Quantum algorithm for testing graph completeness

Testing graph completeness is a critical problem in computer science and network theory. Leveraging quantum computation, we present an efficient algorithm using the Szegedy quantum walk and quantum phase estimation (QPE). Our algorithm, which takes the number of nodes and the adjacency matrix as input, constructs a quantum walk operator and applies QPE to estimate its eigenvalues. These eigenvalues reveal the graph’s structural properties, enabling us to determine its completeness. We establish a relationship between the number of nodes in a complete graph and the number of marked nodes, optimizing the success probability and running time. The time complexity of our algorithm is O ( log 2 n ) , where n is the number of nodes of the graph. offering a clear quantum advantage over classical methods. This approach is useful in network structure analysis, evaluating classical routing algorithms, and assessing systems based on pairwise comparisons.

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Institutions

Publication Details

Journal
Annals of Physics
Published
2025-11-25
DOI
https://doi.org/10.1016/j.aop.2025.170305
Citations
1
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
2.48
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article

Quantum algorithm for testing graph completeness

Sara Giordano, M. A. Martín-Delgado
1 citations
Annals of Physics
Quantum Computing Algorithms and Architecture
2.48
article

Quantum algorithm for testing graph completeness

Sara Giordano, M. A. Martín-Delgado
article en
1 citations

Abstract

Testing graph completeness is a critical problem in computer science and network theory. Leveraging quantum computation, we present an efficient algorithm using the Szegedy quantum walk and quantum phase estimation (QPE). Our algorithm, which takes the number of nodes and the adjacency matrix as input, constructs a quantum walk operator and applies QPE to estimate its eigenvalues. These eigenvalues reveal the graph’s structural properties, enabling us to determine its completeness. We establish a relationship between the number of nodes in a complete graph and the number of marked nodes, optimizing the success probability and running time. The time complexity of our algorithm is O ( log 2 n ) , where n is the number of nodes of the graph. offering a clear quantum advantage over classical methods. This approach is useful in network structure analysis, evaluating classical routing algorithms, and assessing systems based on pairwise comparisons.

Annals of PhysicsVol. 484
Universidad Complutense de Madrid (ES), Universidad Politécnica de Madrid (ES)
Openalex Percentile: Top 8%
Quantum Computing Algorithms and Architecture
2.48
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