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相关论文: Energy Scaling of Minimum-Bias Tunes

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We present 9 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 data sets used to constrain the models include hadronic Z0 decays at LEP,…

高能物理 - 唯象学 · 物理学 2015-03-17 Peter Zeiler Skands

Many of the basic ideas in multiparton interaction (MPI) phenomenology were first developed in the context of the PYTHIA event generator, and MPIs have been central in its modelling of both minimum-bias and underlying-event physics in one…

高能物理 - 唯象学 · 物理学 2017-06-08 Torbjörn Sjöstrand

The CMS data on the multiplicity distributions are compared with the results from the 8.142 version of the PYTHIA MC event generator with the default tuning and realistic impact parameter profile. The agreement is reasonable. However, it…

高能物理 - 唯象学 · 物理学 2011-03-24 K. Fialkowski , R. Wit

We present a combined analysis of the Pythia 8 event generator using accelerator data and evaluate its impact on air shower observables. Reliable simulations with event generators are essential for particle physics analyses, achievable…

高能天体物理现象 · 物理学 2025-09-19 Michael Windau , Chloé Gaudu , Karl-Heinz Kampert , Kevin Kröninger

A plethora of inflationary models can produce interesting small-scale phenomenology, such as enhanced scalar fluctuations leading to primordial black hole (PBH) production and large scalar-induced GW. Nevertheless, good models must…

宇宙学与河外天体物理 · 物理学 2025-06-10 Laura Iacconi , Michael Bacchi , Luiz Filipe Guimarães , Felipe T. Falciano

Despite being the overwhelming majority of events produced in hadron or heavy ion collisions, minimum bias events do not enjoy a robust first-principles theoretical description as their dynamics are dominated by low-energy quantum…

高能物理 - 唯象学 · 物理学 2021-10-27 Andrew J. Larkoski , Tom Melia

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…

高能物理 - 唯象学 · 物理学 2011-03-18 Richard Corke , Torbjörn Sjöstrand

MC models of multiple partonic scattering inevitably introduce many free parameters, either fundamental to the models or from their integration with MC treatments of primary-scattering evolution. This non-perturbative and non-factorisable…

高能物理 - 唯象学 · 物理学 2018-07-02 Andy Buckley , Holger Schulz

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…

高能物理 - 唯象学 · 物理学 2016-10-12 S. Mrenna , P. Skands

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…

高能物理 - 实验 · 物理学 2016-03-21 CMS Collaboration

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…

高能物理 - 实验 · 物理学 2021-04-15 CMS Collaboration

As one of the key components of perturbative QCD theory, it is helpful to find a systematic and reliable way to set the renormalization scale for a high-energy process. The conventional treatment is to take a typical momentum as the…

高能物理 - 唯象学 · 物理学 2015-03-18 Yang Ma , Xing-Gang Wu , Hong-Hao Ma , Hua-Yong Han

Nonstatistical fluctuation in pseudorapidity ($\eta$), azimuthal ($\phi$), and pseudorapidity-azimuthal ($\eta-\phi$) distribution spectra of primary particles of PYTHIA Monash (default) generated $pp$ events at $\sqrt{s}=$ 2.76, 7, and 13…

高能物理 - 唯象学 · 物理学 2019-03-06 Buddhadeb Bhattacharjee , Pranjal Sarma

Generative models of complex systems often require post-hoc parameter adjustments to produce useful outputs. For example, energy-based models for protein design are sampled at an artificially low ''temperature'' to generate novel,…

定量方法 · 定量生物学 2025-12-11 Peter W Fields , Vudtiwat Ngampruetikorn , David J Schwab , Stephanie E Palmer

The energy test is a powerful binning-free, multi-dimensional and distribution-free tool that can be applied to compare a measurement to a given prediction (goodness-of-fit) or to check whether two data samples originate from the same…

数据分析、统计与概率 · 物理学 2018-04-30 G. Zech

The sphericity distribution in minimum bias events obtained with PYTHIA event generator, incorporating different parton distribution functions is presented. The results show that for minimum bias pp collisions the sphericity distribution…

高能物理 - 唯象学 · 物理学 2010-01-06 E. Cuautle , A. Ortiz , G. Paic

Monte Carlo event generators contain a large number of parameters that must be determined by comparing the output of the generator with experimental data. Generating enough events with a fixed set of parameter values to enable making such a…

数据分析、统计与概率 · 物理学 2017-04-28 Philip Ilten , Mike Williams , Yunjie Yang

Multi-Parton Interactions (MPI) in pp collisions have attracted the attention of the heavy-ion community since they can help to elucidate the origin of collective-like effects discovered in small collision systems at the LHC. In this work,…

高能物理 - 唯象学 · 物理学 2020-10-28 Antonio Ortiz , Antonio Paz , Jose D. Romo , Sushanta Tripathy , Erik A. Zepeda , Irais Bautista

Physical understanding of how the interplay between symmetries and nonlinear effects can control the scaling and multiscaling properties in a coupled driven system, such as magnetohydrodynamic turbulence or turbulent binary fluid mixtures,…

统计力学 · 物理学 2021-03-23 Sudip Mukherjee , Abhik Basu

We introduce a method for matching the neutral-current deep inelastic scattering process with parton showers at first order in the strong coupling. This multiplicative matching is achieved by reweighting leading-order Born-level events and…

高能物理 - 唯象学 · 物理学 2026-05-13 Ilkka Helenius , Joni O. Laulainen , Christian T. Preuss
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