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Register a new userStudy of charged-particle multiplicity fluctuations in pp collisions with Monte Carlo event generators at the LHC
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Proton-Proton ($pp$) collisions at the Large Hadron Collider (LHC) are simulated in order to study events with a high local density of charged particles produced in narrow pseudorapidty windows of $Deltaeta$ = 0.1, 0.2, and 0.5. The $pp$ collisions are generated at center of mass energies of $sqrt{s} = 2.36$, $7$, $8$, and $13$ TeV, i.e. the energies at which the LHC has operated so far, using PYTHIA and HERWIG event generators. We have also studied the average of the maximum charged-particle density versus the event multiplicity for all events, using the different pseudorapidity windows. This study prepares for the multi-particle production background expected in a future search for anomalous high-density multiplicity fluctuations using the LHC data.
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Quarkonium production as a function of the charged-particle multiplicity could provide an insight into particle production processes at the partonic level in hadronic collisions. It is believed that multiple partonic interactions play an important role in particle production and affect both soft and hard processes. The study of correlations between quarkonia and charged-particle multiplicity may provide information about this. In this contribution, ALICE measurements of J$/psi$ and $Upsilon$ production as a function of charged-particle multiplicity are presented for pp collisions at center-of-mass energies $sqrt{s}$ = 5.02 and 13 TeV. A similar measurement performed in ptextendash Pb collisions at $sqrt{s_{rm{NN}}}$ = 8.16 TeV at both forward and backward rapidity is also discussed.
We analyse the charged${text -}$particle multiplicity distributions measured by the ALICE experiment, over a wide pseudorapidity range, for $pp$ collisions at $sqrt{s}$=8,,7,and, 2.76~TeV at the LHC.~The analysis offers an understanding of particle production in high energy collisions in the purview of a new distribution, the shifted Gompertz distribution.~Data are compared with the distribution and moments of the distributions are calculated.~A modified version of the distribution is also proposed and used to improve the description of the data consisting of two different event classes; the inelastic and the non${text -}$single${text -}$diffractive and their subsets in different windows of pseudorapidity, $eta$.~The distribution used to analyse the data has a wide range of applicability to processes in different fields and complements the analysis done by the ALICE collaboration in terms of various LHC event generators and IP-Glasma calculations.
Monte Carlo event generators (MCEGs) are the indispensable workhorses of particle physics, bridging the gap between theoretical ideas and first-principles calculations on the one hand, and the complex detector signatures and data of the experimental community on the other hand. All collider physics experiments are dependent on simulated events by MCEG codes such as Herwig, Pythia, Sherpa, POWHEG, and MG5_aMC@NLO to design and tune their detectors and analysis strategies. The development of MCEGs is overwhelmingly driven by a vibrant community of academics at European Universities, who also train the next generations of particle phenomenologists. The new challenges posed by possible future collider-based experiments and the fact that the first analyses at Run II of the LHC are now frequently limited by theory uncertainties urge the community to invest into further theoretical and technical improvements of these essential tools. In this short contribution to the European Strategy Update, we briefly review the state of the art, and the further developments that will be needed to meet the challenges of the next generation.
In this talk the most recent results obtained by interfacing GoSam with external Monte Carlo event generators are presented and summarized. In the last year the automatic one-loop amplitude generator GoSam has been used for the computation of several processes relevant for the LHC physics program. In the first part of the talk the latest results are summarized and the status of the interfaces to several external Monte Carlo programs, based on the Binoth-Les-Houches-Accord, is reported. The second part is dedicated to two selected computations. One concerning the associated production of a Higgs and a vector boson in association with 0 and 1 jet computed with GoSam+Powheg, and one focusing on the analysis of the forward-backward asymmetry in the production of top quark pairs using 0 and 1 jet merged samples with GoSam+Sherpa. Finally some recent results on Beyond-Standard-Model physics are also presented.
A machine learning technique is used to fit multiplicity distributions in high-energy proton-proton collisions and applied to make predictions for collisions at higher energies. The method is tested with Monte Carlo event generator events. Charged-particle multiplicity and transverse-momentum distributions within different pseudorapidity intervals in proton-proton collisions were simulated using the PYTHIA event generator for center of mass energies $sqrt{s}$= 0.9, 2.36, 2.76, 5, 7, 8, 13 TeV for model training and validation and at 10, 20, 27, 50, 100 and 150 TeV for model predictions. Comparisons are made in order to ensure the model reproduces the relation input variables and output distributions for the charged particle multiplicity and transverse-momentum. The multiplicity and transverse-momentum distributions are described and predicted very well, not only in the case of the trained but also in the untrained energy values. The study proposes a way to predict multiplicity distributions at a new energy by extrapolating the information inherent in the lower energy data. Using real data instead of Monte Carlo, as measured at the LHC, the technique has the potential to project the multiplicity distributions for different intervals at very high collision energies, e.g. 27 TeV or 100 TeV for the upgraded HE-LHC and FCC-hh respectively, using only data collected at the LHC, i.e. at center of mass energies from 0.9 up to 13 TeV.
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