4.7 Article

Using Complex Probability Amplitudes to Simulate Solute Transport in Composite Porous Media

Journal

WATER RESOURCES RESEARCH
Volume 57, Issue 9, Pages -

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2021WR030249

Keywords

quantum mathematics; probability amplitudes; solute transport modeling; composite porous media

Funding

  1. US Department of Energy, Office of Science [DE-SC0019123]
  2. National Science Foundation [EAR-2049687]
  3. U.S. Department of Energy (DOE) [DE-SC0019123] Funding Source: U.S. Department of Energy (DOE)

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The article discusses how the mathematical concepts used in modeling quantum systems can be applied to subsurface water resources problems, proposing a probability amplitude-based model for describing transport in porous media. This complex model introduces different dispersion coefficients, affecting the system's behavior even when the dispersion coefficients are identical.
Probability amplitudes are fundamental to quantum mechanics and offer robust descriptions of complicated systems, which have allowed physicists to explain behaviors inaccessible to classical physics. This article ponders how some of the same conceptual underpinnings of the mathematics used for modeling quantum systems might be applied to subsurface water resources problems and speculates how these tools could facilitate applications on quantum computers. A probability amplitude-based model for describing advective-dispersive transport in porous media using linear operators is investigated. The proposed complex valued model decomposes spreading into two sub-continuum partial dispersion coefficients, and this recovers classical spreading when the sum of these coefficients is the Fickian dispersion coefficient. However, the probability amplitudes have a many-to-one relationship to a probability distribution, so it embeds a level of heterogeneity into seemingly equivalent functions. Two propagators with different sub-continuum coefficients may have the same macroscopic behavior when either is considered in isolation, but when they act on the other the system's behavior changes. Differences in the amplitudes cause a reduction in spreading as velocity correlations are disrupted, despite both propagators having identical dispersion coefficients, and this cannot be achieved using classical methods without changing the dispersion coefficient. The main point is that these amplitude-based models offer a way to embed information about the system into the propagators, instead of just averaging it out when making an upscaled model.

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