Perspective

Exploiting Locality in Quantum Computation for Quantum Chemistry

Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
Department of Physics, Haverford College, Haverford, Pennsylvania 19041, United States
J. Phys. Chem. Lett., 2014, 5 (24), pp 4368–4380
DOI: 10.1021/jz501649m
Publication Date (Web): November 25, 2014
Copyright © 2014 American Chemical Society
Biography

Jarrod R. McClean is a Department of Energy Computational Graduate Science Fellow currently studying with Alán Aspuru-Guzik as a Ph.D. student at Harvard University. He is interested in the intersection between traditional and quantum computation for applications to chemistry.

Biography

Ryan Babbush is a P.hD. student in Chemical Physics studying quantum information with Alán Aspuru-Guzik at Harvard University. As an undergraduate, he doubled majored in chemistry and physics at Carleton College and will go on to join Google’s quantum computing research team following the defense of his dissertation next year.

Biography

Peter J. Love is an Associate Professor of Physics at Haverford College.

Biography

Alán Aspuru-Guzik is Professor of Chemistry and Chemical Biology of Harvard University. His research group works at the intersection of quantum information and chemistry. He has been working on quantum computing for quantum chemistry since 2005. He has received numerous awards, including a Technology Review 35 Innovators under 35 award. http://aspuru.chem.harvard.edu

Abstract

Abstract Image

Accurate prediction of chemical and material properties from first-principles quantum chemistry is a challenging task on traditional computers. Recent developments in quantum computation offer a route toward highly accurate solutions with polynomial cost; however, this solution still carries a large overhead. In this Perspective, we aim to bring together known results about the locality of physical interactions from quantum chemistry with ideas from quantum computation. We show that the utilization of spatial locality combined with the Bravyi–Kitaev transformation offers an improvement in the scaling of known quantum algorithms for quantum chemistry and provides numerical examples to help illustrate this point. We combine these developments to improve the outlook for the future of quantum chemistry on quantum computers.

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Metrics

Received 6 August 2014
Date accepted 25 November 2014
Published online 25 November 2014
Published in print 18 December 2014
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