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Physics Simulations in Python

A computer program that models the behavior of a physical system is called a computer simulation Creating and using computer simulations is an integral part of modern science and engineering This manual is intended for a hands-on introductory course in computer simu- lations of physical systems using the Python programming language

How do I add a GitHub repository to a computational physics topic?
Add a description, image, and links to the computational-physics topic page so that developers can more easily learn about it. To associate your repository with the computational-physics topic, visit your repo's landing page and select "manage topics." GitHub is where people build software.
What topics are covered in computational physics?
Subsequent chapters cover a range of further topics in computational physics, including the solution of linear and nonlinear systems of equations, the solution of ordinary and partial differential equations, Fourier transforms, stochastic processes, and Monte Carlo methods. For a full table of contents, see here .
What are some examples of physics problems?
Practice at Physics Problems: Moment of inertia, magnetic field of a wire, radioactive decay, harmonic oscillators, free fall, rolling balls Application to Advanced Problems: Chaotic systems, heat equation, 3-body problem, spaceship mission, coupled pendulums, magnetism, graphene & quantum physics

Chapters For Download

Here are several complete book chapters on Python computational physics.You're welcome to download these chapters, print them out, use them inclass, or just read them for yourself. Comments or questions are welcome. 1. Chapter 2: Python programming forphysicists– This chapter gives an introduction to the Pythonlanguage at a level suitable for reade

Appendices

Here are three useful appendices that go with the chapters above: 1. Appendix A: Installing Python– How to install Python on your computer, plus some additionalpackages that you'll need to do the examples and exercises in the chaptersabove 2. Appendix B: Differences between Pythonversions– A summary of the differences between versions 2and 3 of Pyt

Example Programs

The following files contain copies of the example programs from thechapters above. All programs are in Python version 3, but they will workfine in version 2 also (technically version 2.6 or later) if you add thisline to the beginning of the program: Chapter 2: 1. evenodd.py– Check twointegers to ensure one is even and the other odd 2. fibonacci.py–

Data Sets

Here are some data sets that accompany the examples and exercises in thechapters above: 1. altitude.txt– Altitudeabove sea level, or depth below it, of points on the Earth'ssurface, measured on a grid 2. circular.txt– Data filefor the density plots in Figure 2.3 3. stars.txt– Catalog oftemperatures and magnitudes for 7860 nearby stars 4. stm.txt– S

Miscellaneous Useful Code

Here are a few other pieces of Python code that are useful for some of theexercises. 1. banded.py– Solve atridiagonal or banded system of linear equations using Gaussianelimination 2. colormaps.py–Definitions of some useful colormaps for density plots 3. dcst.py– Perform forward andinverse fast cosine and sine transforms 4. gaussxw.py– Calculatepos

Computational Physics in Python Rutgers University 2021 lecture 1

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