Starts 12 Apr 2022 11:00
Ends 12 Apr 2022 12:00
Central European Time
Hybrid seminar
room 128, SISSA (via Bonomea 265) + Zoom

Elisa Ercolessi
(Bologna)

Abstract:
The recent advances in machine learning algorithms have boosted the application of these techniques to the field of condensed matter physics. 

Here we demonstrate that,  if we employ a training set made by single-particle correlation functions of a non-interacting quantum wire,unsupervised and supervised machine learning techniques are able to reconstruct the phase diagram of a related interacting model and identify topological phases with a high degree of accuracy.