Tesi etd-07032023-213929 |
Link copiato negli appunti
Tipo di tesi
Tesi di laurea magistrale
URN
etd-07032023-213929
Titolo
Towards a quantum version of the Markov Clustering Algorithm
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA
Relatori
.
relatore Prof.ssa Bernasconi, Anna
relatore Prof.ssa Del Corso, Gianna Maria
relatore Dott. Berti, Alessandro
relatore Prof.ssa Del Corso, Gianna Maria
relatore Dott. Berti, Alessandro
Parole chiave
- markov clustering algorithm
- quantum clustering
- quantum computing
Data inizio appello
21/07/2023
Consultabilità
Completa
Riassunto (Inglese)
Riassunto (Italiano)
Quantum computing is an emerging technology that uses the principles of quantum mechanics to solve problems faster than classical computers. In recent years, a growing number of new quantum methods have been proposed.
In this thesis, we investigate the possibility of realising a quantum version of a well-known graph-based clustering algorithm, the Markov Clustering algorithm. We propose a quantum procedure to show how, by exploiting quantum computing, it is possible to achieve a speedup in terms of time complexity for this algorithm, moving from O(N^3) to O(N^2 log N) for graphs of N nodes.
In this thesis, we investigate the possibility of realising a quantum version of a well-known graph-based clustering algorithm, the Markov Clustering algorithm. We propose a quantum procedure to show how, by exploiting quantum computing, it is possible to achieve a speedup in terms of time complexity for this algorithm, moving from O(N^3) to O(N^2 log N) for graphs of N nodes.
File
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| Thesis.pdf | 2.24 Mb |
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