Carnegie Mellon University

Hy Trac

Associate Professor

Astrophysics & Cosmology
Wean Hall 8307

lab website

Prof. Hy Trac

Education & Professional Experience

Ph.D.: University of Toronto (Canada), Astronomy & Astrophysics (2004)
B.Sc.: University of British Columbia (Canada), Physics and Astronomy (1999)


Curriculum Vitae

Associate Professor, Carnegie Mellon University, 2016–
Assistant Professor, Carnegie Mellon University, 2010–16
Post-doctoral Research: Harvard University, 2007–10
Post-doctoral Research: Princeton University, 2004–07

Research Interests

I work on computational and theoretical cosmology and astrophysics. My research involves the development and application of numerical simulations to model and interpret the observable University. In cosmology, I work on complex problems involving the gas, stars, galaxies, quasars, and clusters of galaxies that provide information about the underlying dark matter and dark energy. In astrophysics, I am interested in the dynamics of stellar systems and the mergers of compact objects that produce gravitational waves. I also collaborate with computer scientists and statisticians to apply modern AI/ML approaches to improve multi-wavelength data analysis and numerical simulations. For example, we are applying Bayesian Deep Learning to map the dark matter in galaxy clusters. I am a member of the Atacama Cosmology Telescope (ACT) and Simons Observatory (SO) Collaborations.

Recent Publications

Dipto Mukherjee et al, Close encounters of the interstellar kind: exploring the capture of interstellar objects in near-Earth orbitMNRAS, 908, 921

Dipto Mukherjee et al, Evolution of massive black hole binaries in collisionally relaxed nuclear star clusters - Impact of mass segregationMNRAS, 518, 4801

Matthew Ho et al, The dynamical mass of the Coma cluster from deep learningNat Astron (2022)

Nianyi Chen et al, Patchy Kinetic Sunyaev-Zel'dovich Effect with Controlled Reionization History and MorphologyAstrophys. J., 943, 138

Hy Trac et al, AMBER: A Semi-numerical Abundance Matching Box for the Epoch of Reionization, Astrophys. J., 927, 186 (2022)

Yizhou He et al, A Hydro-particle-mesh Code for Efficient and Rapid Simulations of the Intracluster Medium, Astrophys. J., 925, 134 (2022)

Dipto Mukherjee et al, Fast Multipole Methods for N-body Simulations of Collisional Star Systems, Astrophys. J., 916, 9 (2021)

Matthew Ho et al, Approximate Bayesian Uncertainties on Deep Learning Dynamical Mass Estimates of Galaxy ClustersAstrophys. J., 908, 204 (2021)

Matthew Ho et al, A Robust and Efficient Deep Learning Method for Dynamical Mass Measurements of Galaxy Clusters,  Astrophys. J., 887, 25 (2019)

The Simons Observatory Collaboration, The Simons Observatory: Science goals and forecasts, JCAP 02, 056 (2019)

Hy Trac et al, SCORCH I: The Galaxy-Halo Connection in the First Billion Years, Astrophys. J., 813, 54 (2015)

More Publications:
ORCID  Researcher ID