Discipline | Scientific computation |
---|---|
Language | English |
Edited by | Hans De Sterck |
Publication details | |
Former name(s) | SIAM Journal on Scientific & Statistical Computing |
History | 1980 to present |
Publisher | |
Frequency | Bimonthly |
no | |
Standard abbreviations | |
ISO 4 | SIAM J. Sci. Comput. |
Indexing | |
CODEN | SJOCE3 |
ISSN | 1064-8275 (print) 1095-7197 (web) |
Links | |
The SIAM Journal on Scientific Computing (SISC), formerly SIAM Journal on Scientific & Statistical Computing, [1] is a scientific journal focusing on the research articles on numerical methods and techniques for scientific computation. [2] It is published by the Society for Industrial and Applied Mathematics (SIAM). Hans De Sterck is the current editor-in-chief, assuming the role in January 2022. [3] The impact factor is currently around 2.
This journal papers address computational issues relevant to solution of scientific or engineering problems and include computational results demonstrating the effectiveness of proposed techniques. They are classified into three categories: 1) Methods and Algorithms for Scientific Computing. 2) Computational Methods in Science and Engineering. 3) Software and High-Performance Computing. The first type papers focus on theoretical analysis, provided that relevance to applications in science and engineering is demonstrated. They are supposed to contain meaningful computational results and theoretical results or strong heuristics supporting the performance of new algorithms. The second type papers pay much attention to describing novel methodologies for solving a specific problem in computational science or engineering. The information about the application to orient other computational scientists is necessary. The third type papers more concern about novel design and development of computational methods and high-quality software, parallel algorithms, high-performance computing issues, new architectures, data analysis or visualization. However, the primary focus should be on computational methods that have huge impact on scientific or engineering problems.
The modern numerical analysis can be dated back to 1947 when John von Neumann and Herman Goldstine wrote a pioneering paper, “Numerical Inverting of Matrices of High Order” (Bulletin of the AMS, Nov. 1947). This paper commonly is considered one of the first papers to study rounding error and include discussion of what is called scientific computing nowadays. Although, from math history, numerical analysis has a longer and richer history, “modern” numerical analysis is defined by the mix of the programmable electronic computer, mathematical analysis, and the opportunity and need to solve large and complex problems in life applications. The need, such as, ballistics prediction, neutron transport, and nonsteady, multidimensional fluid dynamics pushed the development of computer and depended strongly on developments in numerical analysis and mathematical modeling.
Computer science is the study of computation, information, and automation. Computer science spans theoretical disciplines to applied disciplines.
Numerical analysis is the study of algorithms that use numerical approximation for the problems of mathematical analysis. It is the study of numerical methods that attempt to find approximate solutions of problems rather than the exact ones. Numerical analysis finds application in all fields of engineering and the physical sciences, and in the 21st century also the life and social sciences, medicine, business and even the arts. Current growth in computing power has enabled the use of more complex numerical analysis, providing detailed and realistic mathematical models in science and engineering. Examples of numerical analysis include: ordinary differential equations as found in celestial mechanics, numerical linear algebra in data analysis, and stochastic differential equations and Markov chains for simulating living cells in medicine and biology.
Computational physics is the study and implementation of numerical analysis to solve problems in physics. Historically, computational physics was the first application of modern computers in science, and is now a subset of computational science. It is sometimes regarded as a subdiscipline of theoretical physics, but others consider it an intermediate branch between theoretical and experimental physics — an area of study which supplements both theory and experiment.
Computer science is the study of the theoretical foundations of information and computation and their implementation and application in computer systems. One well known subject classification system for computer science is the ACM Computing Classification System devised by the Association for Computing Machinery.
Theoretical computer science (TCS) is a subset of general computer science and mathematics that focuses on mathematical aspects of computer science such as the theory of computation (TOC), formal language theory, the lambda calculus and type theory.
A computer scientist is a scholar who specializes in the academic study of computer science.
