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A portrait photo of Sophie Beck.
A portrait photo of Sophie Beck.
Past

Research Staff

Sophie Beck, Ph.D.

Associate Research Scientist, Center for Computational Quantum Physics

Bio

Sophie Beck joined the Flatiron Institute as a Flatiron Research Fellow in the Center for Computational Quantum Physics (CCQ) in September 2020 and served as an Associate Research Scientist from 2023 to 2024. Her research focuses on the application and development of computational methods for the simulation of quantum materials with strong electronic correlations. She obtained her Ph.D. in materials science from the ETH Zurich in Switzerland in 2020 and did her undergraduate studies in physics at the University of Freiburg in Germany.

Publications

Insulating transport in anisotropic metals: breakdown of Drude transport and the puzzling \(c\)-axis resistivity of Sr\(_2\)RuO\(_4\) and other layered oxides

arXiv:2510.03756, October 4, 2025

Sophie Beck, Matthew Shammami, Lorenzo Van Muñoz, Jason Kaye, Antoine Georges, and Jernej Mravlje

High-order and adaptive optical conductivity calculations using Wannier interpolation

Physical Review B, arXiv:2406.15466, May 28, 2025

Lorenzo Van Muñoz, Jason Kaye, Alex Barnett, and Sophie Beck

Low-temperature transport in high-conductivity correlated metals: a density-functional plus dynamical mean-field study of cubic perovskites

arXiv:2505.04508, May 7, 2025

Harrison LaBollita , Jeremy Lee-Hand, Fabian B. Kugler, Lorenzo Van Muñoz, Sophie Beck, Alexander Hampel, et al.

Electron-phonon coupling in correlated metals: A dynamical mean-field theory study

Physical Review B, arXiv:2505.03958, May 6, 2025

David J. Abramovitch, Jennifer Coulter, Sophie Beck, and Andrew J. Millis

Featuring Sophie Beck

A portrait photo of Sophie Beck.

Controlling the Complexity: Tuning Quantum Materials for Science and Technology

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Center for Computational Quantum Physics

CCQ’s mission is to develop the concepts, theories, algorithms and codes needed to solve the quantum many-body problem and use the solutions to predict the behavior of materials and molecules of scientific and technological interest.

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