Temporal variations of long-term correlations in seismic activity fluctuations

The scaling behavior of the 1998-2009 seismicity in Guerrero, southern Mexico, was studied by means of the detrended fluctuation analysis (DFA). We found that inter-seismic periods are correlated with a transition in the scaling behavior at about 200 seismic events. Correlations are relatively weak for small time scales. However, for large time scales, correlations are associated with a 1/f fractional process, indicating that the seismicity pattern emerges from a self-organized critical state. Temporal variations of the scaling exponent along years computed from the DFA indicate the presence of a quasi-biennial cycle in the seismicity correlations. This cyclic behavior was apparently triggered by the large 2001-2002 slow slip event in the Guerrero seismic gap. Besides, the significant seismic events (M_w>5) originate, on the average, at deeper regions in each cycle.     

Space-magnitude dependent scaling behaviour in seismic interevent series revealed by detrended fluctuation analysis

The scaling behaviour of the 1981-2007 seismicity data in central Italy, which is one of the most seismically active areas in Italy is investigated. In particular we examined the earthquakes located in a circular area centred on the epicentre of the strongest event, occurred in September 26, 1997 (duration magnitude M_D=5.8). On the base of the detrended fluctuation analysis (DFA), we found that in the magnitude range between 2.5 and 2.9 the scaling exponents fall into disjoint sets for events relatively close and far from the epicentre of the strongest event.     

Detecting long-range correlations in fire sequences with Detrended fluctuation analysis

The spatial-temporal power-law distributions are found in many natural systems, which have self-similarity and fractal behavior. By analyzing the time series of such systems, we could expect to explore and understand the underlying mechanisms. In this paper, the Detrended fluctuation analysis (DFA) is used to analyze the long-range correlations of forest and urban fires in Japan and China. It is found that the interevent time series of both forest and urban fires have the persistent long-range power-law correlations, and they all have two scaling exponents, α₁ and α₂, which are both bigger than 0.5 and smaller than 1.0, despite the different regions and countries. For forest fires, 0.61<α₁<0.73,0.87<α₂<0.98 and for urban fires, 0.52<α₁<0.61,0.59<α₂<0.88. The result suggests that fires have self-similarity characteristics. The occurrence of forest fires may have connection with the weather fluctuations, which have significant effects on the ignition and have the similar temporal correlations. It is shown that the interval sequences of urban fires closely resemble that of white noise in small timescale, and the correlations are weaker than that of forest fires. Human behavior and human density may affect the long-range correlation in some way. This seems to be helpful to understand the complexity of fire system in temporal aspect.     

Long-range correlations and generic scale invariance in classical fluids and disordered electron systems

Long-ranged, or power-law, behavior of correlation functions in both space and time is discussed for classical systems and for quantum systems at finite temperature, and is compared with the corresponding behavior in quantum systems at zero temperature. The origin of the long-ranged correlations is explained in terms of soft modes. In general, correlations at zero temperature are of longer range than their finite-temperature or classical counterparts. This phenomenon is due to additional soft modes that exist at zero temperature.     

Multibin long-range correlations

A new method to study the long-range correlations in multiparticle production is developed. It is proposed to measure the joint factorial moments or cumulants of multiplicity distribution in several (more than two) bins. It is shown that this step dramatically increases the discriminative power of data.     

Hydrodynamics and long range correlations

It is shown that the recently proposed method of studying the long-range correlations in multiparticle production can be effectively used to verify the hydrodynamic nature of the longitudinal expansion of the partonic system created in the collision. The case of ALICE detector is explicitly considered.     

Long-range correlations in kinetic theory

It is shown that macroscopic correlations in a fluid are conserved for macroscopically long times. The equations of conservation can be written in a form independent of the density of the fluid and are therefore valid for a liquid as well as for a gas. The possibility of developing a kinetic theory of turbulence on the basis of these equations (along the lines of V. N. Zhigulev and of S. Tsugé) is indicated.The contents of this paper formed part of the Ph.D. thesis submitted by the author under the supervision of Prof. Harold Grad to the Department of Mathematics, New York University and issued as NYU-Courant Institute of Mathematical Sciences Technical Report MF-72, October 1973.     

