Collaborative Research: GCR: Mineral Detection of Dark Matter
- Institution
- Regents of the University of Michigan - Ann Arbor, MI
- Principal investigator
- Joshua Spitz
- Funding
- $662K
- Duration
- 2024–2029
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Abstract
This Growing Convergence Research project brings together researchers from engineering, physics, geo- and materials sciences with the goal of establishing a convergence framework to address the feasibility of mineral detection (MD) of dark matter. There is overwhelming evidence from astrophysics and cosmology that there is about five times as much dark matter as there is ordinary matter, i.e. the stuff we are made of. In MD, one studies geological samples of gram- to kilogram-scale, which have been exposed to dark matter interactions for billions of years. This allows MD to have the potential to match or exceed the sensitivity of conventional experiments. MD may therefore provide a path to answering the question of what dark matter actually is. In MD, the interactions of crystals with dark matter results in permanent changes to the crystal lattice which can be measured much later than the original interaction. This long intervening time combined with the geological changes the samples have encountered is a challenge for the interpretation of dark matter signals in MD. The changes to the crystal lattice are happening at the nano-scale and thus methods which can record nano-scale features scattered over a large, cubic millimeter to cubic centimeter, volume are required. This also implies a challenge in terms of data volumes and subsequent analysis. In addition, a dedicated simulation effort, from particle transport to molecular dynamics, is required to gain a theoretical understanding of damage formation and permanence. This project will test the feasibility of the MD approach to detecting interactions between ordinary and dark matter. 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.
Research team
- Joshua SpitzPI
- Igor Jovanovic
- Kai Sun
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