This is the most fun class I ever had to teach. I have been teaching it every fall to undergraduate and graduate physics students since 2016 (although we sometimes get chemistry and math majors). We are not going to talk about loops, semicolons, and syntax rules in this class. It is understood that you will figure it out on your own. This class is focused around physics! We will solve and simulate a wide range of problems from classical, quantum, and statistical mechanics and the E&M that are not solvable analytically. The kind of topics we end up exploring are:
Trajectories of ballistic rockets. Accounting for air resistance, changing gravity, and Coriolis force.
Nonlinear oscillations and chaotic motion.
Motions of astronomical systems like planetary systems and binary black holes.
Electric fields in all sorts of boundary conditions.
Quantum wave-functions for a Hydrogen atom, nonlinear harmonic oscillator, Leonard-Jones potential.
Random systems like diffusion of sugar in a coffee cup and Ising model of magnetism.
We use python programming language and very little prior knowledge in programming is required to take the class. I have had students with zero programming skills run very cool animated simulations towards the end of the semester.
Computational Physics by Giordano & Nakanishi is the book that I try to follow and recommend.
Numerical solutions to the Navier-Stokes equations (left) and 2D waves (right) by PHYS639 student Nathan Marshall (class of 2019)
The most challenging class I had to teach. I taught it three times in 2014-2016 and would be happy to go back.
It is difficult to name a single "best" textbook on this subject. This is not surprising, the subject is vast, and difficult trade-offs between size, coverage, and what to stress need to be made. I tried to create my own set of lecture notes (maybe to be a book in 20 years?) from the following textbooks:
Mathematics for Physics by Goldbart & Stone is the book I really like. It is a bit terse and hard for self-study though and you will need someone to guide you through it. It is a very good summary of what you need to know.
Mathematics for Physics by Dennery & Krzywicki is another classic I often recommend. It is very concise easy to read and has all essential "XIX century mathematics" covered. You will need a supplementary book for geometry.
An Introduction to Tensors and Group Theory for Physicists by Jeevanjee is another great book if you are interested in the basics of tensors and group theory.
Finally, Data Analysis: A Bayesian Tutorial by Sivia & Skilling is a very good concise guide to Bayesian statistics.
lecturenotes.pdfThis is a K-STATE physics department flagship course. 300+ students take it every semester. Mostly engineering majors but we also have people from all over arts and sciences as well as physics majors and engineers.
I taught it in spring 2020, exactly as COVID hit, and it was kind of a mess. I am teaching it again in spring 2021, and probably every spring after that.
I will be using OpenStax University Physics 1 and OpenStax University Physics 2 free textbooks, and ExpertTA as the homework engine.
The class is very fast paced and at least some familiarity with conceptual physics and algebra based physics is a big plus, but I have had really dedicated students who started from scratch and managed to do very well in the past.
I have had lots of fun teaching this class in 2019. Turns out you can learn quite a lot of physics without math.
I followed this textbook Physics Matters by Trefil & Hazen. It is so good, I find it hard to believe it is out of print.
PHYS101_Syllabus.pdf