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His work ranges from mathematical physics, to developing computational methods for the many-body problem, to working on “ab initio” calculations in real materials. He has been awarded the Kusaka Memorial Prize in Physics from Princeton University (1985), the Oak Ridge Associated Universities, Junior Faculty Enhancement Award (1995), the Office of Naval Research Young Investigator Program award (1996), the Georgetown University Distinguished Achievement in Research award (2007), and the Alpha Sigma Nu National Book Award for the Natural Sciences (2009). He has been a Fellow of the American Physical Society from the Division of Condensed Matter Physics since 2006. In 2010, he was named the inaugural holder of the McDevitt Chair in Physics at Georgetown.
Professor Freericks has worked in a wide variety of different areas in condensed matter and cold atomic physics. He has been working in dynamical mean-field theory since 1992 and has been involved in solving the Falicov-Kimball model, Hubbard model, periodic Anderson model, and the Holstein model. Dynamical mean-field theory is a relatively new theoretical and computational method that allows one to solve the many-body problem; it becomes exact in the limit of large spatial dimensions. His computational work has focused on exact solutions, quantum Monte Carlo methods, and the numerical renormalization group. Many of these computational projects are carried out on large national supercomputers, and run on thousands of processors. Recently he has focused on inhomogeneous systems (multilayers, cold atoms in a trap) and on nonequilibrium effects, showing how to generalize dynamical mean-field theory for nonequilibrium situations. Currently, his group is funded by the National Science Foundation, the Defense Advanced Research Projects Agency, the Army Research Office, the Air Force Office of Scientific Research (under a MURI), and the Department of Energy.
Professor Freericks has worked in a wide variety of different areas in condensed matter and cold atomic physics. He has been working in dynamical mean-field theory since 1992 and has been involved in solving the Falicov-Kimball model, Hubbard model, periodic Anderson model, and the Holstein model. Dynamical mean-field theory is a relatively new theoretical and computational method that allows one to solve the many-body problem; it becomes exact in the limit of large spatial dimensions. His computational work has focused on exact solutions, quantum Monte Carlo methods, and the numerical renormalization group. Many of these computational projects are carried out on large national supercomputers, and run on thousands of processors. Recently he has focused on inhomogeneous systems (multilayers, cold atoms in a trap) and on nonequilibrium effects, showing how to generalize dynamical mean-field theory for nonequilibrium situations. Currently, his group is funded by the National Science Foundation, the Defense Advanced Research Projects Agency, the Army Research Office, the Air Force Office of Scientific Research (under a MURI), and the Department of Energy.
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Symmetryno. 3 (2024): 297
Physical review lettersno. 10 (2024): 100601-100601
GIREP MALTA WEBINAR 2021 (2023)
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American Journal of Physicsno. 11 (2023): 885-892
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James K. Freericks, Leanne Doughty
SEVENTEENTH CONFERENCE ON EDUCATION AND TRAINING IN OPTICS AND PHOTONICS: ETOP 2023 (2023)
PHYSICAL REVIEW LETTERSno. 26 (2023): 266401
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