arXiv subjects

Marco Patriarca

Publications and source records attributed to Marco Patriarca.

At least 19 recordsLinked to original sources

arXiv2026

A memory-based three-state model of competing technology adoption: substitution regimes, multi-homing, and churn

Technologies, products, platforms, and behavioral routines often compete through gradual adoption, reinforcement-dependent use, and temporary multi-homing. We formulate a homogeneous, well-mixed, three-state agent-based model of competition between an incumbent option (X) and a challenger (Y). Agents are exclusive users of (X), exclusive users of (Y), or dual adopters (Z). Adoption is memory-based: an exclusive user adds the alternative only after enough adoption-relevant encounters within a finite learning window. Retention is also memory-based: a dual adopter continues to use both options only if each is sufficiently reinforced within a finite retention window. This microscopic mechanism reproduces aggregate usage signatures analogous to the four Adner--Kapoor technology-substitution regimes---creative destruction, robust coexistence, the illusion of resilience, and robust resilience---without explicitly representing ecosystems, complementors, prices, or strategic investment. Starting from the same small challenger seed, the benchmark simulations differ only in adoption burden, retention burden, post-adoption usage preference, and the teaching role of dual adopters. Rolling usage shares reproduce the four aggregate substitution patterns, while state-resolved trajectories and phase portraits reveal distinct microscopic pathways. Thus, similar market-level substitution curves need not have unique causal interpretations: although ecosystem mechanisms may be essential in many empirical cases, finite-memory learning and retention alone can generate qualitatively similar regimes. The model provides a compact baseline linking technology-substitution trajectories to observable individual-level adoption, multi-homing, and discontinuance.

physics.soc-ph↗

arXiv2026

Boundary conditions for the Schr\"odinger equation in the numerical simulation of quantum systems

We study the problem of the boundary conditions in the numerical simulation of closed and open quantum systems, described by a Schr\"odinger equation. On one hand, we show that a closed quantum system is defined by local boundary conditions. On the other hand, we argue that, because of the uncertainty principle, no local boundary condition can be defined for open quantum systems. For this reason plane waves or wave packet trains cannot be simulated on a finite numerical lattice with the usual procedures. We suggest a method that avoids these difficulties by using only a small numerical lattice and maintains the correspondence with the physical picture, in which the incident and scattered waves may be infinitely extended.

quant-ph↗

arXiv2025

Threshold model of language competition including the bilingual state

We propose a threshold model of language competition which includes intermediate bilingual state. The model is based on the Minett-Wang model but through the introduction of thresholds in the language shift rates it incorporates the effects of memory and learning. The model is piecewise-linear, allowing the exact analytical treatment. We study the symmetric case where two competing languages are equivalent in terms of status and social pressure and provide a complete list of the various dynamical regimes. We also study several limiting regimes corresponding to asymmetric systems and characterize the full spectrum of possible asymptotic behaviors. Unlike the Minett-Wang model, which always predicts the extinction of one of the languages, the proposed new model exhibits a wide range of possible equilibrium scenarios, including equilibrium states of coexistence. Most commonly, in such coexistence regimes the minority language speakers are either completely monolingual or completely bilingual.

physics.soc-ph↗

arXiv2025

The role of zealots in the spread of linguistic traits

We investigate the diffusion of linguistic innovations on a fully connected network in order to understand the emergence of linguistic diversity. We employ an agent-based dynamics based on the Axelrod model, where interactions between agents are driven by homophily and social influence, with the difference that we assume that all agents share a number of common features that ensure a finite probability of pairwise interaction. We start from a homogeneous population and introduce zealots that act like agents spreading linguistic innovations, without being influenced by other agents. We analyze how different factors, such as the degree of cohesion and number of zealots in different linguistic states, determine the linguistic configurations that populations can adopt and contribute to the possible emergence of a multi-linguistic community. The results are compared with those derived within the mean-field approximation.

nlin.AO↗

arXiv2025

Effect of diversity distribution symmetry on global oscillations of networks of excitable units

We investigate the role of the degree of symmetry of the diversity distribution in shaping the collective dynamics of networks of coupled excitable units modeled by FitzHugh-Nagumo equations. While previous studies have focused primarily on the ratio between the numbers of individually oscillatory and excitable units, we show that the symmetry of the diversity distribution plays a fundamental role in the emergence of global network oscillations. By exploring various symmetric and asymmetric distributions and simulating network dynamics across various topologies, we demonstrate that symmetric distributions promote resonant collective oscillations even in the absence of oscillatory units. We propose two quantitative metrics, the normalized center of mass and the symmetry balance score, to assess the degree of symmetry and predict the presence or absence of global oscillations. By studying a minimal two-unit system and its effective pseudo-potential, we show that symmetry enables the formation of a landscape characterized by a cyclic valley supporting limit cycles, whereas asymmetry collapses the system into a single non-oscillatory equilibrium. These results provide a general mechanism by which network symmetry drives emergent synchronization in heterogeneous excitable systems.

nlin.AO↗

arXiv2025

Dynamical equivalence between resonant translocation of a polymer chain and diversity-induced resonance

Networks of heterogeneous oscillators are often seen to display collective synchronized oscillations, even when single elements of the network do not oscillate in isolation. It has been found that it is the diversity of the individual elements that drives the phenomenon, possibly leading to the appearance of a resonance in the response. Here we study the way in which heterogeneity acts in producing an oscillatory regime in a network and show that the resonance response is based on the same physics underlying the resonant translocation regime observed in models of polymer diffusion on a substrate potential. Such a mechanical analog provides an alternative viewpoint that is useful to interpret and understand the nature of collective oscillations in heterogeneous networks.

physics.bio-ph↗

arXiv2024

Learning thresholds lead to stable language coexistence

We introduce a language competition model that is based on the Abrams-Strogatz model and incorporates the effects of memory and learning in the language shift dynamics. On a coarse grained time scale, the effects of memory and learning can be expressed as thresholds on the speakers fractions of the competing languages. In its simplest form, the resulting model is exactly solvable. Besides the consensus on one of the two languages, the model describes additional equilibrium states that are not present in the Abrams-Strogatz model: a stable dynamical coexistence of the two languages and a frozen state coinciding with the initial state. We show numerically that these results are preserved for threshold functions of a more general shape. The comparison of the model predictions with historical datasets demonstrates that while the Abrams-Strogatz model fails to describe some relevant language competition situations, the proposed model provides a good fitting.

physics.soc-ph↗

arXiv2022

Diversity-induced decoherence

We analyze the effect of small-amplitude noise and heterogeneity in a network of coupled excitable oscillators with strong time scale separation. Using mean-field analysis, we uncover the mechanism of a new nontrivial effect -- diversity-induced decoherence (DIDC) -- in which heterogeneity modulates the mechanism of self-induced stochastic resonance to inhibit the coherence of oscillations. We argue that DIDC may offer one possible mechanism via which, in excitable neural systems, generic heterogeneity and background noise can synergistically prevent unwanted resonances that may be related to hyperkinetic movement disorders.

nlin.AO↗

arXiv2022

The interplay between diversity and noise in an excitable cell network model

We study the interplay between diversity and noise in a 3D network of FitzHugh-Nagumo elements, with topology and dimensions chosen to model a pancreatic beta-cell cluster, as an example of an excitable cell network. Our results show that diversity and noise are not equivalent sources of disorder but have different effects on network dynamics. Their synchronization mechanisms may act independently of one another or synergistically, depending on the mean value of the diversity distribution compared to the intrinsic oscillatory range of the network elements.

physics.bio-ph↗

arXiv2021

The Role of bilinguals in the Bayesian naming game

We study the recently introduced Bayesian naming game model, in which the one-shot learning of the minimal naming game is replaced by a more realistic learning process defined according to Bayesian inference. The results are compared with those obtained from the minimal naming game model. We focus on the dynamics of the bilingual population, providing analytical estimates of the upper bound for the number of bilinguals in both models based on the mean-field equations, and validate them through numerical simulations of the multi-agent models. We show that in the Bayesian model the maximum number of bilinguals is always lower with respect to the minimal naming game and that the two models are characterized by qualitatively different time evolutions.

physics.soc-ph↗

arXiv2021

Hubs, diversity, and synchronization in FitzHugh-Nagumo oscillator networks: Resonance effects and biophysical implications

Using the FitzHugh-Nagumo equations to represent the oscillatory electrical behavior of beta-cells, we develop a coupled oscillator network model with cubic lattice topology, showing that the emergence of pacemakers or hubs in the system can be viewed as a natural consequence of oscillator population diversity. The optimal hub to non hub ratio is determined by the position of the diversity-induced resonance maximum for a given set of FitzHugh-Nagumo equation parameters and is predicted by the model to be in a range that is fully consistent with experimental observations. The model also suggests that hubs in a beta-cell network should have the ability to "switch on" and "off" their pacemaker function. As a consequence, their relative amount in the population can vary in order to ensure an optimal oscillatory performance of the network in response to environmental changes, such as variations of an external stimulus.

physics.bio-ph↗

arXiv2020

A Bird's-Eye View of Naming Game Dynamics: From Trait Competition to Bayesian Inference

