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Prof. Dr. Nils Blümer |

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Attention: these pages are mostly outdated! For current information on Nils Blümer, see web pages at the KU.
Computer simulations in statistical physics
Lecture in winter semester 2007/2008
N. Blümer, P. Virnau
Lecture hours: 3 V + 1 Ü (lectures + tutorials)
Time and Place: Tuesdays 10 - 12 am, Lorentzraum (Staudingerweg 7, 05-127), Thursdays 10 - 12 am, Seminarraum A (Staudingerweg 9, 01-219)
Target group: physics students after Vordiplom, PhD students
Univis entry: see list of lectures by N. Blümer in WS 2007/2008
Consultation hours: after lectures or by appointment
Notes: The lecture is given in english.
Contents / lecture notes
- Lecture 0 (2007/10/23)
- Overview over contents of lecture
- Questionnaire
- Introductory beamer presentations
- Lecture 1 (2007/10/25) comp-sim-ws0708-v01.pdf
- Start Chapter I: Statistical analysis of time series
- Trace, transient, autocorrelation, probability distribution, moments, probability distributions of sums/averages, central limit theorem
- Unbiased estimators for mean and variance for data set without autocorrelation
- Lecture 2 (2007/10/30) comp-sim-ws0708-v02.pdf
- Improved estimator for variance for data set with autocorrelation
- Estimator for variance / standard deviation of average
- Practical data analysis using the programs gnuplot and stats
- Lecture 3 (2007/11/6+8) comp-sim-ws0708-v03.pdf
- Solutions for HW (statistical data analysis): comp-sim_hw2a.pdf
- Random number generators
- Lecture 4 (2007/11/8) awk_tutorial.pdf
- Lecture 5 (2007/11/13) awk_tutorial.pdf
- Lecture 6 (2007/11/15)
- Lecture 7 (2007/11/20)
- Lecture 8 (2007/11/22) comp-sim-ws0708-v08.pdf
- Ising model: history, hamiltonian, interpretation, and relation to more general spin models
- Excursion: statistical physics in the canonical ensemble
- Phase transitions, thermodynamic limit, and critical exponents
- Boundary conditions for finite systems
- Metropolis Monte Carlo for the Ising model
- Lecture 9 (2007/11/27) comp-sim-ws0708-v09.pdf
- Addendum: impossibility for importance-sampline MC to measure Z, F, or S
- Ising model: mean-field solution, solutions in d=1 and d=2
- Ising model: critical temperatures and critical exponents
- Finite-size scaling (FSS)
- Lecture 10 (2007/11/29) comp-sim-ws0708-v10.pdf
- Finite-size scaling, continued; Binder cumulant
- Solution of home work: 2d Ising model comp-sim_hw4.pdf
- Lecture 11 (2007/12/04)
- Lecture 12 (2007/12/06)
- Lecture 13 (2007/12/11) num-meth-ss07-v07.pdf
- Cluster Monte Carlo methods: Kasteleyn-Fortuin mapping, Swendson-Wang update, Wolff update
- Tutorial (2007/12/13)
- Q/A for homework (cluster MC Ising)
- Lecture 14 (2007/12/18)
- Lecture 15 (2007/12/20)
- Lecture 16 (2008/01/08)
- Lecture 17 (2008/01/10)
- Lecture 18 (2008/01/15) comp-sim-ws0708-v18.pdf
- Solutions for homework (PV)
- Chapter ?: Quantum Monte Carlo Simulations
- Classification of QMC methods
- Path integral Monte Carlo (PIMC)
- Lecture 19 (2008/01/17) comp-sim-ws0708-v19.pdf
- Path integral Monte Carlo (PIMC), continued
- Lecture 20 (2008/01/22) comp-sim-ws0708-v19.pdf
- Path integral Monte Carlo (PIMC), continued
- Lecture 21 (2008/01/24) comp-sim-ws0708-v21.pdf
- PIMC: Observables
- Quantum Heisenberg model
- World line quantum Monte Carlo simulations
- (2008/01/29) comp-sim-ws0708-v22.pdf
- WL-QMC: plaquette weights, Metropolis/heat bath rules, energy and other observables
- (2008/01/31) comp-sim-ws0708-v23.pdf
- (2008/02/05)
- Project presentations (2008/02/07)
Problem sets / Tutorials / Sample codes
- 2006/10/26 Variance estimator: bias for autocorrelated data?
