**Computational Physics II**

**Instructor: Peter Love**

KINSC
Link 105

795-6505 (office)

Textbook and supplies

Computational Physics, N. J. Giordano and H. Nakanishi, Pearson, Prentice Hall

We will be using the Python programming language, combined with the numpy package for numerical calculations, the scipy package for scientific python and the matplotlib (pylab) package for plotting. Homework with dependencies on other packages will not be graded.

Online documentation for these packages is available from:

Python Tutorial: http://docs.python.org/tut/tut.html

Python Documentation page: http://www.python.org/doc/

Numpy/Scipy documentation page: http://docs.scipy.org/doc/

Numpy reference guide: http://docs.scipy.org/doc/numpy/reference/

Scipy reference guide: http://docs.scipy.org/doc/scipy/reference/

Plotting with Matplotlib tutorial: http://matplotlib.sourceforge.net/tutorial.html

Matplotlib documentation is available from their website matplotlib

Two 90 minute class meetings per week. Class periods will comprise a short lecture some exercises. Completing reading assignments prior to class is MANDATORY.

**Location and times**:

**Lecture**: TTh 2.30
– 4.00 in KINSC H110 (CS lab). Please
be on time.

**Office hours:** See course website

**Course
Description:**

The first seven weeks of the course will be devoted to lectures and exercises covering several aspects of computational physics. The course will begin by considering effects in Newtonian mechanics which are usually neglected, including air resistance in projectile motion and nonlinear and chaotic behavior of mechanical systems. We will learn how to use numerical simulation to study such effects. We will then turn to the numerical treatment of fields in physics, and consider the numerical solution of Poisson's equation. This enables the solution of problems in electromagnetism which possess insufficient symmetry for analytical treatment. The last portion of the lecture section of the course will move from deterministic algorithms to stochastic algorithms, and we shall consider the numerical treatment of systems in statistical mechanics using Monte Carlo techniques.

The remaining seven weeks of the course will be devoted to a student project. Students may choose from a selection of pre-prepared projects or propose their own. The project will include:

- Application of a numerical technique to the solution of a problem from physical science
- Implementation of a new feature in a numerical calculation.
- Execution of code and production of data
- Analysis and presentation of the data, including consideration of the limitations of the numerical techniques and estimation of errors and uncertainties in the results

Students may propose their own projects or choose a project outline provided by the instructor. The schedule for proposals and completion is

Project proposals due: 03/03/2008

Projects Begin: 03/17/2008

Projects Due: 05/01/2008

**Assignments: **

Each week you will
receive a worksheet containing exercise and examples to work through,
many of which will be taken from your textbook. You will begin this
work in class as we work through examples together, and complete the
work for your homework assignment. Written assignments should be
handed in in class, however, each week you will write several computer
programs, these should be collected into a folder named
(YourName)Week(N) and placed in my public read-write directory on the
storage server.

**Grading procedures:**

**Course
grade** -- will be computed using
the
following weighting:

Written exercises 50%

Project 50%

**Honor Code Issues:**

The important guiding principle of academic honesty is that you must never represent the work of another as your own. The following guidelines should govern your behavior in the course; please request clarification if you find yourself in any doubtful situations.

You may seek assistance for the Instructor or work together with other students (except on individual problems) in doing the weekly assigned exercises and in preparing for class discussions. If working with other students in the course avoid situations in which you are either contributing too much or too little to the collaborative effort. (Neither results in optimal learning, but are not violations of the honor code.) While working together is permitted and even expected and therefore does not need to be acknowledged, merely copying the work of another student without indicating that you have done so is clearly a representation of his or her work as your own and so is a violation of the code.

The exams must be entirely your own work. You must also follow all procedures and respect time limits without deviation.

**Accommodations:**

Students
who think they may need accommodations in this course because of the
impact of
a disability are encouraged to meet with me privately early in the
semester.
Students should also contact Rick Webb, Coordinator, Office of
Disabilities
Services (rwebb@haverford.edu,
610-896-1290) to verify their eligibility for reasonable accommodations
as soon
as possible. Early contact will help to avoid unnecessary inconvenience
and
delays.