Overview
The lecture will cover optimization problems in physical systems with
an emphasis on optimization algorithms. Some combinatorial as well
as typical optimization problems (such as kSAT, traveling salesman,
number partitioning, ...) will also be discussed. Furthermore, some
topics such as complexity theory as well as finitesize scaling will
be reviewed. Most of the examples will be based on physics spin models
(e.g., Ising model).

Lecture Notes
 02/10: General introductory concepts,
complexity theory.
 09/10: Spin glasses as algorithm benchmarks, Monte Carlo methods (simulated annealing, parallel tempering)
 16/10: Genetic algorithms, hysteretic
optimization, extremal optimization
 30/10: Patchwork dynamics, quantum annealing, SAT/UNSAT phase transition
 06/11: Introduction to graphs, simple
algorithms and optimization problems
 13/11: Random graphs, phase transitions in
the vertex cover problem
 27/11: Maximumflow methods
 04/12: Dynamics in the cov/uncov
transition, methods to study spin glasses, genetic cluster exact
approximation
 11/12: Probing lowprobability tails,
the number partitioning problem
 18/12: Matchings
Complete lecture (24 Mb)
If you would like to access the lectures
notes (pdf) please send me an email to email
and you might receive the username and password. Students can find
the username and password on the first handout.

Recommended books
 Optimization Algorithms in Physics, A. K. Hartmann and H.
Rieger (WileyVCH).
 New Optimization Algorithms in Physics, A. K. Hartmann and H.
Rieger (WileyVCH).
 Algorithms and Computations, W. Krauth (Oxford University Press).
 Phase Transitions in Combinatorial Optimization Problems, A. K.
Hartmann and M. Weigt (WileyVCH).
 Quantum Annealing and Related Optimization Methods, A. Das and B. K.
Chakrabarti (Springer).
