Simulation Techniques for Soft Matter Sciences (SS 2008)

Overview

Type

Lecture (2 SWS) and Tutorials (2 SWS)

Lecturer

PD Dr. Christian Holm (Lecture) and working group (Tutorials)

Course language

English

Time and Room

Lecture: Thu special appointment, FIAS Room 200
Tutorials: Thu 16:00-18:00, Phys 1.120

Soft matter science is the science of "soft" materials, like polymers, liquid crystals, colloidal suspensions, ionic solutions, hydrogels and most biological matter. The phenomena that define the properties of these materials occur on mesoscopic length and time scales, where thermal fluctuations play a major role. These scales are hard to tackle both experimentally and theoretically. Instead, computer simulations and other computational techniques play a major role.

The course will give an introduction to the computational tools that are used in soft matter science, like Monte-Carlo (MC) and Molecular dynamics (MD) simulations (on- and off-lattice) and Poisson-Boltzmann theory (and extensions).

Prerequisites

The course is intended for participants in the Master Program "Computational Science", but should also be useful for FIGSS students and for other interested science students.

We expect the participants to have basic knowledge in classical and statistical mechanics, thermodynamics, electrodynamics, and partial differential equations, as well as knowledge of a programming language (preferably C or C++).

Lecture and tutorials

The lecture is accompanied by hands-on-tutorials which will be held in the computer room (Physics, 1.120). They consist of practical excercises at the computer, like small programming tasks, simulations, visualisation and data analysis.

The tutorials build on each other, therefore continous attendance is expected.

The dates of the tutorials will be scheduled in the first lecture.

Lecture

Date	Subject
10.4.	Monte-Carlo integration/simulation (Simple vs. Importance sampling) Look at Zuse's Z3 computer from 1941: Z3 and read something about the first big US computer at Los Alamos Evolving from Calculators to Computers
17.4.	2D Random walks (RW) and Self-avoiding random walks (SAW)--Ising model I (Phase transitions, Critical phenomena, Finite size scaling)
24.4.	2D Ising model II (Reweighting, Cluster Algorithm)
1.5.	Holiday
08.5.	Error Analysis (Binning, Jackknife, ...)
15.5.	Molecular Dynamics I (Velocity Verlet algorithm, Reduced units, Langevin thermostat, Potentials, Forces, Atomistic force fields)
22.5.	Holiday
29.5.	Molecular Dynamics II
5.6.	Long range interactions (Direct sum, Ewald summation, P3M, Fast Multipole method) This pdf file long_range_lecture.pdf (216 KB) contains surely too many details, but I will walk you through in class. In case you like to have some more background material, here is a review article by A. Arnold and me about this topic (arnold05a.pdf ())
12.6.	Continuation of long range lecture, beginning of How to simulate Polymers and Polyelectrolytes.
19.6.	Continuation on How to simulate Polymers and Polyelectrolytes and background of Poisson-Boltzmann Theory.
26.6.	Introduction to the Project work: charged infinite rods in ionic solution-comparison to PB theory. CompMethods.pdf (1.65 MB) A good background reading is the thesis of M. Deserno thesis_deserno.pdf (3.57 MB)
03.7.	Extended tutorial: project work
July.	Oral examination in my office FIAS 02.301, date to be fixed .

Tutorials

Materials on the tutorials will be sent to students by tutors via mail!

Date	Subject	Tutors
17.4.	Introductory tutorial, random walks	Nadezhda Gribova
24.4.	Monte Carlo: The Ising model I	Marcello Sega
1.5.	Holiday
8.5.	Monte Carlo: The Ising model II	Marcello Sega
15.5.	Error analysis	Joan Josep Cerdà
22.5.	Holiday
29.5.	Molecular Dynamics: Lennard-Jones liquid	Florian Dommert
5.6.	Introduction to MD simulations with ESPResSo	Mehmet Süzen
12.6.	Long range interactions: Direct sum and Ewald summation	Kai Grass
19.6.	Visualisation of MD simulations with VMD	Olaf Lenz
26.6.	Simulation of polymers and polyeletrolytes; Project work

Recommended literature

• Daan Frenkel, Berend Smit.
  Understanding Molecular Simulation: From Algorithms to Applications.
  Part of Computational Science, volume 1. Edition 2.
  Academic Press, San Diego, 2002. ISBN: 978-0-12-267351-1.
  [DOI]
• Mike P. Allen, Dominik J. Tildesley.
  Computer Simulation of Liquids.
  Part of Oxford Science Publications. Edition 1.
  Clarendon Press, Oxford, 1987.
  
• D. C. Rapaport.
  The Art of Molecular Dynamics Simulation.
  Edition 2.
  Cambridge University Press, 2004. ISBN: 9780511816581.
  [DOI]
• D. P. Landau, K. Binder.
  A guide to Monte Carlo Simulations in Statistical Physics.
  Edition second edition.
  Cambridge, 2005.
  
• M. E. J. Newman, G. T. Barkema.
  Monte Carlo Methods in Statistical Physics.
  Edition 2002 edition.
  Oxford University Press, 1999.