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An approach to quantum-computational hydrologic inverse analysis

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TLDR
While quantum computing is in an early stage compared to classical computing, it is demonstrated that it is sufficiently developed that it can be used to solve certain subsurface flow problems and the era of quantum-computational hydrology may not be too far in the future.
Abstract
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.

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Journal Article

Flow and transport in highly heterogeneous formations: 3. Numerical simulations and comparison with theoretical results

TL;DR: In this article, two approximate semianalytical solutions, based on a self-consistent model (SC) and on a first-order perturbation in the log conductivity variance (FO), are used in order to compute the statistical moments of flow and transport variables for a lognormal conductivity pdf.
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References
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TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
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Journal ArticleDOI

Quantum annealing in the transverse Ising model

TL;DR: In this article, the authors introduce quantum fluctuations into the simulated annealing process of optimization problems, aiming at faster convergence to the optimal state. But quantum fluctuations cause transitions between states and thus play the same role as thermal fluctuations in the conventional approach.
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Trending Questions (2)
Are quantum computers good at hydrologic modeling?

Yes, quantum computers can be used for hydrologic modeling, as demonstrated by the use of a D-Wave 2X quantum annealer to solve hydrologic inverse problems.

How can quantum computers be used to improve hydrologic modeling?

Quantum computers can be used for hydrologic inverse analysis to infer properties of aquifers, such as permeability, from observable quantities like hydraulic head.