MadGraph5_aMC@NLO automates tree-level, NLO, shower-matched, and merged cross-section computations for collider processes in a unified flexible framework.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
method 2
citation-polarity summary
roles
method 2polarities
use method 2representative citing papers
DELPHES 3 delivers a modular fast-simulation framework with particle-flow and pile-up features for reconstructing physics objects in collider detector studies.
Jarvis-HEP introduces a YAML-based Python framework for composing workflows and performing parameter scans in high-energy physics.
citing papers explorer
-
The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations
MadGraph5_aMC@NLO automates tree-level, NLO, shower-matched, and merged cross-section computations for collider processes in a unified flexible framework.
-
DELPHES 3, A modular framework for fast simulation of a generic collider experiment
DELPHES 3 delivers a modular fast-simulation framework with particle-flow and pile-up features for reconstructing physics objects in collider detector studies.
-
Jarvis-HEP: A lightweight Python framework for workflow composition and parameter scans in high-energy physics
Jarvis-HEP introduces a YAML-based Python framework for composing workflows and performing parameter scans in high-energy physics.