Agenda de l’IDP

Séminaire de Physique Théorique

Machine learning for string theory
Harold Erbin (Université Louis-et-Maximilien de Munich, Allemagne)
Thursday 27 September 2018 13:00 -  Tours -  Salle 1180 (Bât E2)

Résumé :
String theory is one of the leading endeavors in theoretical physics for quantizing general relativity together with the unification of all forces and matter. Thus, it provides potentially a complete description of the Universe and of its content. However, while all ingredients are present, the details for a precise contact with the Standard model are missing, mostly because the number of possible realizations is huge and no selection mechanism is known. Since the most immediate difficulties are computational and boil down to studying the statistics of geometries (the "string landscape") and to approximating functions and geometries (to build a string field theory), machine learning seems to provide an adequate framework to address the challenges faced by string theory. In this talk, I will overview the method and the status of string theory before indicating where machine learning could enter the game.

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