arXiv: optimising hadronic collider simulations using amplitude neural networks
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physics
acat
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acat2021
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amplitudes
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arxiv
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colliders
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computational physics
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conference
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contribution
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cross sections
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differential cross sections
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durham
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hadron colliders
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high energy physics
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inspirehep
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machine learning
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neural networks
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open source
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particle physics
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particle physics phenomenology
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phd
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precision qcd
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preprint
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proceedings
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qcd
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quantum chromodynamics
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quantum electrodynamics
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quantum field theory
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scattering amplitudes
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standard model
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theoretical physics
Preprint on arXiv for ACAT 2021 proceedings contribution