A variational eigenvalue solver on a photonic quantum processor

Alberto Peruzzo (), Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J. Love, Alán Aspuru-Guzik () and Jeremy L. O’Brien ()
Additional contact information
Alberto Peruzzo: Centre for Quantum Photonics, University of Bristol
Jarrod McClean: Harvard University
Peter Shadbolt: Centre for Quantum Photonics, University of Bristol
Man-Hong Yung: Harvard University
Xiao-Qi Zhou: Centre for Quantum Photonics, University of Bristol
Peter J. Love: Haverford College
Alán Aspuru-Guzik: Harvard University
Jeremy L. O’Brien: Centre for Quantum Photonics, University of Bristol

Nature Communications, 2014, vol. 5, issue 1, 1-7

Abstract: Abstract Quantum computers promise to efficiently solve important problems that are intractable on a conventional computer. For quantum systems, where the physical dimension grows exponentially, finding the eigenvalues of certain operators is one such intractable problem and remains a fundamental challenge. The quantum phase estimation algorithm efficiently finds the eigenvalue of a given eigenvector but requires fully coherent evolution. Here we present an alternative approach that greatly reduces the requirements for coherent evolution and combine this method with a new approach to state preparation based on ansätze and classical optimization. We implement the algorithm by combining a highly reconfigurable photonic quantum processor with a conventional computer. We experimentally demonstrate the feasibility of this approach with an example from quantum chemistry—calculating the ground-state molecular energy for He–H+. The proposed approach drastically reduces the coherence time requirements, enhancing the potential of quantum resources available today and in the near future.

Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (29)

Downloads: (external link)
https://www.nature.com/articles/ncomms5213 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms5213

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/ncomms5213

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().