Subject offerings of new and developing areas of knowledge in physics intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

The most interesting and difficult problems in physics are strongly correlated systems, where emergent phenomena arise that appear fundamentally different from their constituent pieces. This course will focus on how we can better understand strongly correlated phenomena from an algorithmic perspective. This includes both learning the computational methods used to simulate quantum systems as well as understanding how an algorithmic perspective, such as tensor networks have given us a new way to think about strongly correlated physics. Algorithms that will be covered include the density matrix renormalization group, tensor networks, quantum Monte Carlo, and dynamical mean field theory. Physics examples will include area laws, understanding the sign structure of quantum systems, and quantum computing.