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Graham D. Fletcher

Principal Project Specialist, Computational Science

Graham Fletcher has a background in quantum chemistry and supercomputing. His research interests focus on the development of highly scalable methods and algorithms for the accurate and reliable prediction of chemical phenomena.

Biography

Graham Fletcher has a background in quantum chemistry and supercomputing. His research interests focus on the development of highly scalable methods and algorithms for the accurate and reliable prediction of chemical phenomena. He gained a Ph.D. (physics) from the University of York, UK, under Graham Doggett, who worked with Coulson on molecular orbital theory. Graham has extensive experience in high performance computing, and has worked at Iowa State University, NASA Ames Research Center, and Daresbury Laboratory in the UK. More recently, he is the originator of the Variational Subspace Valence Bond (VSVB) method [1].

VSVB is a rigorous ab initio electronic structure method, and the only general, scalable alternative to molecular orbital theory. VSVB obviates the famous N! problem’ – the long-standing limitation of general, non-orthogonal orbitals – allowing valence bond type wave functions to be constructed from objects familiar to chemists such as bonds and lone pairs’. VSVB can model many classes of chemical problem in a single method: ground and excited states; open- and closed-shell systems; bond-breaking/formation; resonance; etc. In addition, VSVB permits transfer learning’, in which the response of a generic orbital type (such as a bond or lone pair) transferred between different molecular environments can be machine-learned, opening the way for automated wave function generation at negligible cost. 

[1] Graham D. Fletcher, The variational subspace valence bond method”, J. Chem. Phys. 142, 134112 (2015). http://​dx​.doi​.org/​10​.​1063​/​1​.​4916743