Hidden asymmetry and long range rapidity correlations

Interpretation of long-range rapidity correlations in terms of the fluctuating rapidity density distribution of the system created in high-energy collisions is proposed. When applied to recent data of the STAR Collaboration, it shows a substantial asymmetric component in the shape of this system in central Au–Au collisions, implying that boost invariance is violated on the event-by-event basis even at central rapidity. This effect may seriously influence the hydrodynamic expansion of the system.     

Long-range dependence in tree-ring width time series of Austrocedrus Chilensis revealed by means of the detrended fluctuation analysis

By using the detrended fluctuation analysis and detrended moving average method, 823 time series of tree-ring widths in Austrocedrus Chilensis in Patagonia were analyzed. The tree-ring widths of A. Chilensis have been widely used for climatological studies. The results point out to the presence of significant scaling in the temporal fluctuations of tree-ring, which is not due to singular probability density function of the widths but due to the presence of long-range correlations. Such results are in good agreement with those concerning the evidence of long-range dependencies in weather time series.     

Non-uniform scaling behavior in ultra-low-frequency (ULF) earthquake-related geomagnetic signals

Investigating highly non-stationary time series, which typically exhibit long-range correlations, is a classic problem in physics. Here, we analyze the scaling properties of the dynamics of ultra-low-frequency (ULF) geomagnetic data (in the frequency range between 1 mHz and 10 Hz) observed at Izu Peninsula in Japan. On the basis of the detrended fluctuation analysis (DFA), deviations from uniform power-law scaling were quantified. Our findings point out to a significant non-uniform scaling behavior in ULF geomagnetic data in relationship with the occurrence of intense seismic clusters.     

Long-term correlations in hourly wind speed records in Pernambuco, Brazil

We study the statistical properties of hourly wind speed time series detected at four weather stations in the state of Pernambuco, Brazil, in the period 2008-2009. We find that the average and maximum hourly wind speeds deviate from a mutual linear relationship, and that they may be well explained individually by a Weibull distribution, however, with different shape parameter values. On the other hand, the long-term correlations of both of these observables obey the same power-law behavior, with two distinct scaling regimes. Our results agree with previous studies on wind speed series correlations in other regions of the world, which is suggestive of universal behavior.     

Strong anticipation: Sensitivity to long-range correlations in synchronization behavior

Strong anticipation has emerged as a new framework for studying prospective control. According to earlier theories of prediction, anticipatory behavior rests on temporally local predictions from internal models. Strong anticipation eschews internal models and draws on the embedding of an organism in its environment. In this formulation, behavior is sensitive to the non-local temporal structure of the environment. We present initial evidence for strong anticipation in a synchronization task with tapping as the behavior. Participants were instructed to synchronize, to the best of their abilities, with a (unpredictable) chaotic signal. Our data suggest a close relationship between the long-range correlations of the chaotic signal and the long-range correlations of the synchronization behavior.     

Analysis of temporal fluctuations in Bach’s sinfonias

The correlation structures in 15 Bach’s sinfonias were analyzed. Each sinfonia is characterized by the superposition of three voices. Each voice is a sequence of pitches. Each voice was transformed in a time series, in which the sampling time was given by the smallest pitch duration in that voice. The scaling properties of the three voices of each sinfonia was quantified by means of the estimate of the scaling exponent, performed using the power spectral density (PSD) and the detrended fluctuation analysis (DFA). The results show that the voice time series are persistent. The DFA was applied not only to any single voice time series, but also to couples (2-DFA) of voices and to the triple (3-DFA) of voices. It was found that the first voice of each sinfonia modulates the scaling behavior of the whole sinfonia.     

毫米波辐照下大鼠脑电的长程相关性

通过脑电长程相关性的分析,定量研究了35 GHz毫米波辐照大鼠时产生的应激反应。通过退趋势分析法,得到反映高频成分的标度指数,显示在辐照前该成分具有布朗噪声的特性,辐照时具有长程相关性;而反映低频成分的标度指数显示在辐照前该成分具有长程相关性,辐照时成为布朗噪声。引进应激指标参量低频成份标度指标数/高频成份标度指标数,用其值的平均变化率来衡量大鼠在35 GHz毫米波作用下应激反应的剧烈程度。通过计算得到辐照时应激指标参量增加了49.9%±13.6%,说明35 GHz毫米波辐照使得大鼠脑电的高频部分变得更加有序,而低频成分变得更加无序,表明大鼠受35 GHz毫米波辐照而产生了剧烈应激反应。     

