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Active RESEARCH AND INNOVATION UKRI Gateway to Research

Mining the Archaeological Record in Galaxy Outskirts

£21.67M GBP

Funder Horizon Europe Guarantee
Recipient Organization University of Edinburgh
Country United Kingdom
Start Date Mar 01, 2025
End Date Feb 28, 2030
Duration 1,825 days
Number of Grantees 1
Roles Principal Investigator
Data Source UKRI Gateway to Research
Grant ID EP/Z534353/1
Grant Description

The low surface brightness peripheral regions of galaxies contain a gold mine of information about their assembly histories, reflecting how minor mergers and accretions have influenced their evolution over cosmic time. Enormous stellar envelopes and copious amounts of faint tidal debris are natural outcomes of the hierarchical assembly process - the quantitative study of these features, while extremely challenging, offers tremendous potential for gaining insight into the detailed histories of galaxies.

I have played a leading role in groundbreaking work that helped to establish and develop this line of research but shortcomings in the previously available datasets (e.g. sample size, surface brightness depth), and the often-disjoint analyses of observations and numerical simulations, have thus far limited the conclusions that can be drawn. My exceptionally timely project MARGO will use state-of-the-art data from world-leading facilities and the forthcoming Euclid and LSST surveys to accurately determine the properties of the faint outskirts of galaxies throughout the local Universe and use them as a new tool to rigorously test the current galaxy formation paradigm.

The approach of MARGO is three-pronged, combining precision analyses of the resolved stellar populations in the halos of the nearest systems beyond the Local Group with unbiased integrated light studies of tidal debris in large statistical samples. Fossil information about past accretion events in galaxy peripheries will be extracted and compared to cosmological simulations of structure formation to stress test their predictions on small scales.

Critical to the success of the project is the development of a new methodology to detect faint tidal features in large galaxy samples using machine learning., MARGO will transform our understanding of low surface brightness galaxy outskirts and finally enable us to place the particular history of our own Milky Way in context.

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University of Edinburgh

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