Dennis Zaritsky
University of Arizona, AZ·Astronomy & Astrophysics
Galaxies are more than their stars. They sit inside large halos filled with material that gives off little or no visible light, and dust is one of those hidden components.
- Fields
Astronomy & Astrophysics
Physics
- Topics
circumgalactic dust
circumgalactic medium
galaxy halos
- Grants
- 1 known grant, through Aug 2028
What they work on
- Measure the reddening of thousands of faint background sources projected near 25 nearby galaxies, using extremely deep images, to estimate how much dust surrounds each galaxy.
- Map the spatial distribution of circumgalactic dust around individual galaxies, going beyond prior work that only confirmed halo dust exists.
- Use halo dust as a tracer of chemically enriched circumgalactic material and of the dark matter halo density profile, constraining the physical nature of the dark matter particle.
- Demonstrate that this background-reddening method can be scaled to the full Rubin Observatory Legacy Survey of Space and Time (LSST) dataset.
More about the research
Dust is hard to detect and even harder to quantify, so very little is known about how much of it surrounds a galaxy or how it is arranged. That matters because dust marks chemically enriched material in the circumgalactic medium, the gas and dust surrounding a galaxy, and because its distribution can be used to infer the density profile of the invisible dark matter halo.
Why it matters
Most of the material around galaxies is invisible to ordinary observation. Measuring halo dust offers an alternative route to tracing chemically enriched halo material and to pinning down how dark matter is distributed around galaxies, which constrains what the dark matter particle can be. Because the technique is built to scale to the full Rubin/LSST survey, it could eventually be applied across very large numbers of galaxies.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Brant Robertson
University of California-Santa Cruz, CA·Astronomy & Astrophysics
Incorporate the Morpheus deep learning framework, which classifies images pixel by pixel, into the Rubin Science Platform for analyzing Rubin Observatory data.
Gary Bernstein
University of Pennsylvania, PA·Astronomy & Astrophysics
Measure precise astrometric positions of stars in hundreds of thousands of Dark Energy Camera images from the Blanco Telescope, collected over 12 years.
Elizabeth Jeffery
California Polytechnic State University-San Luis Obispo, CA·Astronomy & Astrophysics
Obtain follow-up spectra of star-forming galaxies in known supercluster filaments, and compare their stellar ages, colors and redshifts with estimates from Rubin images alone; use the spectra to compute how long galaxies take to fall into clusters.
The school
University of Arizona: 36 labs on PI Pages, $1.0B a year on research, 487 research doctorates a year.
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