The Simplicial Characterisation of TS networks: Theory and applications

We use the visibility algorithm to construct the time series networks obtained from the time series of different dynamical regimes of the logistic map. We define the simplicial characterisers of networks which can analyse the simplicial structure at both the global and local levels. These characterisers are used to analyse the TS networks obtained in different dynamical regimes of the logisitic map. It is seen that the simplicial characterisers are able to distinguish between distinct dynamical regimes. We also apply the simplicial characterisers to time series networks constructed from fMRI data, where the preliminary results indicate that the characterisers are able to differentiate between distinct TS networks.Comment: 11 pages, 2 figures, 4 tables. Accepted for publication in Proceedings of the 4th International Conference on Applications in Nonlinear Dynamics (ICAND 2016

Horizontal Visibility graphs generated by type-I intermittency

The type-I intermittency route to (or out of) chaos is investigated within the Horizontal Visibility graph theory. For that purpose, we address the trajectories generated by unimodal maps close to an inverse tangent bifurcation and construct, according to the Horizontal Visibility algorithm, their associated graphs. We show how the alternation of laminar episodes and chaotic bursts has a fingerprint in the resulting graph structure. Accordingly, we derive a phenomenological theory that predicts quantitative values of several network parameters. In particular, we predict that the characteristic power law scaling of the mean length of laminar trend sizes is fully inherited in the variance of the graph degree distribution, in good agreement with the numerics. We also report numerical evidence on how the characteristic power-law scaling of the Lyapunov exponent as a function of the distance to the tangent bifurcation is inherited in the graph by an analogous scaling of the block entropy over the degree distribution. Furthermore, we are able to recast the full set of HV graphs generated by intermittent dynamics into a renormalization group framework, where the fixed points of its graph-theoretical RG flow account for the different types of dynamics. We also establish that the nontrivial fixed point of this flow coincides with the tangency condition and that the corresponding invariant graph exhibit extremal entropic properties.Comment: 8 figure

Phase transition in the Countdown problem

Here we present a combinatorial decision problem, inspired by the celebrated quiz show called the countdown, that involves the computation of a given target number T from a set of k randomly chosen integers along with a set of arithmetic operations. We find that the probability of winning the game evidences a threshold phenomenon that can be understood in the terms of an algorithmic phase transition as a function of the set size k. Numerical simulations show that such probability sharply transitions from zero to one at some critical value of the control parameter, hence separating the algorithm's parameter space in different phases. We also find that the system is maximally efficient close to the critical point. We then derive analytical expressions that match the numerical results for finite size and permit us to extrapolate the behavior in the thermodynamic limit.Comment: Submitted for publicatio

Characterization of the non-Gaussianity of radio and IR point sources at CMB frequencies

This study, using publicly available simulations, focuses on the characterization of the non-Gaussianity produced by radio point sources and by infrared (IR) sources in the frequency range of the cosmic microwave background from 30 to 350 GHz. We propose a simple prescription to infer the angular bispectrum from the power spectrum of point sources considering independent populations of sources, with or without clustering. We test the accuracy of our prediction using publicly available all-sky simulations of radio and IR sources and find very good agreement. We further characterize the configuration dependence and the frequency behaviour of the IR and radio bispectra. We show that the IR angular bispectrum peaks for squeezed triangles and that the clustering of IR sources enhances the bispectrum values by several orders of magnitude at scales ℓ∼ 100. At 150 GHz the bispectrum of IR sources starts to dominate that of radio sources on large angular scales, and it dominates the whole multipole range at 350 GHz. Finally, we compute the bias on fNL induced by radio and IR sources. We show that the positive bias induced by radio sources is significantly reduced by masking the sources. We also show, for the first time, that the form of the IR bispectrum mimics a primordial ‘local' bispectrum fNL. The IR sources produce a negative bias which becomes important for Planck-like resolution and at high frequencies (ΔfNL∼−6 at 277 GHz and ΔfNL∼−60-70 at 350 GHz). Most of the signal being due to the clustering of faint IR sources, the bias is not reduced by masking sources above a flux limit and may, in some cases, even be increased due to the reduction of the shot-noise ter

