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Galaxies are made of many different components, not only stars, and some of their parts are difficult to detect because they do not emit visible light. Dust is one of these dark, yet ubiquitous, components of galaxies. Due to its nature, dust is very difficult to detect and quantify. This program will measure the amount of dust in the halos that surround galaxies by measuring the dimming of light sources in the background of 25 galaxies. The dimming of background sources will provide an estimate of the amount of dust surrounding these galaxies. Mapping the distribution of dust around galaxies will also help us understand the nature of dark matter. As part of this program, the PI will expand an established series of public talks given to the local community in the Tucson area. This program will also support the training of a graduate student in the field of astronomy with an emphasis on machine learning. This program aims to quantify the properties of circumgalactic dust by mapping the reddening of the many thousands of faint background sources projected near local galaxies. This work will be done with a set of 25 high-quality, extremely deep images of local galaxies to make the first measurements of halo dust in individual galaxies and demonstrate what will eventually be done with the full Rubin/LSST dataset. There is almost no work on tracing halo dust beyond the mere confirmation of its existence. Despite constituting a relatively minor component of the circumgalactic medium (CGM), this dust provides an alternative avenue for tracing chemically enriched halo material and determining the dark matter halo density profile, which in turn constrains the physical nature of the dark matter particle. 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.
Up to $490K
2028-08-31
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