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Quantum Information Processing

On new PageRank computation methods using quantum computing

  • 01-03-2023
Published in:
Authors
Théodore Chapuis-Chkaiban
Zeno Toffano
Benoît Valiron
Published in
Quantum Information Processing | Issue 3/2023

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Abstract

The article introduces innovative methods for computing PageRank using quantum computing, aiming to improve the efficiency and accuracy of classical PageRank algorithms. It presents three main proposals: an efficient quantum circuit for classical PageRank computation using the HHL algorithm, a quantum framework for Spectral Graph Theory, and a generalized PageRank formalism that can be applied in both classical and quantum signal processing. The generalized PageRank method leverages Spectral Graph Theory to produce more refined rankings by investigating the input graph's structure. The article also compares the proposed methods with existing quantum PageRank algorithms and provides numerical results to validate their effectiveness. Additionally, it discusses the potential applications and extensions of the generalized PageRank algorithm in various fields.
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Title
On new PageRank computation methods using quantum computing
Authors
Théodore Chapuis-Chkaiban
Zeno Toffano
Benoît Valiron
Publication date
01-03-2023
Publisher
Springer US
Published in
Quantum Information Processing / Issue 3/2023
Print ISSN: 1570-0755
Electronic ISSN: 1573-1332
DOI
https://doi.org/10.1007/s11128-023-03856-y
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