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Title: An adaptive variational algorithm for exact molecular simulations on a quantum computer

Abstract

Quantum simulation of chemical systems is one of the most promising near-term applications of quantum computers. The variational quantum eigensolver, a leading algorithm for molecular simulations on quantum hardware, has a serious limitation in that it typically relies on a pre-selected wavefunction ansatz that results in approximate wavefunctions and energies. Here we present an arbitrarily accurate variational algorithm that, instead of fixing an ansatz upfront, grows it systematically one operator at a time in a way dictated by the molecule being simulated. This generates an ansatz with a small number of parameters, leading to shallow-depth circuits. We present numerical simulations, including for a prototypical strongly correlated molecule, which show that our algorithm performs much better than a unitary coupled cluster approach, in terms of both circuit depth and chemical accuracy. Our results highlight the potential of our adaptive algorithm for exact simulations with present-day and near-term quantum hardware.

Authors:
; ; ; ORCiD logo
Publication Date:
Research Org.:
Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)
Sponsoring Org.:
USDOE Office of Science (SC); National Science Foundation (NSF)
OSTI Identifier:
1619531
Alternate Identifier(s):
OSTI ID: 1613145
Grant/Contract Number:  
SC0019199; SC0019318; 1839136
Resource Type:
Published Article
Journal Name:
Nature Communications
Additional Journal Information:
Journal Name: Nature Communications Journal Volume: 10 Journal Issue: 1; Journal ID: ISSN 2041-1723
Publisher:
Nature Publishing Group
Country of Publication:
United Kingdom
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Grimsley, Harper R., Economou, Sophia E., Barnes, Edwin, and Mayhall, Nicholas J.. An adaptive variational algorithm for exact molecular simulations on a quantum computer. United Kingdom: N. p., 2019. Web. https://doi.org/10.1038/s41467-019-10988-2.
Grimsley, Harper R., Economou, Sophia E., Barnes, Edwin, & Mayhall, Nicholas J.. An adaptive variational algorithm for exact molecular simulations on a quantum computer. United Kingdom. https://doi.org/10.1038/s41467-019-10988-2
Grimsley, Harper R., Economou, Sophia E., Barnes, Edwin, and Mayhall, Nicholas J.. Mon . "An adaptive variational algorithm for exact molecular simulations on a quantum computer". United Kingdom. https://doi.org/10.1038/s41467-019-10988-2.
@article{osti_1619531,
title = {An adaptive variational algorithm for exact molecular simulations on a quantum computer},
author = {Grimsley, Harper R. and Economou, Sophia E. and Barnes, Edwin and Mayhall, Nicholas J.},
abstractNote = {Quantum simulation of chemical systems is one of the most promising near-term applications of quantum computers. The variational quantum eigensolver, a leading algorithm for molecular simulations on quantum hardware, has a serious limitation in that it typically relies on a pre-selected wavefunction ansatz that results in approximate wavefunctions and energies. Here we present an arbitrarily accurate variational algorithm that, instead of fixing an ansatz upfront, grows it systematically one operator at a time in a way dictated by the molecule being simulated. This generates an ansatz with a small number of parameters, leading to shallow-depth circuits. We present numerical simulations, including for a prototypical strongly correlated molecule, which show that our algorithm performs much better than a unitary coupled cluster approach, in terms of both circuit depth and chemical accuracy. Our results highlight the potential of our adaptive algorithm for exact simulations with present-day and near-term quantum hardware.},
doi = {10.1038/s41467-019-10988-2},
journal = {Nature Communications},
number = 1,
volume = 10,
place = {United Kingdom},
year = {2019},
month = {7}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1038/s41467-019-10988-2

Citation Metrics:
Cited by: 22 works
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