Journal article
Variational quantum algorithms for nonlinear problems
- Abstract:
- We show that nonlinear problems including nonlinear partial di↵erential equations can be e- ciently solved by variational quantum computing. We achieve this by utilizing multiple copies of variational quantum states to treat nonlinearities eciently and by introducing tensor networks as a programming paradigm. The key concepts of the algorithm are demonstrated for the nonlinear Schr¨odinger equation as a canonical example. We numerically show that the variational quantum ansatz can be exponentially more ecient than matrix product states and present experimental proof-of-principle results obtained on an IBM Q device.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 5.0MB, Terms of use)
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- Publisher copy:
- 10.1103/PhysRevA.101.010301
Authors
- Publisher:
- American Physical Society
- Journal:
- Physical Review A More from this journal
- Volume:
- 101
- Article number:
- 010301(R)
- Publication date:
- 2020-01-06
- Acceptance date:
- 2019-12-11
- DOI:
- EISSN:
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1094-1622
- ISSN:
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1050-2947
- Language:
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English
- Keywords:
- Pubs id:
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pubs:1078316
- UUID:
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uuid:ebd47ad9-8cdd-44cd-926f-258c3da098e7
- Local pid:
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pubs:1078316
- Source identifiers:
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1078316
- Deposit date:
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2019-12-18
Terms of use
- Copyright holder:
- American Physical Society
- Copyright date:
- 2020
- Rights statement:
- © 2020 American Physical Society
- Notes:
- This is the accepted manuscript version of the article. The final version is available from The Royal Society at: https://doi.org/10.1103/PhysRevA.101.010301
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