![](platzhalterrot.gif)
![AofA](home1.gif)
![call](previous1.gif)
![call](call1.gif)
![dates](dates1.gif)
![submission](info1.gif)
![submission](summer1.gif)
![programm](programm1.gif)
![speakers](speakers1.gif)
![committees](committees1.gif)
![registration](registration1.gif)
![venue](venue1.gif)
![travel](travel1.gif)
![events](events1.gif)
![sponsors](sponsors1.gif)
![contact](contact1.gif)
![](platzhalterrot.gif) |
![](U-summer.gif)
Angelika STEGER
On Boltzmann samplers and properties of combinatorial
structures
In the past decades the G(n,p) model of random graphs, introduced by
Erdős and Rényi in the 60's, has led to numerous beautiful and deep
results. A key feature that is used in basically all proofs is that
edges in G(n,p) appear independently. This situation changes
dramatically if one considers graph classes with structural side constraints.
For example, in a random planar graph Pn (a graph drawn uniformly at
random from the class of all labeled planar graphs on n vertices) the edges are
obviously far from being independent. In this talk we show that recent
progress in the construction of Boltzmann samplers can be used to reduce the study
of properties of combinatorial objects to properties of sequences of
independent and identically distributed random variables -- to which
we can then again apply well known machinery from random graph theory.
|