Study Of Long-range Correlations Research Articles

MFDFA: Efficient multifractal detrended fluctuation analysis in python

Multifractal detrended fluctuation analysis (MFDFA) has become a central method to characterise the variability and uncertainty in empiric time series. Extracting the fluctuations on different temporal scales allows quantifying the strength and correlations in the underlying stochastic properties, their scaling behaviour, as well as the level of fractality. Several extensions to the fundamental method have been developed over the years, vastly enhancing the applicability of MFDFA, e.g. empirical mode decomposition for the study of long-range correlations and persistence. In this article we introduce an efficient, easy-to-use python library for MFDFA, incorporating the most common extensions and harnessing the most of multi-threaded processing for very fast calculations.

Magnetic turbulence and long-range correlation studies in the GOLEM tokamak

The small university-scale tokamak GOLEM equipped with the electric and magnetic probes becomes a test bench for studying the plasma turbulence and Zonal Flows, which are the essential processes affecting the plasma confinement. The broadband (f BB < 250 kHz) magnetic turbulence was detected for the first time using the Mirnov probes. The two-dimensional (frequency–wavelength) Fourier power spectra S(k, f) of the magnetic turbulence indicate the turbulence poloidal propagation. The long-range correlations (LRC) between the signals of magnetic and electric probes installed at different toroidal cross-sections were detected in the low-frequency range (f LRC < 60 kHz), which is similar to the plasma potential LRC range observed in other devices.

Long-range correlation studies in deep earthquakes global series

In the present paper we have conducted studies on seismological properties using worldwide data of deep earthquakes (depth larger than 70 km), considering events with magnitude greater than or equal to 4.5. This work is an extension of a previous study using a similar approach, for shallow events. We have addressed the problem under the perspective of complex networks, using a time window model to build the networks for deep earthquakes. These networks present scale-free and small-world features, contributing to strengthen the use of the time window model to construct epicenters networks. The results for deep events were analyzed using Nonextensive Statistical Mechanics and they corroborate with those found for the shallow ones, since the connectivity distribution for deep earthquakes also follows a q-exponential distribution and the scaling behavior is present. Our findings reinforce the idea of long-range correlations between earthquakes and the criticality of the seismological system.

A Modified Fluctuation Analysis of Nonstationary Processes

We consider a method of detrended fluctuation analysis (DFA method), which enables the study of long-range correlations in nonstationary processes. Its modification is proposed, including the calculation of additional quantity, that is, a scaling index, characterizing the effects of nonstationarity in the experimental data. Using the dynamics of the blood flow velocity in cerebral vessels as an example, the possibilities of a quantitative description of changes in the signal structure using the proposed modification of the DFA method have been demonstrated.

Monte-Carlo study of long-range correlations of average transverse momentum and multiplicity for strange particles in pp-collisions at the LHC energies

This study is motivated by the puzzling enhanced production of multi-strange hadrons observed for the first time by the ALICE Collaboration in high-multiplicity pp-collisions at at the LHC. We investigate this effect of strangeness enhancement in pp-collisions in the framework of the MC event generator PYTHIA 8 where the collectivity processes are taken into account by the formation of a so-called flavour rope. The latter is hadronized with a larger effective string tension providing the increase of strangeness yield. This concept of the flavour rope, as a source of multi-strange hadrons, extended in rapidity, is being tested by the study of so called long-range correlations (LRC) between the average transverse momentum 〈pT〉 and multiplicity n for charged particles containing strange quarks produced in high energy pp-collisions.The dependencies of correlation coefficients bn−n, bPT−n and bPT−PT on the gap between forward and backward pseudorapidity windows, and on the width of the forward pseudorapidity windows, are studied and the results are discussed.

Measuring Long-Range 13C–13C Correlations on a Surface under Natural Abundance Using Dynamic Nuclear Polarization-Enhanced Solid-State Nuclear Magnetic Resonance

We report that spatial (<1 nm) proximity between different molecules in solid bulk materials and, for the first time, different moieties on the surface of a catalyst, can be established without isotope enrichment by means of homonuclear CHHC solid-state nuclear magnetic resonance experiment. This 13C–13C correlation measurement, which hitherto was not possible for natural-abundance solids, was enabled by the use of dynamic nuclear polarization. Importantly, it allows the study of long-range correlations in a variety of materials with high resolution.

Isotope effect physics, turbulence and long-range correlation studies in the TJ-II stellarator

The impact of isotope mass on the radial correlation length () and long-range correlation (LRC) of plasma turbulence has been investigated in electron cyclotron resonance heated (ECRH) low-density deuterium-hydrogen plasmas in the TJ-II stellarator. We find that the increases with the deuterium/hydrogen (D/H) ratio. However, the amplitude of LRC decreases slightly with the D/H ratio, in contrast to previous results in tokamak plasmas Xu et al (2013 Phys. Rev. Lett. 110 265005). These findings show the impact of the isotope effect on both the largest scales (LRC determined by the size of the device) and the characteristic radial scale of turbulent structures.

