Related papers: Improving Air Shower Simulations by Tuning Pythia …
We propose that the flexibility offered by modern event-generator tuning tools allows for more than just obtaining "best fits" to a collection of data. In particular, we argue that the universality of the underlying physics model can be…
Autonomous self-triggering for radio detection of extensive air showers remains a long-standing challenge, particularly in environments dominated by strong and variable radio-frequency interference. Current radio arrays usually rely on…
In the era of precision physics measurements at the LHC, efficient and exhaustive estimations of theoretical uncertainties play an increasingly crucial role. In the context of Monte Carlo (MC) event generators, the estimation of such…
Atmospheric parameters, such as pressure (P), temperature (T) and density, affect the development of extensive air showers initiated by energetic cosmic rays. We have studied the impact of atmospheric variations on extensive air showers by…
Particle accelerators are complex facilities that produce large amounts of structured data and have clear optimization goals as well as precisely defined control requirements. As such they are naturally amenable to data-driven research…
At ultra-high energies, the flux of cosmic rays is too low for direct measurements to be meaningful. When a cosmic ray enters the atmosphere, it initiates an extensive air shower, producing a cascade of secondary particles that propagate…
Studies of the nature of cosmic ray particles at the highest energies are based on the measurement of extensive air showers. Most cosmic ray properties can therefore only be obtained from the interpretation of air shower data and are thus…
Simulations of particle showers in calorimeters are computationally time-consuming, as they have to reproduce both energy depositions and their considerable fluctuations. A new approach to ultra-fast simulations are generative models where…
The pursuit of understanding fundamental particle interactions has reached unparalleled precision levels. Particle physics detectors play a crucial role in generating low-level object signatures that encode collision physics. However,…
The PYTHIA program is a standard tool for the generation of events in high-energy collisions, comprising a coherent set of physics models for the evolution from a few-body hard process to a complex multiparticle final state. It contains a…
High-quality simulated data is crucial for particle physics discoveries. Therefore, parton shower algorithms are a major building block of the data synthesis in event generator programs. However, the core algorithms used to generate parton…
Very high energy cosmic rays are typically studied by measuring extensive air showers formed by secondary particles produced in collisions with air nuclei. The indirect character of the measurement makes the physics interpretation of cosmic…
We aim to improve the modelling of deep inelastic scattering by implementing multi-jet merging capabilities in Vincia parton shower in the general-purpose Monte Carlo event generator, Pythia. Merging allows to combine event samples of…
We introduce multi-jet merging for deep inelastic scattering in the Vincia parton shower in the Monte Carlo event generator Pythia 8. Merging combines event samples of different parton multiplicities with logarithmically enhanced…
The description of high-energy hadronic interactions plays an important role in the (astrophysical) interpretation of air shower data. The parameter space important for the development of air showers (energy and kinematical range) extends…
The PYTHIA program can be used to generate high-energy-physics 'events' with sets of outgoing particles produced in the interactions between two incoming particles. The objective is to provide a representation, as accurate as possible, of…
A configurable calorimeter simulation for AI (COCOA) applications is presented, based on the Geant4 toolkit and interfaced with the Pythia event generator. This open-source project is aimed to support the development of machine learning…
Employing data augmentation methods to enhance perception performance in adverse weather has attracted considerable attention recently. Most of the LiDAR augmentation methods post-process the existing dataset by physics-based models or…
Atmospheric conditions, such as the pressure (P), temperature (T) or air density ($\rho \propto P/T$), affect the development of extended air showers initiated by energetic cosmic rays. We study the impact of the atmospheric variations on…
In this paper, we show predictions from a new QGP-free, no-equilibration, improved baseline model for heavy-ion collisions. It is comprised of the PYTHIA Angantyr event generator coupled to UrQMD, as a hadronic cascade simulator, and…