Treffer: Quantum machine learning: a theoretical study-case and practical implementation of PCA using quantum computing

Title:
Quantum machine learning: a theoretical study-case and practical implementation of PCA using quantum computing
Authors:
Laguna Guantiva, Mateo
Contributors:
Núñez Castro, Haydemar María
Publisher Information:
Universidad de los Andes
Ingeniería de Sistemas y Computación
Facultad de Ingeniería
Departamento de Ingeniería Sistemas y Computación
Publication Year:
2022
Collection:
Universidad de los Andes Colombia: Séneca
Subject Terms:
Quantum computing, Machine learning, AWS, Ingeniería
Document Type:
Dissertation bachelor thesis
File Description:
33 páginas; application/pdf
Language:
English
Relation:
[1] Russell Stuart and Peter Norvig. Artificial Intelligence: A Modern Approach. Harlow: Pearson Education, Limited., 2016.; [2] Hidary Jack D. Quantum Computing: An Applied Approach. Cham: Springer International Publishing, 2019.; [3] Ian T. Jolliffe and Jorge Cadima. Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374, April 2016.; [4] C. He, J. Li, W. Liu, J. Peng, and Z. J. Wang. A low-complexity quantum principal component analysis algorithm,. IEEE Transactions on Quantum Engineering, 3(3):1-13, 2022.; [5] Lin Jie et al. An improved quantum principal component analysis algorithm based on the quantum singular threshold method. Physics Letters A, 383:2862-68, aug 2019.; [6] Lloyd Seth et al. Quantum principal component analysis. Nature Physics, 10:631-33, sept 2014.; [7] Phillip Kaye, Raymond Laflamme, and Michele Mosca. An Introduction to Quantum Computing. Oxford University Press, 2007.; [8] Zakaria Jaadi. Principal Component Analysis (PCA) Explained. https://builtin.com/data-science/step-step-explanation-principal-component- analysis, 2022.; http://hdl.handle.net/1992/63600; instname:Universidad de los Andes; reponame:Repositorio Institucional Séneca; repourl:https://repositorio.uniandes.edu.co/
Availability:
http://hdl.handle.net/1992/63600
Rights:
Atribución 4.0 Internacional ; http://creativecommons.org/licenses/by/4.0/ ; info:eu-repo/semantics/openAccess ; http://purl.org/coar/access_right/c_abf2
Accession Number:
edsbas.164CF54A
Database:
BASE

Weitere Informationen

Quantum computing is an emerging technology that has the potential to change human history. In this thesis, we propose to dive deep into this new technology through theory background and computational experimentation. We explain the theoretical background needed to understand how quantum computing works, then we use this theory background to make a computational implementation on the AWS cloud using Amazon Braket (i.e. AWS service to use quantum processors). As the result of this project, we deliver a document with the theory background required and the Python- code that implements PCA using Amazon Braket. Computational results are consistent with the theory background described in the thesis. ; Amazon Web Services (AWS) ; Ingeniero de Sistemas y Computación ; Pregrado