Scaling in Non-stationary time series I

Most data processing techniques, applied to biomedical and sociological time series, are only valid for random fluctuations that are stationary in time. Unfortunately, these data are often non stationary and the use of techniques of analysis resting on the stationary assumption can produce a wrong information on the scaling, and so on the complexity of the process under study. Herein, we test and compare two techniques for removing the non-stationary influences from computer generated time series, consisting of the superposition of a slow signal and a random fluctuation. The former is based on the method of wavelet decomposition, and the latter is a proposal of this paper, denoted by us as step detrending technique. We focus our attention on two cases, when the slow signal is a periodic function mimicking the influence of seasons, and when it is an aperiodic signal mimicking the influence of a population change (increase or decrease). For the purpose of computational simplicity the random fluctuation is taken to be uncorrelated. However, the detrending techniques here illustrated work also in the case when the random component is correlated. This expectation is fully confirmed by the sociological applications made in the companion paper. We also illustrate a new procedure to assess the existence of a genuine scaling, based on the adoption of diffusion entropy, multiscaling analysis and the direct assessment of scaling. Using artificial sequences, we show that the joint use of all these techniques yield the detection of the real scaling, and that this is independent of the technique used to detrend the original signal.Comment: 39 pages, 13 figure

Heat transfer simulation of evacuated tube collectors (ETC): An application to a prototype

Since fossil fuels shortages are predicted for the forthcoming generations, the use of renewable energy sources is playing a key role and is strongly recommended worldwide by national and international regulations. In this scenario, solar collectors for hot water preparation, space heating and cooling are becoming an increasingly interesting alternative, especially in the building sector because of population growth. Thus, the present paper is addressed to numerically investigate the thermal behaviour of a prototypal evacuated tube by solving the heat transfer differential equations using the Finite Element Method. This is to reproduce the heat transfer process occurring within the real system, helping the industry improve the prototype

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

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 $\psi (\tau)$ for the time intervals between successively recorded breakdowns. In the intermittent case $\psi (t)\sim t^{-\mu}$, with complexity index $\mu$. We show that two systems can exchange information through complexity matching and present theoretical and numerical calculations describing a system with complexity index $\mu_{S}$ perturbed by a signal with complexity index $\mu_{P}$. The analysis focuses on the non-ergodic (non-stationary) case $\mu \leq 2$ showing that for $\mu_{S}\geq \mu_{P}$, the system $S$ statistically inherits the correlation function of the perturbation $P$. The condition $\mu_{P}=\mu_{S}$ is a resonant maximum for correlation information exchange.Comment: 4 pages, 1 figur

Non-Poisson dichotomous noise: higher-order correlation functions and aging

We study a two-state symmetric noise, with a given waiting time distribution $\psi (\tau)$, and focus our attention on the connection between the four-time and the two-time correlation functions. The transition of $\psi (\tau)$ from the exponential to the non-exponential 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

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.Comment: Phylosophica

Activity autocorrelation in financial markets. A comparative study between several models

We study the activity, i.e., the number of transactions per unit time, of financial markets. Using the diffusion entropy technique we show that the autocorrelation of the activity is caused by the presence of peaks whose time distances are distributed following an asymptotic power law which ultimately recovers the Poissonian behavior. We discuss these results in comparison with ARCH models, stochastic volatility models and multi-agent models showing that ARCH and stochastic volatility models better describe the observed experimental evidences.Comment: 15 pages, 4 figure

Modellazione e caratterizzazione sperimentale di un attuatore idraulico fail-operative per comandi primari di volo Fly-By-Wire

La presente tesi si inserisce nell’ambito delle attività di ricerca in corso presso il Dipartimento di Ingegneria Aerospaziale dell’Università di Pisa (DIA) relative allo studio dei moderni sistemi di controllo di volo Fly-By-Wire con attuazione idraulica. Il lavoro ha come scopo lo sviluppo e la convalidazione sperimentale del modello di simulazione di un attuatore tandem con servovalvola a molteplice ridondanza elettrica per superficie primaria di controllo di volo, con una particolare attenzione allo studio della risposta del sistema nelle diverse condizioni fail-operative, definite dalle possibili combinazioni di avarie elettriche ed idrauliche. Lo studio della variazione del comportamento dinamico dell’attuatore a seguito di avarie riveste infatti un ruolo fondamentale nel progetto e nella messa a punto di un moderno sistema di controllo di volo Fly-By-Wire. Dopo aver caratterizzato la risposta dinamica dell’attuatore reale mediante prove sperimentali su banco, il modello di simulazione dell’attuatore sviluppato nel corso di precedenti attività di ricerca è stato opportunamente modificato al fine di riprodurre in modo più efficace alcune importanti non linearità caratteristiche del sistema (trafilamenti di servovalvola, fenomeni di stick-slip). Una volta messo a punto il modello di simulazione, sono stati variati i parametri del controllo in ciclo chiuso dell’attuatore e della servovalvola, adattandoli a quelli utilizzati per il controllo di un attuatore primario di un moderno velivolo Fly-By-Wire. La risposta dinamica del sistema è stata caratterizzata numericamente e sperimentalmente nelle diverse condizioni fail-operative e l’analisi dei risultati ottenuti ha permesso di evidenziare le condizioni operative più critiche per il funzionamento dell’attuatore

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.Comment: Conference FRACTAL 200

Additive N-Step Markov Chains as Prototype Model of Symbolic Stochastic Dynamical Systems with Long-Range Correlations

A theory of symbolic dynamic systems with long-range correlations based on the consideration of the binary N-step Markov chains developed earlier in Phys. Rev. Lett. 90, 110601 (2003) is generalized to the biased case (non equal numbers of zeros and unities in the chain). In the model, the conditional probability that the i-th symbol in the chain equals zero (or unity) is a linear function of the number of unities (zeros) among the preceding N symbols. The correlation and distribution functions as well as the variance of number of symbols in the words of arbitrary length L are obtained analytically and verified by numerical simulations. A self-similarity of the studied stochastic process is revealed and the similarity group transformation of the chain parameters is presented. The diffusion Fokker-Planck equation governing the distribution function of the L-words is explored. If the persistent correlations are not extremely strong, the distribution function is shown to be the Gaussian with the variance being nonlinearly dependent on L. An equation connecting the memory and correlation function of the additive Markov chain is presented. This equation allows reconstructing a memory function using a correlation function of the system. Effectiveness and robustness of the proposed method is demonstrated by simple model examples. Memory functions of concrete coarse-grained literary texts are found and their universal power-law behavior at long distances is revealed.Comment: 19 pages, 8 figure