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Edward Valeev

Professor
Edward Valeev
421G Davidson Hall

Research Interests

Electronic structure theory is routinely used to interpret experimental results and guide designs of new experiments in chemistry and materials science. The workhorse of modern electronic structure, the Density Functional Theory (DFT), is fast and reasonably accurate for well-behaved systems, but it is too empirical to be predictive. Truly predictive Wave Function or Green's Function methods which can replace some or most experiments are too expensive to be applicable to experimentally-relevant systems in condensed phase chemistry or materials science. The goal of our research is to develop electronic structure methods that can predict properties of molecules and materials. This objective can only be achieved by advancing molecular structure theory in accord with modern applied mathematics and computational science. Some of the ongoing efforts include:

- Development of reduced-scaling wave function methods that can be routinely applied to systems with 1000 or more atoms at the cost comparable to DFT. Such reduced-scaling approaches utilize novel tensor compression (tensor network) techniques that we develop.

- Development of real-space representations for wave functions that can be used to describe electronic structure more accurately than the traditional Gaussian atomic orbitals, especially in relativistic (heavy element) chemistry, high-density materials, and in laser-driven processes.

- Development of self-interaction-free approaches to the density functional theory that seek to cure one of its fundamental ills.

- Development of effective hamiltonian approaches suitable for chemistry simulation on quantum computers.

- Development of efficient methods for periodic solids.

- Development of advanced software for computation of electronic structure, including chemistry software for deployment on the DOE exascale computers. These developments are enabled by our development of programming models for composing scientific applications on extreme-scale distributed-memory heterogeneous machines.

Our group deploys our ideas in open-source, free, and commercial software to be usable by other computational researchers and experimentalists alike. Our main research platform MPQC (mpqc.org) is designed for large scale distributed parallel memory machines; we also develop many components for electronic structure (Libint for Gaussian integrals, TiledArray for tensor computation) that are used by many research and production codes around the world. Our contributions are found in end-user packages for chemistry Orca, CP2K, Psi, and others.

Our work is currently supported by the US National Science Foundation and US Department of Energy. Past research has also been supported by Sloan Foundation, Camille and Henry Dreyfus Foundation, and ACS Petroleum Research Fund.

  1. “Robust Pipek-Mezey Orbital Localization in Periodic Solids”, Marjory C. Clement, Xiao Wang, and Edward F. Valeev, J. Chem. Theor. Comp. 17, 7406-7415 (2021), https://doi.org/10.1021/acs.jctc. 1c00238.
  2. “Robust approximation of tensor networks: application to grid-free tensor factorization of the Coulomb interaction”, Karl Pierce, Varun Rishi, and Edward F. Valeev, J. Chem. Theor. Comp. 17, 2217-2230 (2021), https://doi.org/10.1021/acs.jctc.0c01310.
  3. “Distributed-memory multi-GPU block-sparse tensor contraction for electronic structure”, Thomas Herault, Yves Robert, George Bosilca , Robert J. Harrison, Cannada A. Lewis, Edward F Valeev, and Jack J. Dongarra, 35th IEEE International Parallel & Distributed Processing Symposium, 537-546 (2021), https://doi.org/10. 1109/IPDPS49936.2021.00062.
  4. “Many-Body Quantum Chemistry on Massively Parallel Computers”, Justus A. Calvin, Chong Peng, Varun Rishi, Ashutosh Kumar, and Edward F. Valeev, Chem. Rev. 121, 1203–1231 (2021), https://doi.org/10. 1021/acs.chemrev.0c00006.
  5. “Quantum simulation of electronic structure with transcorrelated Hamiltonian: increasing accuracy without extra quantum resources”, Mario Motta, Tanvi P. Gujarati, Julia E. Rice, Ashutosh Kumar, Conner Masteran, Joseph A. Latone, Eunseok Lee, Edward F. Valeev, and Tyler Y. Takeshita, Phys. Chem. Chem. Phys. 22, 24270-24281 (2020), https://doi.org/10.1039/D0CP04106H
  6. “Explicitly correlated coupled cluster method for accurate treatment of open-shell molecules with hundreds of atoms”, Ashutosh Kumar, Frank Neese, and Edward F Valeev, J. Chem. Phys. 153, 094105 (2020), https: //doi.org/10.1063/5.0012753.
  7. “Massively Parallel Quantum Chemistry: A High-Performance Research Platform for Electronic Structure”, Chong Peng, Cannada A. Lewis, Xiao Wang, Marjory C. Clement, Karl Pierce, Varun Rishi, Fabijan Pavošević, Samuel Slattery, Jinmei Zhang, Nakul Teke, Ashutosh Kumar, Conner Masteran, Andrey Asadchev, Justus A. Calvin, and Edward F. Valeev, J. Chem. Phys., J. Chem. Phys. 153, 044120 (2020), https://doi.org/10. 1063/5.0005889.
  8. “Direct determination of optimal pair-natural orbitals in a real-space representation: the second-order Møller-Plesset energy”, Jakob S. Kottmann, Florian A. Bischoff, Edward F. Valeev, J. Chem. Phys. 152, 074105 (2020), https://doi.org/10.1063/1.5141880.
  9. “Coupled-Cluster Singles, Doubles and Perturbative Triples with Density Fitting Approximation for Massively Parallel Heterogeneous Platforms”, Chong Peng, Justus A. Calvin and Edward F. Valeev, Int. J. Quant. Chem. 119, e25894 (2019), http://dx.doi.org/10.1002/QUA.25894
  10. “Sparse Maps: A systematic infrastructure for reduced-scaling electronic structure methods. 1. An efficient and simple linear scaling local MP2 method that uses an intermediate basis of pair natural orbitals.”, Peter Pinski, Christoph Riplinger, Edward F. Valeev, and Frank Neese, J. Chem. Phys. 143, 034108 (2015), http: //dx.doi.org/10.1063/1.4926879.
  11. “Explicitly Correlated R12/F12 Methods for Electronic Structure”, L. Kong, F. A. Bischoff, and E. F. Valeev, Chem. Rev. 112, 75 (2012), http://dx.doi.org/10.1021/cr200204r.
  • The Blavatnik National Award Finalist, The Blavatnik Family Foundation, 2016
  • Dirac Medal, World Association of Theoretical and Computational Chemists (WATOC), 2015
  • Annual Medal of The International Academy of Quantum Molecular Sciences, 2014
  • Kavli Fellow, 25th Symposium Kavli Froniers of Science, U.S. National Academy of Sciences, 2013
  • Camille Dreyfus Teacher-Scholar Award, The Camille & Henry Dreyfus Foundation, 2010
  • John C. Schug Research Award, Virginia Tech Department of Chemistry, 2010
  • NSF CAREER Award, National Science Foundation, 2009
  • Alfred P. Sloan Research Fellow, The Alfred P. Sloan Foundation, 2009
  • ACS Hewlett-Packard Outstanding Young Investigator Award, American Chemical Society, 2009
  • Wiley International Journal of Quantum Chemistry Young Investigator Award, 2007
  • M.S. Higher Chemistry College of Russian Academy of Sciences, Moscow, Russia, 1996
  • Ph.D. University of Georgia, 2000
  • Research Scientist II, Center for Computational Molecular Science and Technology, Georgia Institute of Technology, 2001–2006