Typical problem areas include the study of parallel algorithms, simulating particle problems, and simulating field equations. This course covers the modeling of scientific and engineering problems, computational methods, possibly parallel applied to problems. Topics may include matrix methods, numerical methods for ordinary and partial differential equations, random numbers, and optimization techniques. Typically, three applications in science and engineering are studied in some detail and the students' work is one large project. Application areas have included statistical analysis of experimental data, CFD Navier-Stokes equations using finite differences, simulating black holes using finite elements, and the Ising model using Monte Carlo techniques.
Students also take courses in algorithms, numerical analysis, and parallel processing.
The Ph.D. level Certificate in Computational Science requires coursework similar to the Master's level Certificate and that the research of the dissertation make a contribution to the field of Computational Science. The Computational Science minor requires the two semester sequence of lecture and lab in computational science for science and engineering problems, CPS311,312,313,314. It also requires a senior project, which may be done in the course CPS 451 and two other electives. More details on the requirements for these programs can be found in this description of computational science academic programs. To apply for any of these programs, send to Computational Science Program, School of Computer and Information Science, Syracuse University, Syracuse, NY 13244.