Quick Navigation
Topics
Trapped Ion Quantum Computing
Quantum Algorithm for Testing Graph Completeness
arXiv
Authors: Sara Giordano, Miguel A. Martin-Delgado
Year
2024
Paper ID
64879
Status
Preprint
Abstract Read
~2 min
Abstract Words
144
Citations
N/A
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 mathcal{O}\(log2n\), 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.
Why This Paper Matters
- This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
- It adds a 2024 reference point for readers tracking recent quantum research.
- Testing graph completeness is a critical problem in computer science and network theory.
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.