The Parallel approximability of the false and true gates problems for nor circuits
We present a parallel algorithm to sample matchings from an almost uniform distribution on the set of matchings of all sizes in a graph. The technique used is based on the definition of a genetic system that converges to the uniform distribution. The system evolves according to a non-linear equation...
| Autores: | , |
|---|---|
| Tipo de recurso: | informe técnico |
| Fecha de publicación: | 1998 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/96511 |
| Acceso en línea: | https://hdl.handle.net/2117/96511 |
| Access Level: | acceso abierto |
| Palabra clave: | Parallel algorithm Uniform distribution Match sampling Non-linear equation False and true gates problems Nor circuits Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica |
| Sumario: | We present a parallel algorithm to sample matchings from an almost uniform distribution on the set of matchings of all sizes in a graph. The technique used is based on the definition of a genetic system that converges to the uniform distribution. The system evolves according to a non-linear equation. Little is known about the convergence of these systems. We can define a non-linear system which converges to a stationary distribution under quite natural conditions. We prove convergence for the system corresponding to the almost uniform sampling of matchings in a graph (up to know the only known convergence for non-linear systems for matchings was matchings on a tree). We give empirical evidence that the system converges fast. |
|---|