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Paolo Allegrini

Publications and source records attributed to Paolo Allegrini.

16 recordsLinked to original sources
arXiv2006

Response of Complex Systems to Complex Perturbations: the Complexity Matching Effect

The dynamical emergence (and subsequent intermittent breakdown) of collective behavior in complex systems is described as a non-Poisson renewal process, characterized by a waiting-time distribution density $ψ(τ)$ for the time intervals between successively recorded breakdowns. In the intermittent case $ψ(t)\sim t^{-μ}$, with complexity index $μ$. We show that two systems can exchange information through complexity matching and present theoretical and numerical calculations describing a system with complexity index $μ_{S}$ perturbed by a signal with complexity index $μ_{P}$. The analysis focuses on the non-ergodic (non-stationary) case $μ\leq 2$ showing that for $μ_{S}\geq μ_{P}$, the system $S$ statistically inherits the correlation function of the perturbation $P$. The condition $μ_{P}=μ_{S}$ is a resonant maximum for correlation information exchange.

cond-mat.stat-mech↗
arXiv2006

Response of Complex Systems to Complex Perturbations: Complexity Matching

We argue that complex systems, defined as non-Poisson renewal process, with complexity index $μ$, exchange information through complexity matching. We illustrate this property with detailed theoretical and numerical calculations describing a system with complexity index $μ_{S}$ perturbed by a signal with complexity index $μ_{P}$. We focus our attention on the case $1.5 \leq μ_S \leq 2$ and $1 \leq μ_{P} \leq 2$. We show that for $μ_{S} \geq μ_P$, the system S reproduces the perturbation, and the response intensity increases with increasing $μ_P$. The maximum intensity is realized by the matching condition $μ_P = μ_S$. For $μ_{P} > μ_{S}$ the response intensity dies out as $1/t^{μ_P-μ_S}$.

cond-mat.stat-mech↗
arXiv2006

Renewal aging and linear response

We study the linear response to an external perturbation of a renewal process, in an aging condition that, with no perturbation, would yield super-diffusion. We use the phenomenological approach to the linear response adopted in earlier work of other groups, and we find that aging may have the effect of annihilating any sign of coherent response to harmonic perturbation. We also derive the linear response using dynamic arguments and we find a coherent response, although with an intensity dying out very slowly. In the case of a step-like perturbation the dynamic arguments yield in the long-time limit a steady signal whose intensity may be significantly smaller than the phenomenological approach prediction.

cond-mat.stat-mech↗
arXiv2005

Renewal, Modulation and Superstatistics

We consider two different proposals to generate a time series with the same non-Poisson distribution of waiting times, to which we refer to as renewal and modulation. We show that, in spite of the apparent statistical equivalence, the two time series generate different physical effects. Renewal generates aging and anomalous scaling, while modulation yields no aging and either ordinary or anomalous diffusion, according to the prescription used for its generation. We argue, in fact, that the physical realization of modulation involves critical events, responsible for scaling. In conclusion, modulation rather than ruling out the action of critical events, sets the challenge for their identification.

cond-mat.stat-mech↗
arXiv2004

Correlation function and generalized master equation of arbitrary age

We study a two-state statistical process with a non-Poisson distribution of sojourn times. In accordance with earlier work, we find that this process is characterized by aging and we study three different ways to define the correlation function of arbitrary age of the corresponding dichotomous fluctuation based respectively on the Generalized Master Equation formalism, on a Liouville-like approach and on a trajectory perspective.

cond-mat.stat-mech↗
arXiv2003

Cognitive scale-free networks as a model for intermittency in human natural language

We model certain features of human language complexity by means of advanced concepts borrowed from statistical mechanics. Using a time series approach, the diffusion entropy method (DE), we compute the complexity of an Italian corpus of newspapers and magazines. We find that the anomalous scaling index is compatible with a simple dynamical model, a random walk on a complex scale-free network, which is linguistically related to Saussurre's paradigms. The model yields the famous Zipf's law in terms of the generalized central limit theorem.

cond-mat.stat-mech↗
arXiv2003

From Knowledge, Knowability and the Search for Objective Randomness to a New Vision of Complexity

