Study of KNO scaling in the emulsion based neutrino experiments

2022

Eur. Phys. J. C

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In this study, the charged particle multiplicity distribution produced in anti-neutrino interactions in nuclear emulsion is investigated in terms of the log-normal parametric model and KNO-G scaling for the first time. The results are based on the data collected by the CHORUS experiment in the $$\nu _{\mu }$$ ν μ beam from CERN SPS. The analysis of 369 $$\bar{\nu }_{\mu }$$ ν ¯ μ CC events showed that anti-neutrino charged-particle multiplicity data shape is well described by a log-normal distribution. Furthermore, KNO-G scaling has been successfully applied to the data and results confirm the validity of KNO-G scaling for the anti-neutrino interactions. Finally, results are presented in detail in the form of figures and tables.

Section: Introductionmentioning

confidence: 99%

Properties of charged particle multiplicities in anti-neutrino interactions of the CHORUS experiment

2022

Eur. Phys. J. C

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“…The multiplicity distribution of charged hadrons is a very important tool to understand the particle production mechanism in the hard scattering processes. Since it is a valuable source of the dynamics of the processes, the characteristics of charged hadron multiplicity distributions have been intensively studied in many experiments like cosmic rays, fixed targets, colliders and neutrino interactions [1][2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Study of negative binomial distribution in charged-current neutrino–lead interactions

2021

Eur. Phys. J. Plus

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The negative binomial distribution is an statistical distribution which has been applied in many interactions and its validity to describe the charged particle multiplicity distribution has been reported. In this paper, charged hadron multiplicity distributions produced in neutrino-lead interactions of OPERA experiment are analyzed in terms of the negative binomial distribution for different W 2 intervals. The compatibility of the data with the applied fit is observed in each energy range and the energy dependence of the free parameters is presented.

“…Therefore, various theoretical, phenomenological models and rules are proposed to parameterize charged particle multiplicity distributions in the literature. However, results from experiments showed that some parametric models are more successful in describing the data and its energy dependence up to now [1][2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Log-normal and Negative Binomial Distributions of DONUT Data

Celal Bayar Üniversitesi Fen Bilimleri Dergisi

2021

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There are several parametric models to describe the charged particle multiplicity distributions in literature. Among them, log-normal distribution and negative binomial distribution are the most well-known parametric models. In this study, negative binomial and log-normal distributions are compared and tested in neutrino interactions produced in DONUT experiment. This analysis was carried out using the real experimental results of the DONUT Collaboration. The results of the analysis show that the neutrino data, reported by DONUT collaboration, is well described by negative binomial and log-normal distribution. In terms of fit parameters, the χ/ndf value of the both distribution NBD and LND are close to unity but log-normal distribution data slightly better than negative binomial distribution.