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| Funder | Science and Technology Facilities Council |
|---|---|
| Recipient Organization | University of Exeter |
| Country | United Kingdom |
| Start Date | Mar 31, 2024 |
| End Date | Mar 30, 2027 |
| Duration | 1,094 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | UKRI Gateway to Research |
| Grant ID | ST/Y001931/1 |
Clusters of millions of stars, often billions of years old, are a fundamental component of galaxies but their origin is poorly understood. In recent years, Hubble Space Telescope observations have inspired a bold new star cluster formation theory, which requires sophisticated computer simulations to test. Five years ago, my collaborators and I developed the first numerical simulations capable of yielding the predictions needed for confrontation with observations of star clusters: these have helped to cement this new idea into our consensus picture of galaxy formation.
Whilst revolutionary, these simulations have a number of shortcomings that limit the lines of enquiry for which they can be used. In particular, they lack the detail and accuracy needed to deliver predictions of the relationship between star clusters and galaxies in the infant Universe (which is now being spectacularly unveiled by the James Webb Space Telescope), nor that between star clusters and low-mass dwarf galaxies, which are important `laboratories' for testing the physics of galaxy formation.
A third high-profile application for which they are ill-suited is to show how the stars that get disrupted "out" of star clusters (by gravitational interactions with molecular clouds) end up distributed in and around galaxies. Streams of such stars can now be identified by the `fingerprint' of their element abundances seen in surveys of our own Milky Way, and astronomers urgently need detailed models of their origin in order to use these observations to reconstruct the Milky Way's assembly history.
This project will implement sophisticated new methods for modelling the formation and evolution of star clusters, which will remedy the shortcomings listed above. The methods will be built into new simulations of galaxy formation that supercede the simulations used for our prior model, and will redefine the state-of-the-art.
University of Exeter
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