PIRSA:21100002

Simulations of Cosmological Structure and Machine Learning

APA

Bird, S. (2021). Simulations of Cosmological Structure and Machine Learning. Perimeter Institute. https://pirsa.org/21100002

MLA

Bird, Simeon. Simulations of Cosmological Structure and Machine Learning. Perimeter Institute, Oct. 19, 2021, https://pirsa.org/21100002

BibTex

          @misc{ pirsa_21100002,
            doi = {},
            url = {https://pirsa.org/21100002},
            author = {Bird, Simeon},
            keywords = {Cosmology},
            language = {en},
            title = {Simulations of Cosmological Structure and Machine Learning},
            publisher = {Perimeter Institute},
            year = {2021},
            month = {oct},
            note = {PIRSA:21100002 see, \url{https://pirsa.org}}
          }
          

Abstract

The large scale distribution of matter in the Universe contains the answers to many mysteries, such as the nature of dark matter, the reionization of the Universe, and the growth of galaxies. Cosmological simulations are the only way to understand these questions. I will talk about how modern current simulation models, work, discuss some new models and improvements in our latest simulation runs, especially our implementations of reionization and cosmology. I will then talk about some new work to dramatically expand the region of applicability of these simulations using machine learning. This can both to expand their dynamic range and combine different simulations to infer the physical parameters of the Universe.