1,720,986 research outputs found

    Entropy production in non-equilibrium systems

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    In questa tesi studiamo la produzione di entropia in sistemi fuori dall'equilibrio. Nella prima parte ci concentriamo su sistemi con un numero finito di stati, vicini all'equilibrio termodinamico, che possono essere descritti da una Master Equation. Per sistemi di questo tipo è possibile mappare la dinamica in una rete di stati, rappresentati da nodi, collegati da rate di transizione, identificati da links. In questo contesto, analizziamo la produzione di entropia di ensemble di reti generate casualmente con vincoli specifici, ad esempio la taglia del sistema, e identifichiamo i parametri più importanti che ne determinano il valore. Questa analisi fornisce una stima per la produzione di entropia basata che può essere utilizzata come punto di partenza per il confronto con particolari sistemi di interesse. Nella seconda parte della tesi esaminiamo come il coarse-graining influenzi la nostra capacità di stimare alcune proprietà fisiche di un sistema. Per sistemi fuori dall’equilibrio descritti da una Master Equation, la produzione di entropia può essere stimata utilizzando la formula di Schnakenberg. D'altra parte, alcuni anni fa Seifert ha derivato una formula analoga per sistemi descritti da una Fokker-Planck Equation. In questa tesi miriamo a creare un ponte fra queste due formulazioni e, partendo da un sistema con un numero finito di stati calcoliamo come la produzione di entropia di Schnakenberg sia influenzata dalla procedura di coarse-graining. Mostriamo che tale valore può essere ridotto alla formula di Seifert per alcune scelte particolari della dinamica, ma che, abbastanza sorprendentemente, in generale i flussi microscopici presenti nel sistema danno un contributo macroscopico non negativo alla produzione di entropia. Di conseguenza, trascurare alcune informazioni porta a sottostimare la produzione di entropia, e solo un limite inferiore può essere fornito quando la dinamica è coarse-grained. Infine, nell’ultima sezione della tesi, studiamo somiglianze e differenze tra stati stazionari di non equilibrio e driving periodico in sistemi diffusivi. Un sistema che viola il bilancio dettagliato evolve asintoticamente in uno stato stazionario, che non è uno stato di equilibrio poiché presenta correnti non nulle. Analogamente, quando il bilancio dettagliato è presente in ogni istante di tempo, ma il sistema subisce variazioni periodiche dei parametri esterni, quest’ultimo evolve verso uno stato periodico in cui sono presenti correnti non nulle. In entrambi i casi il costo per produrre tali correnti in tutto il sistema è rappresentato dalla produzione di entropia. In questa tesi miriamo a confrontare questi due scenari per un sistema diffusivo continuo monodimensionale con condizioni al contorno periodiche, descritto da un'equazione di Fokker-Planck, che è il modo più naturale per analizzare le macchine molecolari. Innanzitutto, mostriamo che la produzione di entropia non è equivalente in questi due scenari: il rate di produzione di entropia in un sistema con driving periodico è sempre maggiore del rate di produzione di entropia in un sistema stazionario senza bilancio dettagliato, quando entrambi producono la stessa corrente e hanno la stessa distribuzione di probabilità (mediata nel tempo). Successivamente, mostriamo come costruire sia uno stato stazionario di non equilibrio sia un protocollo di variazione periodica dei parametri esterni che producano una data probabilità (mediata nel tempo) e una data corrente

    Information-driven transitions in projections of underdamped dynamics

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    Low-dimensional representations of underdamped systems often provide useful insights and analytical tractability. Here, we build such representations via information projections, obtaining an optimal model that captures the most information on observed spatial trajectories. We show that, in paradigmatic systems, the minimization of the information loss drives the appearance of a discontinuous transition in the optimal model parameters. Our results raise serious warnings for general inference approaches, and they unravel fundamental properties of effective dynamical representations impacting several fields, from biophysics to dimensionality reduction

    Mutual information in changing environments: Nonlinear interactions, out-of-equilibrium systems, and continuously varying diffusivities

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    Biochemistry, ecology, and neuroscience are examples of prominent fields aiming at describing interacting systems that exhibit nontrivial couplings to complex, ever-changing environments. We have recently shown that linear interactions and a switching environment are encoded separately in the mutual information of the overall system. Here we first generalize these findings to a broad class of nonlinear interacting models. We find that a new term in the mutual information appears, quantifying the interplay between nonlinear interactions and environmental changes, and leading to either constructive or destructive information interference. Furthermore, we show that a higher mutual information emerges in out-of-equilibrium environments with respect to an equilibrium scenario. Finally, we generalize our framework to the case of continuously varying environments. We find that environmental changes can be mapped exactly into an effective spatially varying diffusion coefficient, shedding light on modeling of biophysical systems in inhomogeneous media.LB

    Excitation-Inhibition Balance Controls Information Encoding in Neural Populations

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    : Understanding how the complex connectivity structure of the brain shapes its information-processing capabilities is a long-standing question. By focusing on a paradigmatic architecture, we study how the neural activity of excitatory and inhibitory populations encodes information on external signals. We show that at long times information is maximized at the edge of stability, where inhibition balances excitation, both in linear and nonlinear regimes. In the presence of multiple external signals, this maximum corresponds to the entropy of the input dynamics. By analyzing the case of a prolonged stimulus, we find that stronger inhibition is instead needed to maximize the instantaneous sensitivity, revealing an intrinsic tradeoff between short-time responses and long-time accuracy. In agreement with recent experimental findings, our results pave the way for a deeper information-theoretic understanding of how the balance between excitation and inhibition controls optimal information-processing in neural populations

    Fluctuations of entropy production of a run-and-tumble particle

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    Out-of-equilibrium systems continuously generate entropy, with its rate of production being a fingerprint of nonequilibrium conditions. In small-scale dissipative systems subject to thermal noise, fluctuations of entropy production are significant. Hitherto, mean and variance have been abundantly studied, even if higher moments might be important to fully characterize the system of interest. Here, we introduce a graphical method to compute any moment of entropy production for a generic discrete-state system. Then, we focus on a paradigmatic model of active particles, i.e., run-and-tumble dynamics, which resembles the motion observed in several micro-organisms. Employing our framework, we compute the first three cumulants of the entropy production for a discrete version of this model. We also compare our analytical results with numerical simulations. We find that as the number of states increases, the distribution of entropy production deviates from a Gaussian. Finally, we extend our framework to a continuous state-space run-and-tumble model, using an appropriate scaling of the transition rates. The approach presented here might help uncover the features of nonequilibrium fluctuations of any current in biological systems operating out-of-equilibrium.LB

    Turing patterns in multiplex networks

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    The theory of patterns formation for a reaction-diffusion system defined on a multiplex is developed by means of a perturbative approach. The intra-layer diffusion constants act as small parameter in the expansion and the unperturbed state coincides with the limiting setting where the multiplex layers are decoupled. The interaction between adjacent layers can seed the instability of an homogeneous fixed point, yielding self-organized patterns which are instead impeded in the limit of decoupled layers. Patterns on individual layers can also fade away due to cross-talking between layers. Analytical results are compared to direct simulations.<br/

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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