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  Partner: UNT College of Arts and Sciences
 Department: Center for Nonlinear Science
Mega et al. Reply

Mega et al. Reply

Date: March 26, 2004
Creator: Mega, Mirko S.; Allegrini, Paolo; Grigolini, Paolo; Latora, Vito; Palatella, Luigi; Rapisarda, Andrea et al
Description: This article is a reply to a comment by A. Helmstetter and D. Sornette about the article 'Power-Law Time Distribution of Large Earthquakes' from 2003.
Contributing Partner: UNT College of Arts and Sciences
Memory Beyond Memory in Heart Beating, a Sign of a Healthy Physiological Condition

Memory Beyond Memory in Heart Beating, a Sign of a Healthy Physiological Condition

Date: April 11, 2002
Creator: Allegrini, Paolo; Grigolini, Paolo; Hamilton, P.; Palatella, Luigi & Raffaelli, G.
Description: This article discusses memory beyond memory in heart beating. Abstract: We describe two types of memory and illustrate each using artificial and actual heartbeat data sets. The first type of memory, yielding anomalous diffusion, implies the inverse power-law nature of the waiting time distribution and the second the correlation among distinct times, and consequently also the occurrence of many pseudoevents, namely, not genuinely random events. Using the method of diffusion entropy analysis, we establish the scaling that would be determined by the real events alone. We prove that the heart beating of healthy patients reveals the existence of many more pseudoevents than in the patients with congestive heart failure.
Contributing Partner: UNT College of Arts and Sciences
Memory Effects in Fractional Brownian Motion with Hurst Exponent H<1/3

Memory Effects in Fractional Brownian Motion with Hurst Exponent H<1/3

Date: August 27, 2010
Creator: Bologna, Mauro; Vanni, Fabio; Krokhin, Arkadii A. & Grigolini, Paolo
Description: This article discusses memory effects in fractional Brownian motion with Hurst exponent H<1/3. Abstract: We study the regression to the origin of a walker driven by dynamically generated fractional Brownian motion (FBM) and we prove that when the FBM scaling, i.e., the Hurst exponent H<1/3, the emerging inverse power law is characterized by a power index that is a compelling signature of the infinitely extended memory of the system. Strong memory effects leads to the relation H=θ/2 between the Hurst exponent and the persistent exponent θ, which is different from the widely used relation H=1 - θ. The latter is valid for 1/3<H<1 and is known to be compatible with the renewal assumption.
Contributing Partner: UNT College of Arts and Sciences
Networking of psychophysics, psychology, and neurophysiology

Networking of psychophysics, psychology, and neurophysiology

Date: November 5, 2012
Creator: West, Bruce J. & Grigolini, Paolo
Description: This article focuses on dynamic networking and dynamic networks in complex research on psychophysics, psychology, and neurophysiology. It states that new ways were suggested by dynamic networking and dynamic networks to transfer information utilizing the long-distance communication through local cooperative interaction. It says that the fluctuations in brain and social dynamics reveal the emergence of complex behavior when analyzed with advanced methods of fractal statistical analysis.
Contributing Partner: UNT College of Arts and Sciences
Noise-induced transition from anomalous to ordinary diffusion: The crossover time as a function of noise intensity

Noise-induced transition from anomalous to ordinary diffusion: The crossover time as a function of noise intensity

Date: December 1995
Creator: Floriani, Elena; Grigolini, Paolo & Mannella, Riccardo
Description: This article discusses noise-induced transition from anomalous to ordinary diffusion and the crossover time as a function of noise intensity. Abstract: We study the interplay between a deterministic process of weak chaos, responsible for the anomalous diffusion of a variable x, and a white noise of intensity ≡. The deterministic process of anomalous diffusion results from the correlated fluctuations of a statistical variable ξ between two distinct values +1 and -1, each of them characterized by the same waiting time distribution ψ(t), given by ψ(t)≃ t(-μ) with 2 < μ < 3, in the long-time limit. We prove that under the influence of a weak white noise of intensity ≡, the process of anomalous diffusion becomes normal at a time t(c) given by t(c) ~ 1/≡(β)(μ). Here β(μ) is a function of μ which depends on the dynamical generator of the waiting-time distribution ψ(t). We derive an explicit expression for β(μ) in the case of two dynamical systems, a one-dimensional superdiffusive map and the standard map in the accelerating state. The theoretical prediction is supported by numerical calculations.
Contributing Partner: UNT College of Arts and Sciences
Non-Gaussian statistics of anomalous diffusion: The DNA sequences of prokaryotes

