PHYS-660 Statistical Mechanics (3)

This course introduces thermodynamics and statistical mechanics. These are the areas of physics that provide general frameworks for understanding how the macroscopic behavior of matter and energy emerges from the microscopic properties of their fundamental constituents and degrees of freedom. Their reach extends well beyond the boundaries of physics, offering essential tools for understanding systems across astronomy, chemistry, biology, and engineering, and providing important mathematical and conceptual connections to machine learning and artificial intelligence. Crosslist: PHYS-460. Permission: instructor. Recommendation: MATH-313 and PHYS-351. Note: Students enrolled at the graduate level explore additional topics including the Ising model, Monte Carlo sampling, and variational approximations that form the mathematical and conceptual foundations of key techniques in machine learning and artificial intelligence, such as energy-based models, Markov Chain Monte Carlo methods, and variational inference.