Clustering quantum Markov chains on trees associated with open quantum random walks-Reference-Cited by-同舟云学术

Clustering quantum Markov chains on trees associated with open quantum random walks

Published:2023 Issue:10 Volume:8 Page:23003-23015
ISSN:2473-6988
Container-title:AIMS Mathematics
language:
Short-container-title:MATH

Author:

Accardi Luigi¹,Andolsi Amenallah²,Mukhamedov Farrukh³,Rhaima Mohamed⁴,Souissi Abdessatar⁵

Affiliation:

1. Centro Vito Volterra, Università di Roma "Tor Vergata", Roma I-00133, Italy

2. Nuclear Physics and High Energy Physics Research Unit, Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis 2092, Tunisia

3. Department of Mathematical Sciences, College of Science, United Arab Emirates University, Al-Ain 15551, United Arab Emirates

4. Department of Statistics and Operations Research, College of Sciences, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia

5. Mathematical Physics, Quantum Modeling and Mechanical Design, University of Carthage, Carthage 1054, Tunisia

Abstract

<abstract><p>In networks, the Markov clustering (MCL) algorithm is one of the most efficient approaches in detecting clustered structures. The MCL algorithm takes as input a stochastic matrix, which depends on the adjacency matrix of the graph network under consideration. Quantum clustering algorithms are proven to be superefficient over the classical ones. Motivated by the idea of a potential clustering algorithm based on quantum Markov chains, we prove a clustering property for quantum Markov chains (QMCs) on Cayley trees associated with open quantum random walks (OQRW).</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

Reference42 articles.

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