Asymptotically safe matrix models

APA

Koslowski, T. (2013). Asymptotically safe matrix models. Perimeter Institute for Theoretical Physics. https://pirsa.org/13100067

MLA

Koslowski, Tim. Asymptotically safe matrix models. Perimeter Institute for Theoretical Physics, Oct. 24, 2013, https://pirsa.org/13100067

BibTex

          @misc{ scivideos_PIRSA:13100067,
            doi = {10.48660/13100067},
            url = {https://pirsa.org/13100067},
            author = {Koslowski, Tim},
            keywords = {Quantum Gravity},
            language = {en},
            title = {Asymptotically safe matrix models},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2013},
            month = {oct},
            note = {PIRSA:13100067 see, \url{https://scivideos.org/pirsa/13100067}}
          }
          

Tim Koslowski Universidad Nacional Autónoma De Mexico (UNAM)

Source Repository PIRSA
Collection

Abstract

The functional renormalization group is a tool in the systematic search for Euclidean QFTs that works with very little input: All one needs to specify is a field content, symmetries and a notion of locality. The functional renormalization group then allows one to scan this theory space for bare actions for which the path integral can be performed nonperturbatively. These actions appear as fixed points (and relevant deformations) of the renormalization group flow (so-called asymptotic safety). Such a systematic search has so far not been performed for the tensor model approach to quantum gravity. We investigate matrix models for 2-dimensional gravity and the Grosse-Wulkenhaar model, which is a simple tensor model for a 4D noncommutative scalar field theory, as a first step. I will report on work, done in collaboration with Astrid Eichhorn and Alessandro Sfondrini, where we confirmed asymptotic safety purely through functional RG methods. Based on the lessons learned from these models I will summarize how the usual continuum RG approach has to be generalized for the investigation of tensor models and conclude with a recipe for the investigation of general tensor models.