Related papers: The MadNIS Reloaded
In general-purpose particle detectors, the particle-flow algorithm may be used to reconstruct a comprehensive particle-level view of the event by combining information from the calorimeters and the trackers, significantly improving the…
Many high-energy-physics (HEP) simulations for the LHC rely on Monte Carlo using importance sampling by means of the VEGAS algorithm. However, complex high-precision calculations have become a challenge for the standard toolbox, as this…
With Run II of the LHC having started, the need for high precision theory predictions whose uncertainty matches that of the data to be taken necessitated a range of new developments in Monte-Carlo Event Generators. This talk will give an…
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…
After a highly successful first data taking period at the LHC, the LHCb experiment developed a new trigger strategy with a real-time reconstruction, alignment and calibration for Run II. This strategy relies on offline-like track…
We present MadAnalysis 5, an analysis package dedicated to phenomenological studies of simulated collisions occurring in high-energy physics experiments. Within this framework, users are invited, through a user-friendly Python interpreter,…
Accurate Monte Carlo simulations for high-energy events at CERN's Large Hadron Collider, are very expensive, both from the computing and storage points of view. We describe a method that allows to consistently re-use parton-level samples…
We introduce a new high dimensional algorithm for efficiency corrected, maximally Monte Carlo event generator independent fiducial measurements at the LHC and beyond. The approach is driven probabilistically using a Deep Neural Network on…
The LHC generates an intense beam of high-energy neutrinos in the forward direction, whose scientific potential has been left unexploited for many years. The FASER and SND@LHC experiments, operating since 2023, have recently measured LHC…
Physics event generators are essential components of the data analysis software chain of high energy physics experiments, and important consumers of their CPU resources. Improving the software performance of these packages on modern…
MadAnalysis 5 is a new Python/C++ package facilitating phenomenological analyses that can be performed in the framework of Monte Carlo simulations of collisions to be produced in high-energy physics experiments. It allows, by means of a…
A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the physical processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have…
In this article we describe Professor, a new program for tuning model parameters of Monte Carlo event generators to experimental data by parameterising the per-bin generator response to parameter variations and numerically optimising the…
Accurate and efficient amplitude predictions are essential for precision studies of multi-jet processes at the LHC. We introduce a novel neural network architecture that predicts multi-jet amplitudes by leveraging the Catani-Seymour…
We present a novel methodology to build powerful predictive process models. Our method, denoted ProcK (Process & Knowledge), relies not only on sequential input data in the form of event logs, but can learn to use a knowledge graph to…
In this proceedings we demonstrate some advantages of a top-bottom approach in the development of hardware-accelerated code. We start with an autogenerated hardware-agnostic Monte Carlo generator, which is parallelized in the event axis.…
We present powerful new analysis techniques to constrain effective field theories at the LHC. By leveraging the structure of particle physics processes, we extract extra information from Monte-Carlo simulations, which can be used to train…
We provide a comprehensive and pedagogical introduction to the MadAnalysis 5 framework, with a particular focus on its usage for reinterpretation studies. To this end, we first review the main features of the normal mode of the program and…
We present the first fully automated implementation of cross-section computation and event generation for loop-induced processes. This work is integrated in the MadGraph5_aMC@NLO framework. We describe the optimisations implemented at the…
The physics reach of the HL-LHC will be limited by how efficiently the experiments can use the available computing resources, i.e. affordable software and computing are essential. The development of novel methods for charged particle…