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

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.