Acín dal Maschio, AntonioCentrone, FedericoKrasimirov Ivanov, Todor2023-10-172023-10-172023-07https://hdl.handle.net/2445/202910Màster Oficial de Ciència i Tecnologia Quàntiques / Quantum Science and Technology, Facultat de Física, Universitat de Barcelona. Curs: 2022-2023. Tutors: Antonio Acín, Federico CentroneQuantum mechanics in conjunction with continuous variables systems are promising for artificial neural networks in terms of information processing and real data domains. For classical simulation concerns, a brand-new continuous variables quantum neural network (QNN) was implemented, analyzed and tested keeping the affinity with quantum hardware. The simulated QNN approach is based on second statistical moments of the system’s Gaussian stage jointly with expectation value expressions acting as the non-Gaussian evolution and measurement of the system. The required components, infrastructure and algorithms were described and developed along with its relative demonstrations giving a complete traceability of the proposed quantum neural network model supported with illustrative examples.25 p.application/pdfengcc-by-nc-nd (c) Krasimirov, 2023http://creativecommons.org/licenses/by-nc-nd/3.0/es/Xarxes neuronalsVariable contínuaÒptica quànticaTreballs de fi de màsterNeural networksContinuous variableQuantum opticsMaster's thesisContinuous Variables Quantum Neural Networksinfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccess