MATSE 485/CSE 485/Phys 466: Atomic-Scale Simulations
Homepage: http://web.mse.uiuc.edu/courses/mse485/
Text: "Polymer Physics" by M. Rubinstien and R. H. Colby
Supplementary Text: Computer Simulation of Liquids, M.P. Allen and D.J. Tildesley (Oxford Univ. Press) 1997 (Reprinted).
Course Developed Software:
In-course developed software for teaching is at http://web.mse.uiuc.edu/matse390/codes.html
Catalog Description, Prerequisites and Schedule:
To learn and apply some of the fundamental techniques of Monte Carlo and Molecular Dynamics used in (primarily classical) simulations in order to help understand and predict properties of microscopic systems in materials science, physics, chemistry, and biology. Numerical algorithms, connections between simulation results and real properties of materials (structural or thermodynamic), as well as statistical and systematic error estimation using real simulation programs will be emphasized. A simulation project composed of scientific research, algorithm development, and presentation is required. Prerequisite: A course in statistical mechanics, or statistical thermodynamics, and prior experience in programming in C, C++, or Fortran, or consent of instructor. 3 hours or 1 unit.3 lecture hours/week
Course Objectives:
Important areas of emphasis will be connections between the
simulation results and real properties of materials (structural
or thermodynamic quantities), as well as numerical algorithms
and systematic and statistical error estimations. Methods and
applications include:
1. Introduction to concepts, use, limitations, and applications
of Molecular Dynamics, including integration algorithms, static
and dynamic correlations functions and their connection to order
and transport.
2. Introduction to concepts, use, limitations, and applications
of Monte Carlo and Random Walks, including variance reduction,
random number generation, and Metropolis algorithms.
3. Introduction to concepts, use, limitations, and applications
of Kinetic Monte Carlo, heat diffusion, Brownian motion, etc.
4. Simulations of Phase Transitions (melting-freezing, calculating
free energies)
5. Simulations of Polymers (growth and equilibrium structure)
6. Quantum Simulation Zero temperature and finite temperature
methods.
7. Optimization techniques, such as simulated annealing, genetic
algortithms.
(Choice of Kinetic Monte Carlo or Quantum Monte Carlo is by instructor.)
Course Outcomes:
1. Familiarity with the basic concepts, use, and limitations
of Molecular Dynamics and Monte Carlo methods for simulation of
materials properties through both theoretical development and
personal application of methods.
2. Introduced to and application of concepts of random number
generation, statistical and systematic error estimation, and variance
reduction.
3. Application of methods to phase transitions, polymer growth,
and kinetic MC, and familiarity with difficulties and limitations
of methods for such.
4. Introduced to optimization ideas and techniques via simplistic
homework simulation.
Assessment Tools:
1. Homework problems (including computer simulation using Engineering
WorkStations) involving fundamental knowledge and application
of each topic.
2. Submit and orally defend proposed group project due at end
of semester.
3. Written mid-term examination on fundamentals of subset of topics.
4. Final Group Project, in lieu of Final Exam, designed to test
the student's understanding of concepts and their ability to apply
his/her knowledge. Project is graded on any pertinent algorithmic
and scientific content and on both oral and electronic report
presentations.
See http://web.mse.uiuc.edu/matse390/projects/index.html for past
reports.
Prepared by:
Duane D. Johnson, March, 2001