Lecture notes for PHYS3820 Computational Physics at Valdosta State University. This course is designed using Computational Physics With Python by Eric Ayars (2013) and Computational Physics: Problem Solving with Computers by Landau, Paez, & Bordeianu (2007), where it will include summaries of the course material and code implementation/exercises.
Course Description: The course will serve as an introduction to scientific writing and computing, which includes basic computational skills (e.g., Python, GitHub, and LaTeX); Data fitting and interpolation; numerical integration and differentiation; and numerically solving ordinary differential equations (ODEs). To this end, students will complete 3 projects, where the results in each of the first two projects will be presented as a "paper" in the style of Physical Review Letters (2000 words). The topics of these projects are:
- Crater counts on the Moon (data fitting), and
- Projectile motion with atmospheric drag.
The final project will be assigned by the instructor at midterm on one of the following topics:
- Ising Model
- Pandemic SIR modeling
- Quantum particle in a box
- Logistic map
- Damped driven oscillator
- Brachistochrone
- Chaotic scattering
will consist of a longer (3000 words) paper detailing the project, and a 15 minute oral (slide) presentation explaining the project to our peers.
- Landau Computational Physics Course
- Peter Young's course at UCSC
- Computational Physics by Richard Fitzpatrick at UT Austin
- Computational Mechanics at UConn
- Epidemic modeling from Simon Dobson at University of St. Andrews
- Jupyter guide to linear algebra by Ben Vanderlei at the University of the Fraser Valley
- Numerical methods for partial differential equations by by Bernard Knaepen & Yelyzaveta Velizhanina at Universite Libre de Bruxelles
- Python for Dynamics and Evolution of Earth and Planets by Norwegian Research School
Shield:
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