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We propose a new method to analyze fluctuations in the strength function phenomena in highly excited nuclei. Extending the method of multifractal analysis to the cases where the strength fluctuations do not obey power scaling laws, we…

核理论 · 物理学 2009-10-31 Hirokazu Aiba , Masayuki Matsuo

Continuous wavelet transform (CWT) based time-scale and multi-fractal analyses have been carried out on the anode glow related nonlinear floating potential fluctuations in a hollow cathode glow discharge plasma. CWT has been used to obtain…

等离子体物理 · 物理学 2010-03-17 Md. Nurujjaman , Ramesh Narayanan , A. N. Sekar Iyengar

The fluctuation scaling law has universally been observed in a wide variety of phenomena. For counting processes describing the number of events occurred during time intervals, it is expressed as a power function relationship between the…

数据分析、统计与概率 · 物理学 2013-07-01 Shinsuke Koyama

Most data processing techniques, applied to biomedical and sociological time series, are only valid for random fluctuations that are stationary in time. Unfortunately, these data are often non stationary and the use of techniques of…

数据分析、统计与概率 · 物理学 2009-11-10 M. Ignaccolo , P. Allegrini , P. Grigolini , P. Hamilton , B. J. West

We probe flows of soft, viscous spheres near the jamming point, which acts as a critical point for static soft spheres. Starting from energy considerations, we find nontrivial scaling of velocity fluctuations with strain rate. Combining…

软凝聚态物质 · 物理学 2015-03-13 Brian P. Tighe , Erik Woldhuis , Joris J. C. Remmers , Wim van Saarloos , Martin van Hecke

In the study of complex networks (systems), the scaling phenomenon of flow fluctuations refers to a certain power-law between the mean flux (activity) $<F_i>$ of the $i$th node and its variance $\sigma_i$ as $\sigma_i \propto < F_{i} >…

数据分析、统计与概率 · 物理学 2009-05-08 Yudong Chen , Li Li , Yi Zhang , Jianming Hu

The information on dynamical fluctuations that can be extracted from the anomalous scaling observed recently in hadron-hadron collision experiments is discussed in some detail. A parameter ``effective fluctuation strength'' is proposed to…

高能物理 - 唯象学 · 物理学 2009-10-31 Liu Lianshou , Fu Jinghua , Wu Yuanfang

The multiscale dynamics of glow discharge plasma is analysed through wavelet transform, whose scale dependent variable window size aptly captures both transients and non-stationary periodic behavior. The optimal time-frequency localization…

量子物理 · 物理学 2015-06-18 Bapun K. Giri , Chiranjit Mitra , Prasanta K. Panigrahi , A. N. Sekar Iyengar

Detrended fluctuation analysis (DFA) is a scaling analysis method used to estimate long-range power-law correlation exponents in noisy signals. Many noisy signals in real systems display trends, so that the scaling results obtained from the…

数据分析、统计与概率 · 物理学 2009-11-07 Kun Hu , Plamen Ch. Ivanov , Zhi Chen , Pedro Carpena , H. Eugene Stanley

The rate of metastable decay in nonequilibrium systems is expected to display scaling behavior: i.e., the logarithm of the decay rate should scale as a power of the distance to a bifurcation point where the metastable state disappears.…

统计力学 · 物理学 2009-09-29 Oleg Kogan

Many fluctuating systems consist of macroscopic structures in addition to noisy signals. Thus, for this class of fluctuating systems, the scaling behaviors are very complicated. Such phenomena are quite commonly observed in Nature, ranging…

统计力学 · 物理学 2007-05-23 Ning-Ning Pang , Hisen-Ching Kao , Wen-Jer Tzeng

Long-range temporal and spatial correlations have been reported in a remarkable number of studies. In particular power-law scaling in neural activity raised considerable interest. We here provide a straightforward algorithm not only to…

定量方法 · 定量生物学 2015-12-09 Robert Ton , Andreas Daffertshofer

The detrended cross-correlation coefficient $\rho_{\rm DCCA}$ has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, non-stationary time series. It is based on the detrended…

数据分析、统计与概率 · 物理学 2015-12-09 Jaroslaw Kwapien , Pawel Oswiecimka , Stanislaw Drozdz

We present results of the numerical simulations and the scaling characteristics of one-dimensional random fluctuations with heavy tailed probability distribution functions. Assuming that the distribution function of the random fluctuations…

统计力学 · 物理学 2017-08-16 Mohsen Ghasemi Nezhadhaghighi

Dynamical phase transitions are nonequilibrium counterparts of thermodynamic phase transitions and share many similarities with their equilibrium analogs. In continuous phase transitions, critical exponents play a key role in characterizing…

统计力学 · 物理学 2025-06-09 Timo Schorlepp , Ohad Shpielberg

Characterising the stratosphere as a turbulent system, temporal fluctuations often show different correlations for different time scales as well as intermittent behaviour that cannot be captured by a single scaling exponent. In this study,…

大气与海洋物理 · 物理学 2016-09-28 Gualtiero Badin , Daniela I. V. Domeisen

We present a multifractal analysis of time series data obtained by repeatedly running a single-qubit quantum circuit on IBM superconducting quantum computers, in which the measurement outcomes are recorded as the number of zeros. By…

量子物理 · 物理学 2025-12-23 Mohammadreza Saghafi , Lamine Mili , Karlton Wirsing

In a recent work on fluid infiltration in a Hele-Shaw cell with the pore-block geometry of Sierpinski carpets (SCs), the area filled by the invading fluid was shown to scale as F~t^n, with n<1/2, thus providing a macroscopic realization of…

统计力学 · 物理学 2017-05-24 F. D. A. Aarao Reis

Dynamical universality plays a fundamental role in understanding the scaling properties of critical dynamics, including absorbing phase transitions and physical aging. Although individual universality classes have been extensively studied,…

统计力学 · 物理学 2025-03-10 Rong Li , Qirui Ding , Weicheng Cui

We show that a scaling approach successfully characterizes clustering and intermittency in space and time, in systems of noninteracting particles driven by fluctuating surfaces. We study both the steady state and the approach to it, for…

软凝聚态物质 · 物理学 2019-01-15 Tapas Singha , Mustansir Barma
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