This is the course web page for the computational physics course. I will put my course notes, the assignments and some sample programs here.

Syllabus and course goals
Grading policy


Lecture notes on topics
Full lecture notes for the whole course (these have not yet been proofread for the sections beyond what we have covered in class)

Notes on a lecture by lecture basis
Notes from week 1: Motivations for learning computational physics
Notes on using Linux and plotting
Notes on approaching computational problems
Notes on pointers and arrays
Notes on Fourier analysis and libraries
Notes on root finding
Notes on round-off errors and numerical integration
Notes on differential equations
Notes on Monte Carlo methods
Notes on fitting data
Sample data set to be fitted in class
Unknown data set 1
Unknown data set 2
Unknown data set 3


Assignments for the course
Assignment 1: simple plotting with gnuplot
plotdata_intro , the file you should plot in the first assignment
Assignment 2: simple algorithm development
Essay assignment description
Calculator assignment
Pulsar assignment
Note: to compile with gsl, you need to add two more flags that were not in the notes, because the gsl libraries' location has been moved since I wrote the notes:
-I /home/tmacc/gsl/include -L /home/tmacc/gsl/lib
Test data for fake pulsar assignment
Newton's method assignment
Integration assignment
Differential equation assignment
Monte Carlo assignment
Modelling assignment
Final project
Final project assignment


Sample programs for the course
helloworld.cc
compute_sines.cc
read_numbers.cc
dot_product.cc
test_gsl.cc
fake_pulsar.cc
fake_pulsar_streamio.cc
read_numbers_stream.cc
sum_1_n.cc
solve_quadratic.cc
pendulum.cc
pendulum_rk4.cc
Other useful information
Sample LaTeX file with notes for the differential equations lecture
The C++ Resources Network, a good place to look up information about syntax for C++ programming
The GNU Scientific Library, a repository of well-tested functions for C++ programmers that implement a wide range of numerical algorithms of use to scientists
Numerical Recipes Web site, links to a free online version of the Numerical Recipes book, which is a good place to learn the basics of numerical analysis