arXiv subjects

Panos Argyrakis

Publications and source records attributed to Panos Argyrakis.

At least 19 recordsLinked to original sources

arXiv2020

The electrostatic graph algorithm: a physics-defined method for converting a time-series into a weighted complex network

This paper proposes a new method for converting a time-series into a weighted graph (complex network), which builds on the electrostatic conceptualization originating from physics. The proposed method conceptualizes a time-series as a series of stationary, electrically charged particles, on which Coulomb-like forces can be computed. This allows generating electrostatic-like graphs associated to time-series that, additionally to the existing transformations, can be also weighted and sometimes disconnected. Within this context, the paper examines the structural relevance between five different types of time-series and their associated graphs generated by the proposed algorithm and the visibility graph, which is currently the most established algorithm in the literature. The analysis compares the source time-series with the network-based node-series generated by network measures that are arranged into the node-ordering of the source time-series, in terms of linearity, chaotic behaviour, stationarity, periodicity, and cyclical structure. It is shown that the proposed electrostatic graph algorithm produces graphs that are more relevant to the structure of the source time-series by introducing a transformation that converts the time-series to graphs. This is more natural rather than algebraic, in comparison with existing physics-defined methods. The overall approach also suggests a methodological framework for evaluating the structural relevance between the source time-series and their associated graphs produced by any possible transformation.

physics.data-an↗

arXiv2020

Globalization emergence in the European Patent Office (EPO) patent network

We studied the evolution of the European Patent Office (EPO) patents applicants' collaborations network, within a 35 years span of data (1978-2013). Focusing on the Giant Component (GC) formation process over many time-windows, distributed throughout the data timeline, we found that the features governing this phenomenon are indicative of emerging globalization in the applicants' collaborations. The timeline appears to be divided into three regimes, corresponding to three states of the network's evolution. In the early years state, the GC takes long to form and the instant of its creation is easily pinpointed, while it features geographically segregated groups of applicants with technologically similar activities. In contrast, in the late years state, the GC forms quickly, the exact point of its creation is harder to spot, the applicants' activities are more disparate technologically, while their inter-regional collaborations are significantly increased. The middle years are an intermediate state between the two extreme of early and late years. Moreover, we concluded that the critical patents, which induce the GC's formation, are typically introduced by large-sized applicants and also that top patent-producing applicants are likely to submit critical patents, albeit at a lower rate than their overall patent submission. Lastly, we uncovered the crucial role that Japan plays in the network's coherence, through its prominent participation in the GC and the critical patents.

physics.soc-ph↗

arXiv2018

Spontaneous repulsion in the $A+B\to0$ reaction on coupled networks

We study the transient dynamics of an $A+B \rightarrow 0$ process on a pair of randomly coupled networks, where reactants are initially separated. We find that, for sufficiently small fractions $q$ of cross-couplings, the concentration of $A$ (or $B$) particles decays linearly in a first stage and crosses over to a second linear decrease at a mixing time $t_x$. By numerical and analytical arguments, we show that for symmetric and homogeneous structures $t_x\propto(\nicefrac{\langle k \rangle}{q})\log(\nicefrac{\langle k \rangle}{q})$ where $\langle k \rangle$ is the mean degree of both networks. Being this behavior in marked contrast with a purely diffusive process---where the mixing time would go simply like $\langle k\rangle/q$---we identify the logarithmic slowing down in $t_x$ to be the result of a novel spontaneous mechanism of {\em repulsion} between the reactants $A$ and $B$ due to the interactions taking place at the networks' interface. We show numerically how this spontaneous repulsion effect depends on the topology of the underlying networks.

cond-mat.stat-mech↗

arXiv2015

Static and dynamic behavior of multiplex networks under interlink strength variation

It has recently been suggested \cite{Radicchi2013} that in a two-level multiplex network, a gradual change in the value of the "interlayer" strength $p$ can provoke an abrupt structural transition. The critical point $p^*$ at which this happens is system-dependent. In this article, we show in a similar way as in \cite{Garrahan2014} that this is a consequence of the graph Laplacian formalism used in \cite{Radicchi2013}. We calculate the evolution of $p^{*}$ as a function of system size for ER and RR networks. We investigate the behavior of structural measures and dynamical processes of a two-level system as a function of $p$, by Monte-Carlo simulations, for simple particle diffusion and for reaction-diffusion systems. We find that as $p$ increases there is a smooth transition from two separate networks to a single one. We cannot find any abrupt change in static or dynamic behavior of the underlying system.

