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.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
abstract
We combine fast amplitude surrogates with neural importance sampling to accelerate NLO calculations. For virtual corrections, a learned ratio to the Born matrix element with calibrated uncertainties guarantees reliable precision across phase space. For real emission, we stick to the standard FKS subtraction and train sector-conditioned surrogates of the regularized integrands away from divergences. MadNIS then uses multi-channel mappings and FKS sectors as conditions. We validate our approach for electron-positron scattering to three and four jets and find significant speed-ups and variance reduction in the integration.
citation-role summary
background 1
method 1
citation-polarity summary
fields
hep-ph 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
A review of initiatives to make LHC Monte Carlo event generations available as open data to minimize redundant simulations and resource use.
A primer that surveys the architecture, methodologies, computational challenges, and future trajectory of the Monte Carlo event generator ecosystem in collider physics.
citing papers explorer
-
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.
-
Open LHC Monte Carlo Event Generation
A review of initiatives to make LHC Monte Carlo event generations available as open data to minimize redundant simulations and resource use.
-
The Monte Carlo Ecosystem in High-Energy Physics: A Primer
A primer that surveys the architecture, methodologies, computational challenges, and future trajectory of the Monte Carlo event generator ecosystem in collider physics.