Jack Joseph Dongarra is an American computer scientist and mathematician. He is the American University Distinguished Professor of Computer Science in the Electrical Engineering and Computer Science Department at the University of Tennessee. He holds the position of a Distinguished Research Staff member in the Computer Science and Mathematics Division at Oak Ridge National Laboratory, Turing Fellowship in the School of Mathematics at the University of Manchester, and is an adjunct professor and teacher in the Computer Science Department at Rice University. He served as a faculty fellow at the Texas A&M University Institute for Advanced Study (2014–2018). Dongarra is the founding director of the Innovative Computing Laboratory at the University of Tennessee. He was the recipient of the Turing Award in 2021.
Computational science, also known as scientific computing, technical computing or scientific computation (SC), is a division of science that uses advanced computing capabilities to understand and solve complex physical problems. This includes
Mesh generation is the practice of creating a mesh, a subdivision of a continuous geometric space into discrete geometric and topological cells. Often these cells form a simplicial complex. Usually the cells partition the geometric input domain. Mesh cells are used as discrete local approximations of the larger domain. Meshes are created by computer algorithms, often with human guidance through a GUI, depending on the complexity of the domain and the type of mesh desired. A typical goal is to create a mesh that accurately captures the input domain geometry, with high-quality (well-shaped) cells, and without so many cells as to make subsequent calculations intractable. The mesh should also be fine in areas that are important for the subsequent calculations.
James Albert Sethian is a professor of mathematics at the University of California, Berkeley and the head of the Mathematics Group at the United States Department of Energy's Lawrence Berkeley National Laboratory.
Computational Engineering is an emerging discipline that deals with the development and application of computational models for engineering, known as Computational Engineering Models or CEM. Computational engineering uses computers to solve engineering design problems important to a variety of industries. At this time, various different approaches are summarized under the term Computational Engineering, including using computational geometry and virtual design for engineering tasks, often coupled with a simulation-driven approach In Computational Engineering, algorithms solve mathematical and logical models that describe engineering challenges, sometimes coupled with some aspect of AI, specifically Reinforcement Learning.
David M. Young Jr. was an American mathematician and computer scientist who was one of the pioneers in the field of modern numerical analysis/scientific computing.
Applied mathematics is the application of mathematical methods by different fields such as physics, engineering, medicine, biology, finance, business, computer science, and industry. Thus, applied mathematics is a combination of mathematical science and specialized knowledge. The term "applied mathematics" also describes the professional specialty in which mathematicians work on practical problems by formulating and studying mathematical models.
The Sidney Fernbach Award established in 1992 by the IEEE Computer Society, in memory of Sidney Fernbach, one of the pioneers in the development and application of high performance computers for the solution of large computational problems as the Division Chief for the Computation Division at Lawrence Livermore Laboratory from the late 1950s through the 1970s. A certificate and $2,000 are awarded for outstanding contributions in the application of high performance computers using innovative approaches. The nomination deadline is 1 July each year.
Validated numerics, or rigorous computation, verified computation, reliable computation, numerical verification is numerics including mathematically strict error evaluation, and it is one field of numerical analysis. For computation, interval arithmetic is used, and all results are represented by intervals. Validated numerics were used by Warwick Tucker in order to solve the 14th of Smale's problems, and today it is recognized as a powerful tool for the study of dynamical systems.
INTLAB (INTerval LABoratory) is an interval arithmetic library using MATLAB and GNU Octave, available in Windows and Linux, macOS. It was developed by S.M. Rump from Hamburg University of Technology. INTLAB was used to develop other MATLAB-based libraries such as VERSOFT and INTSOLVER, and it was used to solve some problems in the Hundred-dollar, Hundred-digit Challenge problems.
Horst D. Simon is a computer scientist known for his contributions to high-performance computing (HPC) and computational science. He is director of ADIA Lab in Abu Dhabi, UAE and editor of TOP500.