cond-mat.stat-mech↗

arXiv2014

Variation of the critical percolation threshold in the Achlioptas processes

We investigate variations of the well-known Achlioptas percolation problem, which uses the method of probing sites when building up a lattice system, or probing links when building a network, ultimately resulting in the delay of the appearance of the critical behavior. In the first variation we use two-dimensional lattices, and we apply reverse rules of the Achlioptas model, thus resulting in a speed-up rather than delay of criticality. In a second variation we apply an attractive (and repulsive) rule when building up the lattice, so that newly added sites are either attracted or repelled by the already existing clusters. All these variations result in different values of the percolation threshold, which are herewith reported. Finally, we find that all new models belong to the same universality class as classical percolation.

physics.comp-ph↗

arXiv2014

Efficiency of message transmission using biased random walks in complex networks in the presence of traps

We study the problem of a particle/message that travels as a biased random walk towards a target node in a network in the presence of traps. The bias is represented as the probability $p$ of the particle to travel along the shortest path to the target node. The efficiency of the transmission process is expressed through the fraction $f_g$ of particles that succeed to reach the target without being trapped. By relating $f_g$ with the number $S$ of nodes visited before reaching the target, we firstly show that, for the unbiased random walk, $f_g$ is inversely proportional to both the concentration $c$ of traps and the size $N$ of the network. For the case of biased walks, a simple approximation of $S$ provides an analytical solution that describes well the behavior of $f_g$, especially for $p>0.5$. Also, it is shown that for a given value of the bias $p$, when the concentration of traps is less than a threshold value equal to the inverse of the Mean First Passage Time (MFPT) between two randomly chosen nodes of the network, the efficiency of transmission is unaffected by the presence of traps and almost all the particles arrive at the target. As a consequence, for a given concentration of traps, we can estimate the minimum bias that is needed to have unaffected transmission, especially in the case of Random Regular (RR), Erdős-Rényi (ER) and Scale-Free (SF) networks, where an exact expression (RR and ER) or an upper bound (SF) of the MFPT is known analytically. We also study analytically and numerically, the fraction $f_g$ of particles that reach the target on SF networks, where a single trap is placed on the highest degree node. For the unbiased random walk, we find that $f_g \sim N^{-1/(γ-1)}$, where $γ$ is the power law exponent of the SF network.

physics.soc-ph↗

arXiv2014

Charge separation in organic photovoltaic cells

We consider a simple model for the geminate electron-hole separation process in organic photovoltaic cells, in order to illustrate the influence of dimensionality of conducting channels on the efficiency of the process. The Miller-Abrahams expression for the transition rates between nearest neighbor sites was used for simulating random walks of the electron in the Coulomb field of the hole. The non-equilibrium kinetic Monte Carlo simulation results qualitatively confirm the equilibrium estimations, although quantitatively the efficiency of the higher dimensional systems is less pronounced. The lifetime of the electron prior to recombination is approximately equal to the lifetime prior to dissociation. Their values indicate that electrons perform long stochastic walks before they are captured by the collector or recombined. The non-equilibrium free energy considerably differs from the equilibrium one. The efficiency of the separation process decreases with increasing the distance to the collector, and this decrease is considerably less pronounced for the three dimensional system. The simulation results are in good agreement with the extension of the continuum Onsager theory that accounts for the finite recombination rate at nonzero reaction radius and non-exponential kinetics of the charge separation process.

physics.comp-ph↗

arXiv2014

Generalized Achlioptas process for the delay of criticality in the percolation process

We extend the Achlioptas model for the delay of criticality in the percolation problem. Instead of having a completely random connectivity pattern, we generalize the idea of the two-site probe in the Achlioptas model for connecting smaller clusters, by introducing two models: the first one by allowing any number k of probe sites to be investigated, k being a parameter, and the second one independent of any specific number of probe sites, but with a probabilistic character which depends on the size of the resulting clusters. We find numerically the complete spectrum of critical points and our results indicate that the value of the critical point behaves linearly with k after the value of k = 3. The range k = 2-3 is not linear but parabolic. The more general model of generating clusters with probability inversely proportional to the size of the resulting cluster produces a critical point which is equivalent to the value of k being in the range k = 5-7.