- 2007/10/30 Data analysis: analyse the following sample data (solutions: comp-sim_hw2a.pdf)
- set 1 (10, 100, 1000, 10000 numbers)
- set 2 (10, 100, 1000, 10000 numbers)
- set 3 (10, 100, 1000, 10000 numbers)
- set 4 (10, 100, 1000, 10000 numbers)
- set 5 (10, 100, 1000, 10000 numbers)
- set 6 (10, 100, 1000, 10000 numbers)
- set 7 (10, 100, 1000, 10000 numbers)
- set 8 (10, 100, 1000, 10000 numbers)
- set 9 (10, 100, 1000, 10000 numbers)
- 2007/11/22 Monte Carlo simulation of 2D Ising model
(solutions: comp-sim_hw4.pdf)
- Write a Monte Carlo program for computing energy and magnetization of the 2 D square Ising model using single-spin flips (possibly using the template C program linked below).
- Compute E(T), |M(T)| in a useful temperature range for lattices with linear sizes between about 4 and 20-40
- Plot Binder's 4th order cumulant U4(T)=1-〈M4〉/(3〈M2〉2) and determine Tc
- Optional: determine specific heat and susceptibility at selected temperatures
- raw statistics data: directory, README
- 2007/12/11 Cluster algorithms for Monte Carlo simulation of 2D Ising model (solution: comp-sim_hw4.pdf, code: mc_Ising_2D_v06.c)
- Implement Wolff or Swendsen-Wang cluster update algorithm
- Compare autocorrelation times for energy and/or magnetization at the critical temperature with single-spin flip algorithm
- Plot "smart observables" (for Tc determination) near Tc and show improvements by cluster algorithm
- Discuss the melting of a magnet at T>Tc; example for freezing at T<Tc: MC_Ising_freeze.png
- Sample codes and tools
Announcement (from annotated list of lectures)
Contents
This lecture covers the basic computer simulation methods for
systems of many particles, particularly as relevant in condensed
matter theory. The focus is on molecular dynamics and
Monte Carlo simulations, the essential methods for
classical statistical physics. While the former is a deterministic
method, the latter is stochastic. Goal of the lecture is to convey
for both methods an understanding of the theoretical background and
the principles of numerical implementations; however, we also want
to discuss the most relevant tricks and possible pitfalls. Both methods
can be generalized for the solution of path integrals of quantum
many-particle systems; these advanced topics are planned to be
addressed in the later parts of the lecture. In particular, we
will present the principles of the most important quantum
Monte Carlo algorithms.
We will gladly adjust the selection and depth of topics depending
on prior knowledge and interests of the participants, in particular
in the second half of the semester. Active participation in the
tutorials is expected. In addition, the students will be asked to
carry out semester projects (by themselves or in small groups) and
to present the results in short talks.
Prerequisites: Classical mechanics, quantum mechanics I, statistical thermodynamics
Literature
- M. P. Allen, D. J. Tildesley: Computer Simulation of
Liquids, Oxford Science Publications, 1997
- D. P. Landau, K. Binder: A Guide to Monte Carlo
Simulations in Statistical Physics, Cambridge University Press, 2005 (eBook, Hardback)
- D. Frenkel, B. Smit: Understanding Molecular Simulations, From Algorithms to Applications, Academic Press, San Diego, 2002
- D. Ceperley: Microscopic Simulations in Physics, RMP 71, S438 (1999)
- Alfred V. Aho, Brian W. Kernighan, Peter J. Weinberger: The AWK Programming Language, Addison-Wesley, 1988,
ISBN 0-201-07981-X.
- N. Metropolis, A. Rosenbluth, M. Rosenbluth, A. Teller und E. Teller: Equation of State Calculations by Fast Computing Machines, Journal of Chemical Physics 21, 1087 (1953).
- D. M. Ceperley: Path integrals in the theory of condensed helium, Rev. Mod. Phys. 67, 279 - 355 (1995).
Classification according to university regulations (in German):
Wahlpflichtvorlesung des Diplomstudiengangs, Vorlesung des Moduls
``Physik der Flüssigkeiten und Festkörper'' des
Masterstudiengangs Computational Sciences
Credits: Awarded for participation in tutorials and for semester project
Comments: A subsequent lecture on
Modern numerical methods of solid state physics
is planned for the summer semester 2008. Positions for diploma and doctoral students are available on related subjects.
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