Clustering quantum Markov chains on trees associated with open quantum random walks
Copyright policy )Clustering quantum Markov chains on trees associated with open quantum random walks
<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>
- University of Rome Tor Vergata Italy
- Tunis El Manar University Tunisia
- Tunis University Tunisia
- University of Carthage Tunisia
- United Arab Emirates University United Arab Emirates
Markov chain, Markov property, cayley tree, Quantum mechanics, Quantum, Graph, Quantum Many-Body Systems and Entanglement Dynamics, Quantum walk, Cluster analysis, Artificial Intelligence, Quantum Computing and Simulation, QA1-939, FOS: Mathematics, Quantum Machine Learning, markov chains, Adjacency matrix, Physics, Statistics, random walks, Statistical and Nonlinear Physics, Discrete mathematics, quantum theory, Computer science, Atomic and Molecular Physics, and Optics, Markov model, Physics and Astronomy, Combinatorics, Computer Science, Physical Sciences, Quantum algorithm, Statistical Mechanics of Complex Networks, Mathematics, clustering
Markov chain, Markov property, cayley tree, Quantum mechanics, Quantum, Graph, Quantum Many-Body Systems and Entanglement Dynamics, Quantum walk, Cluster analysis, Artificial Intelligence, Quantum Computing and Simulation, QA1-939, FOS: Mathematics, Quantum Machine Learning, markov chains, Adjacency matrix, Physics, Statistics, random walks, Statistical and Nonlinear Physics, Discrete mathematics, quantum theory, Computer science, Atomic and Molecular Physics, and Optics, Markov model, Physics and Astronomy, Combinatorics, Computer Science, Physical Sciences, Quantum algorithm, Statistical Mechanics of Complex Networks, Mathematics, clustering
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!