Reinforcement Learning based Circuit Compilation via ZX-calculus

Màster Oficial de Ciència i Tecnologia Quàntiques / Quantum Science and Technology, Facultat de Física, Universitat de Barcelona. Curs: 2022-2023. Tutors: Jordi Riu, Marta P Estarellas

Detalles Bibliográficos
Autor: Nogué Gómez, Jan
Tipo de recurso: tesis de maestría
Fecha de publicación:2023
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/202911
Acceso en línea:https://hdl.handle.net/2445/202911
Access Level:acceso abierto
Palabra clave:Ordinadors quàntics
Aprenentatge automàtic
Circuits quàntics
Treballs de fi de màster
Quantum computers
Machine learning
Quantum circuit
Master's thesis
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spelling Reinforcement Learning based Circuit Compilation via ZX-calculusNogué Gómez, JanOrdinadors quànticsAprenentatge automàticCircuits quànticsTreballs de fi de màsterQuantum computersMachine learningQuantum circuitMaster's thesisMàster Oficial de Ciència i Tecnologia Quàntiques / Quantum Science and Technology, Facultat de Física, Universitat de Barcelona. Curs: 2022-2023. Tutors: Jordi Riu, Marta P EstarellasZX-calculus is a formalism that can be used for quantum circuit compilation and optimization. We developed a Reinforcement Learning approach for enhanced circuit optimization via the ZX-diagram graph representation of the quantum circuit. The agent is trained using the well-established Proximal Policy Optimization (PPO) algorithm, and it uses Conditional Action Trees to perform Invalid Action Masking to reduce the space of actions available to the agent and speed up its training. Additionally, we also design and implement a Genetic Algorithm for the same task. Both the genetic algorithm and the most widely used ZX-calculus-based library for circuit optimization, the PyZX library, are used to benchmark our RL approach. We find our RL algorithm to be competitive against both approaches, but further exploration is required.Riu Vicente, JordiEstarellas, Marta P.2023info:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/2445/202911Màster Oficial - Ciència i Tecnologia Quàntiques / Quantum Science and Technologyreponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaIngléscc-by-nc-nd (c) Nogué, 2023http://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/2029112026-05-27T06:46:51Z
dc.title.none.fl_str_mv Reinforcement Learning based Circuit Compilation via ZX-calculus
title Reinforcement Learning based Circuit Compilation via ZX-calculus
spellingShingle Reinforcement Learning based Circuit Compilation via ZX-calculus
Nogué Gómez, Jan
Ordinadors quàntics
Aprenentatge automàtic
Circuits quàntics
Treballs de fi de màster
Quantum computers
Machine learning
Quantum circuit
Master's thesis
title_short Reinforcement Learning based Circuit Compilation via ZX-calculus
title_full Reinforcement Learning based Circuit Compilation via ZX-calculus
title_fullStr Reinforcement Learning based Circuit Compilation via ZX-calculus
title_full_unstemmed Reinforcement Learning based Circuit Compilation via ZX-calculus
title_sort Reinforcement Learning based Circuit Compilation via ZX-calculus
dc.creator.none.fl_str_mv Nogué Gómez, Jan
author Nogué Gómez, Jan
author_facet Nogué Gómez, Jan
author_role author
dc.contributor.none.fl_str_mv Riu Vicente, Jordi
Estarellas, Marta P.
dc.subject.none.fl_str_mv Ordinadors quàntics
Aprenentatge automàtic
Circuits quàntics
Treballs de fi de màster
Quantum computers
Machine learning
Quantum circuit
Master's thesis
topic Ordinadors quàntics
Aprenentatge automàtic
Circuits quàntics
Treballs de fi de màster
Quantum computers
Machine learning
Quantum circuit
Master's thesis
description Màster Oficial de Ciència i Tecnologia Quàntiques / Quantum Science and Technology, Facultat de Física, Universitat de Barcelona. Curs: 2022-2023. Tutors: Jordi Riu, Marta P Estarellas
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/202911
url https://hdl.handle.net/2445/202911
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv cc-by-nc-nd (c) Nogué, 2023
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by-nc-nd (c) Nogué, 2023
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv Màster Oficial - Ciència i Tecnologia Quàntiques / Quantum Science and Technology
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300724

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