Project description
Decoding dark matter through stellar streams
Understanding dark matter, which makes up 80 % of the Universe’s matter, remains one of astrophysics’ greatest challenges. Stellar streams, formed by disrupted star clusters and galaxies, hold vital clues to the distribution and behaviour of dark matter. These streams are influenced by dark matter’s mass, shape, and interaction properties, yet their full potential remains untapped. With a flood of data from cutting-edge observatories such as the Vera C. Rubin Observatory, Euclid, and the Nancy Grace Roman Space Telescope, researchers are poised to revolutionise the field. The ERC-funded BeyondSTREAMS project will harness these data to create novel statistical models and simulations, transforming stellar stream analysis. By comparing observations with predictions, it will refine our understanding of particle physics.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2023-STG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
1165 KOBENHAVN
Denmark
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