Transforming the Bootstrap: Using Transformers to Compute Scattering Amplitudes in Planar N = 4 Super Yang-Mills Theory

We pursue the use of deep learning methods to improve state-of-the-art computations in theoretical high-energy physics. Planar N = 4 Super Yang-Mills theory is a close cousin to the theory that describes Higgs boson production at the Large Hadron Collider; its scattering amplitudes are large mathema...

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Bibliographic Details
Published in:arXiv.org 2024-09
Main Authors: Cai, Tianji, Merz, Garrett W, Charton, François, Nolte, Niklas, Wilhelm, Matthias, Cranmer, Kyle, Dixon, Lance J
Format: Article
Language:English
Subjects:
Amplitudes
Exact solutions
Higgs bosons
Large Hadron Collider
Mathematical analysis
Scattering
Theoretical physics
Transformers
Yang-Mills theory
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Summary:We pursue the use of deep learning methods to improve state-of-the-art computations in theoretical high-energy physics. Planar N = 4 Super Yang-Mills theory is a close cousin to the theory that describes Higgs boson production at the Large Hadron Collider; its scattering amplitudes are large mathematical expressions containing integer coefficients. In this paper, we apply Transformers to predict these coefficients. The problem can be formulated in a language-like representation amenable to standard cross-entropy training objectives. We design two related experiments and show that the model achieves high accuracy (> 98%) on both tasks. Our work shows that Transformers can be applied successfully to problems in theoretical physics that require exact solutions.
ISSN:2331-8422
DOI:10.48550/arxiv.2405.06107