Cross Sections and Charged-Particle Multiplicities at 102 and 405 GeV/<i>c</i>

Bromberg, C.; Chaney, D.; Cohen, D.; Ferbel, T.; Slattery, P.; Underwood, D. G.; Chapman, J.; Cooper, J.; Green, N.; Roe, B. P.; Seidl, A. A.; Velde, J.C. Vander

doi:10.1103/physrevlett.31.1563

Cited by 163 publications

(17 citation statements)

References 12 publications

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“…The values obtained from Eq. (2) for the AA mean multiplicity are based on: nonsingle diffractivepp collisions at FNAL by the E735 experiment [7,24], at CERN by the UA5 experiment at √ spp = 546 GeV [25] and √ spp = 200 and 900 GeV [26]; pp collisions from CERN-ISR [27], and from the inelastic data from the bubble chamber experiments [28][29][30], the latter having been compiled and analyzed in [31]. The LHC multiplicities in pp interactions are calculated using the hybrid fit obtained here, Eq.…”

Section: The Participant Dissipating Energy Approachmentioning

confidence: 99%

“…energy dependence of the charged particle mean multiplicity in pp/pp collisions. The measurements are taken from: nonsingle diffractivepp collisions at FNAL by the E735 experiment[7,24], at CERN by the UA5 experiment at √ spp = 546 GeV[25] and √ spp = 200 and 900 GeV[26]; pp collisions from CERN-ISR[27], and from the inelastic data from the bubble chamber experiments[28][29][30][31]44].The solid line shows the hybrid fit, 1.60−0.03 ln(spp)+0.18 ln 2 (spp)+0.03 s 0.29 pp , the dotted line shows the power-law fit, −7.36+6.97 s 0.133 pp , and the dashed line shows the second-order log fit, 3.18−0.57 ln(spp)+0.216 ln 2 (spp). The open stars show the predictions by the PDE approach with the error bars of 5% uncertainty.…”

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confidence: 99%

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Multihadron production dynamics exploring the energy balance in hadronic and nuclear collisions

et al. 2016

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The relation of multihadron production in nucleus-nucleus and (anti)proton-proton collisions is studied by exploring the collision-energy and centrality dependencies of the charged particle mean multiplicity in the measurements to date. The study is performed in the framework of the recently proposed effectiveenergy approach which, under the proper scaling of the collision energy, combines the constituent quark picture with Landau relativistic hydrodynamics counting for the centrality-defined effective energy of participants. Within this approach, the multiplicity energy dependence and the pseudorapidity spectra from the most central nuclear collisions are well reproduced. The study of the multiplicity centrality dependence reveals a new scaling between the measured pseudorapidity spectra and the calculations. By means of this scaling, referred to as energy-balanced limiting fragmentation scaling, one reproduces the pseudorapidity spectra for all centralities. The scaling elucidates some differences in the multiplicity and midrapidity density centrality dependence obtained at RHIC and LHC. These findings reveal an inherent similarity in the multiplicity energy dependence from the most central collisions and centrality data. Predictions are made for the mean multiplicities to be measured in proton-proton and heavy-ion collisions at the LHC.

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Section: The Participant Dissipating Energy Approachmentioning

confidence: 99%

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confidence: 99%

Multihadron production dynamics exploring the energy balance in hadronic and nuclear collisions

et al. 2016

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“…(5) are shown in Fig. 9 which shows the best agreement between calculated by GPII model and the corresponding experimental data [36][37][38][39][40][41][42][43][44][45][46][47] 3 . The monotonic increase of with √ is shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

“…The experimental data of p-p interactions have been measured, by using different giant accelerators and from cosmic rays, over the largest range of energies (up to √ ≈ 63 GeV for the multiplicity distribution, up to √ ≈ 10 3 GeV for the average multiplicity and up to √ ≈ 10 TeV for the total cross sections) [36][37][38][39][40][41][42][43][44][45][46][47] 1 . The GP is implemented using the experimental data to produce three different models, GPI, GPII, and GPIII that will simulate ( ), and (σ ), respectively, for the p-p interactions at the given range of energies.…”

Section: Resultsmentioning

confidence: 99%

Application of genetic programming for proton-proton interactions

El‐Dahshan

2011

Open Physics

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Abstract:The aim of the present work is to use one of the machine learning techniques named the genetic programming (GP) to model the p-p interactions through discovering functions. In our study, GP is used to simulate and predict the multiplicity distribution of charged pions (P( )), the average multiplicity ( ) and the total cross section (σ ) at different values of high energies. We have obtained the multiplicity distribution as a function of the center of mass energy ( √ ) and charged particles ( ). Also, both the average multiplicity and the total cross section are obtained as a function of √ . Our discovered functions produced by GP technique show a good match to the experimental data. The performance of the GP models was also tested at non-trained data and was found to be in good agreement with the experimental data.PACS (

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“…Results of the fits to the negatively charged particle multiplicity distributions in inelastic pp collisions[22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. Results of the fits to the negatively charged particle multiplicity distributions in pp interactions[2,40].…”

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confidence: 99%

Multiplicity distributions at high energies as a sum of Poissonian-like distributions

Tchikilev

1999

Phys. Rev. D

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It is shown that at collider energies experimental distributions in the multiplicity n of negatively charged particles in inelastic and non-single diffractive pp collisions are well parameterized by a sum of so-called Gupta-Sarma distributions having the Poisson distribution as a particular case. This extends the earlier description of the multiplicity distributions in hadron-hadron collisions at c.m. energies below 65 GeV by the two parameter sum of Poissonians. Implications of the proposed parametrization for the LHC energy are discussed.

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Cross Sections and Charged-Particle Multiplicities at 102 and 405 GeV/c

Cited by 163 publications

References 12 publications

Multihadron production dynamics exploring the energy balance in hadronic and nuclear collisions

Multihadron production dynamics exploring the energy balance in hadronic and nuclear collisions

Application of genetic programming for proton-proton interactions

Multiplicity distributions at high energies as a sum of Poissonian-like distributions

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