202 FRIB Graduate Brochure

Brian O’Shea
Professor of Computational Mathematics, Science
and Engineering and Physics and Astronomy
Keywords: Galatic Chemical Evolution, Uncertainty Quantification High-
Performance Computing, Machine Learning Cosmological Structure Formation
Theoretical Nuclear Astrophysics
About
• MS, Physics, 2002 University of Illinois at Urbana-
Champaign
• PhD, Physics, 2005 University of Illinois at Urbana-
Champaign
• Joined the laboratory in September 2015
• oshea@msu.edu
Research
My research focuses on the growth and evolution of galaxies
over the age of the Universe, as well as understanding the
behavior of the hot, diffuse plasmas that constitute much
of the baryons in and around galaxies (for example, the
interstellar medium). I do this using numerical simulations
on some of the world’s biggest supercomputers, and by
comparing those simulations to astronomical observations
and nuclear and plasma experiments. In relation to NSCL
and FRIB, I am particularly interested in using observations
of atomic abundances in stars, along with multi-messenger
astrophysical information from black holes, neutron
stars, and supernovae, to learn more about how stellar
populations grow within galaxies and in turn affect the
behavior of those galaxies.
Biography
I grew up in the suburbs of Chicago and went to the
University of Illinois as an undergraduate and graduate
student to study physics (BS in Engineering Physics, 2000;
PhD in Physics, 2005). I spent most of my PhD in residence
in the Laboratory for Computational Astrophysics at the
University of California at San Diego. After that, I spent
three years as a Director’s Postdoctoral Fellow at Los
Alamos National Laboratory before coming to Michigan
State University in 2008. I am one of the co-founders of
the Department of Computational Mathematics, Science
and Engineering and am currently the Director of the
Institute for Cyber-Enabled Research. I’m interested in
understanding how galaxies form and evolve over the age
of the universe (and how nuclear experiments and theory
can inform that understanding!), in how plasmas behave
in extreme conditions, and how students learn about
computational and data science.
How Students can Contribute as Part
of my Research Team
Undergraduate and graduate students are key members
of my research group. Our work focuses on using
computational models and data science techniques to
understand galaxies, and involves software development,
running and analyzing simulations, making synthetic
observations of those simulations, and comparing to real
astronomical observations (from, e.g., the Hubble Space
Telescope or the SOAR telescope). I have projects for
students that can range from data analysis suitable for
first-year undergraduates through software development
and simulation campaigns that would constitute an entire
PhD thesis. Much of this work ties to FRIB’s mission of
probing matter under extreme conditions, particularly in
astrophysical environments.
This is a figure of one of the first galaxies to form in the
universe, from a large-scale simulation including cosmological
expansion, dark matter, fluid dynamics, radiation transport,
and prescriptions for the formation and feedback of stars
and black holes. This image shows both stars and nebular
emission from ionized gas. Image credit: John Wise, Georgia
Institute of Technology.
Selected Publications
Probing the Ultraviolet Luminosity Function of the Earliest
Galaxies with the Renaissance Simulations, B.W. O’Shea,
J.H. Wise, H. Xu, M.L. Norman, ApJL, 805, 12 (2015)
Bringing Simulation and Observation Together to Better
Understand the Intergalactic Medium, H. Egan, B.D. Smith,
B.W. O’Shea, J.M. Shull, ApJ, 791, 64 (2014)
Dissecting Galaxy Formation Models with Sensitivity
Analysis—a New Approach to Constrain the Milky Way
Formation History F.A. Gomez, C. Coleman-Smith, B.W.
O’Shea, J. Tumlinson, R. Wolpert, ApJ, 787, 20 (2014)
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