2010
DOI: 10.1088/1674-1137/34/8/007
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Central nucleus-nucleus collisions at relativistic energies with a new method based on Random Matrix Theory

Abstract: Using the method based on Random Matrix Theory (RMT), the results for the nearest-neighbor distributions obtained from the experimental data on 12 C-C collisions at 4.2 AGeV/c have been discussed and compared with the simulated data on 12 C-C collisions at 4.2 AGeV/c produced with the aid of the Dubna Cascade Model. The results show that the correlation of secondary particles decreases with an increasing number of charged particles N ch . These observed changes in the nearest-neighbor distributions of charged … Show more

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Cited by 2 publications
(15 citation statements)
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“…Indeed, one can find a good agreement between the results obtained in this way and a standard analysis based on the method of effective mass spectra and two-pair correlation function often used in high energy physics [18]. The purpose of the present review is to discuss a novel criterion for the centrality of collision, using a rigorous mathematical framework of the RMT [18][19][20][21][22]. Section 2 briefly reviews how to detect the manifestation of correlations with the aid of nearest-neighbor spacing energy distribution (NND) from the data obtained in light nuclei collisions in Dubna Experiments.…”
Section: Introductionmentioning
confidence: 54%
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“…Indeed, one can find a good agreement between the results obtained in this way and a standard analysis based on the method of effective mass spectra and two-pair correlation function often used in high energy physics [18]. The purpose of the present review is to discuss a novel criterion for the centrality of collision, using a rigorous mathematical framework of the RMT [18][19][20][21][22]. Section 2 briefly reviews how to detect the manifestation of correlations with the aid of nearest-neighbor spacing energy distribution (NND) from the data obtained in light nuclei collisions in Dubna Experiments.…”
Section: Introductionmentioning
confidence: 54%
“…In general [18][19][20][21][22], this procedure does not involve any uncertainty or spurious contributions and deals with a direct processing of physical data.…”
Section: Basic: Nearest-neighbor Energy Spacing Distributionmentioning
confidence: 99%
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