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Decoding quantum field theory with machine learning

Abstract We demonstrate how one can use machine learning techniques to bypass the technical difficulties of designing an experiment and translating its outcomes into concrete claims about fundamental features of quantum fields. In practice, all measurements of quantum fields are carried out through...

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Bibliografski detalji
Glavni autori: Daniel Grimmer, Irene Melgarejo-Lermas, José Polo-Gómez, Eduardo Martín-Martínez
Format: Artigo
Jezik:Inglês
Izdano: SpringerOpen 2023-08-01
Serija:Journal of High Energy Physics
Teme:
Online pristup:https://doi.org/10.1007/JHEP08(2023)031
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