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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-02062026-090521


Tipo di tesi
Tesi di laurea magistrale
Autore
NICASSIO, GAETANO
URN
etd-02062026-090521
Titolo
Evaluating Quantum Reservoir Computing: Richness, Memory and Prediction
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA
Relatori
relatore Prof. Bacciu, Davide
relatore Prof. Gallicchio, Claudio
relatore Prof. Ceni, Andrea
Parole chiave
  • echo state network
  • neural network
  • quantum machine learning
  • quantum neural network
  • quantum reservoir network
  • recurrent network
  • reservoir computing
Data inizio appello
27/02/2026
Consultabilità
Completa
Riassunto (Inglese)
Riassunto (Italiano)
The aim of this thesis is to evaluate a reservoir computing model inspired by the dynamics of a quantum system proposed in the literature.
The work involves comparing this model with a traditional reservoir computing approach, with the aim of identifying the parametric conditions that make the use of a quantum reservoir advantageous in solving classic time series processing problems.
The evaluation includes analyzing the memory capacity, estimating the effective dimensionality using techniques based on Principal Component Analysis, and measuring the predictive capacity on autoregressive and chaotic time series.
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