Physics 115/242, Computational Physics
(Spring 2008)
Instructor: Peter Young, ISB, 212
Time and Place: MWF 9:30 - 10:40, Earth & Marine B214
Office Hour: Wednesdays 2:00-4:00
Note:
This course assumes that you can write a
simple program in one of the following languages: C, C++, or Fortran.
If you are not sure whether you have sufficient fluency in programming,
please see me.
The second half of the course will use Mathematica. No
previous experience of this is required, since the basics will be discussed in
the lectures and a 50 page introduction
has been written for the class (which will be available
below).
You will also need
a knowledge of classical and quantum mechanics at the undergraduate level.
Please email me at
if you have any
questions about necessary prior experience.
I have prepared a considerable amount of material for this class, which will
be available on this web site.
Students' performance will be evaluated from homework assignments and projects,
and a take
home final examination.
Table of contents:
-
Course Description
-
Homework:
-
Handouts:
-
Representation of numbers on the computer
[pdf]
-
Mathematical equivalence does not mean
computational equivalence
[pdf]
-
Numerical Differentiation: Approximation and Roundoff Errors
[pdf]
-
Romberg Integration
[pdf]
-
Slowing down of the rate of convergence in numerical
integration due to
a singularity at the boundary of the region of
integration (and how to avoid this)
[pdf]
-
Numerical results for some root finding algorithms
[pdf]
-
Comparison of methods for integrating the simple harmonic
oscillator
[pdf]
-
Leapfrog (Verlet) and other "symplectic" methods for
integrating Newton's equations of motion
[pdf]
-
The Kepler problem
[pdf]
-
Numerov method for integrating the one dimensional
Schrödinger Equation
[pdf]
-
Sorting routines
[pdf]
Slides demonstrating heapsort
[pdf]
-
Least squares fitting
[pdf]
-
Randu: a bad random number generator
[pdf]
-
Approach to the central limit theorem
[pdf]
-
How to use the C built-in random number generator rand():
randomnos.c
-
A simple random number generator in C:
testrandpy.c
-
Estimating the error bar from the data
[pdf]
-
Monte Carlo simulations in Statistical Physics
[pdf]
-
Introduction to Mathematica
[pdf]
-
Notebooks used in class to illustrate Mathematica (note,
these are rather sketchy; they are simply to complement the
lectures):
-
The zeroes of the Riemann zeta function
[nb]
[pdf]
Peter Young's Home Page
Last modified:
Wed May 14 15:38:12 PDT 2008