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.
General-purpose event generators for LHC physics
9 Pith papers cite this work. Polarity classification is still indexing.
9
Pith papers citing it
abstract
We review the physics basis, main features and use of general-purpose Monte Carlo event generators for the simulation of proton-proton collisions at the Large Hadron Collider. Topics included are: the generation of hard-scattering matrix elements for processes of interest, at both leading and next-to-leading QCD perturbative order; their matching to approximate treatments of higher orders based on the showering approximation; the parton and dipole shower formulations; parton distribution functions for event generators; non-perturbative aspects such as soft QCD collisions, the underlying event and diffractive processes; the string and cluster models for hadron formation; the treatment of hadron and tau decays; the inclusion of QED radiation and beyond-Standard-Model processes. We describe the principal features of the ARIADNE, Herwig++, PYTHIA 8 and SHERPA generators, together with the Rivet and Professor validation and tuning tools, and discuss the physics philosophy behind the proper use of these generators and tools. This review is aimed at phenomenologists wishing to understand better how parton-level predictions are translated into hadron-level events as well as experimentalists wanting a deeper insight into the tools available for signal and background simulation at the LHC.
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representative citing papers
A reweighting method is introduced to efficiently study and tune MPI and CR parameter variations in Sherpa using relative weights, demonstrated with LHC and Tevatron data.
A method to approximate kinematic distributions from Monte Carlo events using coefficients of orthogonal basis functions produces smooth curves and removes bin-to-bin fluctuations in subtracted perturbative calculations.
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.
Continuous normalizing flows improve unweighting efficiency in Monte Carlo event generation for high-jet-multiplicity collider processes by factors up to 184, with wall-time gains of about ten when combined with coupling-layer flows.
Vistas is an interactive 3D visualization interface that renders distinct computational stages of Pythia Monte Carlo events as toggleable particle lines with kinematic filters.
Implementation of two NLL-accurate dipole showers in Herwig shows that differences in infrared cutoffs produce noticeable effects at the hadron level and affect model tunability.
PYTHIA 8.2 is a mature C++ event generator that combines hard processes, parton showers, multiparton interactions, and string fragmentation into a complete simulation framework for high-energy collisions.
Reviews selected challenges in Monte Carlo event generators for future lepton colliders including electroweak corrections, initial-state radiation, beam dynamics, perturbative QCD and non-perturbative modelling.
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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Reweighting Underlying Event and Colour Reconnection parameter variations in Sherpa
A reweighting method is introduced to efficiently study and tune MPI and CR parameter variations in Sherpa using relative weights, demonstrated with LHC and Tevatron data.
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On the reconstruction of kinematic distributions computed with Monte Carlo methods using orthogonal basis functions
A method to approximate kinematic distributions from Monte Carlo events using coefficients of orthogonal basis functions produces smooth curves and removes bin-to-bin fluctuations in subtracted perturbative calculations.
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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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Monte Carlo Event Generation with Continuous Normalizing Flows
Continuous normalizing flows improve unweighting efficiency in Monte Carlo event generation for high-jet-multiplicity collider processes by factors up to 184, with wall-time gains of about ten when combined with coupling-layer flows.
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Vistas: A Visualization Interface for Particle Collision Simulations
Vistas is an interactive 3D visualization interface that renders distinct computational stages of Pythia Monte Carlo events as toggleable particle lines with kinematic filters.
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Studying the Infrared Behaviour of Improved Logarithmic Accuracy Parton Showers with Herwig
Implementation of two NLL-accurate dipole showers in Herwig shows that differences in infrared cutoffs produce noticeable effects at the hadron level and affect model tunability.
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An Introduction to PYTHIA 8.2
PYTHIA 8.2 is a mature C++ event generator that combines hard processes, parton showers, multiparton interactions, and string fragmentation into a complete simulation framework for high-energy collisions.
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Monte Carlo Event Generators for Future Lepton Colliders
Reviews selected challenges in Monte Carlo event generators for future lepton colliders including electroweak corrections, initial-state radiation, beam dynamics, perturbative QCD and non-perturbative modelling.