Recent highlights from the PHENIX heavy ion program

It is accepted that a QGP can be formed in relativistic collisions of heavy nuclei (A+A). Recently long-range correlations have been observed in p+A collisions at the LHC in high multiplicity events. PHENIX has carried out a series of studies of d+Au collisions at 200 GeV to see if such correlations persist at lower energies compared to those at the LHC. Results of a study of long-range correlations and flow are presented for d+Au collisions. Data from Au+Au collisions collected during the beam energy scan (BES) was used to determine both quark and nucleon number scaling. The HBT method was used to determine radii of the fireball at kinetic freezeout. Implications for the nuclear EOS are discussed. Also results of a search for “dark photons” are presented. Recent PHENIX highlights on heavy flavor, electromagnetic probes, spin and plans for PHENIX upgrades were presented in other talks at this conference.

Recent highlights from the PHENIX heavy ion program

It is accepted that a QGP can be formed in relativistic collisions of heavy nuclei (A+A). Recently long-range correlations have been observed in p+A collisions at the LHC in high multiplicity events. PHENIX has carried out a series of studies of d+Au collisions at 200 GeV to see if such correlations persist at lower energies compared to those at the LHC. Results of a study of long-range correlations and flow are presented for d+Au collisions. Data from Au+Au collisions collected during the beam energy scan (BES) was used to determine both quark and nucleon number scaling. The HBT method was used to determine radii of the fireball at kinetic freezeout. Implications for the nuclear EOS are discussed. Also results of a search for “dark photons” are presented. Recent PHENIX highlights on heavy flavor, electromagnetic probes, spin and plans for PHENIX upgrades were presented in other talks at this conference.

MULTI-PARTICLE PRODUCTION OF HADRONS

The phenomenology of multi-particle production of hadrons is reviewed, with emphasis on the results at the Large Hadron Collider (LHC): the first part of the review focuses on the basic kinematic measurements of charged tracks and identified hadrons in minimum bias interactions; the second part reports the short- and long-range correlation studies; the third part concentrates on the underlying event phenomenology in different final states; the fourth part, which constitutes a bottom line on the phenomenology of multiple parton interactions, considers the consequences of multiple hard-scatterings in a single hadron–hadron collisions. Some relevant highlights from the heavy ion program are also discussed.

Soft QCD results from the CMS experiment

The CMS soft QCD results in proton-proton collisions at different LHC centre-of-mass energies are reviewed. The first part of the review focuses on the basic kinematic measurements of charged tracks and identified hadrons in minimum bias proton-proton interactions. The second part reports the short- and long-range correlation studies with emphasis on the results exploiting a special trigger specifically developed for large multiplicity events. The third part concentrates on the underlying event phenomenology in jet and Drell-Yan events. Some relevant highlights from the CMS heavy ion program are also discussed.

Evolution towards ergodic behavior of stationary fractal random processes with memory: application to the study of long-range correlations of nucleotide sequences in DNA

The possible occurrence of ergodic behavior for large times is investigated in the case of stationary random processes with memory. It is shown that for finite times the time average of a state function is generally a random variable and thus two types of cumulants can be introduced: for the time average and for the statistical ensemble, respectively. In the limit of infinite time a transition from the random to the deterministic behavior of the time average may occur, resulting in an ergodic behavior. The conditions of occurrence of this transition are investigated by analyzing the scaling behavior of the cumulants of the time average. A general approach for the computation of these cumulants is developed; explicit computations are presented both for short and long memory in the particular case of separable stationary processes for which the cumulants of a statistical ensemble can be factorized into products of functions depending on binary time differences. In both cases the ergodic behavior emerges for large times provided that the cumulants of a statistical ensemble decrease to zero as the time differences increase to infinity. The analysis leads to the surprising conclusion that the scaling behavior of the cumulants of the time average is relatively insensitive to the type of memory considered: both for short and long memory the cumulants of the time average obey inverse different from zero for large time differences, then the time averaage is random even as the length of the total time interval tends to infinity and the ergodic behavior no longer holds. The theory is applied to the study of long range correlations of nucleotide sequences in DNA; in this case the length t of a sequence of nucleotides plays the role of the time variable. A proportionality relationship is established between the cumulants of the pyrimidine excess in a sequence of length t and the cumulants of the time (length) average of the probability of occurrence of a pyrimidine. It is shown that the statistical analysis of the DNA data presented in the literature is consistent with the occurrence of the ergodic behavior for large lengths. The implications of the approach to the analysis of the large time behavior of stochastic cellular automata and of fractional Brownian motion are also investigated.

Study of long-range correlations in PC binary files

We employ fractal techniques to investigate long-range correlations in some commonly-used PC binary files. We find that strong long-range correlations exist in most of those files and argue that traditional models of information theory are not appropriate for calculating the information content of computer files in the real world.