Computational science
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
Not to be confused with computer science.In practical use, it is typically the application of computer simulation and other forms of computation from numerical analysis and theoretical computer science to solve problems in various scientific disciplines. The field is different from theory and laboratory experiments, which are the traditional forms of science and engineering. The scientific computing approach is to gain understanding through the analysis of mathematical models implemented on computers. Scientists and engineers develop computer programs and application software that model systems being studied and run these programs with various sets of input parameters. The essence of computational science is the application of numerical algorithms[1] and computational mathematics. In some cases, these models require massive amounts of calculations (usually floating-point) and are often executed on supercomputers or distributed computing platforms.
The term computational scientist is used to describe someone skilled in scientific computing. Such a person is usually a scientist, an engineer, or an applied mathematician who applies high-performance computing in different ways to advance the state-of-the-art in their respective applied disciplines in physics, chemistry, or engineering.
Computational science is now commonly considered a third mode of science , complementing and adding to experimentation/observation and theory (see image).[2] Here, one defines a system as a potential source of data,[3] an experiment as a process of extracting data from a system by exerting it through its inputs[4] and a model (M) for a system (S) and an experiment (E) as anything to which E can be applied in order to answer questions about S.[5] A computational scientist should be capable of:
Substantial effort in computational sciences has been devoted to developing algorithms, efficient implementation in programming languages, and validating computational results. A collection of problems and solutions in computational science can be found in Steeb, Hardy, Hardy, and Stoop (2004).[6]
Philosophers of science addressed the question to what degree computational science qualifies as science, among them Humphreys[7] and Gelfert.[8] They address the general question of epistemology: how does gain insight from such computational science approaches? Tolk[9] uses these insights to show the epistemological constraints of computer-based simulation research. As computational science uses mathematical models representing the underlying theory in executable form, in essence, they apply modeling (theory building) and simulation (implementation and execution). While simulation and computational science are our most sophisticated way to express our knowledge and understanding, they also come with all constraints and limits already known for computational solutions.
Conferences and journals[edit]
In 2001, the International Conference on Computational Science (ICCS) was first organized. Since then, it has been organized yearly. ICCS is an A-rank conference in the CORE ranking.[48]
The Journal of Computational Science published its first issue in May 2010.[49][50][51] The Journal of Open Research Software was launched in 2012.[52]
The ReScience C initiative, which is dedicated to replicating computational results, was started on GitHub in 2015.[53]