Exploring the Universe with radio and optical galaxy surveys
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Physics and Astronomy
Abstract
This project will provide the largest 3-dimensional map of the Universe, covering 12 billion years of cosmic history. It will exploit radio intensity mapping and optical galaxy surveys to deliver measurements that are at least 10 times better than the current state-of-the-art. Innovative observational, computational, and statistical methods will be used to answer two of the most important questions in astrophysics: what is the nature of dark energy, and how galaxies evolve.
To answer these questions, optical galaxy surveys with major UK involvement are going to be used as the main resource for precision cosmology in this decade. Forthcoming state-of-the-art cosmological experiments like ESA's Euclid satellite mission will scan huge volumes and answer fundamental questions about the Universe's beginning, evolution, and late time accelerated expansion. At the same time, radio observations of the redshifted neutral hydrogen 21cm line and new instruments like the SKA Observatory (SKAO) and its MeerKAT precursor, will provide a novel way to explore and understand the Universe.
The project has two overarching aims: the first aim is to kick-off the era of precision cosmology using radio telescopes like MeerKAT and the SKAO. I am leading the development of an innovative technique to detect the target signal, called "neutral hydrogen intensity mapping". This technique can revolutionise our understanding of galaxy evolution and cosmology, but it is currently severely limited by systematic effects and lack of realistic simulations. The project will deliver the new simulations and analysis methods needed in order to establish intensity mapping as a key resource for cosmology. The second aim is to address the biggest theoretical challenge in optical galaxy surveys such as ESA's Euclid mission. Most of the high precision data these surveys deliver are within the small-scale regime, which is extremely challenging to model. Without significant progress, the global error budget will be limited by our theoretical understanding rather than statistical or systematic errors. The project will ensure the models catch up with the data sensitivity and develop new analysis techniques using machine learning technologies.
This grant will consolidate the world-leading position of the UKRI FLF research group initiated by Alkistis Pourtsidou.
To answer these questions, optical galaxy surveys with major UK involvement are going to be used as the main resource for precision cosmology in this decade. Forthcoming state-of-the-art cosmological experiments like ESA's Euclid satellite mission will scan huge volumes and answer fundamental questions about the Universe's beginning, evolution, and late time accelerated expansion. At the same time, radio observations of the redshifted neutral hydrogen 21cm line and new instruments like the SKA Observatory (SKAO) and its MeerKAT precursor, will provide a novel way to explore and understand the Universe.
The project has two overarching aims: the first aim is to kick-off the era of precision cosmology using radio telescopes like MeerKAT and the SKAO. I am leading the development of an innovative technique to detect the target signal, called "neutral hydrogen intensity mapping". This technique can revolutionise our understanding of galaxy evolution and cosmology, but it is currently severely limited by systematic effects and lack of realistic simulations. The project will deliver the new simulations and analysis methods needed in order to establish intensity mapping as a key resource for cosmology. The second aim is to address the biggest theoretical challenge in optical galaxy surveys such as ESA's Euclid mission. Most of the high precision data these surveys deliver are within the small-scale regime, which is extremely challenging to model. Without significant progress, the global error budget will be limited by our theoretical understanding rather than statistical or systematic errors. The project will ensure the models catch up with the data sensitivity and develop new analysis techniques using machine learning technologies.
This grant will consolidate the world-leading position of the UKRI FLF research group initiated by Alkistis Pourtsidou.
