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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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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Preprint on arXiv for ACAT 2021 proceedings contribution
ACAT 2021 talk: optimising simulations for diphoton production at hadron colliders using amplitude neural networks
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physics
acat
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acat2021
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amplitudes
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colliders
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computational physics
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conference
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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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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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presentation
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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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talk
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theoretical physics
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virtual
Talk at 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research
JHEP: gluon fusion to diphoton plus jets with amplitude neural networks
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physics
amplitudes
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colliders
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computational physics
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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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jhep
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machine learning
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neural networks
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open access
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open source
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paper
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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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publication
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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
New paper in Journal of High Energy Physics: Optimising simulations for diphoton production at hadron colliders using amplitude neural networks
arXiv: gluon fusion to diphoton plus jets with amplitude neural networks
1 min read
physics
amplitudes
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arxiv
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colliders
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computational physics
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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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lhc
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neural networks
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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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quantum chromodynamics
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quantum electrodynamics
·
quantum field theory
·
scattering amplitudes
·
standard model
·
theoretical physics
New preprint on arXiv: Optimising simulations for diphoton production at hadron colliders using amplitude neural networks
n3jet_diphoton version 1 release
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physics
c++
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code
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durham
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neural networks
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particle physics
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phd
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python
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release
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software
Finalisation of the project