Monte Carlo Methods   in Statistical Physics and Field Theory Lecturer:      Dr. Wolfgang Unger unger at physik.uni-bielefeld.de Room E6-118 Lecture: Thu. 10:15-11:45 in Room D6-135 Exercises: tba

					3-state Potts Model on 20x20 square lattice,     Metropolis algorithm
T=0.8	T=1.0	T=1.2	T=1.4	T=1.6
					3-state Potts Model on 20x20 square lattice,     Worm algorithm

Lectures: (preliminary, subject to change)

The lecture notes will be published successively after each lecture.

► Lecture 1 (14. Oct. '21): Introduction, Historical Remarks, 5 Ways to compute π

► Lecture 2 (21. Oct. '21): Basic Sampling, Monte Carlo Integration

► Lecture 3 (28. Oct. '21): Importance Sampling, Basic Facts in Probability Theory

► Lecture 4 (01. Nov. '21): Markov Chains, Markov Chain Monte Carlo

► Lecture 5 (04. Nov. '21): Percolation, Random Walks, Equilibrium Monte Carlo

► Lecture 6 (11. Nov. '21): Hard Discs and Spheres, Heatbath Algorithm

► Lecture 7 (18. Nov. '21): Ising Model (Low/High Temperature Expansion, MC in d>2)

► Lecture 8 (25. Nov. '21): Potts Model

► Lecture 9 (02. Dec. '21): Cluster Algorithm

► Lecture 10 (09. Dec. '21): Worm Algorithm

► Lecture 11 (16. Dec. '21): Entropic Forces, Dimer Systems

► Lecture 12 (23. Dec. '21): Path Integrals, Anharmonic Oscillator

► Lecture 13 (13. Jan. '22): Relativistic Bose Gas

► Lecture 14 (20. Jan. '22): Lattice Gauge Models

► Lecture 15 (27. Jan. '22): Compact QED, Outlook to Yang-Mills Theory

Exercises:

► To qualify for the oral exam (you can earn 5 CP)
you need to get 50% of the points from the homework.

► The sheets consist of about 70% computing exercises and 30% paper and pencil exercises.
The points of each sheet sum up to 20 points.

► Computing exercises should be handed in as a short report, explaining the approach and summarizing the result.
Also, the code should be sent to me prior to the tutorial on mondays.
We will discuss the solutions immediately, hence I cannot accept solutions after this deadline.

Literature:

► David P. Landau, Kurt Binder, A Guide to Monte Carlo Simulations in Statistical Physics, Cambridge University Press

► Werner Krauth: Statistical Mechanics: Algorithms and Computations, Oxford University Press

► Andreas Wipf: Statistical Approach to Quantum Field Theory, Springer

► Charles M. Grinstead, J. Laurie Snell: Introduction to Probability

Links on Monte Carlo:

► Website of Werner Krauth, including some illustrations from his book: http://www.lps.ens.fr/~krauth/index.php/Main_Page

► Percolation: http://www.physics.buffalo.edu/gonsalves/Java/Percolation.html

► Drunken Sailor Problem (Random Walk): http://www.chem.uoa.gr/applets/AppletSailor/Appl_Sailor2.html

► Self-avoiding random walk: http://polymer.bu.edu/java/java/saw

► Applets for 2D Lennard-Jones System, Ising Model, 2D Dipoles: http://personal-pages.ps.ic.ac.uk/~achremos/Applets-page.htm

► Applet of Ising Model and XY Model: https://itp.tugraz.at/MML/isingxy

► Anharmonic Oscillator: http://fisteo12.ific.uv.es/~santamar/arcapplets.html

Links on Lattice Gauge Theory:

Introductory Material:

► Introduction by Rajan Gupta:http://arxiv.org/abs/hep-lat/9807028

► Introductory Presentation by Hartmut Wittig: http://www.gk-eichtheorien.physik.uni-mainz.de/Dateien/Wittig.pdf

Lattice QCD Software Projects:

► FermiQCD: http://web2py.com/fermiqcd

► Columbia Physics System (CPS): http://phys.columbia.edu/~cqft/physics_sfw/physics_sfw.htm

Miscellaneous:

► Lattice QCD Blog: http://latticeqcd.blogspot.com/

► Resources of Michael Creutz: http://latticeguy.net/lattice.html