Herein we consider various concepts of entropy as measures of the complexity of phenomena and in so doing encounter a fundamental problem in physics that affects how we understand the nature of reality. In essence the difficulty has to do with our understanding of randomness, irreversibility and unpredictability using physical theory, and these in turn undermine our certainty regarding what we can and what we cannot know about complex phenomena in general. The sources of complexity examined herein appear to be channels for the amplification of naturally occurring randomness in the physical world. Our analysis suggests that when the conditions for the renormalization group apply, this spontaneous randomness, which is not a reflection of our limited knowledge, but a genuine property of nature, does not realize the conventional thermodynamic state, and a new condition, intermediate between the dynamic and the thermodynamic state, emerges. We argue that with this vision of complexity, life, which with ordinary statistical mechanics seems to be foreign to physics, becomes a natural consequence of dynamical processes.

cond-mat.stat-mech↗
arXiv2003

Detection of invisible and crucial events: from seismic fluctuations to the war against terrorism

We prove the efficiency of a new method for the detection of crucial events that might have useful applications to the war against terrorism. This has to do with the search for rare but significant events, a theme of research that has been made of extreme importance by the tragedy of September 11. This method is applied here to defining the statistics of seismic main-shocks, as done in cond-mat/0212529. The emphasis here is on the conceptual issues behind the results obtained in cond-mat/0212529 than on geophysics. This discussion suggests that the method has a wider range of validity. We support this general discussion with a dynamic model originally proposed in cond-mat/0107597 for purposes different from geophysical applications. However, it is a case where the crucial events to detect are under our control, thereby making it possible for us to check the accuracy of the method of detection of invisible and crucial events that we propose here for a general purpose, including the war against terrorism. For this model an analytical treatment has been recently found [cond-mat/0209038], supporting the claims that we make in this paper for the accuracy of the method of detection. For the reader's convenience, the results on the seismic fluctuations are suitably reviewed, and discussed in the light of the more general perspective of this paper. We also review the model for seismic fluctuations, proposed in the earlier work of cond-mat/0212529. This model shares with the model of cond-mat/0107597 the property that the crucial events are imbedded in a sea of secondary events, but it allows us to reveal with accuracy the statistics of the crucial events for different mathematical reasons.

cond-mat.stat-mech↗
arXiv2003

Intermittency and scale-free networks: a dynamical model for human language complexity

In this paper we try to model certain features of human language complexity by means of advanced concepts borrowed from statistical mechanics. We use a time series approach, the diffusion entropy method (DE), to compute the complexity of an italian corpus of newspapers and magazines. We find that the anomalous scaling index is compatible with a simple dynamical model, a random walk on a complex scale-free network, which is linguistically related to Saussurre's paradigms. The network complexity is independently measured on the same corpus, looking at the co-occurrence of nouns and verbs. This connection of cognitive complexity with long-range time correlations also provides an explanation for the famous Zipf's law in terms of the generalized central limit theorem.

cond-mat.stat-mech↗
arXiv2003

In the search for the low-complexity sequences in prokaryotic and eukaryotic genomes: how to derive a coherent picture from global and local entropy measures

We investigate on a possible way to connect the presence of Low-Complexity Sequences (LCS) in DNA genomes and the nonstationary properties of base correlations. Under the hypothesis that these variations signal a change in the DNA function, we use a new technique, called Non-Stationarity Entropic Index (NSEI) method, and we prove that this technique is an efficient way to detect functional changes with respect to a random baseline. The remarkable aspect is that NSEI does not imply any training data or fitting parameter, the only arbitrarity being the choice of a marker in the sequence. We make this choice on the basis of biological information about LCS distributions in genomes. We show that there exists a correlation between changing the amount in LCS and the ratio of long- to short-range correlation.

cond-mat.stat-mech↗
arXiv2003

Breakdown of the Onsager principle as a sign of aging

We discuss the problem of the equivalence between Continuous Time Random Walk (CTRW) and Generalized Master Equation (GME). The walker, making instantaneous jumps from one site of the lattice to another, resides in each site for extended times. The sojourn times have a distribution psi(t) that is assumed to be an inverse power law. We assume that the Onsager principle is fulfilled, and we use this assumption to establish a complete equivalence between GME and the Montroll-Weiss CTRW. We prove that this equivalence is confined to the case when psi(t) is an exponential. We argue that is so because the Montroll-Weiss CTRW, as recently proved by Barkai [E. Barkai, Phys. Rev. Lett. 90, 104101 (2003)], is non-stationary, thereby implying aging, while the Onsager principle, is valid only in the case of fully aged systems. We consider the case of a dichotomous fluctuation, and we prove that the Onsager principle is fulfilled for any form of regression to equilibrium provided that the stationary condition holds true. We set the stationary condition on both the CTRW and the GME, thereby creating a condition of total equivalence, regardless the nature of the waiting time distribution. As a consequence of this procedure we create a GME that it is a "bona fide" master equation, in spite of being non-Markovian. We note that the memory kernel of the GME affords information on the interaction between system of interest and its bath. The Poisson case yields a bath with infinitely fast fluctuations. We argue that departing from the Poisson form has the effect of creating a condition of infinite memory and that these results might be useful to shed light into the problem of how to unravel non-Markovian master equations.

