DiscoverThe Academic MinuteVera Glusevic, University of Southern California Dornsife – Understanding Dark Matter By Coding Milky Way Twin Galaxies
Vera Glusevic, University of Southern California Dornsife – Understanding Dark Matter By Coding Milky Way Twin Galaxies

Vera Glusevic, University of Southern California Dornsife – Understanding Dark Matter By Coding Milky Way Twin Galaxies

Update: 2025-10-01
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On University of Southern California Dornsife Week: We’re still seeking to better understand dark matter in our universe.


Vera Glusevic, associate professor of physics and astronomy, examines one way to do so.


Vera received her B.Sc. from University of Belgrade (Serbia) in 2007, and her Ph.D. from Caltech in 2013. After completing a postdoctoral fellowship at the Institute for Advanced Study in Princeton, she moved to Princeton University as a Visiting Research Associate in Physics in 2018. In 2019, she joined USC as Gabilan Assistant professor of Physics and Astronomy, and was promoted to Associate professor in 2024. Vera is one of the founding members of two large international collaborations, CMB-S4 and the Simons Observatory. She is also the lead of an LA-based research Hub bringing together scientists from USC, Carnegie Observatories, and UC Riverside to study Lyman-alpha cosmology. In 2022, Vera received USC Raubenheimer Outstanding Junior Faculty Award, in 2023, she was named a Cottrell Scholar and in 2024 a Scialog Fellow by the Research Corporation for Science Advancement. Her research is supported by NSF, NASA, the Research Corporation for Science Advancement, and the Templeton Foundation.


Understanding Dark Matter By Coding Milky Way Twin Galaxies



 


What if you could build a synthetic twin of the Milky Way—then tweak the laws of physics inside it?


Dark matter makes up 85% of the matter in the universe. It is tricky to study because it doesn’t emit any light or energy that can be easily detected.


We can only observe dark matter indirectly—by watching how it affects galaxies. It’s like studying someone’s shadow without seeing the person casting it. Still, we know dark matter is there. Galaxies, for example, spin so fast they should fly apart. Something invisible must be holding them together. We believe that dark matter is at the heart of this phenomenon.


To test different theories of dark matter, we created a new suite of high-resolution galaxy simulations called COZMIC—short for “Cosmological Zoom-in Simulations with Initial Conditions beyond Cold Dark Matter.” For the first time, we can explore what happens when forces other than gravity act between normal and dark matter, affecting the formation of galaxies like our own.


We tested three possibilities. In the first, dark matter particles bounce off regular matter like billiard balls, smoothing out small-scale structure. In the second, only some dark matter particles interact; others pass through normal matter without effect. In the third, dark matter interacts only with itself, changing how galaxies form over time.


As we ran these simulations, we programmed new physics into a supercomputer and watched as a galaxy took shape—its structure reflecting the microscopic character of dark matter particles.


This is a major step toward figuring out what dark matter is. By comparing these simulated galaxies to real telescope images, we’re getting closer to solving one of the universe’s biggest mysteries: what dark matter is, and how it shapes the cosmos.


Read More:

[USC Today] – Scientists code Milky Way twin galaxies to better understand

I. Cosmological Zoom-in Simulations with Initial Conditions Beyond Cold Dark Matter

II. Cosmological Zoom-in Simulations with Fractional non-CDM Initial Conditions

III. Cosmological Zoom-in Simulations of Self-interacting Dark Matter with Suppressed Initial Conditions


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Vera Glusevic, University of Southern California Dornsife – Understanding Dark Matter By Coding Milky Way Twin Galaxies

Vera Glusevic, University of Southern California Dornsife – Understanding Dark Matter By Coding Milky Way Twin Galaxies

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