Time series irreversibility: a visibility graph approach

We propose a method to measure real-valued time series irreversibility which combines two differ- ent tools: the horizontal visibility algorithm and the Kullback-Leibler divergence. This method maps a time series to a directed network according to a geometric criterion. The degree of irreversibility of the series is then estimated by the Kullback-Leibler divergence (i.e. the distinguishability) between the in and out degree distributions of the associated graph. The method is computationally effi- cient, does not require any ad hoc symbolization process, and naturally takes into account multiple scales. We find that the method correctly distinguishes between reversible and irreversible station- ary time series, including analytical and numerical studies of its performance for: (i) reversible stochastic processes (uncorrelated and Gaussian linearly correlated), (ii) irreversible stochastic pro- cesses (a discrete flashing ratchet in an asymmetric potential), (iii) reversible (conservative) and irreversible (dissipative) chaotic maps, and (iv) dissipative chaotic maps in the presence of noise. Two alternative graph functionals, the degree and the degree-degree distributions, can be used as the Kullback-Leibler divergence argument. The former is simpler and more intuitive and can be used as a benchmark, but in the case of an irreversible process with null net current, the degree-degree distribution has to be considered to identifiy the irreversible nature of the series.Comment: submitted for publicatio

Time reversibility from visibility graphs of nonstationary processes

Visibility algorithms are a family of methods to map time series into networks, with the aim of describing the structure of time series and their underlying dynamical properties in graph-theoretical terms. Here we explore some properties of both natural and horizontal visibility graphs associated to several non-stationary processes, and we pay particular attention to their capacity to assess time irreversibility. Non-stationary signals are (infinitely) irreversible by definition (independently of whether the process is Markovian or producing entropy at a positive rate), and thus the link between entropy production and time series irreversibility has only been explored in non-equilibrium stationary states. Here we show that the visibility formalism naturally induces a new working definition of time irreversibility, which allows to quantify several degrees of irreversibility for stationary and non-stationary series, yielding finite values that can be used to efficiently assess the presence of memory and off-equilibrium dynamics in non-stationary processes without needs to differentiate or detrend them. We provide rigorous results complemented by extensive numerical simulations on several classes of stochastic processes

Monensin and forskolin inhibit the transcription rate of sucrase-isomaltase but not the stability of its mRNA in Caco-2 cells

AbstractTreatment of Caco-2 cells with forskolin (25 μM) or monensin (1 μM) has previously been shown to cause a marked decrease in the level of sucrase-isomaltase (SI) mRNA, without any effect on the expression of dipeptidylpeptidase IV (DPP-IV). In the present work, we report that there is no significant difference in the stability of SI mRNA between control and treated cells. On the other hand, we demonstrate a decrease in the transcription rate of SI mRNA which is sufficient to account for the decrease in the steady-state level of SI mRNA both in forskolin- and monensin-treated Caco-2 cells

Feigenbaum graphs: a complex network perspective of chaos

The recently formulated theory of horizontal visibility graphs transforms time series into graphs and allows the possibility of studying dynamical systems through the characterization of their associated networks. This method leads to a natural graph-theoretical description of nonlinear systems with qualities in the spirit of symbolic dynamics. We support our claim via the case study of the period-doubling and band-splitting attractor cascades that characterize unimodal maps. We provide a universal analytical description of this classic scenario in terms of the horizontal visibility graphs associated with the dynamics within the attractors, that we call Feigenbaum graphs, independent of map nonlinearity or other particulars. We derive exact results for their degree distribution and related quantities, recast them in the context of the renormalization group and find that its fixed points coincide with those of network entropy optimization. Furthermore, we show that the network entropy mimics the Lyapunov exponent of the map independently of its sign, hinting at a Pesin-like relation equally valid out of chaos.Comment: Published in PLoS ONE (Sep 2011