Modelling Collective Opinion Formation by Means of Active Brownian Particles

The concept of active Brownian particles is used to model a collective opinion formation process. It is assumed that individuals in community create a two-component communication field that influences the change of opinions of other persons and/or can induce their migration. The communication field is described by a reaction-diffusion equation, the opinion change of the individuals is given by a master equation, while the migration is described by a set of Langevin equations, coupled by the communication field. In the mean-field limit holding for fast communication we derive a critical population size, above which the community separates into a majority and a minority with opposite opinions. The existence of external support (e.g. from mass media) changes the ratio between minority and majority, until above a critical external support the supported subpopulation exists always as a majority. Spatial effects lead to two critical ``social'' temperatures, between which the community exists in a metastable state, thus fluctuations below a certain critical wave number may result in a spatial opinion separation. The range of metastability is particularly determined by a parameter characterizing the individual response to the communication field. In our discussion, we draw analogies to phase transitions in physical systems.Comment: Revised text version. Accepted for publication in European Physics Journal B. For related work see http://summa.physik.hu-berlin.de/~frank/active.html and http://www.if.pw.edu.pl/~jholys

Nonlinear Phenomena in Canonical Stochastic Quantization

Stochastic quantization provides a connection between quantum field theory and statistical mechanics, with applications especially in gauge field theories. Euclidean quantum field theory is viewed as the equilibrium limit of a statistical system coupled to a thermal reservoir. Nonlinear phenomena in stochastic quantization arise when employing nonlinear Brownian motion as an underlying stochastic process. We discuss a novel formulation of the Higgs mechanism in QED.Comment: 8 pages, invited talk at the International Workshop ``Critical Phenomena and Diffusion in Complex Systems'', Dec. 5-7, 2006, Nizhni Novgorod, Russi

Monte Carlo Simulation of Deffuant opinion dynamics with quality differences

In this work the consequences of different opinion qualities in the Deffuant model were examined. If these qualities are randomly distributed, no different behavior was observed. In contrast to that, systematically assigned qualities had strong effects to the final opinion distribution. There was a high probability that the strongest opinion was one with a high quality. Furthermore, under the same conditions, this major opinion was much stronger than in the models without systematic differences. Finally, a society with systematic quality differences needed more tolerance to form a complete consensus than one without or with unsystematic ones.Comment: 8 pages including 5 space-consuming figures, fir Int. J. Mod. Phys. C 15/1

A revision of the genus Metaxaglaea (Lepidoptera: Noctuidae, Cuculliinae) with descriptions of two new species

Two new species, Metaxaglaea violacea and M.australis, are described and figured from southeastern North America. Distributions and life histories, including figures of the larvae, are given for all species in the genus. Eggs of four species are also figured. The larva of M. violacea differs strikingly from that of other species of this or any related genus, although the adults can be reliably distinguished from M. viatica only by color. M. australis is at best only statistically separable from M. semitaria on the basis of male genitalia but differs markedly in egg characters as well as exhibiting subtle differences in adult maculation and at least one distinctive larval character. Certain characters of the male genitalia are markedly variable in M. viatica and M. violacea. In particular, the presence or absence of certain spines on the valves is variable within all populations studied. Every species of the genus occurs in partial sympatry with at least three congeners, but no single locality is known to have all of the five species. Flight seasons of all species overlap broadly in any given locality. There appears to be essentially complete separation of larval feeding niches, although the natural food-plants of M. australis are not yet known

An agent-based model of collective emotions in onlinecommunities

Abstract.: We develop an agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agent's individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a superlinear feedback between the information field and the agent's arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communitie

Agent-based modeling of intracellular transport

We develop an agent-based model of the motion and pattern formation of vesicles. These intracellular particles can be found in four different modes of (undirected and directed) motion and can fuse with other vesicles. While the size of vesicles follows a log-normal distribution that changes over time due to fusion processes, their spatial distribution gives rise to distinct patterns. Their occurrence depends on the concentration of proteins which are synthesized based on the transcriptional activities of some genes. Hence, differences in these spatio-temporal vesicle patterns allow indirect conclusions about the (unknown) impact of these genes. By means of agent-based computer simulations we are able to reproduce such patterns on real temporal and spatial scales. Our modeling approach is based on Brownian agents with an internal degree of freedom, θ, that represents the different modes of motion. Conditions inside the cell are modeled by an effective potential that differs for agents dependent on their value θ. Agent's motion in this effective potential is modeled by an overdampted Langevin equation, changes of θ are modeled as stochastic transitions with values obtained from experiments, and fusion events are modeled as space-dependent stochastic transitions. Our results for the spatio-temporal vesicle patterns can be used for a statistical comparison with experiments. We also derive hypotheses of how the silencing of some genes may affect the intracellular transport, and point to generalizations of the mode

Nonlinear voter models: the transition from invasion to coexistence

In nonlinear voter models the transitions between two states depend in a nonlinear manner on the frequencies of these states in the neighborhood. We investigate the role of these nonlinearities on the global outcome of the dynamics for a homogeneous network where each node is connected to m = 4 neighbors. The paper unfolds in two directions. We first develop a general stochastic framework for frequency dependent processes from which we derive the macroscopic dynamics for key variables, such as global frequencies and correlations. Explicit expressions for both the mean-field limit and the pair approximation are obtained. We then apply these equations to determine a phase diagram in the parameter space that distinguishes between different dynamic regimes. The pair approximation allows us to identify three regimes for nonlinear voter models: (i) complete invasion; (ii) random coexistence; and - most interestingly - (iii) correlated coexistence. These findings are contrasted with predictions from the mean-field phase diagram and are confirmed by extensive computer simulations of the microscopic dynamic

The Efficiency and Evolution of R&D Networks

This work introduces a new model to investigate the efficiency and evolution of networks of firms exchanging knowledge in R&D partnerships. We first examine the efficiency of a given network structure in terms of the maximization of total profits in the industry. We show that the efficient network structure depends on the marginal cost of collaboration. When the marginal cost is low, the complete graph is efficient. However, a high marginal cost implies that the efficient network is sparser and has a core-periphery structure. Next, we examine the evolution of the network struc- ture when the decision on collaborating partners is decentralized. We show the existence of mul- tiple equilibrium structures which are in general inefficient. This is due to (i) the path dependent character of the partner selection process, (ii) the presence of knowledge externalities and (iii) the presence of severance costs involved in link deletion. Finally, we study the properties of the emerg- ing equilibrium networks and we show that they are coherent with the stylized facts of R&D net- works.R&D networks, technology spillovers, network efficiency, network formation

Non-equilibrium dynamics of an active colloidal "chucker"

We report Monte Carlo simulations of the dynamics of a "chucker": a colloidal particle which emits smaller solute particles from its surface, isotropically and at a constant rate k_c. We find that the diffusion constant of the chucker increases for small k_c, as recently predicted theoretically. At large k_c the chucker diffuses more slowly due to crowding effects. We compare our simulation results to those of a "point particle" Langevin dynamics scheme in which the solute concentration field is calculated analytically, and in which hydrodynamic effects can be included albeit in an approximate way. By simulating the dragging of a chucker, we obtain an estimate of its apparent mobility coefficient which violates the fluctuation-dissipation theorem. We also characterise the probability density profile for a chucker which sediments onto a surface which either repels or absorbs the solute particles, and find that the steady state distributions are very different in the two cases. Our simulations are inspired by the biological example of exopolysaccharide-producing bacteria, as well as by recent experimental, simulation and theoretical work on phoretic colloidal "swimmers".Comment: re-submission after referee's comment