such as Princeton University and University of Illinois Urbana-Champaign. More recent decades have seen submissions reflecting collaborations with researchers at California Institute of Technology, ETH Zurich, University of Cambridge, and National University of Singapore.
The journal emphasizes numerical linear algebra, time-stepping schemes, and discretization strategies used in computational science, attracting work from authors at institutions like University of Oxford, École Polytechnique Fédérale de Lausanne, and Tokyo Institute of Technology. Articles frequently address algorithmic foundations underlying software libraries developed in contexts such as BLAS, LAPACK, and projects associated with MPI and OpenMP, and they often reference performance studies performed on systems at National Center for Supercomputing Applications and European Centre for Medium-Range Weather Forecasts. Topics span fast solvers, preconditioning, eigenvalue problems, uncertainty quantification with ties to RAND Corporation collaborations, and reduced-order modeling used in partnerships with NASA and European Space Agency. The journal also covers multiscale methods relevant to research from Harvard University and Yale University, and Monte Carlo techniques that intersect work at Columbia University and New York University.
The editorial board comprises editors and associate editors drawn from leading universities and labs, including faculty affiliated with University of Texas at Austin, University of Michigan, Imperial College London, and Peking University. The journal follows a single- or double-blind peer-review process coordinated through the publisher and administered by editors who solicit reviewers from communities linked to SIAM activity groups and conference programs such as International Conference on Computational Science and Society for Industrial and Applied Mathematics Conference on Computational Science and Engineering. Editorial decisions often rely on referee reports from specialists at institutions like Duke University, Johns Hopkins University, Technische Universität München, and Seoul National University. Special issues have been guest-edited with contributions from organizing committees of workshops held at Argonne and Los Alamos.
Published monthly by the Society for Industrial and Applied Mathematics, the journal issues printed volumes and maintains an online archive accessed by libraries at Cornell University and University of Toronto. SIAM coordinates subscription access and offers individual articles through institutional subscriptions used by research centers such as Max Planck Society and CNRS. The journal participates in digital preservation through arrangements similar to those used by repositories at LOCKSS-participating libraries and university libraries including University of California system. Authors often retain certain rights that permit posting preprints on servers like those used by research groups at Los Alamos and university e-print initiatives at University of Cambridge.
The journal is widely cited in fields influenced by algorithmic innovations from contributors affiliated with Princeton Plasma Physics Laboratory and Flatiron Institute. Its impact is reflected in citation networks overlapping with outlets such as Numerische Mathematik, Journal of Computational Physics, and ACM Transactions on Mathematical Software, and it is read by researchers participating in programs at National Institutes of Health when computational methods intersect biomedical modeling. Reviews in specialist communities note the journal's role in validating robust numerical techniques applied in climate studies associated with Met Office and in structural simulations conducted by teams at General Electric and Siemens.
The journal has published foundational work on multigrid and Krylov subspace methods authored by researchers with affiliations to University of Cambridge, University of Colorado Boulder, and Rutgers University. Influential articles address preconditioners used in large-scale simulations at Los Alamos and scalable eigensolvers applied in materials science collaborations with Lawrence Berkeley National Laboratory. Other high-impact contributions include algorithmic analyses for implicit-explicit integrators tied to studies at California Institute of Technology and spectral element methods developed in conjunction with groups at University of Minnesota and Brown University.
Category:Academic journals Category:Applied mathematics journals Category:Computational science