syllabus and schedule
Writing of atomic trajectories to pdb files for import
into molecular visualization programs:
A simple molecular dynamics simulation of the
Weeks 1, 2
Weeks 4, 5
Weeks 5, 6
- read: Statistical
of classical systems and Other ensembles
- do: Start
thinking about a final project topic.
Exercise 4, due 11/7/19
- related reading:
Leach Chapter 8; Frenkel and Smit Chapters 3, 5
Weeks 7, 8
- related reading
Leach Chapter 11; Frenkel & Smit Chapters 7,
Weeks 9, 10
- related reading:
Leach Chapters 8, 11; Frenkel & Smit Chapters
7, 9, 10
Software to install
Programming exercises in the course will require a Python
installation, the NumPy and SciPy add-on libraries for
Python, C/C++ and Fortran compilers, and (optionally)
a Python script editor. In this course,
examples will use the Python 2.7 series (latest version
2.7.2), not the Python 3 series that breaks
compatability with the earlier version of the language.
You are welcome to use Python 3 for your code,
Python, a Python editor, plus all of the support libraries
that you will need for scientific computing are
conveniently combined in the Anaconda
Distribution, which is available on Windows, Mac,
and Linux platforms. You can download it for free.
In particular, it includes a nice Python editor
called Spyder that you are encouraged to explore and use.
Anaconda installs a default set of Python modules that are
generally sufficient for most tasks. However, as a
part of this course we will need to write Fortran code
that is much faster for numercally-intense calculations.
The Fortran code can be compiled into
Python-importable functions, rather automatically.
To enable such a workflow, you will need to add
several additional packages to your Anaconda Installation,
which you can do with the Anaconda Navigator:
- gfortran, an open source Fortran compiler
For Windows machines, you will also need: