Related papers: Tuning Monte Carlo Generators: The Perugia Tunes
We present 7 new tunes of the pT-ordered shower and underlying-event model in Pythia 6.4. These "Perugia" tunes update and supersede the older "S0" family. The new tunes include the updated LEP fragmentation and flavour parameters reported…
We present the Monte Carlo generator tuning strategy followed, and the tools developed, by the MCnet CEDAR project. We also present new tuning results for the Pythia 6.4 event generator which are based on event shape and hadronisation…
We present an updated set of parameters for the PYTHIA 8 event generator. We reevaluate the constraints imposed by LEP and SLD on hadronization, in particular with regard to heavy-quark fragmentation and strangeness production. For hadron…
A new tune (set of model parameters) is found for the six most important parameters of the Pythia8 final state parton shower and hadronization model using Bayesian optimization. The tune fits the LEPI data from ALEPH better than the default…
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…
New sets of parameters ("tunes") for the underlying-event (UE) modeling of the PYTHIA8, PYTHIA6 and HERWIG++ Monte Carlo event generators are constructed using different parton distribution functions. Combined fits to CMS UE proton-proton…
We report an underlying event tune for the PYTHIA 8 Monte Carlo event generator that is applicable for hadron collisions primarily at $\sqrt{s}$ ranges available at the Relativistic Heavy-Ion Collider (RHIC). We compare our new PYTHIA 8…
The CDF PYTHIA 6.2 Tune DW predictions of the LHC underlying event (UE) data at 900 GeV and 7 TeV are examined in detail. The behavior of the UE at the LHC is roughly what we expected. The new LHC PYTHIA 6.4 Tune Z1 does an even better job…
We present parameter sets corresponding to new underlying event tunes for the Herwig7.3 Monte Carlo event generator. The existing Herwig tunes are in good agreement with LHC data, however, they are not typically designed for center-of-mass…
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…
This paper presents a new set of parameters ("tunes") for the underlying-event model of the HERWIG 7 event generator. These parameters control the description of multiple-parton interactions (MPI) and colour reconnection in HERWIG 7, and…
General-purpose Monte Carlo event generators have become important tools in particle physics, allowing the simulation of exclusive hadronic final states. In this article we examine the Pythia 8 generator, in particular focusing on its…
Recent QCD Monte Carlo tuning studies done in the CMS Collaboration are presented. Jet kinematics, jet substructure, and underlying event measurements in top quark pair events are discussed. New CMS PYTHIA 8 event tunes are presented,…
Event generators like Pythia play an important role in physics studies at the Large Hadron Collider (LHC). While they make accurate predictions in the central region, i.e. at pseudorapidities $\eta<5$, a disagreement between Pythia and…
The modelling of the formation of colour-singlet hadrons from coloured partons, known as Hadronization, is crucial for generating realistic events in Monte Carlo Event Generators. Due to limited understanding of the non-perturbative regime,…
We present a sequential nine-parameter retune of PYTHIA 8.316, built on the Monash 2013 baseline, for soft-QCD observables in proton--proton collisions at $\sqrt{s}=0.9$--$13$ TeV. The tune is constructed with direct generator evaluation…
New sets of CMS underlying-event parameters ("tunes") are presented for the PYTHIA8 event generator. These tunes use the NNPDF3.1 parton distribution functions (PDFs) at leading (LO), next-to-leading (NLO), or next-to-next-to-leading (NNLO)…
The optimisation (tuning) of the free parameters of Monte Carlo event generators by comparing their predictions with data is important since the simulations are used to calculate experimental efficiency and acceptance corrections, or…
The CDF PYTHIA 6.2 Tune DW predictions for the behavior of the LHC underlying event (UE) data at 900 GeV and 7 TeV are examined in detail. The behavior of the UE at the LHC is roughly what we expected. The LHC PYTHIA 6.4 Tune Z1 does an…
In a very short time the experiments at the LHC have collected a large amount of data that can be used to study minimum bias (MB) collisions and the underlying event (UE) in great detail. The CDF PYTHIA 6.2 Tune DW predictions for the LHC…