Nested-GPT is an autoregressive Transformer surrogate that generates variable-multiplicity parton showers while enforcing ordered Markovian branching and matches reference Monte Carlo results for leading-log non-global logarithm resummation in the large-Nc limit.
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GAPS v2 is a GPU-accelerated parton shower for initial and final state emissions with NLO matching that achieves speed and energy performance on par with a 96-core CPU cluster for NLO Z production at the LHC.
Implementing improved logarithmic accuracy parton showers in Herwig reveals that differences in infrared cutoffs have important effects on hadron-level predictions and tunability.
The paper provides a detailed physics and user manual for the PYTHIA 8.3 Monte Carlo event generator used in high-energy physics.
citing papers explorer
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Nested-GPT for variable-multiplicity parton showers: A case study in the resummation of non-global logarithms
Nested-GPT is an autoregressive Transformer surrogate that generates variable-multiplicity parton showers while enforcing ordered Markovian branching and matches reference Monte Carlo results for leading-log non-global logarithm resummation in the large-Nc limit.
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An NLO-Matched Initial and Final State Parton Shower on a GPU
GAPS v2 is a GPU-accelerated parton shower for initial and final state emissions with NLO matching that achieves speed and energy performance on par with a 96-core CPU cluster for NLO Z production at the LHC.
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Studying the Infrared Behaviour of Improved Logarithmic Accuracy Parton Showers with Herwig
Implementing improved logarithmic accuracy parton showers in Herwig reveals that differences in infrared cutoffs have important effects on hadron-level predictions and tunability.
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A comprehensive guide to the physics and usage of PYTHIA 8.3
The paper provides a detailed physics and user manual for the PYTHIA 8.3 Monte Carlo event generator used in high-energy physics.