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Advances in High Energy Physics

Volume 2015 (2015), Article ID 612390, 30 pages

http://dx.doi.org/10.1155/2015/612390

## Charged Particle, Photon Multiplicity, and Transverse Energy Production in High-Energy Heavy-Ion Collisions

^{1}Indian Institute of Technology Indore, Indore 452017, India^{2}Indian Institute of Technology Bombay, Mumbai 400067, India

Received 24 August 2014; Revised 17 January 2015; Accepted 24 January 2015

Academic Editor: Andrey Leonidov

Copyright © 2015 Raghunath Sahoo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The publication of this article was funded by SCOAP^{3}.

#### Abstract

We review the charged particle and photon multiplicities and transverse energy production in heavy-ion collisions starting from few GeV to TeV energies. The experimental results of pseudorapidity distribution of charged particles and photons at different collision energies and centralities are discussed. We also discuss the hypothesis of limiting fragmentation and expansion dynamics using the Landau hydrodynamics and the underlying physics. Meanwhile, we present the estimation of initial energy density multiplied with formation time as a function of different collision energies and centralities. In the end, the transverse energy per charged particle in connection with the chemical freeze-out criteria is discussed. We invoke various models and phenomenological arguments to interpret and characterize the fireball created in heavy-ion collisions. This review overall provides a scope to understand the heavy-ion collision data and a possible formation of a deconfined phase of partons via the global observables like charged particles, photons, and the transverse energy measurement.

#### 1. Introduction

At extreme temperatures and energy density, hadronic matter undergoes a phase transition to partonic phase called Quark-Gluon Plasma (QGP) [1–3]. The main goal of heavy-ion collision experiments is to study the QGP by creating such extreme conditions by colliding heavy nuclei at relativistic energies. During the last decade, there are many heavy-ion collision experiments carried out at SPS, RHIC, and LHC to create and study QGP in the laboratory. Global observables like transverse energy (), particle multiplicities (, etc.), -spectra of the produced particles, and their pseudorapidity distributions () with different colliding species and beam energies provide insight about the dynamics of the system and regarding the formation of QGP [2, 4]. It is also proposed that the correlation of mean transverse momentum and the multiplicity of the produced particles may serve as a probe for the Equation of State (EoS) of hot hadronic matter [5]. In a thermodynamic description of the produced system, the rapidity density () reflects the entropy and the mean transverse momentum () corresponds to the temperature of the system. Except at the phase transition points, the rapidity density linearly scales with . If the phase transition is of first order, then the temperature remains constant at the coexistence of the hadron gas and the QGP phase, thereby increasing the entropy density. In such a scenario, shows a plateau with increase of entropy, thereby characterizing the phase transition associated with the time evolution of the system. Hence, the global observables like and give indication of a possible existence of a QGP phase and the order of phase transition. gives the maximum energy density produced in the collision process which is necessary to understand the reaction dynamics. The formation of QGP may also change the shape of the pseudorapidity distribution [6, 7]. The event multiplicity distribution gives information of the centrality and energy density of the collision. The scaling of multiplicity with number of participant nucleons () reflects the particle production due to soft processes (low-). However, at high energy when hard processes (high-) dominate, it is expected that the multiplicity will scale with the number of nucleon-nucleon collisions (). There are models [8] to explain the particle production taking a linear combination of and (called two-component model). The most viable way of studying QGP is via the particles produced in the collision in their respective domain of proposed methods. Then one of the most fundamental questions arises about the mechanism of particle production and how they are related with the initial energy density, gluon density in the first stage of the collision evolution, and entropy of the system. Similarly, question can be put to figure out the role of soft and hard process of particle productions. It is proposed that the charged particle multiplicity technically called the pseudorapidity density distributions of charged particles, , can be used to address the above questions [9–15]. Here the pseudorapidity is defined as, = −ln tan , where is the polar angle made by the produced particles with the detector, with respect to the beam direction. So is called one of the global variables to characterize the system produced in the heavy-ion collisions. Experimentally, it is more easy to estimate this quantity as most of the detectors are capable of detecting charged particles and it involves only kinematics of the charged particles.

