A study of high energy hadron–nucleus interactions

1983 ◽  
Vol 61 (7) ◽  
pp. 1120-1141 ◽  
Author(s):  
H. Khushnood ◽  
A. Shakeel ◽  
A. Ahmad ◽  
M. Z. Ahsan

An attempt has been made to investigate the multiplicity distributions of grey, black, shower, and heavy tracks, the dispersions of their distributions, intercorrelations between them, the dependence of the mean normalized multiplicity on the target mass and energy, etc., in hadron–nucleus interactions at 24, 50, and 400 GeV incident energies. The results obtained in the study reveal that the behaviour of the multiplicity distribution is independent of the nature and energy of the impinging hadron. Furthermore, on redefining the mean normalized multiplicity, it is found to be not only energy independent but also projectile independent, suggesting a new kind of scaling in particle–nucleus interactions.

2011 ◽  
Vol 20 (08) ◽  
pp. 1735-1754 ◽  
Author(s):  
M. MOHERY ◽  
M. ARAFA

The present paper deals with the interactions of 22 Ne and 28 Si nuclei at (4.1–4.5)A GeV /c with emulsion. Some characteristics of the compound multiplicity nc given by the sum of the number of shower particles ns and grey particles ng have been investigated. The present experimental data are compared with the corresponding ones calculated according to modified cascade evaporation model (MCEM). The results reveal that the compound multiplicity distributions for these two reactions are consistent with the corresponding ones of MCEM data. It can also be seen that the peak of these distributions shifts towards a higher value of nc with increasing projectile mass. It may further be seen that the compound multiplicity distributions becomes broader with increasing target size and its width increases with the size of the projectile nucleus. In addition, it has been found that the MCEM can describe the compound multiplicity characteristics of the different projectile, target and the correlation between different emitted particles. The values of average compound multiplicity increase with increasing mass of the projectile. Furthermore, it is observed that while the value of 〈nc〉 depends on the mass number of the projectile Ap and the target mass number At, the value of the ratio 〈nc〉/D(nc) seems to be independent of Ap and At. The impact parameter is found to affect the shape of the compound multiplicity distribution. Finally, the dependence of the average compound multiplicity on the numbers of grey and black particles, and the sum of them, is obvious. The values of the slope have been found to be independent of the projectile nucleus.


2017 ◽  
Vol 26 (03) ◽  
pp. 1750006 ◽  
Author(s):  
S. Sharma ◽  
M. Kaur ◽  
S. Thakur

Concepts from statistical mechanics and ensemble theory are applied to study the characteristic properties of charged particle production in hadron–nucleus collisions at high energy. In the present study we utilize the predictions from different approaches using statistical mechanics. The Tsallis q-statistics is used to study the regularity in multiplicity distributions in hadron–nucleus collisions at high energies as one of the interesting options. Gamma distributions and a possible microcanonical generalization of Tsallis distribution have also been exploited to describe the data.


2016 ◽  
Vol 25 (06) ◽  
pp. 1650041 ◽  
Author(s):  
S. Sharma ◽  
M. Kaur ◽  
Sandeep Kaur

The nonextensive behavior of entropy is exploited to explain the regularity in multiplicity distributions in [Formula: see text] collisions at high energies. The experimental data are analyzed by using Tsallis [Formula: see text]-statistics. We propose a new approach of applying Tsallis [Formula: see text]-statistics, wherein the multiplicity distribution is divided into two components; two-jet and multijet components. A convoluted Tsallis distribution is fitted to the data. It is shown that this method gives the best fits which are several orders better than the conventional fit of Tsallis distribution.


2020 ◽  
Vol 29 (04) ◽  
pp. 2050021
Author(s):  
S. Sharma ◽  
G. Chaudhary ◽  
K. Sandeep ◽  
A. Singla ◽  
M. Kaur

The study of higher-order moments of a distribution and its cumulants constitute a sensitive tool to investigate the correlations between the particle produced in high-energy interactions. In our previous work, we have used the Tsallis [Formula: see text] statistics, NBD, Gamma and shifted Gamma distributions to describe the multiplicity distributions in [Formula: see text]-nucleus and [Formula: see text]-nucleus fixed target interactions at various energies ranging from [Formula: see text][Formula: see text]GeV to 800[Formula: see text]GeV. In this study, we have extended our analysis by calculating the moments using the Tsallis model at these fixed target experiment data. By using the Tsallis model, we have also calculated the average charged multiplicity and its dependence on energy. It is found that the average charged multiplicity and moments predicted by the Tsallis statistics are in much agreement with the experimental values and indicates the success of the Tsallis model on data from visual detectors. The study of moments also illustrates that KNO scaling hypothesis holds good at these energies.


1972 ◽  
Vol 40 ◽  
pp. 317-334 ◽  
Author(s):  
Z. Koba ◽  
H.B. Nielsen ◽  
P. Olesen

1990 ◽  
Vol 05 (23) ◽  
pp. 1851-1869 ◽  
Author(s):  
R. SZWED ◽  
G. WROCHNA ◽  
A. K. WRÓBLEWSKI

It has been observed that the e+e− multiplicity distributions exhibit the following properties: the dispersions are linear functions of the mean and the distributions obey the KNO-G scaling with the scaling function of the lognormal shape. In this paper the scale invariant branching is assumed as a mechanism within which all these properties could be derived. It is shown that the lognormal shape of the scaling function can be obtained within proposed mechanism by using the generalization of the Central Limit Theorem. The dependence of the average multiplicity on energy is also derived within the postulated framework. It is also shown that many other phenomena encountered in nature have the similar statistical properties.


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