Note that we will be using Version 8.0 of these course notes for this semester. Occasionally additional links may be added to this page.

Students should have already taken PHYS-2110/20 (Technical Physics I & II) and/or MATH-2120 (Differential Equations) before taking this course. Though previous computer programming experience is not required, such experience will be beneficial to the student. We will primarily be using the Python programming language throughout most of the course, though we will occasionally also use Fortran, since this old language is still widely used in physics and astronomical research. Introductions on using Fortran, Python, and IDL are given in Appendices B, C, and D, respectively, of the course notes. Appendix E contains a reference guide to the C programming language for those of you interested in using this language in your research.

Computational Physics is a problem-solving course, that is, the measure of a student's progress is demonstrated by the ability to solve numerical problems in physics and astronomy using computer programming methods. Upon completion of this course, the student will possess the basic knowledge of numerical modeling and data analysis that may be required for graduate school or in a position at a technical corporation.

In this course, the student will be using the Linux operating system on the computers in Brown Hall Room 264. Besides learning how to solve numerical problems with a computer, the student also will gain experience writing manuscripts in a scientific-journal style using the mark-up language LaTeX. As a matter of fact, the syllabus and all of the course notes are written in LaTeX with the graphics being created in IDL. LaTeX is used by a large number of professional journals, conference proceedings, and textbooks in both the physical sciences and mathematics.

ETSU Supplemental Syllabus Attachment.

I.	An Introduction to Scientific Computing
II.	Choosing a Programming Language
III.	Preparing Scientific Manuscripts: LaTeX
IV.	Error Analysis and Uncertainties
V.	Methods of Data Fitting
VI.	Numerical Differentiation and Integration
VII.	Matrices and Solutions of Linear Equations
VIII.	Numerical Solutions of Ordinary Differential Equations (ODE)
IX.	Computing Trajectories
X.	Computing Orbits
XI.	Numerical Solutions to Partial Differential Equations (PDE)
App. A:	Operating Systems
App. B:	Scientific Programming Using Fortran
App. C:	Scientific Programming Using Python
App. D:	Scientific Programming Using IDL
App. E:	Scientific Computing Using C
App. F:	How Computers `See' Numbers and Letters
App. G:	Numerical Integration Using Gaussian Quadrature
App. H:	Fourier Analysis and Non-Linear Oscillations

Even though most of the material you will need for this course is on the Course Web Page (where you are at now), there may be times when you will need to log into the D2L Course Website.

To access the ETSU D2L web site, click on the following link:

D2L Web Site Login Page,

then select the PHYS-4007 course link once you log in, in order to get to the D2L Course Web Page.

Homewotrk Assignments will be posted below as the semester ptogresses.

Homework Assignments:

Problem Set 1

• Web site of PCTeX.

• Another free version of LaTeX, can be used at the web site ShareLaTeX. At this site, one does all LaTeXing online through a web GUI.

• Software (Ghostscript and Ghostview) to view and print postscript files on a Windows machine can be found at the GhostScript site.

• Details of programming in PostScript can be found at this link.

• Web site of NetLib, which contains high-quality free-ware, software packages for Fortran.

• Web site of the Numerical Algorithms Group (NAG), which has developed various numerical libraries containing over 1000 user-callable subroutines for solving general applied math problems, including: ordinary and partial differential equations, optimization problems, FFT and other transforms, quadrature, linear algebra, non-linear equations, integral equations, and more.

• Web site of GAMS (Guide to Available Mathematical Software) from the National Bureau of Standards and Technology (NIST).

• A very useful textbook concerning the mathematics of data reduction is Data Reduction and Error Analysis for the Physical Sciences 3rd Edition by Bevington and Robinson. One can buy this book on Amazon at this link (just click).

• Web site of the Digital FORTRAN compiler as sold by Intel. Note that this version of Fortran is one of the best Fortran compilers on the market.

• Web site of the free-ware GNU version of the Fortran compiler. Note that GFortran is an updated and improved version of the g77 Fortran compiler.