毫米波辐照下大鼠脑电的长程相关性

通过脑电长程相关性的分析,定量研究了35 GHz毫米波辐照大鼠时产生的应激反应.通过退趋势分析法,得到反映高频成分的标度指数.显示在辐照前该成分具有布朗噪声的特性,辐照时具有长程相关性;而反映低频成分的标度指数显示在辐照前该成分具有长程相关性,辐照时成为布朗噪声.引进应激指标参量低频成份标度指标数/高频成份标度指标数,...     

Long-range correlations and charge transport properties of DNA sequences

By using Hurst's analysis and transfer approach, the rescaled range functions and Hurst exponents of human chromosome 22 and enterobacteria phage lambda DNA sequences are investigated and the transmission coefficients, Landauer resistances and Lyapunov coefficients of finite segments based on above genomic DNA sequences are calculated. In a comparison with quasiperiodic and random artificial DNA sequences, we find that λ-DNA exhibits anticorrelation behavior characterized by a Hurst exponent 0.5<H<1 while, as far as the segments selected in our Letter are concerned, Ch22 sequence displays a transition from correlation behavior to anticorrelation behavior. The resonant peaks of the transmission coefficient in genomic sequences can survive in longer sequence length than in random sequences but in shorter sequence length than in quasiperiodic sequences. It is shown that the genomic sequences have long-range correlation properties to some extent but the correlations are not strong enough to maintain the scale invariance properties.     

Decay of correlations in classical fluids with long-range forces

We show with simple arguments that, as a consequence of the Poisson equation, the correlations of a charged system at equilibrium decay faster than any inverse power, if they are integrable and monotonous at infinity. For all other longrange systems (with potential(x)b¦x¦^–s , ¦x¦ , 0v,s} 2), the decay is bounded below by an inverse power.Partially supported by the Swiss National Foundation for Scientific Research.     

Scaling analysis of phase fluctuations in experimental three-phase flows

The characterization of complex patterns arising from three-phase (e.g., oil-gas-water) flows is an important problem with significant engineering and industrial applications. Based solely on measured conductance fluctuation signals from experimental three-phase flows, we propose a method to characterize and distinguish three commonly observed flow patterns. Using the phase characterization method, we first calculate the instantaneous phase from the signals. Then, through performing a scaling analysis, detrended fluctuation analysis (DFA), we extract scaling behaviors associated with the phase fluctuations and find that the DFA scaling exponent is sensitive to the transition among different flow patterns, which can be used to characterize nonlinear dynamics of the three-phase flow. From a novel perspective, we investigate the three-phase flow in terms of phase characterization and scaling analysis. The results indicate that our method can provide new insights into the exploration of complex mechanism in flow pattern transition. The effectiveness of the method is demonstrated and its broader applicability is articulated.     

Non-linear characteristics and long-range correlations in Asian stock markets

We test several non-linear characteristics of Asian stock markets, which indicates the failure of efficient market hypothesis and shows the essence of fractal of the financial markets. In addition, by using the method of detrended fluctuation analysis (DFA) to investigate the long range correlation of the volatility in the stock markets, we find that the crossover phenomena exist in the results of DFA. Further, in the region of small volatility, the scaling behavior is more complicated; in the region of large volatility, the scaling exponent is close to 0.5, which suggests the market is more efficient. All these results may indicate the possibility of characteristic multifractal scaling behaviors of the financial markets.     

Detecting long-range correlations in time series of neuronal discharges

We have studied the discharge dynamics of dorsal horn neurons (DHN) by applying the detrended fluctuation analysis (DFA) and the wavelet transform (WT) technique. We have adopted that discharge dynamics is manifested by the random time series of the interspike intervals (ISI), that is, by intervals between two consecutive neuronal electrical activities. In all cases studied, we found two different power-law type behaviors across ISI enumeration scale, that are separated by a crossover region. Our results reveal that complex neuronal dynamics may change in the presence of external stimulation, which is manifested by changing the noise characteristics that appear before the crossover region (the noise after the crossover region is of the 1/f type).