General Information:

• Course description
• Course outline
• Text and books on reserve in Physics Library
• Grade
• Computing

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Course description:

The combination of computers and physics presents exciting opportunities for tackling problems not only in physics, but also in areas spanning chemistry, biology, material science, engineering, and even financial and economic modeling. This course teaches the fundamentals of computer simulations and how they are used to treat real problems that are otherwise intractable. Examples of such real problems include particle transport (e.g., in accelerator physics), fluid and traffic flows, earthquakes and forest fire, fracture mechanics, quantum physics, protein folding, and phase transitions and statistical physics.

The course is for graduate students and advanced undergraduate students in physics and related disciplines. It assumes knowledge of calculus, mechanics, some statistical physics, and basic quantum mechanics. Extensive computer background is not required; homework and course projects are designed to facilitate a steady accumulation of hands-on experience.

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Preliminary course outline:

• The ``random point of view.'' (5 lectures)
  Probability distribution and characterization; random numbers; basic Monte Carlo sampling; the central limit theorem and characterization of errors; random walks and diffusion; particle transport simulations.

• Just how far can you go with randomness? (6 lectures)
  Markov chains and the Metropolis algorithm; Monte Carlo integration; phase transitions (melting); simulated annealing and the traveling salesman problem; protein folding; quantum mechanics by random walks.

• More computer Experiments. (4 lectures)
  fractals; percolation and renormalization group; cellular automata; forest fire; earthquakes; game of life.

• Newton's laws in real life. (5 lectures)
  basics of finite-difference and related methods; bicycle racing; baseball; golf; the solar system; molecular dynamics; properties of a dilute gas; the melting transition again.

• Potentials, fields, and waves. (4 lectures)
  Electric potentials and fields; potentials and fields near charges; motion of a string; fluid and traffic flow.

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Textbook: On reserve

Harvey Gould, Jan Tobochnik, and Wolfgang Christian, An introduction to computer simulation methods: applications to physical systems, 3rd edition, Addison-Wesley, 2006

Books on reserve in Physics Library:

M.T.Heath, Scientific computing : an introductory survey, New York : McGraw-Hill, c1997.

N.J.Giordano, Computational Physics, Prentice Hall, 1997.

M.H. Kalos and P.A. Whitlock, Monte Carlo Methods, Vol I, Wiley, 1986.

W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes -- the Art of Scientific Computing, Cambridge.

P.L. DeVries, A first course in computational physics, Wiley, 1994.

A. L. Garcia, Numerical Methods for Physics, Prentice Hall, 1994.

M.P. Allen and D.J. Tildesley, Computer Simulation of Liquids, Oxford, 1987.

S. E. Koonin and Dawn Meredith, Computational Physics, Addison-Wesley, 1989.

D. Frenkel and B. Smit, Understanding molecular simulations, 2nd edition, Academic Press, 2002.

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Grade: (not entirely based on a curve!)

• 60% --- homework (6 sets)
• 10% --- classroom participation and overall effort
• 15% --- mid-term
• 15% --- final project and oral presentation

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Computing:

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• Some things to note when computing.
  • Always 'nice' your jobs, e.g., 'nice executable_name &' in unix. Use the maximum level (lowest priority) for any job that you expect to run more than a few minutes. Do 'man nice' to find out how.

  • Heavy number crunching should not be done on departmental servers.

  • If you need to use xmaple on spiffy, please:
    • avoid busy hours;
    • look around (e.g., with the command 'top') and see how much is going on before deciding to launch a session.

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