cond-mat.stat-mech↗

arXiv2013

Anomalous biased diffusion in networks

We study diffusion with a bias towards a target node in networks. This problem is relevant to efficient routing strategies in emerging communication networks like optical networks. Bias is represented by a probability $p$ of the packet/particle to travel at every hop towards a site which is along the shortest path to the target node. We investigate the scaling of the mean first passage time (MFPT) with the size of the network. We find by using theoretical analysis and computer simulations that for Random Regular (RR) and Erdős-Rényi (ER) networks, there exists a threshold probability, $p_{th}$, such that for $p p_{th}$ the MFPT scales logarithmically with $N$. The threshold value $p_{th}$ of the bias parameter for which the regime transition occurs is found to depend only on the mean degree of the nodes. An exact solution for every value of $p$ is given for the scaling of the MFPT in RR networks. The regime transition is also observed for the second moment of the probability distribution function, the standard deviation.

physics.soc-ph↗

arXiv2013

Random walk with priorities in communication-like networks

We study a model for a random walk of two classes of particles (A and B). Where both species are present in the same site, the motion of A's takes precedence over that of B's. The model was originally proposed and analyzed in Maragakis et al., Phys. Rev. E 77, 020103 (2008); here we provide additional results. We solve analytically the diffusion coefficients of the two species in lattices for a number of protocols. In networks, we find that the probability of a B particle to be free decreases exponentially with the node degree. In scale-free networks, this leads to localization of the B's at the hubs and arrest of their motion. To remedy this, we investigate several strategies to avoid trapping of the B's: moving an A instead of the hindered B; allowing a trapped B to hop with a small probability; biased walk towards non-hub nodes; and limiting the capacity of nodes. We obtain analytic results for lattices and networks, and discuss the advantages and shortcomings of the possible strategies.

cond-mat.dis-nn↗

arXiv2012

Nature of segregation of reactants in diffusion controlled A+B reactions: Role of mobility in forming compact clusters

We investigate the A+B=0 bimolecular chemical reaction taking place in low-dimensional spaces when the mobilities of the two reacting species are not equal. While the case of different reactant mobilities has been previously reported as not affecting the scaling of the reactant densities with time, but only the pre-exponential factor, the mechanism for this had not been explained before. By using Monte-Carlo simulations we show that the nature of segregation is very different when compared to the normal case of equal reactant mobilities. The clusters of the mobile species are statistically homogeneous and randomly distributed in space, but the clusters of the less mobile species are much more compact and restricted in space. Due to the asymmetric mobilities, the initial symmetric random density fluctuations in time turn into asymmetric density fluctuations. We explain this trend by calculating the correlation functions for the positions of particles for the several different cases.

cond-mat.stat-mech↗

arXiv2011

Explosive site percolation and finite size hysteresis

We report the critical point for site percolation for the "explosive" type for 2D square lattices using Monte Carlo simulations and compare it to the classical well known percolation. We use similar algorithms as have been recently reported for bond percolation and networks. We calculate the "explosive" site percolation threshold as $p_c=0.695$ and we find evidence that "explosive" site percolation surprisingly may belong to a different universality class than bond percolation on lattices, providing that the transitions (a) are continuous and (b) obey the conventional finite size scaling forms. We do not attempt to determine the order of the explosive transition. Finally, we study and compare the direct and reverse processes, showing that while the reverse process is different from the direct process for finite size systems, the two cases become equivalent in the thermodynamic limit of large $L$.

cond-mat.stat-mech↗

arXiv2010

Worldwide spreading of economic crisis

We model the spreading of a crisis by constructing a global economic network and applying the Susceptible-Infected-Recovered (SIR) epidemic model with a variable probability of infection. The probability of infection depends on the strength of economic relations between the pair of countries, and the strength of the target country. It is expected that a crisis which originates in a large country, such as the USA, has the potential to spread globally, like the recent crisis. Surprisingly we show that also countries with much lower GDP, such as Belgium, are able to initiate a global crisis. Using the {\it k}-shell decomposition method to quantify the spreading power (of a node), we obtain a measure of ``centrality'' as a spreader of each country in the economic network. We thus rank the different countries according to the shell they belong to, and find the 12 most central countries. These countries are the most likely to spread a crisis globally. Of these 12 only six are large economies, while the other six are medium/small ones, a result that could not have been otherwise anticipated. Furthermore, we use our model to predict the crisis spreading potential of countries belonging to different shells according to the crisis magnitude.

physics.soc-ph↗

arXiv2010

Percolation of randomly distributed growing clusters: Finite Size Scaling and Critical Exponents

