Actions for Many Body Methods from Chemistry to Physics [electronic resource] : Novel Computational Techniques for Materials-Specific Modelling A Computational Materials Science and Chemistry Network

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Many Body Methods from Chemistry to Physics [electronic resource] : Novel Computational Techniques for Materials-Specific Modelling A Computational Materials Science and Chemistry Network

Published
Washington, D.C. : United States. Dept. of Energy. Office of Basic Energy Sciences, 2016.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy
Physical Description
6 pages : digital, PDF file
Additional Creators
Columbia University, United States. Department of Energy. Office of Basic Energy Sciences, and United States. Department of Energy. Office of Scientific and Technical Information
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Summary
Understanding the behavior of interacting electrons in molecules and solids so that one can predict new superconductors, catalysts, light harvesters, energy and battery materials and optimize existing ones is the ``quantum many-body problem’’. This is one of the scientific grand challenges of the 21st century. A complete solution to the problem has been proven to be exponentially hard, meaning that straightforward numerical approaches fail. New insights and new methods are needed to provide accurate yet feasible approximate solutions. This CMSCN project brought together chemists and physicists to combine insights from the two disciplines to develop innovative new approaches. Outcomes included the Density Matrix Embedding method, a new, computationally inexpensive and extremely accurate approach that may enable first principles treatment of superconducting and magnetic properties of strongly correlated materials, new techniques for existing methods including an Adaptively Truncated Hilbert Space approach that will vastly expand the capabilities of the dynamical mean field method, a self-energy embedding theory and a new memory-function based approach to the calculations of the behavior of driven systems. The methods developed under this project are now being applied to improve our understanding of superconductivity, to calculate novel topological properties of materials and to characterize and improve the properties of nanoscale devices.
Report Numbers
E 1.99:doe-columbia--sc0006613
doe-columbia--sc0006613
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Other Subject(s)
Note
Published through SciTech Connect.
11/17/2016.
"doe-columbia--sc0006613"
Andrew Millis.
Type of Report and Period Covered Note
Final;
Funding Information
SC0006613
View MARC record | catkey: 24056464