The one-dimensional Universe. Investigating filaments in observations and simulations with 1 DREAM, from GAIA to the Cosmic Web.
Marco Canducci (University of Birmingham)
Tuesday 14/03/2023 @ 14:00, Sala IV piano Battiferro - Presenza + remoto
Filamentary structures (one-dimensional manifolds) are ubiquitous in astronomical data sets. Be it in particle simulations or observations, filaments are always tracers of gravitational and/or hydrodynamical interactions within the observed (simulated) system. However, the recovery of such structures is often complicated by the presence of a large amount of background and transverse noise in the observation space. To further complicate the scenario, one-dimensional manifolds (filaments) are generally non-linear and their geometry difficult to extract and model. Thus, in order to study hidden manifolds within the dataset, particular care has to be devoted to background noise removal and transverse noise modelling, while still maintaining accuracy in the recovery of their geometrical structure. 1-DREAM is a toolbox composed of five main Machine Learning methodologies whose aim is to facilitate manifold extraction in such cases. Each methodology has been designed to address particular issues when dealing with complicated low-dimensional structures convoluted with noise. I will demonstrate its workings on two particularly interesting astronomical cases: the stellar stream of Omega-Centauri as observed with GAIA DR2 and a filament extracted from a simulated Cosmic Web. Visualization of results is aided by two newly developed techniques specifically designed to highlight properties of the recovered structures.