Artificial Neural Network methods in quantum mechanics

dc.contributor.authorLagaris, I. E.en
dc.contributor.authorLikas, A.en
dc.contributor.authorFotiadis, D. I.en
dc.date.accessioned2015-11-24T17:32:10Z
dc.date.available2015-11-24T17:32:10Z
dc.identifier.issn0010-4655-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/13682
dc.rightsDefault Licence-
dc.subjectneural networksen
dc.subjecteigenvalue problemsen
dc.subjectschrodingeren
dc.subjectdiracen
dc.subjectcollocationen
dc.subjectoptimizationen
dc.titleArtificial Neural Network methods in quantum mechanicsen
heal.abstractIn a previous article we have shown how one can employ Artificial Neural Networks (ANNs) in order to solve non-homogeneous ordinary and partial differential equations, In the present work we consider the solution of eigenvalue problems for differential and integrodifferential operators, using ANNs. We start by considering the Schrodinger equation for the Morse potential that has an analytically known solution, to test the accuracy of the method, We then proceed with the Schrodinger and the Dirac equations for a muonic atom, as well as with a nonlocal Schrodinger integrodifferential equation that models the n + alpha system in the framework of the resonating group method, In two dimensions we consider the well-studied Henon-Heiles Hamiltonian and in three dimensions the model problem of three coupled anharmonic oscillators, The method in all of the treated cases proved to be highly accurate, robust and efficient. Hence it is a promising tool for tackling problems of higher complexity and dimensionality. (C) 1997 Elsevier Science B.V.en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.identifier.secondary<Go to ISI>://A1997XV31900001-
heal.identifier.secondaryhttp://ac.els-cdn.com/S0010465597000544/1-s2.0-S0010465597000544-main.pdf?_tid=eac59c8dc37cf320726731f84ebcd814&acdnat=1339758278_d45f17985aa0b867056309c637ea1539-
heal.journalNameComputer Physics Communicationsen
heal.journalTypepeer reviewed-
heal.languageen-
heal.publicationDate1997-
heal.publisherElsevieren
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Επιστήμης Υλικώνel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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