Computational Physics (PHYS 60050, CRN 31767)

• General Information (Syllabus)

• Lecture 1. Introduction. Slides. See the Ananconda installation videos below, under LINKS and install it on your computer. You can watch either, or both. You just need the installation parts, but they go more in-depth, if you are interested. In class we will use the Spyder IDE, which is part of the Anaconda distribution; what Toufiq shows later uses Visual Studio Code, we don't need that.
• Lecture 2. Variables, operators and control flow . Slides. In-class Python codes.
• Lecture 3. Containers and For Loops . Slides. In-class Python codes. updated 02/02/23
• Lecture 4. Functions, Modules, Packages . Slides. In-class Python codes. updated 02/02/23
• Lecture 5. Input and Output . Slides. In-class Python codes
• Lecture 6. Plotting . Slides. In-class Python codes
• Lecture 7. Numpy . Slides. In-class Python codes.
• Lecture 8. Data Analysis with Python I. . Slides. In-class Python codes.
• Lecture 9. Data Analysis with Python II. . In-class Python codes.
• Lecture 10. Random events, probabilities. Slides. Codes.
• Lecture 11. Monte Carlo methods. Slides.Codes.
• Lecture 12. Markov Chain Monte Carlo. Slides. Codes.
• Lecture 13. Numerical integration and differentiation. Slides. Codes.
• Lecture 14. Equation solving. Slides. Codes.
• Lecture 15. Ordinary differential equations I. Slides. Codes.
• Lecture 16. Ordinary differential equations II. Slides. Codes.
• Lecture 17. Partial differential equations I. Boundary value problems. Slides. Codes.
• Lecture 18. Partial differential equations II. Initial value problems. Codes.
• Lecture 19. Partial differential equations III. Variational formulation, advanced methods. Codes.
• Module 1. Computational Statistical Mechanics: the Ising model Slides. Codes.
• Module 2. Introduction to Machine Learning. Slides. Codes.
• Module 3. Machine Learning: Classification. Slides. Codes.
• Module 4. Machine Learning: Dimension reduction, PCA. Slides. Codes.

1. HW1  (due Mon Jan 30, 11:59pm);   Solutions  
2. HW2  (due Mon Feb 13, 11:59pm);   Solutions  
3. HW3  (due Mon Feb 27, 11:59pm);  Solutions  
4. HW4  (due Thu Mar 9, 11:59pm);  Solutions  
5. HW5  (due Mon Mar 27, 11:59pm);  Solutions  
6. HW6  (due Mon Apr 10, 11:59pm);  eclipse data NOTE: corrected sign errors in Pr. 3 Solutions  
7. HW7  (due Wed Apr 19, 11:59pm);  Solutions  

• How to code it? - The two lists problem   codes
• Banach's matchboxes problem - analytic derivation of the formula.
• Making animations (slides)   codes

• Solar system satellites dataset from https://devstronomy.com/#/datasets  
• Chicago crimes dataset from the 2001 - 19 period.   You can get the full dataset from 2001 to present from here.
• Midterm exam dataset: exoplanets  
• Final exam dataset: clothing items MNIST dataset  

1. Midterm exam. (due Sat, Mar 11th, midnight (11:59pm) ).  Solutions  
2. Final exam. (due Sun, May 7th, 11:59pm). Solutions  

• Anaconda installation videos for Lecture 1:
  • by Thoufiq
  • by Corey Schafer
• How to download stock market data into Python:
  • Free Live Stock Data in Python with IEX Cloud
  • Get Real-Time Stock Market Data in Python using IEX Cloud and Pandas
• An introduction video for Object oriented Programming in Python, for beginners: Link
• Some links about jobs and Python
  • 8 World-Class Software Companies That Use Python
  • python-development-skills-are-in-great-demand
  • most-in-demand-tech-skills-javascript-java-python
  • programming-languages-in-highest-demand
  • half-of-the-high-paying-jobs-in-america-now-require-this-skill-2016
• Online courses for learning Python
• A nice resource for honing your coding skills is Project Euler:
  • It enlists hundreds of problems of varying difficulty and their Python solutions.
• Access Rosenblatt's "Principles of neurodynamics. Perceptrons and the theory of brain mechanisms." book here.

• Profiling your code to find bottlenecks: How to and profiling doc.
• Python parallelism Efficiently Exploiting Multiple Cores with Python.
• Amazon's own machine learning courses and algorithms are now available . See the link at the bottom of that page to access the materials on Amazon.