Lie Group Cohomology and (Multi)Symplectic Integrators: New Geometric Tools for Lie Group Machine Learning Based on Souriau Geometric Statistical Mechanics

In this paper, we describe and exploit a geometric framework for Gibbs probability densities and the associated concepts in statistical mechanics, which unifies several earlier works on the subject, including Souriau’s symplectic model of statistical mechanics, its polysymplectic extension, Koszul m...

Descripción completa

Detalles Bibliográficos
Autores principales: Barbaresco, Frédéric, Gay-Balmaz, François
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516986/
https://www.ncbi.nlm.nih.gov/pubmed/33286271
http://dx.doi.org/10.3390/e22050498

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516986/
https://www.ncbi.nlm.nih.gov/pubmed/33286271
http://dx.doi.org/10.3390/e22050498

Ejemplares similares