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Machine learning Post-Minkowskian integrals

Abstract We study a neural network framework for the numerical evaluation of Feynman loop integrals that are fundamental building blocks for perturbative computations of physical observables in gauge and gravity theories. We show that such a machine learning approach improves the convergence of the...

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Principais autores: Ryusuke Jinno, Gregor Kälin, Zhengwen Liu, Henrique Rubira
Format: Artigo
Jezik:Inglês
Izdano: SpringerOpen 2023-07-01
Serija:Journal of High Energy Physics
Teme:
Online dostop:https://doi.org/10.1007/JHEP07(2023)181
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