Influence of a network structure on the network effect in the communication service market

In this study, we analyze the network effect in a model of a personal communication market, by using a multi-agent based simulation approach. We introduce into the simulation model complex network structures as the interaction patterns of agents. With complex network models, we investigate the dynamics of a market in which two providers are competing. We also examine the structure of networks that affect the complex behavior of the market. By a series of simulations, we show that the structural properties of complex networks, such as the clustering coefficient and degree correlation, have a major influence on the dynamics of the market. We find that the network effect is increased if the interaction pattern of agents is characterized by a high clustering coefficient, or a positive degree correlation. We also discuss a suitable model of the interaction pattern for reproducing market dynamics in the real world, by performing simulations using real data of a social network.     

Coupled disease–behavior dynamics on complex networks: A review

It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease–behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease–behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.     

Hybrid phase transitions of spreading dynamics in multiplex networks

In this paper, we study the spreading dynamics of social behaviors and focus on heterogenous responses of individuals depending on whether they realize the spreading or not. We model the system with a two-layer multiplex network, in which one layer describes the spreading of social behaviors and the other layer describes the diffusion of the awareness about the spreading. We use the susceptible-infected-susceptible (SIS) model to describe the dynamics of an individual if it is unaware of the spreading of the behavior. While when an individual is aware of the spreading of the social behavior its dynamics will follow the threshold model, in which an individual will adopt a behavior only when the fraction of its neighbors who have adopted the behavior is above a certain threshold. We find that such heterogenous reactions can induce intriguing dynamical properties. The dynamics of the whole network may exhibit hybrid phase transitions with the coexistence of continuous phase transition and bi-stable states. Detailed study of how the diffusion of the awareness influences the spreading dynamics of social behavior is provided. The results are supported by theoretical analysis.     

Enforcing social behavior in an Ising model with complex neighborhoods

We consider the problem of enforcing desired behavior in a population of individuals modeled by an Ising model. Although there is a large literature dealing with social interaction models, the problem of controlling behavior in a system modeled by the Ising model seems to be an unexplored field. First, we provide and analytically characterize an optimal policy that may be used to achieve this objective. Second, we show that complex neighborhoods highly influence the decision making process. Third, we use Lagrange multipliers associated to some constraints of a related problem to identify the role of individuals in the system.     

Using agent-based simulation to assess disease prevention measures during pandemics

Despite the growing interest in macroscopic epidemiological models to deal with threats posed by pandemics such as COVID-19, little has been done regarding the assessment of disease spread in day-to-day life, especially within buildings such as supermarkets where people must obtain necessities at the risk of exposure to disease. Here, we propose an integrated customer shopping simulator including both shopper movement and choice behavior, using a force-based and discrete choice model, respectively. By a simple extension to the force-based model, we implement the following preventive measures currently taken by supermarkets; social distancing and one-way systems, and different customer habits,assessing them based on the average individual disease exposure and the time taken to complete shopping(shopping efficiency). Results show that maintaining social distance is an effective way to reduce exposure, but at the cost of shopping efficiency. We find that the one-way system is the optimal strategy for reducing exposure while minimizing the impact on shopping efficiency. Customers should also visit supermarkets less frequently, but buy more when they do, if they wish to minimize their exposure. We hope that this work demonstrates the potential of pedestrian dynamics simulations in assessing preventative measures during pandemics, particularly if it is validated using empirical data.     

Threshold model of cascades in empirical temporal networks

Threshold models try to explain the consequences of social influence like the spread of fads and opinions. Along with models of epidemics, they constitute a major theoretical framework of social spreading processes. In threshold models on static networks, an individual changes her state if a certain fraction of her neighbors has done the same. When there are strong correlations in the temporal aspects of contact patterns, it is useful to represent the system as a temporal network. In such a system, not only contacts but also the time of the contacts are represented explicitly. In many cases, bursty temporal patterns slow down disease spreading. However, as we will see, this is not a universal truth for threshold models. In this work we propose an extension of Watts’s classic threshold model to temporal networks. We do this by assuming that an agent is influenced by contacts which lie a certain time into the past. I.e., the individuals are affected by contacts within a time window. In addition to thresholds in the fraction of contacts, we also investigate the number of contacts within the time window as a basis for influence. To elucidate the model’s behavior, we run the model on real and randomized empirical contact datasets.     

Direct measurements of colloidal hydrodynamics near flat boundaries using oscillating optical tweezers

We studied the hydrodynamic interaction between a colloidal particle close to flat rigid boundaries and the surrounding fluid using oscillating optical tweezers. A colloidal particle located near walls provides a model system to study the behavior of more complex systems whose boundaries can be modeled as effective walls, such as a blood tube, cell membrane, and capillary tube in bio-MEMS. In this study, we measure the hydrodynamic interaction directly without using the Stokes–Einstein relation. Two different cases are studied: a colloidal sphere near a single flat wall and a colloidal sphere located at the midplane between two flat walls. The colloidal hydrodynamics is measured as a function of the distance between the particle and the walls, and is compared with the theoretical results from well-defined hydrodynamics approximations.     

Emergent hierarchical structures in multiadaptive games

We investigate a game-theoretic model of a social system where both the rules of the game and the interaction structure are shaped by the behavior of the agents. We call this type of model, with several types of feedback couplings from the behavior of the agents to their environment, a multiadaptive game. Our model has a complex behavior with several regimes of different dynamic behavior accompanied by different network topological properties. Some of these regimes are characterized by heterogeneous, hierarchical interaction networks, where cooperation and network topology coemerge from the dynamics.     

