PIRSA:17090019

Video URL

https://pirsa.org/17090019

Computational Frameworks for Quantum Gravity and Beyond

Rideout, D. (2017). Computational Frameworks for Quantum Gravity and Beyond. Perimeter Institute for Theoretical Physics. https://pirsa.org/17090019

Rideout, David. Computational Frameworks for Quantum Gravity and Beyond. Perimeter Institute for Theoretical Physics, Sep. 11, 2017, https://pirsa.org/17090019 

          @misc{ scivideos_PIRSA:17090019,
            doi = {10.48660/17090019},
            url = {https://pirsa.org/17090019},
            author = {Rideout, David},
            keywords = {Quantum Gravity},
            language = {en},
            title = {Computational Frameworks for Quantum Gravity and Beyond},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2017},
            month = {sep},
            note = {PIRSA:17090019 see, \url{https://scivideos.org/pirsa/17090019}}
          }

David Rideout University of California, San Diego

Talk numberPIRSA:17090019
DOI10.48660/17090019
Source RepositoryPIRSA
Collection
Talk Type Scientific Series
Subject

Abstract

Causal set quantum gravity, computational methods Series

The Cactus High Performance Computing (HPC) Framework was designed to
facilitate the development of software to simulate astrophysically realistic
inspiral and merger of binary black holes and neutron stars.  A major part of the motivation for
its design was the US Binary Black Hole Grand Challenge in the 1990s, which
was an alliance of hundreds of scientists, all attempting to collaborate on
the same code base.  In order to handle such a large, diverse collaboration,
the design ended up being extremely general and versatile, able to support
virtually any sort of scientific computation.

I have developed an extensive software suite within the Cactus Framework for
doing large scale computations in discrete quantum gravity, using Causal Sets,
and also spin networks in Loop Quantum Gravity.  Recently, evidence is
emerging that ideas from discrete quantum gravity, and consequently this
software, may have much broader application in areas of Data Science,
including social science, computational neuroscience, and drug design.