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Camille Avestruz

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Dr. Avestruz is a computational cosmologist. She uses simulations to model, predict, and interpret observed large-scale cosmic structures. Her primary focus is to understand the evolution of galaxy clusters. These are the most massive gravitationally collapsed structures in our universe, comprised of hundreds to thousands of galaxies. Other aspects of her work prepare for the next decade of observations, which will produce unprecedented volumes of data. In particular, she is leading software development efforts within the clusters working group of the Large Synoptic Survey Telescope to calibrate galaxy cluster masses from simulation data. Dr. Avestruz also incorporates big data methods, including machine learning, to extract gravitational lensing signatures that probe the mass distribution of massive galaxies and galaxy clusters.

[Click on image to see video] Image projection of various components and properties of a simulated galaxy cluster in its last 8 gigayears of formation. The top left panel shows the underlying dark matter content, the top middle image shows the distribution of stars, and the remaining four panels are properties of the gas content: density, temperature, entropy, and metallicity. To model the evolution of galaxy clusters in a cosmological volume, the simulation uses adaptive refinement in space and time in order to span the relevant dynamic range of the system.

Michal Zochowski

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Michal Zochowski is a Professor in the Departments of Physics and Biophysics Program. His research interests lie in the intersection of physics and neuroscience. His group focuses on understanding the mechanisms of the formation of spatio-temporal patterns in coupled dynamical systems, their applicability and role during information processing in the brain. They use theoretical and experimental approaches, including computational modeling of various brain processes including memory storage, consolidation and its retrieval.

Charles Doering

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Charles Doering is the Nicholas D. Kazarinoff Collegiate Professor of Complex Systems, Mathematics and Physics and the Director of the Center for the Study of Complex Systems. He is a Fellow of the American Physical Society, and a Fellow of the Society of Industrial and Applied Mathematics (SIAM). He uses stochastic, dynamical systems arising in biology, chemistry and physics models, as well as systems of nonlinear partial differential equations to extract reliable, rigorous and useful predictions. His research spans rigorous estimation, numerical simulations and abstract functional and probabilistic analysis.

Kai Sun

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His  research focuses on understanding the role of strong correction effects in many-body quantum systems. The objective is to discover novel quantum states/materials and to understand their exotic properties using theoretical/numerical methods (with emphasis on topological properties). In his research, numerical techniques are applied to resolve the fate of a quantum material (or a theoretical model) in the presence of multiple competing ground states and to provide quantitative guidance for further (experimental/theoretical) investigations.

TI Animation

Interaction induced topological insulator with spontaneously-generated orbital rotations. This figure demonstrate how to use strong interactions to generate a topological state of matter in a many-body quantum system.