Difference between revisions of "Simulationsmethoden I"
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 MonteCarlo integration/simulation (Simple vs. Importance sampling)   MonteCarlo integration/simulation (Simple vs. Importance sampling)  
−  Look at Zuse's Z3 computer from 1941: [http://  +  Look at Zuse's Z3 computer from 1941: [http://de.wikipedia.org/wiki/Zuse_Z3 Z3] and 
read something about the first big US computer at Los Alamos [http://www.lanl.gov/history/atomicbomb/computers.shtml Evolving from Calculators to Computers]  read something about the first big US computer at Los Alamos [http://www.lanl.gov/history/atomicbomb/computers.shtml Evolving from Calculators to Computers]  
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== Recommended literature ==  == Recommended literature ==  
<bibentry>frenkel02b,allen87a,rapaport04a,landau05a,newman99a</bibentry>  <bibentry>frenkel02b,allen87a,rapaport04a,landau05a,newman99a</bibentry> 
Revision as of 22:54, 19 March 2009
Overview
Simulationsmethoden in der Physik I:Simulation Methods in Physics I
 Type
 Lecture (2 SWS) and Tutorials (2 SWS)
 The course will take place during the first 6 weeks of the semester with 4 hours per week lectures, and 4 hours tutorial
 Lecturer
 Prof. Dr. Christian Holm (Lecture) and Joan Josep Cerdà, Fatemeh Tabatabaei, Nadezhda Gribova (Tutorials)
 Course language
 Deutsch oder Englisch, wie gewünscht German or English, by vote
 Time and Room
 Lecture times: Tue 11.30  13.00 in V57.04 and Wed 9.45  11.15 in S6.331 (Seminarraum im 6. O.G.)
The lecture is accompanied by handsontutorials which will take place in the CIPPool of the ICP, Pfaffenwaldring 27, U 104 or U 108. 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 fixed in the first lecture.
Scope
The course will give an introduction to modern simulational techniques, like MonteCarlo (MC) and Molecular dynamics (MD) simulations (on and offlattice), and how to solve nonlinear PDEs like the PoissonBoltzmann equation.
Prerequisites
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++).
Certificate Requirements:
 1. Attendance of the exercise classes
 2. Obtaining 50% of the possible marks in the handin exercises
Lecture (still under revision, please keep looking)
Date  Subject 

20.4.  Initial informational meeting  Vorbesprechung 
23.4.  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 
27.4.  2D Random walks (RW) and Selfavoiding random walks (SAW)Ising model I (Phase transitions, Critical phenomena, Finite size scaling) 
30.4.  2D Ising model II (Reweighting, Cluster Algorithm) 
4.5.  Error Analysis (Binning, Jackknife, ...)

7.5.  Molecular Dynamics I (Velocity Verlet algorithm, Reduced units, Langevin thermostat, Potentials, Forces, Atomistic force fields) 
11.5.  Molecular Dynamics II

14.5.  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 (file does not exist!)) 
14.5.  
18.5.  
25.5.  
28.5.  last lecture of Simulationsmethoden I

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.

Rapaport, D. C..
"The Art of Molecular Dynamics Simulation".
Cambridge University Press, 2004.
[DOI] 
D. P. Landau and K. Binder.
"A guide to Monte Carlo Simulations in Statistical Physics".
Cambridge, 2005.

M. E. J. Newman and G. T. Barkema.
"Monte Carlo Methods in Statistical Physics".
Oxford University Press, 1999.