Course
description
The goal of this course is to equip students of a variety
of backgrounds with the basic skills necessary to design
and carry out molecular simulations:
- formulation of both atomistically detailed and
simplified molecular models
- basic and advanced algorithms for computing
thermodynamic and kinetic behavior
- modern analysis techniques and visualization
packages
- physical intuition for developing and interpreting
new simulation experiments
- knowledge of computational issues and methods for
improving efficiency
Topics discussed in the course include: ab initio methods,
classical semi-empirical force fields, energy
minimization, molecular dynamics techniques, Monte Carlo
methods, free energy algorithms, advanced sampling
strategies, coarse-graining and multiscale methods, and
rare events algorithms. Case studies in soft
condensed matter, materials, and biophysics will be
presented throughout the lecture material.
This course focuses more on concepts, algorithms, and
tools than on specific programming styles and languages,
although enrolling students should have had at least
minimal exposure to coding or mathematical software (e.g.,
have used any of Matlab, Mathematica, C, C++, Visual
Basic, or Fortran). From early in the course, a
strong emphasis will be placed on students performing and
visualizing their own simulation projects.
Coursework consists of a series of exercises in which
students write their own small simulation programs based
on methodologies discussed in lecture, run these, and
provide analysis of results. At the end of the
course, students will complete a project in which they
simulate a system of interest, based on current topics in
the literature, using methodologies discussed in
class. The course will present Python as a
particularly powerful and freely available programming
platform for scientific computing and highly encourage its
use.
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Course
information
| instructors |
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Professor M. Scott Shell
shell (at) engineering.ucsb.edu
Engineering II 3321
office hours: Tu 12:15-1:15pm, Wed 2-3pm, or drop
by if my office door is open, or by
appointment
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| schedule |
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TR
11:00-12:15pm,
Engineering II 3301
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| textbook |
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Understanding
Molecular Simulation: From Algorithms to
Applications (2nd edition)
Daan Frenkel and Berend Smit, Academic Press
(2007)
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| grading |
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50%
simulation
exercises, 50% final project
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Course syllabus and schedule
Download here.
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