We study the percolation properties of the growing clusters model. In this model, a number of seeds placed on random locations on a lattice are allowed to grow with a constant velocity to form clusters. When two or more clusters eventually touch each other they immediately stop their growth. The model exhibits a discontinuous transition for very low values of the seed concentration $p$ and a second, non-trivial continuous phase transition for intermediate $p$ values. Here we study in detail this continuous transition that separates a phase of finite clusters from a phase characterized by the presence of a giant component. Using finite size scaling and large scale Monte Carlo simulations we determine the value of the percolation threshold where the giant component first appears, and the critical exponents that characterize the transition. We find that the transition belongs to a different universality class from the standard percolation transition.

cond-mat.stat-mech↗

arXiv2009

A Random Matrix Approach to Language Acquisition

Since language is tied to cognition, we expect the linguistic structures to reflect patterns we encounter in nature and analyzed by physics. Within this realm we investigate the process of protolanguage acquisition, using analytical and tractable methods developed within physics. A protolanguage is a mapping between sounds and objects (or concepts) of the perceived world. This mapping is represented by a matrix and the linguistic interaction among individuals is described by a random matrix model. There are two essential parameters in our approach. The strength of the linguistic interaction $β$, which following Chomsky's tradition, we consider as a genetically determined ability, and the number $N$ of employed sounds (the lexicon size). Our model of linguistic interaction is analytically studied using methods of statistical physics and simulated by Monte Carlo techniques. The analysis reveals an intricate relationship between the innate propensity for language acquisition $β$ and the lexicon size $N$, $N \sim \exp(β)$. Thus a small increase of the genetically determined $β$ may lead to an incredible lexical explosion. Our approximate scheme offers an explanation for the biological affinity of different species and their simultaneous linguistic disparity.

physics.soc-ph↗

arXiv2008

Filtering of complex systems using overlapping tree networks

We introduce a technique that is capable to filter out information from complex systems, by mapping them to networks, and extracting a subgraph with the strongest links. This idea is based on the Minimum Spanning Tree, and it can be applied to sets of graphs that have as links different sets of interactions among the system's elements, which are described as network nodes. It can also be applied to correlation-based graphs, where the links are weighted and represent the correlation strength between all pairs of nodes. We applied this method to the European scientific collaboration network, which is composed of all the projects supported by the European Framework Program FP6, and also to the correlation-based network of the 100 highest capitalized stocks traded in the NYSE. For both cases we identified meaningful structures, such as a strongly interconnected community of countries that play important role in the collaboration network, and clusters of stocks belonging to different sectors of economic activity, which gives significant information about the investigated systems.

physics.soc-ph↗

arXiv2008

Trapping in complex networks

We investigate the trapping problem in Erdos-Renyi (ER) and Scale-Free (SF) networks. We calculate the evolution of the particle density $ρ(t)$ of random walkers in the presence of one or multiple traps with concentration $c$. We show using theory and simulations that in ER networks, while for short times $ρ(t) \propto \exp(-Act)$, for longer times $ρ(t)$ exhibits a more complex behavior, with explicit dependence on both the number of traps and the size of the network. In SF networks we reveal the significant impact of the trap's location: $ρ(t)$ is drastically different when a trap is placed on a random node compared to the case of the trap being on the node with the maximum connectivity. For the latter case we find $ρ(t)\propto\exp\left[-At/N^\frac{γ-2}{γ-1}\av{k}\right]$ for all $γ>2$, where $γ$ is the exponent of the degree distribution $P(k)\propto k^{-γ}$.

cond-mat.dis-nn↗

arXiv2008

A network approach for the scientific collaboration in the European Framework Programs

We construct the networks of collaboration between partners for projects carried out with the support of European Commission Framework Programs FP5 and FP6. We analyze in detail these networks, not only in terms of total number of projects, but also for the different tools employed, the different geographical partitions, and the different thematic areas. For all cases we find a scale free behavior, as expected for such social networks, and also reported in the literature. In comparing FP5 to FP6, we show that despite a decrease in the number of signed contracts, and the total number of unique partners, there is an increase in the average number of collaborative partners per institution. Furthermore, we establish a measure for the central role (hub) for each country, by using the Minimum Spanning Tree (MST), which we construct in detail for each thematic area (e.g. Informatics, Nanoscience, Life Sciences, etc.). The importance of these network hubs is highlighted, as this information can be used by policy planners in designing future research plans regarding the distribution of available funds.

physics.soc-ph↗