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Next Generation Computers Warrant Next Generation Groundwater Models.

Nicholas B Engdahl1

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Quantum computing may revolutionize groundwater (GW) modeling by enabling direct integration of uncertainty. This approach could lead to more accurate subsurface flow simulations by embedding uncertainty from the start.

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Area of Science:

  • Hydrology
  • Computational Science
  • Quantum Computing

Background:

  • Modern hydrologic models excel at simulating surface-subsurface systems.
  • Representing uncertainty in these simulations remains a significant challenge.
  • Current methods for uncertainty characterization are computationally expensive and not seamlessly integrated.

Purpose of the Study:

  • To explore the potential of quantum computing for addressing uncertainty in groundwater modeling.
  • To propose a reformulation of hydrologic models for quantum computing hardware.
  • To enhance the predictive capabilities of groundwater models by embedding uncertainty.

Main Methods:

  • Revising the foundational equations of groundwater models for quantum computation.
  • Tailoring governing equations for efficient execution on quantum hardware.
  • Embedding uncertainty by evolving distribution functions within simulations.

Main Results:

  • Quantum computing offers a pathway to directly handle uncertainty in flow system simulations.
  • Certain complex, uncertain problems like groundwater flow are well-suited for quantum computation.
  • Integrating uncertainty from the outset can lead to more efficient and accurate simulations.

Conclusions:

  • Next-generation groundwater models can leverage quantum computing to fundamentally address uncertainty.
  • This paradigm shift moves beyond mere acceleration to tackle inherent model deficiencies.
  • Quantum-enhanced models promise a novel approach to simulating subsurface flows with embedded uncertainty.