Computational science is the field of study that integrates natural science, computer science, and applied mathematics. The problems addressed by computational science typically come from one of the natural sciences. The models developed to describe these problems and the methods used to solve them are often (although not always) mathematical in nature. The implementation of the algorithmic methods requires computer science knowledge for accurate, efficient, and reliable results. The spectrum of scientific problems ranges from models that can be solved on a calculator, through models that require symbolic, numeric, and visualization software, to simulation and optimization models that are so complex that a supercomputer is necessary to solve them
Computational science has now taken up a position along with the traditional use of scientific theory and experimentation as a third paradigm of scientific methodology. This is largely due to the successful employment of the computer in research and development to model complex physical events, to process large quantities of data, and to provide important insights. Because of the increasing importance of computational science, some of these skills must be provided to the undergraduate science student as well as to the graduate student. Computational science courses clearly strengthen a science program. In addition, within a broad-based liberal arts setting, it is also important to provide a balance that includes communication skills and an appropriate combination of ethics and philosophy of science.
Goals of Computational Science Within a Liberal Arts Environment:
Required Courses for the Wittenberg Computational Science Minor:
Contact the Director of Computational Science, Dr. Eric Stahlberg, for more information.
Other Computational Science Programs and Resources: