arXiv subjects

Franco Bagnoli

Publications and source records attributed to Franco Bagnoli.

At least 19 recordsLinked to original sources

arXiv2026

Internal Reliability of Coupled Kuramoto-Sakaguchi Phase Oscillators

The notion of internal reliability in dynamical networks describes whether replicas of a particular unit follow the dynamics of the reference unit. Reliability and anti-reliability can be quantified by the transversal Lyapunov exponents. We study phase oscillators coupled via Kuramoto-Sakaguchi-type interactions. Already the simplest solvable system of two oscillators demonstrates nontrivial reliability properties. We present numerical evidence of reliability and anti-reliability in small networks with a uniform distribution of natural frequencies. The dynamics of an ensemble of replicas can be described within the Watanabe-Strogatz theory, which predicts symmetry of the transversal Lyapunov exponents for replica-attractor and replica-repeller.

nlin.CD↗

arXiv2026

Control of Cellular Automata by Moving Agents with Reinforcement Learning

In this exploratory paper we introduce the problem of cognitive agents that learn how to modify their environment according to local sensing to reach a global goal. We concentrate on discrete dynamics (cellular automata) on a two-dimensional system. We show that agents may learn how to approximate their goal when the environment is passive, while this task becomes impossible if the environment follows an active dynamics.

nlin.CG↗

arXiv2026

General control of linear cellular automata

In mathematics and engineering, control theory is concerned with the analysis of dynamical systems through the application of suitable control inputs. One of the prominent problems in control theory is controllability which concerns the ability to determine whether there exists a control input that can steer a dynamical system from an initial state to a desired final state within a finite time horizon. There is a general theory for controlling linear or linearizable system, but it cannot be applied to discrete systems like cellular automata, which is the problem of that we address in this paper. We develop a general theory for linear (and affine) cellular automata, and apply it to examples of one-dimensional and two-dimensional Boolean cases. We introduce the concept of controllability matrix and show that controllability holds if and only if the controllability matrix is invertible.

nlin.CG↗

arXiv2026

Coarsening and Bifurcations in Wide-Range Two-Dimensional Totalistic Cellular Automata

We investigate Boolean, totalistic cellular automata with a majority or frustrated majority vote rule, and an interaction range of variable span. These two models show a behavior which differs from the mean-field one. The majority vote model is characterized by the presence of absorbing states, and there is a related bifurcation according to the initial density, in agreement with the mean-field approximation. For initial density equal to $0.5$, however, the dynamics is dominated by a coarsening process, which stops when clusters with a definite curvature radius are established. For the frustrated majority vote model, the mean-field approximation gives chaotic oscillations or a limit cycle. Instead, we observe active patterns, with stable density. Above a certain critical value for the interacting radius there is a bifurcation of the asymptotic density as a function of the initial one.

nlin.CG↗

arXiv2026

Emulating the logistic map with totalistic cellular automata

We investigate the conditions under which the mean-field formulation of a probabilistic, totalistic cellular automaton approximates the logistic equation. We show that this goal can be only fulfilled for an infinite-range neighborhood. We numerically study the corresponding one-dimensional implementation, showing that the mean-field description is obviously approached by shuffling the configuration at each time step, but also by rewiring a fraction of links, either at each time step, or using the same random sampling once and for all, in the spirit of the "small-world" mechanism. We show that it is possible to obtain a good approximation of the logistic behavior already with a fraction of rewired links different from one. We also show that there is a bifurcation cascade of the density as a function of the fraction of the rewired links, and that this scenario also holds for a deterministic, totalistic CA with the same basic symmetries of the probabilistic one.

nlin.CG↗

arXiv2026

Introducing the Physics of Complex Systems through Videogames

The purpose of this work is to explore a teaching methodology aimed at communicating topics and subjects not typically studied and analyzed in the (Italian) secondary school. We focused specifically on the use of videogames as a recreational and educational tool, grounding our approach in a broadened conceptual view in which engagement and attentional allocation interact with motivational and affective components of play. Within this perspective, the playful format is considered not only to enhance motivation and enjoyment, but also to attenuate learners' counter-arguing tendencies when confronted with unfamiliar or abstract material. Building on this framework, we developed or adapted several videogames whose central scientific topics are phase transitions, sensitivity to initial conditions, and synchronization. We had a certain number of high school students playing the games, and we asked them several questions to guide them and determine whether the communication was successful. At the end of the activity, we administered a questionnaire about the enjoyment and the difficulties encountered in each game, and the relevant critics.

