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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Texas At Austin |
| Country | United States |
| Start Date | Sep 01, 2024 |
| End Date | Aug 31, 2027 |
| Duration | 1,094 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2413016 |
One of the most prominent and exciting challenges in fundamental physics is understanding the nature of dark matter, which accounts for 85% of all matter throughout the known Universe. Dark matter plays a crucial role in forming galaxies, galaxy clusters, and larger structures of matter through its gravitational effects on ordinary particles. A key question is whether or not dark matter experiences any forces beyond gravity.
The PI's research program will tackle the dark matter problem at the intersection of cosmology and particle physics, using cosmological and astrophysical observations to study the microscopic properties of dark matter. Such observations have emerged as a powerful probe of dark matter, due to their increase in precision and sensitivity over recent years.
The PI's research will provide foundational work for future dark matter analyses, in preparation for potential new discoveries as next-generation instruments and surveys begin operations in the upcoming decade. In conjunction with research, this program includes the mentoring and support of undergraduate women in physics.
This research will study the impact of dark matter interactions with ordinary particles and dark matter self-interactions throughout cosmic time. These interactions can affect the formation and evolution of dark matter structures, thereby enabling the opportunity to search for new dark matter physics using current and future cosmological and astrophysical observations.
This research will pursue new avenues to bridge theoretical models and observational techniques to study dark matter. It will involve the development of sophisticated tools to perform joint analyses using multiple datasets.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
University of Texas At Austin
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