ASTRO 7690

Last Updated

  • Schedule of Classes - May 8, 2025 11:33AM EDT

ASTRO 7690
Computational Physics

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.

Last 4 terms offered 2024FA, 2022FA, 2020FA, 2019FA

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Syllabi: none

  •   Regular Academic Session.  Combined with: PHYS 4480, PHYS 7680

  • 3 Credits Sat/Unsat

  •  8861 ASTRO 7690   LEC 001

  •  
    • TR
    • Aug 25 - Dec 8, 2025

    • Mueller, E

  • Instruction Mode: In Person