Multiplicity distributions in the low x regime in a simple model

Germano, G. R.; Navarra, F. S.

doi:10.48550/arxiv.2011.08912

Cited by 3 publications

(8 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Increasing the lower p T cut and selecting higher p T particles, we reduce the contribution of the fragmentation region yield (which is mostly forward and with low transverse momentum) and improve the agreement between the KL model and data, as is indeed seen in the comparison with set III data. Finally, it is worth mentioning that the discrepancy between the KL model and the set II data is visible not only in the C n moments but also in the entire distribution P (n), as shown in [22].…”

Section: B the Cn Momentsmentioning

confidence: 97%

The energy dependence of the multiplicity moments at the LHC

Germano,

Navarra

2021

Preprint

Self Cite

View full text Add to dashboard Cite

In this work, from the experimental data we evaluate the first C-moments of the multiplicity distributions recently measured in proton-proton collisions at the LHC and compare them with the predictions of two models: the Kharzeev-Levin model and the Bialas-Praszalowicz model. We divide the data into three sets according to their phase space coverage: I: pT > 100 MeV and |η| < 0.5; II: pT > 100 MeV and |η| < 2.4 and II: pT > 500 MeV and |η| < 2.4. The mean multiplicity grows with the energy according to a power law and the power is different for each set. The Cn moments grow continuously with the energy, slowly in set I and faster in the other sets. Except for KL in set II, both models reproduce the main features of the data. The negative binomial parameter k decreases continuously with the energy and there is no sign of change in this behavior.

show abstract

Section: B the Cn Momentsmentioning

confidence: 97%

The energy dependence of the multiplicity moments at the LHC

Germano,

Navarra

2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…When k is large (1/k → 0), the distribution P NBD tends to a Poisson distribution. The mean multiplicity is an input to calculate P NBD and can be parametrized as [5] :…”

Section: Pos(xvhadronphysics)063mentioning

confidence: 99%

“…In [5] we fixed q 0 and ∆ from the fit of the available experimental data and the results are shown in Table 1. The data of sets I and II have the same lower p T cut and very different rapidity coverage.…”

Section: Pos(xvhadronphysics)063mentioning

confidence: 99%

“…The expressions for C 4 and C 5 can be found in [5]. All the moments are functions only of C 2 and n .…”

Section: Pos(xvhadronphysics)063mentioning

confidence: 99%

“…In the most recent experimental papers, the multiplicity distributions P(n) were presented but the moments C n were not. In [5] we computed the moments from the multiplicity tables, which we took from the hepdata.net databasis.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multiplicity moments at the LHC: how bad is the negative binomial distribution ?

Germano¹,

Navarra²

2022

Proceedings of XV International Workshop on Hadron Physics — PoS(XVHadronPhysics)

View full text Add to dashboard Cite

In this work, we compare the first C-moments of the multiplicity distributions recently measured in proton-proton collisions at the LHC with the predictions of the Bialas-Praszalowicz model. In this model the multiplicity distribution is given by a negative binomial distribution (NBD). In our comparison, we try to identify the regions of the phase space where the NBD fails. We divide the data into three sets according to their phase space coverage: I: p T > 100 MeV and |η| < 0.5; II: p T > 100 MeV and |η| < 2.4 and II: p T > 500 MeV and |η| < 2.4. The mean multiplicity grows with the energy according to a power law and the power is different for each set. The C n moments grow continuously with the energy, slowly in set I and faster in the other sets. We find that the NBD gives a very good description of the measured moments C 2 , C 3 and C 4 and slightly overestimates C 5 in all data sets. The negative binomial parameter k decreases continuously with the energy and there is no sign of change in this behavior.

show abstract

Parton branching in the low x regime and multiplicity distributions at the LHC

Germano

Navarra

2022

J. Phys.: Conf. Ser.

Self Cite

View full text Add to dashboard Cite

We study the multiplicity distribution measured in pp collisions at the LHC using a distribution which is derived from the Giovannini equations under the assumption that the evolution parameter is energy dependent. We obtain a negative binomial distribution with explicit energy dependence and fit it to three data sets, corresponding to different pseudorapidity and transverse momentum cuts, and also verify the applicability of the model for a fourth data set, corresponding to jets. We find a reasonable agreement with data for all sets.

show abstract

Multiplicity distributions in the low x regime in a simple model

Cited by 3 publications

References 31 publications

The energy dependence of the multiplicity moments at the LHC

The energy dependence of the multiplicity moments at the LHC

Multiplicity moments at the LHC: how bad is the negative binomial distribution ?

Parton branching in the low x regime and multiplicity distributions at the LHC

Contact Info

Product

Resources

About