Related papers: MadAnalysis 5: status and new developments
HOOMD-blue is a particle simulation engine designed for nano- and colloidal-scale molecular dynamics and hard particle Monte Carlo simulations. It has been actively developed since March 2007 and available open source since August 2008.…
We present a cross-language C++/Python program for simulations of quantum mechanical systems with the use of Quantum Monte Carlo (QMC) methods. We describe a system for which to apply QMC, the algorithms of variational Monte Carlo and…
Even todays most advanced machine learning models are easily fooled by almost imperceptible perturbations of their inputs. Foolbox is a new Python package to generate such adversarial perturbations and to quantify and compare the robustness…
Monte Carlo sampling is a powerful toolbox of algorithmic techniques widely used for a number of applications wherein some noisy quantity, or summary statistic thereof, is sought to be estimated. In this paper, we survey the literature for…
We present the pyerrors python package for statistical error analysis of Monte Carlo data. Linear error propagation using automatic differentiation in an object oriented framework is combined with the $\Gamma$-method for a reliable…
The DeepMind Control Suite is a set of continuous control tasks with a standardised structure and interpretable rewards, intended to serve as performance benchmarks for reinforcement learning agents. The tasks are written in Python and…
We present a novel event generation framework for the efficient simulation of vector boson plus multi-jet backgrounds at the high-luminosity LHC and at possible future hadron colliders. MPI parallelization of parton-level and particle-level…
We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements.…
Matrix element reweighting is a powerful experimental technique widely employed to maximize the amount of information that can be extracted from a collider data set. We present a procedure that allows to automatically evaluate the weights…
Differentiable programming opens exciting new avenues in particle physics, also affecting future event generators. These new techniques boost the performance of current and planned MadGraph implementations. Combining phase-space mappings…
Heading towards a full automation of next-to-leading order (NLO) QCD corrections, one important ingredient is the analytical integration over the one-particle phase space of the unresolved particle that is necessary when adding the…
The Monte Carlo program \texttt{SUSYGEN}, initially designed for computing distributions and generating events for supersymmetric particle production in $e^+e^-$ collisions, has now been upgraded to study supersymmetric processes at linear…
Monte Carlo event generators are an essential tool for data analysis in collider physics. To include subleading quantum corrections, these generators often need to produce negative weight events, which leads to statistical dilution of the…
Magpy is a C++ accelerated Python package for modelling and simulating the magnetic dynamics of nano-sized particles. Nanoparticles are modelled as a system of three-dimensional macrospins and simulated with a set of coupled stochastic…
A fast, simple to use Monte Carlo based event generator is presented which is intended to facilitate simulation studies and the development of analysis software for the Solenoidal Tracker at RHIC (Relativistic Heavy Ion Collider) (STAR)…
Studying the impact of new-physics models on low-energy observables necessitates matching to effective field theories at the relevant mass thresholds. We introduce the first public version of Matchete, a computer tool for matching…
This paper proposes a new theory and methodology to tackle the problem of unifying distributed analyses and inferences on shared parameters from multiple sources, into a single coherent inference. This surprisingly challenging problem…
We describe the multi-purpose Monte-Carlo event generator WHIZARD for the simulation of high-energy particle physics experiments. Besides the presentation of the general features of the program like SM physics, BSM physics, and QCD effects,…
We present the first public release (v0.1) of the open-source GADGET Dataframe Library: gadfly. The aim of this package is to leverage the capabilities of the broader python scientific computing ecosystem by providing tools for analyzing…
This work reports on a method for uncertainty estimation in simulated collider-event predictions. The method is based on a Monte Carlo-veto algorithm, and extends previous work on uncertainty estimates in parton showers by including…