PIRSA:23030101

Video URL

https://pirsa.org/23030101

Machine learning for lattice field theory and back

Aarts, G. (2023). Machine learning for lattice field theory and back. Perimeter Institute for Theoretical Physics. https://pirsa.org/23030101

Aarts, Gert. Machine learning for lattice field theory and back. Perimeter Institute for Theoretical Physics, Mar. 10, 2023, https://pirsa.org/23030101 

          @misc{ scivideos_PIRSA:23030101,
            doi = {10.48660/23030101},
            url = {https://pirsa.org/23030101},
            author = {Aarts, Gert},
            keywords = {Other Physics},
            language = {en},
            title = {Machine learning for lattice field theory and back},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2023},
            month = {mar},
            note = {PIRSA:23030101 see, \url{https://scivideos.org/index.php/pirsa/23030101}}
          }

Gert Aarts Swansea University

Talk numberPIRSA:23030101
DOI10.48660/23030101
Source RepositoryPIRSA
Collection
Talk Type Scientific Series
Subject

Abstract

Recently, machine learning has become a popular tool to use in fundamental science, including lattice field theory. Here I will report on some recent progress, including the Inverse Renormalisation Group and quantum-field theoretical machine learning, combining insights of lattice field theory and machine learning in a hopefully constructive manner.

Zoom link:  https://pitp.zoom.us/j/95456375462?pwd=WmtZMloyclAyZzBwVEZHQ3gxVnkrUT09