The present contribution reviews a set of different versions of the basic naming game model, differing in the underlying topology or in the mechanisms regulating the interactions between agents. We include also a Bayesian naming game model recently introduced, which merges the social dynamics of the basic naming game model with the Bayesian learning framework introduced by Tenenbaum and co-workers. The latter model goes beyond the fixed nature of names and concepts of standard semiotic dynamics models and the corresponding one-shot learning process, by describing dynamically how agents can generalize a concept from a few examples, according to principles of Bayesian inference.

physics.soc-ph↗

arXiv2019

A Bayesian Approach to the Naming Game Model

We present a novel Bayesian approach to semiotic dynamics, which is a cognitive analogue of the naming game model restricted to two conventions. The one-shot learning that characterizes the agent dynamics in the basic naming game is replaced by a word-learning process, in which agents learn a new word by generalizing from the evidence garnered through pairwise-interactions with other agents. The principle underlying the model is that agents, like humans, can learn from a few positive examples and that such a process is modeled in a Bayesian probabilistic framework. We show that the model presents some analogies but also crucial differences with respect to the dynamics of the basic two-convention naming game model. The model introduced aims at providing a starting point for the construction of a general framework for studying the combined effects of cognitive and social dynamics.

physics.soc-ph↗

arXiv2018

Nucleation and dynamics of dislocations in mismatched heterostructures

In this paper we have investigated, through computer simulations, dislocation nucleation and dislocation dynamics in a heterostructure system with the lattice-mismatch interface, i.e. a system with internal strain. In particular, we have studied the dependence of the nucleation thresholds on the basic parameters of the crystals, such as the amount of mismatch and the system temperature. These studies have been carried out by using the simulation code with a graphical user interface developed at our laboratory. This on-line simulation system produces a real time interactive visualization of the 3-D Molecular Dynamics model. Furthermore, it detects the presence of dislocations and tracks them by an algorithm based on potential energy mapping.

cond-mat.mtrl-sci↗

arXiv2018

Feynman-Vernon model of a moving thermal environment

This paper reviews the formulation of the Feynman-Vernon model of linear dissipative systems for a standard Brownian particle moving in an external potential $V(x,t)$ and introduces the formulation of a generalized oscillator model of a Brownian particle coupled to a thermal environment moving with a given velocity $v_{env}$. Diffusion processes in a moving environment are of interest e.g. in the study of the motion of vortices in superfluids. The starting point of the paper is the formulation of the oscillator model that takes into account space and time invariance of a thermal environment [M. Patriarca, Statistical correlations in the oscillator model of quantum Brownian motion, Il Nuovo Cimento B, 111(1), 61-72 (1996), doi: 10.1007/BF02726201, arXiv:1801.02429], which has the property of being finite and consistent with the classical limit. The Langevin equation and the influence functional for a Brownian particle in a moving environment are derived.

quant-ph↗

arXiv2018

Statistical correlations in the oscillator model of quantum dissipative systems

The problem of the initial conditions for the oscillator model of quantum dissipative systems is studied. It is argued that, even in the classical case, the hypothesis that the environment is in thermal equilibrium implies a statistical correlation between environment oscillators and central system. A simple form of initial conditions for the quantum problem, taking into account such a correlation in analogy with the classical ones, is derived on the base of symmetry considerations. The same symmetries also determine unambiguously the form of the Lagrangian. As a check of the new form of correlated initial conditions (and of that of the Lagrangian), the problem of a forced Brownian particle under the action of arbitrary colored noise is studied: it is shown that one obtains an average position of a quantum wave packet equal to that of the corresponding classical Brownian particle. Instead, starting from uncorrelated initial conditions based on the factorization hypothesis or from a different form of Lagrangian, non-physical results are obtained. Similar considerations apply also to the mean square displacement.

quant-ph↗

arXiv2018

Quantum Mechanical versus Stochastic Processes in Path Integration

By using path integrals, the stochastic process associated to the time evolution of the quantum probability density is formally rewritten in terms of a stochastic differential equation, given by Newton's equation of motion with an additional multiplicative stochastic force. However, the term playing the role of the stochastic force is defined by a non-positive-definite probability functional, providing a clear example of the negative (or "extended") probabilities characteristic of quantum mechanics.

quant-ph↗

arXiv2016

Patterns of Linguistic Diffusion in Space and Time: The Case of Mazatec

In the framework of complexity theory, which provides a unified framework for natural and social sciences, we study the complex and interesting problem of the internal structure, similarities, and differences between the Mazatec dialects, an endangered Otomanguean language spoken in south-east Mexico. The analysis is based on some databases, which are used to compute linguistic distances between the dialects. The results are interpreted in the light of linguistics as well as statistical considerations and used to infer the history of the development of the observed pattern of diversity.

physics.soc-ph↗