Teaching

The course is an introduction to basic numerical methods commonly used in scientific computation. It is not a course in computer programming. Rather, the focus is on developing models for physical systems, choosing appropriate algorithms to solve the model, validating the simulations, tracking sources of error, and analyzing the data. It is assumed that students have had some experience writing computer codes in a language like C, Fortran, Python, etc.

• Learning goals:  techniques for simulating both continuous and discrete physical systems; skills for verifying code and testing for correctness; analyze data to assess convergence, sources of error, error bars, etc…; design a set of simulations to answer a scientific question.
• The course is offered in Spring.
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Soft condensed matter physics covers materials such as polymers, colloids, surfactants, liquid crystals, which are of paramount importance for modern  (and future) technologies. The course is an introduction to the basic physics concepts needed to rationalize their complex structure and dynamics. Themes discussed in the course will include phase separation, order-disorder transitions, Brownian motion, fluctuation-dissipation theorem, deformation of soft materials.

• Learning goals:  the class of materials referred to as soft materials and their applications; physics concepts needed to rationalize their structure and dynamics; using methods of thermodynamics, statistical mechanics and condensed matter physics to solve problems related to soft materials; identify and use basic concepts of non-equilibrium statistical physics.
• The course is offered in the Fall.
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