PHYS 7680

Computational Physics

Course Description

Course information provided by the 2025-2026 Catalog.

Develops tools for using computers to model the physical world. Uses examples pulled broadly from core areas of physics: Mechanics, Electricity and Magnetism, Statistical Mechanics and Thermodynamics, and Quantum Mechanics. Focus is on algorithmic thinking, converting mathematical representations into practical algorithms, working with data, and drawing physical conclusions from numerical results. Model problems will involve numerical quadratures, ordinary and partial differential equations, numerical linear algebra, event based simulations, and Monte Carlo techniques. May include modern techniques, such as those drawn from machine learning and artificial intelligence. Instruction will largely be in Julia, with computer labs integrated into lectures. No prior experience with Julia is necessary, but students should have some experience with programming. Graduate versions, PHYS 7680 and ASTRO 7690, require an additional project which is not required in the undergraduate version, PHYS 4480.

Enrollment Information REF-F25 Requires familiarity with core undergraduate curriculum, and some experience with programming.

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