PIRSA:19070003

Deep learning for quantum many-body physics or: Toolmaking beyond the papyrus complexity

Carleo, G. (2019). Deep learning for quantum many-body physics or: Toolmaking beyond the papyrus complexity . Perimeter Institute. https://pirsa.org/19070003

Carleo, Giuseppe. Deep learning for quantum many-body physics or: Toolmaking beyond the papyrus complexity . Perimeter Institute, Jul. 08, 2019, https://pirsa.org/19070003 

          @misc{ pirsa_PIRSA:19070003,
            doi = {10.48660/19070003},
            url = {https://pirsa.org/19070003},
            author = {Carleo, Giuseppe},
            keywords = {Condensed Matter},
            language = {en},
            title = {Deep learning for quantum many-body physics or: Toolmaking beyond the papyrus complexity },
            publisher = {Perimeter Institute},
            year = {2019},
            month = {jul},
            note = {PIRSA:19070003 see, \url{https://pirsa.org}}
          }

Giuseppe Carleo ETH Zurich - Institut für Theoretische Physik

DOI 10.48660/19070003
Collection
Talk Type Conference
Subject

Abstract

In this talk I will discuss some of the long-term challenges emerging with the effort of making deep learning a relevant tool for controlled scientific discovery in many-body quantum physics. The current state of the art of deep neural quantum states and learning tools will be discussed in connection with open challenging problems in condensed matter physics, including frustrated magnetism and quantum dynamics.