Course Synopses

Prerequisite: Programming experience. Survey of applications. Survey of hardware and software of a computer installation, interactive computing. Advanced Fortran, program structures, style, documentation, debugging. Machine language basics, data acquisition, equipment control. Use of data tapes, data processing. Monte Carlo techniques. Statistics and data fitting. Basic numerical methods. Laboratory: programming on several computers. The course is designed for the student who has some experience and wishes to broaden his/her knowledge of applications and develop techniques.

This course introduces logarithmic concepts and familiarizes students with the basic conputational tools which are essential for graduate students in computational physics and related areas. In this course, students work toward mastering computational skills, needed to work in classical and quantum physics using the computer. Examples will be drawn from various areas of physics. As the programing language, we will use mostly Python and its scientific library scipy & numpy. To speed up parts of the code, we will also use C++ and fortran90 for short examples, which will be used through the Python interface. This course has no prerequsites except for familiarity with some programming language. It is designed for the student who wishes to broaden his/her knowledge of applications and develop techniques. To follow the course more efficiently, and perform the hands on training, it is desired that students bring their own laptops to the class.