This course explores the connections between information theory and physics. Information theory was developed by Shannon in the 1940s as a tool for optimizing communication systems in telephone networks. But how is the concept of entropy used by communications engineers related to that introduced a century earlier in thermodynamics and statistical mechanics? And what does information theory tell us about the physical limits of computation? Topics studied include communication systems, probability and random variables, discrete information sources, information and entropy, joint and conditional entropy, relative entropy and mutual information, capacity of a noiseless channel, source coding, capacity of a noisy channel, Bayesian probability, maximum entropy and thermodynamics, and Maxwell’s demon.