Non-Gaussian statistics of anomalous diffusion: The DNA sequences of prokaryotes

Date: September 1998
Creator: Allegrini, Paolo; Buiatti, Marco, 1972-; Grigolini, Paolo & West, Bruce J.
Description: This article discusses non-Gaussian statistics of anomalous diffusion. Abstract: We adopt a non-Gaussian indicator to measure the deviation from Gaussian statistics of a diffusion process generated by dichotomous fluctuations with infinite memory. We also make analytical predictions on the transient behavior of the non-Gaussian indicator as well as on its stationary value. We then apply this non-Gaussian analysis to the DNA sequences of prokaryotes adopting a theoretical model where the "DNA dynamics" are assumed to be determined by the statistical superposition of two independent generators of fluctuations: a generator of fluctuations with no correlation and a generator of fluctuations with infinite correlation "time". We study also the influence that the finite length of the observed sequences has on the short-range fluctuation and sequence truncation. Nevertheless, under proper conditions, fulfilled by all the DNA sequences of prokaryotes that have been examined, a non-Gaussian signature remains to signal the correlated nature of the driving process.
Contributing Partner: UNT College of Arts and Sciences
Non-Markovian Nonstationary Completely Positive Open-Quantum-System Dynamics

Non-Markovian Nonstationary Completely Positive Open-Quantum-System Dynamics

Date: August 4, 2009
Creator: Budini, Adrián A. & Grigolini, Paolo
Description: This article discusses non-Markovian nonstationary completely positive open-quantum-system dynamics. Abstract: By modeling the interaction of a system with an environment through a renewal approach, we demonstrate that completely positive non-Markovian dynamics may develop some unexplored nonstandard statistical properties. The renewal approach is defined by a set of disruptive events, consisting in the action of a completely positive superoperator over the system density matrix. The random time intervals between events are described by an arbitrary waiting-time distribution. We show that, in contrast to the Markovian case, if one performs a system preparation (measurement) at an arbitrary time, the subsequent evolution of the density-matrix evolution is modified. The nonstationary character refers to the absence of an asymptotic master equation even when the preparation is performed at arbitrary long times. In spite of this property, we demonstrate that operator expectation values and operators correlations have the same dynamical structure, establishing the validity of a nonstationary quantum regression hypothesis. The nonstationary property of the dynamics is also analyzed through the response of the system to an external weak perturbation.
Contributing Partner: UNT College of Arts and Sciences
Non-Poisson Dichotomous Noise: Higher-Order Correlation Functions and Aging

Non-Poisson Dichotomous Noise: Higher-Order Correlation Functions and Aging

Date: October 26, 2004
Creator: Allegrini, Paolo; Grigolini, Paolo; Palatella, Luigi & West, Bruce J.
Description: This article discusses non-Poisson dichotomous noise and higher-order correlation functions and aging. Abstract: We study a two-state symmetric noise, with a given waiting time distribution ψ(τ), and focus our attention on the connection between the four-time and two-time correlation functions. The transition of ψ(τ) from the exponential to the nonexponential condition yields the breakdown of the usual factorization condition of high-order correlation functions, as well as the birth of aging effects. We discuss the subtle connections between these two properties and establish the condition that the Liouville-like approach has to satisfy in order to produce a correct description of the resulting diffusion process.
Contributing Partner: UNT College of Arts and Sciences
Non-Poisson distribution of the time distances between two consecutive clusters of earthquakes

Non-Poisson distribution of the time distances between two consecutive clusters of earthquakes

Date: 2004
Creator: Palatella, Luigi; Allegrini, Paolo; Grigolini, Paolo; Latora, Vito; Mega, Mirko S.; Rapisarda, Andrea et al
Description: This article discusses non-Poisson distribution of the time distances between two consecutive clusters of earthquakes. Abstract: With the help of the Diffusion Entropy technique the authors show the non-Poisson statistics of the distances between consecutive Omori's swarms of earthquakes. The authors give an analytical proof of the numerical results of an earlier paper [Mega et al., Phys. Rev. Lett. 90 (2003) 188501].
Contributing Partner: UNT College of Arts and Sciences
Power-Law Time Distribution of Large Earthquakes

Power-Law Time Distribution of Large Earthquakes

Date: May 2003
Creator: Mega, Mirko S.; Allegrini, Paolo; Grigolini, Paolo; Latora, Vito; Palatella, Luigi; Rapisarda, Andrea et al
Description: In this article, the authors study the statistical properties of time distribution of seismicity in California by means of a new method of analysis, the diffusion entropy. The authors find that the distribution of time intervals between a large earthquake (the main shock of a given seismic sequence) and the next one does not obey Poisson statistics, as assumed by the current models. The authors prove that this distribution is an inverse power law with an exponent μ = 2.06 ± 0.01. The authors propose the long-range model, reproducing the main properties of the diffusion entropy and describing the seismic triggering mechanisms induced by large earthquakes.
Contributing Partner: UNT College of Arts and Sciences