Parallel Large-scale Semidefinite Programming for Strong Electron Correlation: Using Correlation and Entanglement in the Design of Efficient Energy-Transfer Mechanisms
Abstract
Challenges addressed under the grant include: (i) improving our understanding of the many-electron quantum mechanisms by which nature uses strong electron correlation for efficient energy transfer, particularly in photosynthesis and bioluminescence, (ii) providing an innovative paradigm for energy transfer in photovoltaic materials by which new levels of solar efficiency are achieved through the use of strong electron correlation and entanglement, (iii) enhancing two-electron reduced-density-matrix (2-RDM)-based electronic-structure methods that significantly expand the range of strongly correlated molecular systems that can be studied with applications throughout science and engineering, and (iv) developing a new generation of large-scale, parallel algorithms for performing semidefinite programming with applications to problems in engineering, computer science, statistics, finance and economics. Research led to important technology transitions including the formation of RDMCHEM LLC, a software company that is developing the next generation of computational software for chemistry with applications to engineering, molecular biology, and physics.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 24, 2014
- Accession Number
- ADA617270
Entities
People
- David A Mazziotti
Organizations
- University of Chicago