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An approach to quantum-computational hydrologic inverse analysis
Making predictions about flow and transport in an aquifer requires knowledge of the heterogeneous properties of the aquifer such as permeability. Computational methods for inverse analysis are commonly used to infer these properties from quantities that are more readily observable such as hydraulic...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5931973/ https://www.ncbi.nlm.nih.gov/pubmed/29720601 http://dx.doi.org/10.1038/s41598-018-25206-0 |
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author | O’Malley, Daniel |
author_facet | O’Malley, Daniel |
author_sort | O’Malley, Daniel |
collection | PubMed |
description | Making predictions about flow and transport in an aquifer requires knowledge of the heterogeneous properties of the aquifer such as permeability. Computational methods for inverse analysis are commonly used to infer these properties from quantities that are more readily observable such as hydraulic head. We present a method for computational inverse analysis that utilizes a type of quantum computer called a quantum annealer. While quantum computing is in an early stage compared to classical computing, we demonstrate that it is sufficiently developed that it can be used to solve certain subsurface flow problems. We utilize a D-Wave 2X quantum annealer to solve 1D and 2D hydrologic inverse problems that, while small by modern standards, are similar in size and sometimes larger than hydrologic inverse problems that were solved with early classical computers. Our results and the rapid progress being made with quantum computing hardware indicate that the era of quantum-computational hydrology may not be too far in the future. |
format | Online Article Text |
id | pubmed-5931973 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-59319732018-08-29 An approach to quantum-computational hydrologic inverse analysis O’Malley, Daniel Sci Rep Article Making predictions about flow and transport in an aquifer requires knowledge of the heterogeneous properties of the aquifer such as permeability. Computational methods for inverse analysis are commonly used to infer these properties from quantities that are more readily observable such as hydraulic head. We present a method for computational inverse analysis that utilizes a type of quantum computer called a quantum annealer. While quantum computing is in an early stage compared to classical computing, we demonstrate that it is sufficiently developed that it can be used to solve certain subsurface flow problems. We utilize a D-Wave 2X quantum annealer to solve 1D and 2D hydrologic inverse problems that, while small by modern standards, are similar in size and sometimes larger than hydrologic inverse problems that were solved with early classical computers. Our results and the rapid progress being made with quantum computing hardware indicate that the era of quantum-computational hydrology may not be too far in the future. Nature Publishing Group UK 2018-05-02 /pmc/articles/PMC5931973/ /pubmed/29720601 http://dx.doi.org/10.1038/s41598-018-25206-0 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article O’Malley, Daniel An approach to quantum-computational hydrologic inverse analysis |
title | An approach to quantum-computational hydrologic inverse analysis |
title_full | An approach to quantum-computational hydrologic inverse analysis |
title_fullStr | An approach to quantum-computational hydrologic inverse analysis |
title_full_unstemmed | An approach to quantum-computational hydrologic inverse analysis |
title_short | An approach to quantum-computational hydrologic inverse analysis |
title_sort | approach to quantum-computational hydrologic inverse analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5931973/ https://www.ncbi.nlm.nih.gov/pubmed/29720601 http://dx.doi.org/10.1038/s41598-018-25206-0 |
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