Simulation Techniques for Soft Matter Sciences (SS 2007)
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 12:15  13:45, Phys 1.114
Tutorials: Thu 14:0016:00, 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 MonteCarlo (MC) and Molecular dynamics (MD) simulations (on and offlattice) and PoissonBoltzmann 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 handsontutorials 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 

19.4.  MonteCarlo 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 
26.4.  2D Random walks (RW) and Selfavoiding random walks (SAW)Ising model I (Phase transitions, Critical phenomena, Finite size scaling) 
3.5.  2D Ising model II (Reweighting, Cluster Algorithm) 
10.5.  Error Analysis (Binning, Jackknife, ...) 
17.5.  Holiday 
24.5.  Molecular Dynamics I (Velocity Verlet algorithm, Reduced units, Langevin thermostat, Potentials, Forces, Atomistic force fields) 
31.5.  Molecular Dynamics II 
7.6.  Holiday 
14.6.  Long range interactions (Direct sum, Ewald summation, P3M, Fast Multipole method)
This * long_range_lecture.pdf (216 KB) contains surely too many details, but I will walk you through in class 
21.6.  Simulations of Polymers and Polyelectrolytes 
28.6.  PoissonBoltzmann Theory 
5.7.  Introduction to the Project work: charged infinite rods in ionic solution 
12.7.  Extended tutorial I: project work 
19.7.  Extended tutorial II: project work 
Tutorials
Materials on the tutorials can be found behind the links!
Date  Subject  Tutors 

19.4.  Introductory tutorial  Kai Grass 
26.4.  Random walks  Kai Grass 
3.5.  Monte Carlo: The Ising model I  Marcello Sega 
10.5.  Monte Carlo: The Ising model II  Marcello Sega 
17.5.  Holiday  
24.5.  Error analysis  Joan Josep Cerdà 
31.5.  Molecular Dynamics: LennardJones liquid  Qiao Baofu 
7.6.  Holiday  
14.6.  Introduction to MD simulations with ESPResSo  Mehmet Süzen 
21.6.  Long range interactions: Direct sum and Ewald summation  Joan Josep Cerdà 
28.6.  Visualisation of MD simulations with VMD  Olaf Lenz 
5.7.  Simulation of polymers and polyeletrolytes  Qiao Baofu 
12.7.  Extended tutorial I: project work  Olaf Lenz and Mehmet Süzen 
19.7.  Extended tutorial II: project work  Olaf Lenz and Mehmet Süzen 
Recommended literature

Daan Frenkel and Berend Smit.
"Understanding Molecular Simulation".
Academic Press, San Diego, 2002.
[DOI] 
Mike P. Allen and Dominik J. Tildesley.
"Computer Simulation of Liquids".
Oxford Science Publications, Clarendon Press, Oxford, 1987.