Summary
One of the key questions driving astrophysics research today is the nature of dark matter, which comprises 80% of the matter in the Universe. Stellar streams are sensitive to the distribution of dark matter and to the population of dark matter subhalos in galaxies, both of which depend on the mass and interactions of the dark matter particle. My proposed work will use the wealth of incoming stellar stream data materializing over the next five years from the Nancy Grace Roman Space Telescope, the Vera C. Rubin Observatory, and the Euclid Space Telescope to measure dark matter halo masses, shapes and concentrations, as well as subhalo populations of external galaxies. I will lead a fundamental shift in the approach to stellar stream studies through statistical model-to-data comparisons between theoretical predictions from various dark matter candidates (cold, warm, wave-like, self-interacting) and the actual stream data. To achieve this goal, I will develop novel numerical techniques which model and fit multiple streams at once in multiple external galaxies, run state-of-the-art N-body simulations of disrupting globular clusters in dwarf galaxies to place theoretical constraints on the expected substructure, and carry out statistical comparisons between dark matter models and properties derived from the stellar stream data. I will rule out dark matter candidates that are inconsistent with the new stellar stream data, and by the end of the 60-month grant period, I will have the world-leading constraints on dark matter from stellar streams. This work provides an innovative method for mapping the otherwise invisible dark matter, and will constrain statistical properties of dark matter related to its nature and possible extensions of the standard model of particle physics.
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| Web resources: | https://cordis.europa.eu/project/id/101115754 |
| Start date: | 01-06-2024 |
| End date: | 31-05-2029 |
| Total budget - Public funding: | 1 686 734,00 Euro - 1 686 734,00 Euro |
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Original description
One of the key questions driving astrophysics research today is the nature of dark matter, which comprises 80% of the matter in the Universe. Stellar streams are sensitive to the distribution of dark matter and to the population of dark matter subhalos in galaxies, both of which depend on the mass and interactions of the dark matter particle. My proposed work will use the wealth of incoming stellar stream data materializing over the next five years from the Nancy Grace Roman Space Telescope, the Vera C. Rubin Observatory, and the Euclid Space Telescope to measure dark matter halo masses, shapes and concentrations, as well as subhalo populations of external galaxies. I will lead a fundamental shift in the approach to stellar stream studies through statistical model-to-data comparisons between theoretical predictions from various dark matter candidates (cold, warm, wave-like, self-interacting) and the actual stream data. To achieve this goal, I will develop novel numerical techniques which model and fit multiple streams at once in multiple external galaxies, run state-of-the-art N-body simulations of disrupting globular clusters in dwarf galaxies to place theoretical constraints on the expected substructure, and carry out statistical comparisons between dark matter models and properties derived from the stellar stream data. I will rule out dark matter candidates that are inconsistent with the new stellar stream data, and by the end of the 60-month grant period, I will have the world-leading constraints on dark matter from stellar streams. This work provides an innovative method for mapping the otherwise invisible dark matter, and will constrain statistical properties of dark matter related to its nature and possible extensions of the standard model of particle physics.Status
SIGNEDCall topic
ERC-2023-STGUpdate Date
03-10-2024
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