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  • Open Access

Block encoding of the three-dimensional heterogeneous Poisson equation with application to fracture flow

Austin Pechan1,*, John Golden2,†, and Daniel O’Malley3

  • *Contact author: agp@berkeley.edu
  • †Contact author: golden@lanl.gov
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Phys. Rev. Applied 25, 044038 – Published 15 April, 2026

DOI: https://doi.org/10.1103/mx5c-8vqk

Abstract

Quantum linear system (QLS) algorithms offer the potential to solve large-scale linear systems exponentially faster than classical methods. However, applying QLS algorithms to real-world problems remains challenging due to issues such as state preparation, data loading, and efficient information extraction. In this work, we study the feasibility of applying QLS algorithms to solve discretized three-dimensional (3D) heterogeneous Poisson equations, with specific examples relating to groundwater flow through geologic fracture networks. We explicitly construct a block encoding for the 3D heterogeneous Poisson matrix by leveraging the sparse local structure of the discretized operator. While classical solvers benefit from preconditioning, we show that block encoding the system matrix and preconditioner separately does not improve the effective condition number that dominates the QLS run-time. This differs from classical approaches where the preconditioner and the system matrix can often be implemented independently. Nevertheless, due to the structure of the problem in three dimensions, the quantum algorithm achieves a run-time of O(N2/3polylog N⋅log(1/ϵ)), outperforming the best classical methods (with run times of O(NlogN⋅log(1/ϵ))) and offering exponential memory savings. These results highlight both the promise and limitations of QLS algorithms for practical scientific computing, and point to effective condition-number reduction as a key barrier in achieving quantum advantages.

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Phys. Rev. Applied 25, 044038– Published 15 April, 2026
  • Received 12 August 2025
  • Revised 16 December 2025
  • Accepted 3 March 2026
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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