Related papers: Automated event generation for loop-induced proces…
The AcerMC Monte Carlo generator gives a possibility to generate some of the Standard Model background processes which were recognised as very dangerous for the searches at LHC, and generation of which was either unavailable or not…
This is the user's manual of MC@NLO 4.0. This package is a practical implementation, based upon the Fortran HERWIG and Herwig++ event generators, of the MC@NLO formalism, which allows one to incorporate NLO QCD matrix elements consistently…
We present an implementation of the Linked Dipole Chain model for deeply inelastic ep scattering into the framework of the Ariadne event generator. Using this implementation we obtain results both for the inclusive structure function as…
We present the first application of a Nested Sampling algorithm to explore the high-dimensional phase space of particle collision events. We describe the adaptation of the algorithm, designed to perform Bayesian inference computations, to…
First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide range…
We present a new class of multifractal process on R, constructed using an embedded branching process. The construction makes use of known results on multitype branching random walks, and along the way constructs cascade measures on the…
The generation of unit-weight events for complex scattering processes presents a severe challenge to modern Monte Carlo event generators. Even when using sophisticated phase-space sampling techniques adapted to the underlying transition…
To extract value from evergrowing volumes of data, coming from a number of different sources, and to drive decision making, organizations frequently resort to the composition of data processing workflows, since they are expressive,…
A Monte-Carlo event-generator has been developed which is dedicated to simulate electron-positron annihilations. Especially a new approach for the combination of matrix elements and parton showers ensures the independence of the…
We present a novel approach for the integration of scattering cross sections and the generation of partonic event samples in high-energy physics. We propose an importance sampling technique capable of overcoming typical deficiencies of…
To measure the $R$ value in an energy scan experiment with $\ee$ collisions, precise calculation of initial state radiation is required in event generators. We present an event generator for this consideration, which incorporates initial…
We present an algorithm to evaluate the exact, tree-level matrix elements for multi-parton processes in QCD. We tested this technique, based on the recursive evaluation of the S-matrix, on processes such as gg -> n gluons and q qbar -> n…
Open-ended text generation tasks, such as dialogue generation and story completion, require models to generate a coherent continuation given limited preceding context. The open-ended nature of these tasks brings new challenges to the neural…
The production of prompt photons is one of the most relevant scattering processes studied at hadron-hadron colliders in recent years. This article will give an overview of the different approaches used to simulate prompt photon production…
This work introduces self-infilling code generation, a general framework that incorporates infilling operations into auto-regressive decoding. Our approach capitalizes on the observation that recent infilling-capable code language models…
This proceeding relates the recent developments of the MadLoop tool. MadLoop automates the computation of one-loop QCD corrections to an arbitrary scattering process in the Standard Model. I first review the current version of the code…
The new matrix element generator AMEGIC++ is introduced, dedicated to describe multi-particle production in high energy particle collisions. It automatically generates helicity amplitudes for the processes under consideration and constructs…
Event cameras are advantageous for tasks that require vision sensors with low-latency and sparse output responses. However, the development of deep network algorithms using event cameras has been slow because of the lack of large labelled…
Machine Learning (ML)-based unfolding methods have enabled high-dimensional and unbinned differential cross section measurements. While a suite of such methods has been proposed, most focus exclusively on the challenge of statistically…
Precision theoretical predictions for high multiplicity scattering rely on the evaluation of increasingly complicated scattering amplitudes which come with an extremely high CPU cost. For state-of-the-art processes this can cause technical…