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Advances in High Energy Physics
Volume 2016 (2016), Article ID 7287803, 9 pages
http://dx.doi.org/10.1155/2016/7287803
Research Article

Comparative Multifractal Detrended Fluctuation Analysis of Heavy Ion Interactions at a Few GeV to a Few Hundred GeV

1Nuclear and Particle Physics Research Centre, Department of Physics, Jadavpur University, Kolkata 700032, India
2Department of Physics, New Alipore College, L Block, New Alipore, Kolkata 700053, India

Received 4 February 2016; Accepted 7 April 2016

Academic Editor: Ming Liu

Copyright © 2016 Gopa Bhoumik 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 SCOAP3.

Abstract

We have studied the multifractality of pion emission process in 16O-AgBr interactions at 2.1 AGeV  and  60 AGeV, 12C-AgBr  and  24Mg-AgBr interactions at 4.5 AGeV, and 32S-AgBr interactions at 200 AGeV using Multifractal Detrended Fluctuation Analysis (MFDFA) method which is capable of extracting the actual multifractal property filtering out the average trend of fluctuation. The analysis reveals that the pseudorapidity distribution of the shower particles is multifractal in nature for all the interactions; that is, pion production mechanism has inbuilt multiscale self-similarity property. We have employed MFDFA method for randomly generated events for 32S-AgBr interactions at 200 AGeV. Comparison of expt. results with those obtained from randomly generated data set reveals that the source of multifractality in our data is the presence of long range correlation. Comparing the results obtained from different interactions, it may be concluded that strength of multifractality decreases with projectile mass for the same projectile energy and for a particular projectile it increases with energy. The values of ordinary Hurst exponent suggest that there is long range correlation present in our data for all the interactions.