MULTIFRACTAL STRUCTURE OF PSEUDORAPIDITY AND AZIMUTHAL DISTRIBUTIONS OF THE SHOWER PARTICLES IN Au + Au COLLISIONS AT 200 A GeV

2008 ◽  
Vol 23 (18) ◽  
pp. 2809-2816 ◽  
Author(s):  
Y. X. ZHANG ◽  
W. Y. QIAN ◽  
C. B. YANG
Keyword(s):  
Long Range ◽  
Detrended Fluctuation Analysis ◽  
Correlation Property ◽  
Fluctuation Analysis ◽  
Analysis Method ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Range Correlation ◽  
Detrended Fluctuation

This paper analyzes the long-range correlation property and the corresponding multifractal structure of the distribution of shower particles in central Au + Au collisions at 200 A GeV by using the Multifractal Detrended Fluctuation Analysis method. The result shows that the pseudorapidity and azimuthal distributions of shower particles are multifractals in those collisions.

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

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Gopa Bhoumik ◽  
Argha Deb ◽  
Swarnapratim Bhattacharyya ◽  
Dipak Ghosh
Keyword(s):  
Long Range ◽  
Detrended Fluctuation Analysis ◽  
Heavy Ion ◽  
Projectile Energy ◽  
Fluctuation Analysis ◽  
Data Set ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Range Correlation ◽  
Multifractal Property ◽  
Detrended Fluctuation

We have studied the multifractality of pion emission process in16O-AgBr interactions at 2.1 AGeV  and  60 AGeV,12C-AgBr  and  24Mg-AgBr interactions at 4.5 AGeV, and32S-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 for32S-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.

MULTIFRACTAL DETRENDED FLUCTUATION ANALYSIS OF ELECTRIC LOAD SERIES

Fractals ◽  
2015 ◽  
Vol 23 (02) ◽  
pp. 1550010 ◽  
Author(s):  
XIAOHUI YUAN ◽  
BIN JI ◽  
YANBIN YUAN ◽  
YUEHUA HUANG ◽  
XIANSHAN LI ◽  
...  
Keyword(s):  
Time Series ◽  
Long Range ◽  
Detrended Fluctuation Analysis ◽  
Quadratic Function ◽  
Fluctuation Analysis ◽  
Electric Load ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Range Correlation ◽  
Detrended Fluctuation ◽  
Multifractal Nature

Multifractal detrended fluctuation analysis (MF-DFA) method is applied to analyze the daily electric load time series. The results of the MF-DFA show that there are three crossover timescales at seven days, 15 days and 365 days approximately in the fluctuation function. Also we find that these fluctuations have multifractal nature with long range correlation behavior. The multifractal singularity spectrum of the daily electric load series has been fitted by the quadratic function model. Comparing the MF-DFA results of the original load series with those of shuffled and surrogate series, it concludes that the multifractal characteristics of the daily electric load time series is due to both broadness of the probability density function and long-range correlation, and the long-range correlation is dominant.

scholarly journals Investigating Long-Range Dependence of Emerging Asian Stock Markets Using Multifractal Detrended Fluctuation Analysis

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1157
Author(s):  
Faheem Aslam ◽  
Saima Latif ◽  
Paulo Ferreira
Keyword(s):  
Time Series ◽  
Long Range ◽  
Stock Markets ◽  
Detrended Fluctuation Analysis ◽  
Financial Time Series ◽  
Long Range Dependence ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Financial Time ◽  
Detrended Fluctuation

The use of multifractal approaches has been growing because of the capacity of these tools to analyze complex properties and possible nonlinear structures such as those in financial time series. This paper analyzes the presence of long-range dependence and multifractal parameters in the stock indices of nine MSCI emerging Asian economies. Multifractal Detrended Fluctuation Analysis (MFDFA) is used, with prior application of the Seasonal and Trend Decomposition using the Loess (STL) method for more reliable results, as STL separates different components of the time series and removes seasonal oscillations. We find a varying degree of multifractality in all the markets considered, implying that they exhibit long-range correlations, which could be related to verification of the fractal market hypothesis. The evidence of multifractality reveals symmetry in the variation trends of the multifractal spectrum parameters of financial time series, which could be useful to develop portfolio management. Based on the degree of multifractality, the Chinese and South Korean markets exhibit the least long-range dependence, followed by Pakistan, Indonesia, and Thailand. On the contrary, the Indian and Malaysian stock markets are found to have the highest level of dependence. This evidence could be related to possible market inefficiencies, implying the possibility of institutional investors using active trading strategies in order to make their portfolios more profitable.

scholarly journals MONA LISA: THE STOCHASTIC VIEW AND FRACTALITY IN COLOR SPACE

2008 ◽  
Vol 19 (06) ◽  
pp. 855-866 ◽  
Author(s):  
POURIA PEDRAM ◽  
G. R. JAFARI
Keyword(s):  
Stochastic Process ◽  
Long Range ◽  
Detrended Fluctuation Analysis ◽  
Color Space ◽  
Statistical Properties ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Mona Lisa ◽  
Artistic Works ◽  
Detrended Fluctuation

A painting consists of objects which are arranged in specific ways. The art of painting is drawing the objects, which can be considered as known trends, in an expressive manner. Detrended methods are suitable for characterizing the artistic works of the painter by eliminating trends. It means that the study of paintings, regardless of its apparent purpose, as a stochastic process. Multifractal detrended fluctuation analysis is applied to characterize the statistical properties of Mona Lisa, as an instance, to exhibit the fractality of the painting. The results show that Mona Lisa is a long-range correlated and almost behaves similar in various scales.

Quantifying Fractal Dynamics of Metallogenic Systems with Detrended Fluctuation Analysis

2012 ◽  
Vol 249-250 ◽  
pp. 26-30 ◽  
Author(s):  
Li Wan ◽  
Peng Chen ◽  
Zhao Xian Gong
Keyword(s):  
Long Range ◽  
Scale Invariance ◽  
Detrended Fluctuation Analysis ◽  
Dynamic Mechanism ◽  
Fluctuation Analysis ◽  
Fractional Dynamics ◽  
Scaling Exponents ◽  
Range Correlation ◽  
Detrended Fluctuation

In this paper, we analysed fractional dynamics behavior in metallogenic elements grade series, using detrended fluctuation analysis (DFA), with the objective to explore and understand the underlying dynamic mechanism. Our results show that the metallogenic elements grade series are the scale invariance and the long-range correlation. As in the case of element grade dynamics, the DFA scaling exponents can be used to discriminate mineral intensity.

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