A variational eigenvalue solver on a photonic quantum processor

Alberto Peruzzo(University of Bristol), Jarrod R. McClean(Harvard University), Peter Shadbolt(University of Bristol), Man‐Hong Yung(Harvard University), Xiaoqi Zhou(University of Bristol), Peter J. Love(Haverford College), Alán Aspuru‐Guzik(Harvard University), Jeremy L. O’Brien(University of Bristol)
Nature Communications
July 23, 2014
Cited by 4,516Open Access
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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. Quantum computers promise to efficiently solve problems that would be practically impossible with a normal computer. Peruzzo et al. develop a variational computation approach that uses any available quantum resources and, with a photonic quantum processing unit, find the ground-state molecular energy of He–H+.


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