physics.ed-ph↗

arXiv2025

Metastability in the diluted parallel Ising model

We present some considerations about the parallel implementations of the kinetic (Monte Carlo) version of the Ising model. In some cases the equilibrium distribution of the parallel version does not present the symmetry breaking phenomenon in the low-temperature phase, i.e., the stochastic trajectory originated by the Monte Carlo simulation can jump between the distributions corresponding to both kinds of magnetization, or the lattice can break into two disjoint sublattices, each of which goes into a different asymptotic distribution (phase). In this latter case, by introducing a small asynchronism (dilution), we can have a transition between the homogeneous and the checkerboard phases, with metastable transients.

cond-mat.stat-mech↗

arXiv2025

Forecasting chaotic dynamic using hybrid system

The literature is rich with studies, analyses, and examples on parameter estimation for describing the evolution of chaotic dynamical systems based on measurements, even when only partial information is available through observations. However, parameter estimation alone does not resolve prediction challenges, particularly when only a subset of variables is known or when parameters are estimated with significant uncertainty. In this paper, we introduce a hybrid system specifically designed to address this issue. The method involves training an artificial intelligent system to predict the dynamics of a measured system by combining a neural network with a simulated system. By training the neural network, it becomes possible to refine the model's predictions so that the simulated dynamics synchronize with the actual system dynamics. After a brief contextualization of the problem, we introduce the hybrid approach employed, describing the learning technique and testing the results on two chaotic systems inspired by atmospheric dynamics in measurement contexts. Although these systems are low-dimensional, they encompass all the fundamental characteristics and predictability challenges that can be observed in more complex real-world systems.

nlin.CD↗

arXiv2025

Effects of a Vanishing Noise on Elementary Cellular Automata Phase-Space Structure

We investigate elementary cellular automata (ECA) from the point of view of (discrete) dynamical systems. By studying small lattice sizes, we obtain the complete phase space of all minimal ECA, and, starting from a maximal entropy distribution (all configurations equiprobable), we show how the dynamics affects this distribution. We then investigate how a vanishing noise alters this phase space, connecting attractors and modifying the asymptotic probability distribution. What is interesting is that this modification not always goes in the sense of decreasing the entropy.

nlin.CG↗

arXiv2025

Regional Controllability of Cellular Automata as a SAT Problem

Controllability, one of the fundamental concepts in control theory, consists in guiding a system from an initial state to a desired one within a limited (and possibly minimum) time interval. When the objective is limited to a specific sub-region of the system's domain, the concept is referred to as regional controllability. We examine this notion in the context of Boolean one-dimensional cellular automata of finite length. Depending on the local evolution rule, we investigate whether it is possible to control the evolution of the system by imposing particular values on the boundary conditions. This approach is related to key dynamical properties of CA, specifically chain transitivity and chain mixing. We show that the control problem can be formulated as a Boolean satisfiability (SAT) problem and can thus be addressed using SAT solvers. We also show how finding shortest paths in the configuration graph allows to determine controllability properties. From our observations we can state that only peripherally-linear rules are fully controllable, while for other rules, the reachability ratio, that is, the fraction of controllable pairs of initial and final configurations, is vanishing when the system size grows.

nlin.CG↗

arXiv2025

An Elementary Microscopic Model of Sympatric Speciation

Using as a narrative theme the example of Darwin's finches, a microscopic agent-based model is introduces to study sympatric speciation as a result of competition for resources in the same ecological niche. Varying competition among individuals and resource distribution, the model exhibits some of the main features of evolutionary branching processing. The model can be extended to include spatial effects, different genetic loci, sexual mating and recombination, etc.

q-bio.PE↗

arXiv2025

Synchronization of branching chain of coupled maps: application to the logistic map

We investigate the synchronization dynamics in a chain of coupled chaotic maps organized in a single-parent family tree, whose properties can be captured considering each parent node connected to two children, one of which also serves as the parent for the subsequent node. Our analysis focuses on two distinct synchronization behaviors: parent-child synchronization, defined by the vanishing distance between successive nodes along the chain, and sibling synchronization, corresponding to the convergence of the states of two child nodes. Our findings reveal significant differences in these two type of synchronization mechanisms, which are closely associated with the probability distribution of the state of parent node. Theoretical analysis and simulations with the logistic map support our findings. We further investigate numerical aspects of the implementation corresponding to cases for which the simulated regimes differ from the theoretically predicted one due to computational finite accuracy. We perform a detailed study on how instabilities are numerically suppressed or amplified along the chain. In some cases, a properly adjusted computational scheme can solve this problem.

