Tensor network based integration methods

Vista senzilla d'ítem
dc.contributor.advisorCarignano, Stefano
dc.contributor.advisorSoto Riera, Joan
dc.contributor.authorTorrente Badia, Pau
dc.date.accessioned2024-10-18T12:21:29Z
dc.date.available2024-10-18T12:21:29Z
dc.date.issued2024-06
dc.descriptionTreballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2024, Tutors: Stefano Carignano, Joan Soto Rieraca
dc.description.abstractIn this work we overview the Tensor Train Cross decomposition of large tensors and its applicability to high-dimensional integration. Furthermore, two different algorithms for building this decomposition are showcased and compared against a Monte Carlo method, both outperforming it in terms of resource efficiency. A python package is also presented, containing these two algorithms along other tools to leverage the power of the framework in a comprehensive and easy to use mannerca
dc.format.extent6 p.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2445/215876
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Torrente, 2024
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Física
dc.subject.classificationXarxes tensorialscat
dc.subject.classificationIntegració numèricacat
dc.subject.classificationTreballs de fi de graucat
dc.subject.otherTensor networkeng
dc.subject.otherNumerical integrationeng
dc.subject.otherBachelor's theseseng
dc.titleTensor network based integration methodseng
dc.typeinfo:eu-repo/semantics/bachelorThesisca

Fitxers

Paquet original

Mostrant 1 - 1 de 1
Miniatura
Nom:
TORRENTE BADIA PAU.pdf
Mida:
862.78 KB
Format:
Adobe Portable Document Format
Descripció:
Descarregar

Col·leccions

Treballs Finals de Grau (TFG) - Física