Mocking The Universe Using Machine Learning

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This project will involve the development of new mock simulations to support the analysis of environmental studies of galaxy formation in DESI data. By using artificial intelligence, we will produce simulations that have sufficient complexity to create realistic mock surveys over the full DESI volume. These mocks can be used to test a wide range of observational techniques and their dependence on environment, such as simple SED fits, clustering, Hierarchical Bayesian modelling of galaxy population, and any observational work that aims to disentangle the many roles of environment in the evolution of galaxies.