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A variational eigenvalue solver on a photonic quantum processor.


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.

SUBMITTER: Peruzzo A 

PROVIDER: S-EPMC4124861 | biostudies-other | 2014

REPOSITORIES: biostudies-other

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A variational eigenvalue solver on a photonic quantum processor.

Peruzzo Alberto A   McClean Jarrod J   Shadbolt Peter P   Yung Man-Hong MH   Zhou Xiao-Qi XQ   Love Peter J PJ   Aspuru-Guzik Alán A   O'Brien Jeremy L JL  

Nature communications 20140723


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 r  ...[more]

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