Random Sampling from Boltzmann principles
Abstract
This note proposes a new framework for random generation based on what we call Boltzmann models. The idea is to perform random generation of possibly complex structured objects by putting an appropriate measure on combinatorial classes. The resulting algorithms often operate in linear time. They can be easily implemented within a computer algebra system and will be theoretically as well as practically efficient.