Search for critical point indications in long-range correlations by energy and system size scanning in string fusion approach

2016 ◽  
Author(s):  
V. N. Kovalenko ◽  
V. V. Vechernin
Keyword(s):  
Critical Point ◽  
Long Range ◽  
System Size ◽  
Long Range Correlations ◽  
Fusion Approach

scholarly journals Patterns and Long Range Correlations in Idealized Granular Flows

1997 ◽  
Vol 08 (04) ◽  
pp. 953-965 ◽  
Author(s):  
J. A. G. Orza ◽  
R. Brito ◽  
T. P. C. van Noije ◽  
M. H. Ernst
Keyword(s):  
Long Range ◽  
Size Effects ◽  
Hard Spheres ◽  
Finite Size ◽  
System Size ◽  
Spatial Correlations ◽  
Finite Size Effects ◽  
Long Range Correlations ◽  
Intrinsic Length ◽  
Dynamics Simulations

An initially homogeneous freely evolving fluid of inelastic hard spheres develops inhomogeneities in the flow field u(r, t) (vortices) and in the density field n (r, t)(clusters), driven by unstable fluctuations, δa = {δn, δu}. Their spatial correlations, <δa(r, t)δa(r′,t)>, as measured in molecular dynamics simulations, exhibit long range correlations; the mean vortex diameter grows as [Formula: see text]; there occur transitions to macroscopic shearing states, etc. The Cahn–Hilliard theory of spinodal decomposition offers a qualitative understanding and quantitative estimates of the observed phenomena. When intrinsic length scales are of the order of the system size, effects of physical boundaries and periodic boundaries (finite size effects in simulations) are important.

scholarly journals Studies of charm and beauty hadron long-range correlations in pp and pPb collisions at LHC energies

2021 ◽  
Vol 813 ◽  
pp. 136036
Author(s):  
A.M. Sirunyan ◽  
A. Tumasyan ◽  
W. Adam ◽  
F. Ambrogi ◽  
T. Bergauer ◽  
...  
Keyword(s):  
Long Range ◽  
Long Range Correlations

scholarly journals Long-range correlations in pinned athermal networks

2021 ◽  
Vol 104 (1) ◽  
Author(s):  
Debankur Das ◽  
Pappu Acharya ◽  
Kabir Ramola
Keyword(s):  
Long Range ◽  
Long Range Correlations

LONG-RANGE CORRELATIONS IN THE PHASE-SHIFTS OF NUMERICAL SIMULATIONS OF BIOCHEMICAL OSCILLATIONS AND IN EXPERIMENTAL CARDIAC RHYTHMS

1999 ◽  
Vol 07 (02) ◽  
pp. 113-130 ◽  
Author(s):  
I. M. DE LA FUENTE ◽  
L. MARTINEZ ◽  
J. M. AGUIRREGABIRIA ◽  
J. VEGUILLAS ◽  
M. IRIARTE
Keyword(s):  
Phase Shift ◽  
Periodic Solutions ◽  
Long Range ◽  
Phase Shifts ◽  
Long Range Correlations ◽  
Rescaled Range ◽  
Biochemical Oscillations ◽  
Phase Shift Data ◽  
Relationship Of ◽  
The Relationship

In biochemical dynamical systems during each transition between periodical behaviors, all metabolic intermediaries of the system oscillate with the same frequency but with different phase-shifts. We have studied the behavior of phase-shift records obtained from random transitions between periodic solutions of a biochemical dynamical system. The phase-shift data were analyzed by means of Hurst's rescaled range method (introduced by Mandelbrot and Wallis). The results show the existence of persistent behavior: each value of the phase-shift depends not only on the recent transitions, but also on previous ones. In this paper, the different kind of periodic solutions were determined by different small values of the control parameter. It was assessed the significance of this results through extensive Monte Carlo simulations as well as quantifying the long-range correlations. We have also applied this type of analysis on cardiac rhythms, showing a clear persistent behavior. The relationship of the results with the cellular persistence phenomena conditioned by the past, widely evidenced in experimental observations, is discussed.

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