Quantum machine learning: a theoretical study-case and practical implementation of PCA using quantum computing
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 w...
- Autores:
-
Laguna Guantiva, Mateo
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2022
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/63600
- Acceso en línea:
- http://hdl.handle.net/1992/63600
- Palabra clave:
- Quantum computing
Machine learning
AWS
Ingeniería
- Rights
- openAccess
- License
- Atribución 4.0 Internacional
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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 |
| spellingShingle |
Quantum machine learning: a theoretical study-case and practical implementation of PCA using quantum computing Quantum computing Machine learning AWS Ingeniería |
| title_short |
Quantum machine learning: a theoretical study-case and practical implementation of PCA using quantum computing |
| title_full |
Quantum machine learning: a theoretical study-case and practical implementation of PCA using quantum computing |
| title_fullStr |
Quantum machine learning: a theoretical study-case and practical implementation of PCA using quantum computing |
| title_full_unstemmed |
Quantum machine learning: a theoretical study-case and practical implementation of PCA using quantum computing |
| title_sort |
Quantum machine learning: a theoretical study-case and practical implementation of PCA using quantum computing |
| dc.creator.fl_str_mv |
Laguna Guantiva, Mateo |
| dc.contributor.advisor.none.fl_str_mv |
Núñez Castro, Haydemar María |
| dc.contributor.author.none.fl_str_mv |
Laguna Guantiva, Mateo |
| dc.subject.keyword.none.fl_str_mv |
Quantum computing Machine learning AWS |
| topic |
Quantum computing Machine learning AWS Ingeniería |
| dc.subject.themes.es_CO.fl_str_mv |
Ingeniería |
| description |
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. |
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2022 |
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2022-12-16T19:03:20Z |
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2022-12-16T19:03:20Z |
| dc.date.issued.none.fl_str_mv |
2022-12-12 |
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Trabajo de grado - Pregrado |
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info:eu-repo/semantics/bachelorThesis |
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info:eu-repo/semantics/acceptedVersion |
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http://hdl.handle.net/1992/63600 |
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instname:Universidad de los Andes |
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eng |
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eng |
| dc.relation.references.es_CO.fl_str_mv |
[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. |
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Atribución 4.0 Internacional |
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Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ http://purl.org/coar/access_right/c_abf2 |
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33 páginas |
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application/pdf |
| dc.publisher.es_CO.fl_str_mv |
Universidad de los Andes |
| dc.publisher.program.es_CO.fl_str_mv |
Ingeniería de Sistemas y Computación |
| dc.publisher.faculty.es_CO.fl_str_mv |
Facultad de Ingeniería |
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Departamento de Ingeniería Sistemas y Computación |
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Universidad de los Andes |
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Atribución 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Núñez Castro, Haydemar Maríae7771691-225a-47f5-be36-32caf6da48ad600Laguna Guantiva, Mateo15a290c8-6db8-4f90-9767-e66f6f8e943a6002022-12-16T19:03:20Z2022-12-16T19:03:20Z2022-12-12http://hdl.handle.net/1992/63600instname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/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 ComputaciónPregrado33 páginasapplication/pdfengUniversidad de los AndesIngeniería de Sistemas y ComputaciónFacultad de IngenieríaDepartamento de Ingeniería Sistemas y ComputaciónQuantum machine learning: a theoretical study-case and practical implementation of PCA using quantum computingTrabajo de grado - Pregradoinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_7a1fTexthttp://purl.org/redcol/resource_type/TPQuantum computingMachine learningAWSIngeniería[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. 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