Enhancement of electromagnetically induced transparency in room temperature alkali metal vapor

Electromagnetically induced transparency (EIT) has led to several quantum optics effects such as lasing without inversion or squeezed light generation. More recently quantum memories based on EIT have been experimentally implemented in different systems such as alkali metal atoms. In this system the excited state of the optical transition splits into several sublevels due to the hyperfine interaction. However, most of the theoretical models used to describe the experimental results are based on a Λ-system with only one excited state. In this article, we present a theoretical model for the Λ-type interaction of two light, fields and an atomic system with multiple excited state. In particular we show that if the control and probe fields are orthogonally circularly polarized the EIT effect in an alkali-metal vapor can almost disappears. We also identify the reasons of this reduction and propose a method to recover the transparency via velocity selective optical pumping.     

A Simple Mean Field Model for Social Interactions: Dynamics,Fluctuations, Criticality

We study the dynamics of a spin-flip model with a mean field interaction. The system is non reversible, spacially inhomogeneous, and it is designed to model social interactions. We obtain the limiting behavior of the empirical averages in the limit of infinitely many interacting individuals, and show that phase transition occurs. Then, after having obtained the dynamics of normal fluctuations around this limit, we analyze long time fluctuations for critical values of the parameters. We show that random inhomogeneities produce critical fluctuations at a shorter time scale compared to the homogeneous system.     

Tripartite entanglement dynamics for an atom interacting with nonlinear couplers

In this communication we introduce a new model which represents the interaction between an atom and two fields injected simultaneously within a cavity including the nonlinear couplers. By using the canonical transformation the model can be regarded as a generalization of several well-known models. We calculate and discuss entanglement between the tripartite system of one atom and the two cavity modes. For a short interaction time, similarities between the behavior based on our solution compared with the other simulation based on a numerical linear algebra solution of the original Hamiltonian with truncated Fock bases for each mode, is shown. For a specific value of the Kerr-like medium defined in this letter, we find that the entanglement, as measured by concurrence, may terminate abruptly in a finite time.     

Asymmetric Evolution of Two Two-Level Atoms Induced by Position-Dependent Excitation Phase

We report a phenomenon of asymmetric evolution of two two-level atoms which results from pump laser phase based on the model of[Phys.Rev.Lett.101(2008) 153601].Other than investigating the dynamical behavior of whole system,in this paper we investigate the effects of the pump laser phase on dynamic behavior of each atom.We find that two atoms show asymmetry both in time evolution of(population) excitation probability and quantum correlation with environment due to the quantum interference induced by pump laser phase as well as the dipole-dipole interaction.These phenomena are deeply related to the dynamical behavior of the whole system,therefore we can understand the dynamical behavior of whole system caused by pump laser phase from this point of view.     

Entanglement Dynamics of Electrons and Photons

Entanglement is a fundamental feature of quantum theory as well as a key resource for quantum computing and quantum communication, but the entanglement mechanism has not been found at present. We think when the two subsystems exist interaction directly or indirectly, they can be in entanglement state. such as, in the Jaynes-Cummings model, the entanglement between the atom and the light field comes from their interaction. In this paper, we have studied the entanglement mechanism of electron-electron and photon-photon, which are from the spin-spin interaction. We found their total entanglement states are relevant both space state and spin state. When two electrons or two photons are far away, their entanglement states should be disappeared even if their spin state is entangled.     

Damping of Bloch oscillations in the Hubbard model

Using nonequilibrium dynamical mean-field theory, we study the isolated Hubbard model in a static electric field in the limit of weak interactions. Linear response behavior is established at long times, but only if the interaction exceeds a critical value, below which the system exhibits an ac-type response with Bloch oscillations. The transition from ac to dc response is defined in terms of the universal long-time behavior of the system, which does not depend on the initial condition.     

Tipping news in information accumulation system

As a continuous opinion dynamics model, the information accumulation system (IAS) includes three basic mechanisms of the news, the inheritance and the diffusion as contributing to the information accumulation process of a system. A system is composed of agents who diffuse information through internal interaction, while each of them has incomplete memory or inheritance rate. The news comes from external sources of information, such as mass media. Previously the model IAS was studied only for the small news problems. In this study, a tipping news problem is considered. A key question of the problem is: what is the minimum strength of advertisement that can tip the minority opinion to a majority one? Dynamics of the IAS is briefly revisited with a special interest on nonlinear behavior of the model. In particular, it is shown that a discrete map of the IAS for a single color problem can be transformed into a logistic map, from which the dynamics of the IAS can be better understood. To show the applicability of the IAS model, the result is applied to explain the concept of the critical population size, which claims that there is a minimum population size for a social knowledge system to be continuously inherited without being lost. And critical size of the tipping news is found analytically in terms of IAS parameters. Some of the key results from the present study are compared in detail with the results from the Brownian particle model, which is believed to be the most similar model to the IAS. The concept of tipping news is used to show that a traditional society can tip at an exceptionally low inter-community exposure. Finally, the result was applied to the language competition problem.     

The extended Hubbard model in the ionic limit

In this paper, we study the Hubbard model with intersite Coulomb interaction in the ionic limit (i.e. no kinetic energy). It is shown that this model is isomorphic to the spin-1 Ising model in presence of a crystal field and an external magnetic field. We show that for such models it is possible to find, for any dimension, a finite complete set of eigenoperators and eigenvalues of the Hamiltonian. Then, the hierarchy of the equations of motion closes and analytical expressions for the relevant Green's functions and correlation functions can be obtained. These expressions are formal because these functions depend on a finite set of unknown parameters, and only a set of exact relations among the correlation functions can be derived. In the one-dimensional case we show that by means of algebraic constraints it is possible to obtain extra equations which close the set and allow us to obtain a complete exact solution of the model. The behavior of the relevant physical properties for the 1D system is reported.