Efficient GPU Integration for Multi-loop Feynman Diagrams with Massless Internal Lines

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Abstract

We compute Feynman loop integrals or expansion coefficients for sets of self-energy diagrams with massless internal lines and which give rise to either finite integral values or UV-divergences. In case of UV-divergence, dimensional regularization can be implemented using a linear extrapolation as the dimensional regularization parameter tends to zero. The numerical integration is performed with lattice and composite lattice rules combined with a transformation to alleviate boundary singularities, and implemented in CUDA C. The GPU results are accurate and efficient in execution time compared to other numerical methods and architectures.

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de Doncker, E., Yuasa, F., & Almulihi, A. (2020). Efficient GPU Integration for Multi-loop Feynman Diagrams with Massless Internal Lines. In Mechanisms and Machine Science (Vol. 75, pp. 737–747). Springer Science and Business Media B.V. https://doi.org/10.1007/978-3-030-27053-7_62

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