In this review, in Section 2, we discuss the method of experimental determination of collision centrality, which is followed by discussions on the midrapidity pseudorapidity density distributions of charged particles for different collision energies, collision species, and centralities in Section 3. In this section, we discuss the longitudinal scaling and factorization of charged particles. The expansion dynamics of the system is discussed using the pseudorapidity density distributions of charged particles and the Landau-Carruthers hydrodynamics. In subsequent subsections, the scaling of total charged particles with collision centrality and its energy dependence are discussed. This is followed with similar discussions on the photon pseudorapidity density at forward rapidities in Section 4, which includes longitudinal scaling of photons. Subsequently, in Section 5, discussions are made on the production of transverse energy and its use for centrality determination. Section 6 includes discussions on collision energy dependence of transverse energy, which is followed by discussions on the centrality dependence in Section 7. Section 8 includes discussions on estimation of initial energy density in Bjorken hydrodynamic scenario and its energy and centrality dependences. Further we correlate the energy and centrality dependence of transverse energy per charged particle with chemical freeze-out criteria in Section 9. In Section 10, we summarize the review with conclusions. Appendix discusses the important properties of Gamma and Negative Binomial Distributions.

#### 2. Centrality Determination

In heavy-ion collisions, the event centrality is of utmost importance to understand the underlying physics of the collision. The event centrality is related to the impact parameter, defined as the distance between the centroids of the two colliding nuclei in a plane transverse to the beam axis, of the collision. The impact parameter tells about the overlap volume of the two nuclei. This overlap volume determines the geometrical parameters, like number of participant nucleons (), number of spectator nucleons (), and the number of binary collisions ().

The impact parameter can not be determined experimentally. However, the global observables, like total charged particles (), transverse energy (), or energy deposited in ZDC (), and so forth, are related to this geometrical quantity. By combining the experimental observables with simulation, one can estimate the impact parameter and hence the centrality of the event class. The centrality is expressed as the percentile () of the total hadronic interaction cross section corresponding to the charged particle multiplicity above certain threshold and is given byIn (1), is the total nuclear interaction cross section of collision. Assuming constant luminosity, the cross section can be replaced by the number of observed events after the trigger efficiency correction. But at very high energy, when these two nuclei pass by each other, there is a large QED cross section because of the electromagnetic field [16, 17]. This QED cross section is much larger than the hadronic cross section and this contaminates the most peripheral events. That is why the centrality determination is restricted to some percentile where the QED contribution is negligible. The fraction of hadronic events excluded by such cut as well as the trigger efficiency can be estimated by using a Glauber model simulation.

For a given impact parameter, the and can be estimated by Glauber Monte Carlo method. The parametrized Negative Binomial Distribution (NBD) can be used to describe the nucleon-nucleon collisions. For heavy-ion collisions, and are used to generate the number of charged particles by incorporating two-component model in the following way:This refers to the “independent emitting source.” The two-component model given in (2) incorporates the soft and hard interactions. Soft process is related to the and hard process is related to .

The functional form of NBD distribution is given byEquation (3) represents the probability of measuring hits per ancestor. Here, represents the mean multiplicity per ancestor and controls the width of the distribution. In collision, a Negative Binomial Distribution (NBD) with a fixed value of and well describes the charged multiplicity data for most of multiplicity range though requiring a second NBD ingredient to well describe the tail of the distribution [18–20]. The charged particle multiplicity for nucleus-nucleus collisions with a given impact parameter is generated by sampling times the multiplicity, which is generated by using NBD. Finally, a minimisation is done by fitting the Glauber Monte Carlo generated multiplicity and the charged particle multiplicity obtained from the collision data. The minimization will give us the value of , , and . This gives a connection between an experimental observable and a Glauber Monte Carlo. From this one can have access to and for a given class of centrality by NBD-Glauber fit. For example, the centrality determination in ALICE using VZERO (V0) amplitude is given in Figure 1. The two-component model is fitted with the V0 amplitude in Figure 1 to find out the and values for a corresponding centrality [16].