Related papers: Automated event generation for loop-induced proces…
We present a new multi-channel integration method and its implementation in the multi-purpose event generator MadEvent, which is based on MadGraph. Given a process, MadGraph automatically identifies all the relevant subprocesses, generates…
Event generators simulate particle interactions using Monte Carlo techniques, providing the primary connection between experiment and theory in experimental high energy physics. These software packages, which are the first step in the…
We detail the implementation of a multi-event interface for next-to-leading order (NLO) calculations in MadGraph5_aMC@NLO, allowing tree-level scattering amplitudes for multiple phase space points to be evaluated in each call to the…
As the quality of experimental measurements increases, so does the need for Monte Carlo-generated simulated events - both with respect to the total amount and to their precision. In perturbative methods, this involves the evaluation of…
Precision phenomenological studies of high-multiplicity scattering processes at collider experiments present a substantial theoretical challenge and are vitally important ingredients in experimental measurements. Machine learning technology…
An event generation framework is presented that enables the automatic simulation of events for next-generation neutrino experiments in the Standard Model or extensions thereof. The new generator combines the calculation of the leptonic…
Madgraph5_aMC@NLO is one of the most-frequently used Monte-Carlo event generators at the LHC, and an important consumer of compute resources. The software has been reengineered to maintain the overall look and feel of the user interface…
Next-to-leading order event generation for the Standard Model effective field theory has started to become available in the MadGraph5_aMC@NLO framework. In this talk we discuss some of the recent progresses in this direction, with a focus…
An important area of high energy physics studies at the Large Hadron Collider (LHC) currently concerns the need for more extensive and precise comparison data. Important tools in this realm are event reweighing and evaluation of more…
A phase-space generation algorithm, capable to efficiently integrate the squared amplitude of any scattering process, is presented. The algorithm has been implemented in a Monte Carlo program, PHEGAS, which, using HELAC, a helicity…
MadGraph5_aMC@NLO is a software package that allows one to simulate processes of arbitrary complexity, at both the leading and the next-to-leading order perturbative accuracy, with or without matching and multi-jet merging to parton…
Machine learning technology has the potential to dramatically optimise event generation and simulations. We continue to investigate the use of neural networks to approximate matrix elements for high-multiplicity scattering processes. We…
The matrix element (ME) calculation in any Monte Carlo physics event generator is an ideal fit for implementing data parallelism with lockstep processing on GPUs and vector CPUs. For complex physics processes where the ME calculation is the…
The CUDACPP plugin for MadGraph5_aMC@NLO aims to accelerate leading order tree-level event generation by providing the MadEvent event generator with data-parallel helicity amplitudes. These amplitudes are written in templated C++ and CUDA,…
We describe the universal Monte-Carlo event generator WHIZARD. The program automatically computes complete tree-level matrix elements, integrates them over phase space, evaluates distributions of observables, and generates unweighted event…
We discuss the theoretical bases that underpin the automation of the computations of tree-level and next-to-leading order cross sections, of their matching to parton shower simulations, and of the merging of matched samples that differ by…
We present the latest developments of the MadGraph/MadEvent Monte Carlo event generator and several applications to hadron collider physics. In the current version events at the parton, hadron and detector level can be generated directly…
The structure of events in high-energy collisions is complex and not predictable from first principles. Event generators allow the problem to be subdivided into more manageable pieces, some of which can be described from first principles,…
High-energy physics data analysis relies heavily on the comparison between experimental and simulated data as stressed lately by the Higgs search at LHC and the recent identification of a Higgs-like new boson. The first link in the full…
We present MadFlow, a first general multi-purpose framework for Monte Carlo (MC) event simulation of particle physics processes designed to take full advantage of hardware accelerators, in particular, graphics processing units (GPUs). The…