Quantum Modeling of Spatial Contiguity Constraints

Quantum computing has demonstrated potential for solving complex optimization problems; however, its application to spatial regionalization remains underexplored.Spatial contiguity, a fundamental constraint requiring spatial entities to form connected components, significantly increases the complexity of regionalization problems, which are typically challenging for quantum modeling.This paper proposes novel quantum formulations based on a flow model that enforces spatial contiguity constraints.Our scale-aware approach employs a Discrete Quadratic Model (DQM), solvable directly on quantum annealing hardware for small-scale datasets.In addition, it designs a hybrid quantum-classical approach to manage larger-scale problems within existing hardware limitations.This work establishes a foundational framework for integrating quantum methods into practical spatial optimization tasks. CCS Concepts Theory of computation Quantum query complexity.

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Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1145/3736393.3736691
Citations
2
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
4.96

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article

Quantum Modeling of Spatial Contiguity Constraints

Amr Magdy, Federico M. Spedalieri, Yuh-Lin Chang
2 citations
Quantum Computing Algorithms and Architecture
4.96
article

Quantum Modeling of Spatial Contiguity Constraints

Amr Magdy, Federico M. Spedalieri, Yuh-Lin Chang
article en
2 citations

Abstract

Quantum computing has demonstrated potential for solving complex optimization problems; however, its application to spatial regionalization remains underexplored.Spatial contiguity, a fundamental constraint requiring spatial entities to form connected components, significantly increases the complexity of regionalization problems, which are typically challenging for quantum modeling.This paper proposes novel quantum formulations based on a flow model that enforces spatial contiguity constraints.Our scale-aware approach employs a Discrete Quadratic Model (DQM), solvable directly on quantum annealing hardware for small-scale datasets.In addition, it designs a hybrid quantum-classical approach to manage larger-scale problems within existing hardware limitations.This work establishes a foundational framework for integrating quantum methods into practical spatial optimization tasks. CCS Concepts Theory of computation Quantum query complexity.

University of California, Riverside (US), University of Southern California (US)
National Science Foundation
Reduced inequalities
Openalex Percentile: Top 5%
Quantum Computing Algorithms and Architecture
4.96
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Quantum Modeling of Spatial Contiguity Constraints — Amr Magdy, Federico M. Spedalieri, et al. · (2025) | TGRS Research Map | TGRS