Related papers: Systematic event generator tuning for the LHC

This paper presents a novel parameter calibration approach for power system stability models using automatic data generation and advanced deep learning technology. A PMU-measurement-based event playback approach is used to identify…

HEP event generators aim to describe high-energy collisions in full exclusive detail. They combine perturbative matrix elements and parton showers with dynamical models of less well-understood phenomena such as hadronization, diffraction,…

Poor computing efficiency of precision event generators for LHC physics has become a bottleneck for Monte-Carlo event simulation campaigns. We provide solutions to this problem by focusing on two major components of general-purpose event…

The updated version of the Helac-Phegas event generator is presented. The matrix elements are calculated through Dyson-Schwinger recursive equations. Helac-Phegas generates parton-level events with all necessary information, in the most…

This paper describes a new multipurpose event generator, ESEPP, which has been developed for the Monte Carlo simulation of unpolarized elastic scattering of charged leptons on protons. The generator takes into account the lowest-order QED…

The LHCb experiment stores around $10^{11}$ collision events per year. A typical physics analysis deals with a final sample of up to $10^7$ events. Event preselection algorithms (lines) are used for data reduction. Since the data are stored…

Monte Carlo (MC) generators are crucial for analyzing data in particle collider experiments. However, often even a small mismatch between the MC simulations and the measurements can undermine the interpretation of the results. This is…

The AcerMC Monte Carlo generator is dedicated to the generation of Standard Model background processes which were recognised as critical for the searches at LHC, and generation of which was either unavailable or not straightforward so far.…

Sherpa is a general-purpose Monte Carlo event generator for the simulation of particle collisions in high-energy collider experiments. We summarise new developments, essential features, and ongoing improvements within the Sherpa 3 release…

Theories of new physics often involve a large number of unknown parameters which need to be scanned. Additionally, a putative signal in a particular channel may be due to a variety of distinct models of new physics. This makes experimental…

A novel tune has been made for the MicroBooNE experiment. The fit uses 4 new parameters within the GENIE v3.0.6 Monte Carlo program. Charged current pionless data from the T2K experiment was used. New uncertainties were obtained. These…

CompHEP, as a partonic event generator, and PYTHIA, as a generator of final states of detectable objects, are interfaced. Thus, integrated tool is proposed for simulation of (almost) arbitrary collision processes at the level of detectable…

In high-energy physics, Monte Carlo event generators (MCEGs) are used to simulate the interactions of high energy particles. MCEG event records store the information on the simulated particles and their relationships, and thus reflects the…

We document several recent updates to the MCPLOTS event-generator validation resource. The project is based on the RIVET analysis library and harnesses volunteer computing provided by LHC@home to generate high-statistics MC comparisons to…

I review the status of the general-purpose Monte Carlo event generators for the LHC, with emphasis on areas of recent physics developments. There has been great progress, especially in multi-jet simulation, but I mention some question marks…

Event generators play a crucial role in the exploration of LHC physics. This presentation summarizes news and plans for the three general-purpose pp generators HERWIG, PYTHIA and SHERPA, as well as briefer notes on a few other generators.…

Large language models (LLMs) can provide automated feedback in educational settings, but aligning an LLMs style with a specific instructors tone while maintaining diagnostic correctness remains challenging. We ask how can we update an LLM…

We introduce a sequential learning algorithm to address a robust controller tuning problem, which in effect, finds (with high probability) a candidate solution satisfying the internal performance constraint to a chance-constrained program…

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…

A new release of the Monte Carlo event generator Herwig++ (version 2.6) is now available. This version comes with a number of improvements including: a new structure for the implementation of next-to-leading order matrix elements; an…