Self-affine pionization in p–p collisions at LHC energy

Bhattacharjee, Shreya; Paul, Subhadeep; Ahmed, Azharuddin; Tawfik, Abdel Nasser; Haldar, Prabir Kumar

doi:10.1142/s0218301323500234

Cited by 3 publications

(1 citation statement)

References 69 publications

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“…energies, (iv) to set a baseline comparison of the minimum bias (MB) data generated by three different models UrQMD, AMPT and PYTHIA, (v) to examine the impact parameter dependencies of UrQMD data in our present investigation. In our earlier work, we took into account the UrQMD-generated p-p collisions for various impact parameters in pseudorapidity (η), azimuthal (f), two-dimensional isotropic and anisotropic (η − f) phase-spaces [28,29]. In this work, we have studied FB correlations and multiplicity fluctuations produced in p-p collisions at different LHC energies not only for MB events but also considered energy-wise variation of correlation strength, probability distribution of roughness parameter for different UrQMD generated impact parameters like b = 0.2, 0.3, 0.4, 0.5 and 0.6 to examine their dependencies.…”

Section: Goal Of the Studymentioning

confidence: 99%

Study of forward–backward correlation and multiplicity fluctuations of pions produced in p–p collisions at recent LHC energies

Paul,

Bhattacharjee,

Ahmed

et al. 2023

J. Phys. G: Nucl. Part. Phys.

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The two-particle rapidity correlation among the pions produced in p-p collisions at recent LHC energies √s= 2.76, 5.02, 7 & 13 TeV is studied in this paper by using the analysis of events generated by UrQMD-3.4, AMPT-2.26 & PYTHIA-8.3. Our investigation for bin-to-bin fluctuation using the variance of Forward-Backward asymmetry parameter σC 2 in the forward-backward pseudo-rapidity windows is done through the simulated data. In addition to that, energy-wise variation of correlation strength (β), the probability distribution of roughness parameter (γk 2) and number density fluctuation parameter (dik) are also incorporated in this investigation. Also, we have tried to study the same for \textbf{the data of different impact parameters generated using the UrQMD model, and the comparison is made with its minimum biased events data-set. The analysis signifies, that the signature of dynamical fluctuation is not so prominent but increases a bit with the increase in energy. An increase in the correlation strength with the increase in energy signifies the contribution of long-range correlation is more in comparison to the short-range one. However, there is no such accountable effect of various impact parameters seen in the present study.

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Section: Goal Of the Studymentioning

confidence: 99%

Study of forward–backward correlation and multiplicity fluctuations of pions produced in p–p collisions at recent LHC energies

Paul,

Bhattacharjee,

Ahmed

et al. 2023

J. Phys. G: Nucl. Part. Phys.

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A review on correlations among the multiplicities of charge particles at SPS, RHIC and LHC energies

Bhattacharjee,

Haldar

2024

Mod. Phys. Lett. A

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Correlation study among the charge particle multiplicities plays an important role to analyze the heavy-ion interactions. Different observables like charged particle multiplicities, azimuthal anisotropy among the multiplicity of charge particles, transverse momentum of the multiplicities, etc. can correlate and these help to comprehend the various phases of heavy-ion collisions. We have reviewed two- and three-particle correlations, azimuthal correlations and Bose–Einstein correlations among the multiplicities of charge particles. We have also studied the forward-backward correlation technique to investigate the correlations among the charged multiplicities. Here, we have discussed various kinds of correlations at SPS energy, RHIC energy and LHC energy.

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An approach to complex network analysis on pp collisions at LHC energies

Ahmed,

Biswas,

Subba

et al. 2024

Int. J. Mod. Phys. E

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We have introduced the complex network analysis techniques such as Visibility Graph (VG), Horizontal Visibility Graph (HVG) and Sandbox (SB) algorithm as a mapping between complex network and time series measurements. This study explores the application of complex network-based analysis techniques to proton–proton [Formula: see text] collisions data at [Formula: see text], 7, 5.02 and 2.76[Formula: see text][Formula: see text]TeV to unravel the underlying dynamics of the particles and their interactions. To ensure the robustness and comprehensive analysis, we have incorporated UrQMD-, PYTHIA- and AMPT-simulated data sets of [Formula: see text] interactions at LHC energies that enable a thorough investigation of the underlying phenomena of the interactions. We have analyzed the fluctuations in pseudorapidity densities of singly charged particles created in [Formula: see text] interactions at LHC energies. We have also investigated some properties like symmetry scaling, correlation, clustering and scale-freeness among the produced particles. The findings from this study contribute to our understanding of the complex dynamics within [Formula: see text] collisions and have implications for the field of high-energy physics and particle phenomenology.

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Self-affine pionization in p–p collisions at LHC energy

Cited by 3 publications

References 69 publications

Study of forward–backward correlation and multiplicity fluctuations of pions produced in p–p collisions at recent LHC energies

Study of forward–backward correlation and multiplicity fluctuations of pions produced in p–p collisions at recent LHC energies

A review on correlations among the multiplicities of charge particles at SPS, RHIC and LHC energies

An approach to complex network analysis on pp collisions at LHC energies

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