nlin.CD↗

arXiv2024

Internal reliability and anti-reliability in dynamical networks

We consider finite dynamical networks and define internal reliability according to the synchronization properties of a replicated unit or a set of units. If the states of the replicated units coincide with their prototypes, they are reliable; otherwise, if their states differ, they are anti-reliable. Quantification of reliability with the transversal Lyapunov exponent allows for a straightforward analysis of different models. For a Kuramoto model of globally coupled phase oscillators with a distribution of natural frequencies, we show that prior to the onset of synchronization, peripheral in frequency units are anti-reliable, while central are reliable. For this model, reliability can be expressed via phase correlations in a sort of a fluctuation-dissipation relation. Sufficiently large sub-networks in the Kuramoto model are always anti-reliable; the same holds for a recurrent neural network, where individual units are always reliable.

nlin.AO↗

arXiv2023

Dynamics of oscillator populations with disorder in the coupling phase shifts

We study populations of oscillators, all-to-all coupled by means of quenched disordered phase shifts. While there is no traditional synchronization transition with a nonvanishing Kuramoto order parameter, the system demonstrates a specific order as the coupling strength increases. This order is characterized by partial phase locking, which is put into evidence by the introduced correlation order parameter and via frequency entrainment. Simulations with phase oscillators, Stuart-Landau oscillators, and chaotic Roessler oscillators demonstrate similar scaling of the correlation order parameter with the coupling and the system size and also similar behavior of the frequencies with maximal entrainment at some finite coupling.

nlin.AO↗

arXiv2022

A simple model of knowledge percolation

We investigate how knowledge percolates and clusters in a given knowledge space. We introduce a simple model of knowledge organization in which each contribution spans a certain number of items. If this contribution overlaps with others above a certain threshold, they form a cluster. A contribution can also merge clusters together. We study the growth of global knowledge and the cluster dynamics, both showing a nontrivial behavior.

physics.soc-ph↗

arXiv2021

Prestrain-induced contraction in 1D random elastic chains

Prestrained elastic networks arise in a number of biological and technological systems ranging from the cytoskeleton of cells to tensegrity structures. To understand the response of such a network as a function of the prestrain, we consider a minimal model in one dimension. We do this by considering a chain (1D network) of elastic springs upon which a random, zero mean, finite variance prestrain is imposed. Numerical simulations and analytical predictions quantify the magnitude of the contraction as a function of the variance of the prestrain, and show that the chain always shrinks. To test these predictions, we vary the topology of the chain and consider more complex connectivity and show that our results are relatively robust to these changes.

cond-mat.stat-mech↗

arXiv2021

Cyber Resilience in IoT network: Methodology and example of assessment through epidemic spreading

Cyber Resilience is an important property of complex systems and is important consideration in developing specific IoT applications. This work aims at introducing a novel approach to assess IoT resilience adopting the risk perception in network based epidemic spreading approach. In particular IoT has been considered a network of devices where the probability of infection and interactions (communication), needs to be balanced in order to reduce the malware outbreack while maintaining the network functionalities at an acceptable level. The mathematical model and the simulation results reveal the benefit of a shift from a risk-based to a resilience based approach to threat management in IoT.

cs.NI↗

arXiv2020

Intransitiveness in the Penney Game and in Random Walks on rings, networks, communities and cities

The concept of intransitiveness for games, which is the condition for which there is no first-player winning strategy can arise surprisingly, as happens in the Penney game, an extension of the heads or tails. Since a game can be converted into a random walk on a graph, i.e., a Markov process, we extend the intransitiveness concept to such systems. The end of the game generally consists in the appearance of a pre-defined pattern. In the language of random walk this corresponds to an absorbing trap, since once that the game has reached this condition the game comes to an end. Therefore, the intransitiveness of the game can be mapped into a problem of competition among traps. We analyse in details random walkers on several kind of networks (rings, scale-free, hierarchical and city-inspired) with several variations: traps can be partially absorbing, the walker can be biased and the initial distribution can be arbitrary. We found that the transitivity concept can be quite useful for characterizing the combined properties of a graph and that of the walkers.

physics.soc-ph↗