Centrone, FedericoStornati, PaoloAcín dal Maschio, AntonioPolo Rodríguez, Beatriz2024-09-182024-09-182024-06https://hdl.handle.net/2445/215245Màster Oficial de Ciència i Tecnologia Quàntiques / Quantum Science and Technology, Facultat de Física, Universitat de Barcelona. Curs: 2023-2024. Tutors: Federico Centrone, Paolo Stornati, Antonio AcínQuantum optical neural networks (QONN) stand out as promising variational algorithms for quantum simulations by leveraging the potential advantages of photonic circuits with respect to other hardware platforms. In this work, the basics of our proposed physically-inspired architecture of a continuousvariable QONN and its applicability to both optimization of quantum energy storage devices and simulation of quantum field theory will be discussed. Concerning the former, the dependence of the relative energy precision on stellar rank and bipartite correlations in quantum battery systems will be analysed, whereas for the latter, a preliminary study of the Orbifold formulation of U(1) Yang-Mills theory through exact diagonalisation will be presented.27 p.application/pdfengcc-by-nc-nd (c) Polo, 2024http://creativecommons.org/licenses/by-nc-nd/3.0/es/Circuit integrat fotònicEmmagatzematge d'energiaSimulador quànticTreballs de fi de màsterPhotonic integrated circuitStorage of energyQuantum simulatorMaster's thesisinfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccess