Rocutto, Lorenzo
  
(2024)
Assessing the current state of adiabatic quantum computers in solving challenging computational problems, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. 
 Dottorato di ricerca in 
Data science and computation, 35 Ciclo. DOI 10.48676/unibo/amsdottorato/11302.
  
 
  
  
        
        
        
  
  
  
  
  
  
  
    
  
    
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      Abstract
      The present Thesis aims to achieve three main objectives. The first is to present and comment the experimental results obtained during my PhD, which show that performances of modern AQCs are steadily improving thanks to both hardware and software advancements, and are getting close to practical utility.
The second objective is to provide the reader with an extensive literature review regarding the design, the use, the capabilities, and the possible applications of AQCs. Indeed, there is currently no document or book on AQCs that contains the comprehensive amount of commented and ordered references presented in this Thesis. Thus, I hope this work can serve as an introductory compendium to a good portion of the modern knowledge regarding this topic.
The third objective is to provide the reader with a collection of the most popular and effective ways to manipulate an AQC at the software (middelware) level in order to enhance its performances.
     
    
      Abstract
      The present Thesis aims to achieve three main objectives. The first is to present and comment the experimental results obtained during my PhD, which show that performances of modern AQCs are steadily improving thanks to both hardware and software advancements, and are getting close to practical utility.
The second objective is to provide the reader with an extensive literature review regarding the design, the use, the capabilities, and the possible applications of AQCs. Indeed, there is currently no document or book on AQCs that contains the comprehensive amount of commented and ordered references presented in this Thesis. Thus, I hope this work can serve as an introductory compendium to a good portion of the modern knowledge regarding this topic.
The third objective is to provide the reader with a collection of the most popular and effective ways to manipulate an AQC at the software (middelware) level in order to enhance its performances.
     
  
  
    
    
      Tipologia del documento
      Tesi di dottorato
      
      
      
      
        
      
        
          Autore
          Rocutto, Lorenzo
          
        
      
        
          Supervisore
          
          
        
      
        
          Co-supervisore
          
          
        
      
        
          Dottorato di ricerca
          
          
        
      
        
      
        
          Ciclo
          35
          
        
      
        
          Coordinatore
          
          
        
      
        
          Settore disciplinare
          
          
        
      
        
          Settore concorsuale
          
          
        
      
        
          Parole chiave
          Adiabatic Quantum Computer, Quantum Annealing, Quantum Computer, Machine Learning, Unsupervised Learning,  Optimization Problems
          
        
      
        
          URN:NBN
          
          
        
      
        
          DOI
          10.48676/unibo/amsdottorato/11302
          
        
      
        
          Data di discussione
          10 Aprile 2024
          
        
      
      URI
      
      
     
   
  
    Altri metadati
    
      Tipologia del documento
      Tesi di dottorato
      
      
      
      
        
      
        
          Autore
          Rocutto, Lorenzo
          
        
      
        
          Supervisore
          
          
        
      
        
          Co-supervisore
          
          
        
      
        
          Dottorato di ricerca
          
          
        
      
        
      
        
          Ciclo
          35
          
        
      
        
          Coordinatore
          
          
        
      
        
          Settore disciplinare
          
          
        
      
        
          Settore concorsuale
          
          
        
      
        
          Parole chiave
          Adiabatic Quantum Computer, Quantum Annealing, Quantum Computer, Machine Learning, Unsupervised Learning,  Optimization Problems
          
        
      
        
          URN:NBN
          
          
        
      
        
          DOI
          10.48676/unibo/amsdottorato/11302
          
        
      
        
          Data di discussione
          10 Aprile 2024
          
        
      
      URI
      
      
     
   
  
  
  
  
  
    
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