cond-mat.stat-mech↗
arXiv2003

Power-Law Time Distribution of Large Earthquakes

We study the statistical properties of time distribution of seimicity in California by means of a new method of analysis, the Diffusion Entropy. We 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. We prove that this distribution is an inverse power law with an exponent $μ=2.06 \pm 0.01$. We propose the Long-Range model, reproducing the main properties of the diffusion entropy and describing the seismic triggering mechanisms induced by large earthquakes.

cond-mat.stat-mech↗
arXiv2002

Conflict between trajectories and density description: the statistical source of disagreement

We study an idealized version of intermittent process leading the fluctuations of a stochastic dichotomous variable $ξ$. It consists of an overdamped and symmetric potential well with a cusp-like minimum. The right-hand and left-hand portions of the potential corresponds to $ξ= W$ and $ξ= -W$, respectively. When the particle reaches this minimum is injected back to a different and randomly chosen position, still within the potential well. We build up the corresponding Frobenius-Perron equation and we evaluate the correlation function of the stochastic variable $ξ$, called $Φ_ξ(t)$. We assign to the potential well a form yielding $Φ_ξ(t) = (T/(t + T))^β$, with $β> 0$. We limit ourselves to considering correlation functions with an even number of times, indicated for concision, by $<12>$, $<1234>$ and, more, in general, by $<1 ... 2n>$. The adoption of a treatment based on density yields $<1 ... 2n > = < 1 2 > ... < (2n-1) 2n>$. We study the same dynamic problem using trajectories, and we establish that the resulting two-time correlation function coincides with that afforded by the density picture, as it should. We then study the four-times correlation function and we prove that in the non-Poisson case it departs from the density prescription, namely, from $<1234 > = < 12 > < 34>$. We conclude that this is the main reason why the two pictures yield two different diffusion processes, as noticed in an earlier work [M. Bologna, P. Grigolini, B.J. West, Chem. Phys. {\bf 284}, (1-2) 115-128 (2002)].

cond-mat.stat-mech↗
arXiv2002

Short- and Long-Term Statistical Properties of Heartbeat Time-Series in Healthy and Pathological Subjects

We analize heartbeat time-series corresponding to several groups of individuals (healthy, heart transplanted, with congestive heart failure (CHF), after myocardial infarction (MI), hypertensive), looking for short- and long-time statistical behaviors. In particular we study the persistency patterns of interbeat times and interbeat-time variations. Long-range correlations are revealed using an information-based technique which makes a wise use of the available statistics. The presence of strong long-range time correlations seems to be a general feature for all subjects, with the exception of some CHF individuals. We also show that short time-properties detected in healthy subjects, and seen also in hypertensive and MI patients, and completely absent in the trasplanted, are characterized by a general behavior when we apply a proper coarse-graining procedure for time series analysis.

cond-mat.soft↗
arXiv1999

Dynamic Entropy as a Measure of Caging and Persistent Particle Motion in Supercooled Liquids

The length-scale dependence of the dynamic entropy is studied in a molecular dynamics simulation of a binary Lennard-Jones liquid above the mode-coupling critical temperature $T_c$. A number of methods exist for estimating the entropy of dynamical systems and we utilize an approximation based on calculating the mean first-passage time (MFPT) for particle displacement because of its tractability and its accessibility in real and simulation measurements. The MFPT dynamic entropy $S(ε)$ is defined to equal the inverse of the average first-passage time for a particle to exit a sphere of radius $ε$. This measure of the degree of chaotic motion allows us to identify characteristic time and space scales and to quantify the increasingly correlated particle motion and intermittency occurring in supercooled liquids. In particular, we identify a ``cage'' size defining the scale at which the particles are transiently localized, and we observe persistent particle motion at intermediate length scales beyond the scale where caging occurs. Furthermore, we find that the dynamic entropy at the scale of one interparticle spacing extrapolates to zero as the mode-coupling temperature $T_c$ is approached.

cond-mat.soft↗