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Modeling dust content of galaxies using cosmological simulations

June 17 @ 12:00 pm - 1:30 pm


Qi Li
Ph.D. Candidate in Astronomy and UFII Fellow
Department of Astronomy
University of Florida

Due to the latest UF and State of Florida directives, Qi Li’s  talk will be presented via Zoom.

RSVP below. Instructions to attend talk via Zoom will be emailed to you.


Modeling dust content of galaxies using cosmological simulations


Dust is integral in astrochemistry, physics of galaxy evolution and radiative transfer in the interstellar medium. The dust-to-gas ratio (DGR)  is particularly critical. This number puts a constraint on theories for the coevolution of dust content with galaxies. Nevertheless, it is observationally notoriously difficult to measure, and the estimate of DGR widely adopted by observers and modelers is still based on an oversimplified formula. On the other hand, large-scale cosmological simulations provide significant numbers of model galaxies covering a wide range of physical properties, and therefore can help us to relate the observables to the true DGR. In this talk, I will present the implementation of dust-related physical processes on the fly into the state-of-the-art cosmological hydrodynamic simulation, and a machine learning-based framework trained on the simulated galaxies to predict DGR from observables of galaxies.


Qi Li is a 5th year PhD student in Astronomy. His research focuses on understanding the dust evolution across cosmic time utilizing hydrodynamic simulations. He is interested in applying machine learning techniques to simulated data to understand physical drivers of cosmic dust and connect dust-related properties to observables.

Wednesday, June 17, 2020




June 17
12:00 pm - 1:30 pm
Event Category: