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Hawoong Jeong

Publications and source records attributed to Hawoong Jeong.

At least 91 records · Page 5Linked to original sources

Effects of substrate network topologies on competition dynamics

We study a competition dynamics, based on the minority game, endowed with various substrate network structures. We observe the effects of the network topologies by investigating the volatility of the system and the structure of follower networks. The topology of substrate structures significantly influences the system efficiency represented by the volatility and such substrate networks are shown to amplify the herding effect and cause inefficiency in most cases. The follower networks emerging from the leadership structure show a power-law incoming degree distribution. This study shows the emergence of scale-free structures of leadership in the minority game and the effects of the interaction among players on the networked version of the game.

cond-mat.dis-nn↗

Epidemic Dynamics of Interacting Two Particle Species on Scale-free Networks

We study the non-equilibrium phase transition in a model for epidemic spreading on scale-free networks. The model consists of two particle species $A$ and $B$, and the coupling between them is taken to be asymmetric; $A$ induces $B$ while $B$ suppresses $A$. This model describes the spreading of an epidemic on networks equipped with a reactive immune system. We present analytic results on the phase diagram and the critical behavior, which depends on the degree exponent $γ$ of the underlying scale-free networks. Numerical simulation results that support the analytic results are also presented.

cond-mat.stat-mech↗

Are better conducting molecules more rigid?

We investigate the electronic origin of the bending stiffness of conducting molecules. It is found that the bending stiffness associated with electronic motion, which we refer to as electro-stiffness, $κ_{e}$, is governed by the molecular orbital overlap $t$ and the gap width $u$ between HOMO and LUMO levels, and behaves as $κ_{e}\sim t^{2}/\sqrt{u^2+t^{2}}$. To study the effect of doping, we analyze the electron filling-fraction dependence on $κ_{e}$ and show that doped molecules are more flexible. In addition, to estimate the contribution of $κ_{e}$ to the total stiffness, we consider molecules under a voltage bias, and study the length contraction ratio as a function of the voltage. The molecules are shown to be contracted or dilated, with $κ_{e}$ increasing nonlinearly with the applied bias.

cond-mat.soft↗

Inhomogeneous substructures hidden in random networks

We study the structure of the load-based spanning tree (LST) that carries the maximum weight of the Erdos-Renyi (ER) random network. The weight of an edge is given by the edge-betweenness centrality, the effective number of shortest paths through the edge. We find that the LSTs present very inhomogeneous structures in contrast to the homogeneous structures of the original networks. Moreover, it turns out that the structure of the LST changes dramatically as the edge density of an ER network increases, from scale free with a cutoff, scale free, to a starlike topology. These would not be possible if the weights are randomly distributed, which implies that topology of the shortest path is correlated in spite of the homogeneous topology of the random network.

cond-mat.dis-nn↗

Systematic analysis of group identification in stock markets

We propose improved methods to identify stock groups using the correlation matrix of stock price changes. By filtering out the marketwide effect and the random noise, we construct the correlation matrix of stock groups in which nontrivial high correlations between stocks are found. Using the filtered correlation matrix, we successfully identify the multiple stock groups without any extra knowledge of the stocks by the optimization of the matrix representation and the percolation approach to the correlation-based network of stocks. These methods drastically reduce the ambiguities while finding stock groups using the eigenvectors of the correlation matrix.

physics.soc-ph↗

Wiring cost in the organization of a biological network

To find out the role of the wiring cost in the organization of the neural network of the nematode \textit{Caenorhapditis elegans} (\textit{C. elegans}), we build the neuronal map of \textit{C. elegans} based on geometrical positions of neurons and define the cost as inter-neuronal Euclidean distance \textit{d}. We show that the wiring probability decays exponentially as a function of \textit{d}. Using the edge exchanging method and the component placement optimization scheme, we show that positions of neurons are not randomly distributed but organized to reduce the total wiring cost. Furthermore, we numerically study the trade-off between the wiring cost and the performance of the Hopfield model on the neural network.

q-bio.NC↗

Spatio-temporal Dynamics in the Origin of Genetic Information

We study evolutionary processes induced by spatio-temporal dynamics in prebiotic evolution. Using numerical simulations we demonstrate that hypercycles emerge from complex interaction structures in multispecies systems. In this work we also find that `hypercycle hybrid' protects the hypercycle from its environment during the growth process. There is little selective advantage for one hypercycle to maintain coexistence with others. This brings the possibility of the outcompetition between hypercycles resulting in the negative effect on information diversity. To enrich the information in hypercycles, symbiosis with parasites is suggested. It is shown that symbiosis with parasites can play an important role in the prebiotic immunology.

q-bio.PE↗

Growing network model for community with group structure

We propose a growing network model for a community with a group structure. The community consists of individual members and groups, gatherings of members. The community grows as a new member is introduced by an existing member at each time step. The new member then creates a new group or joins one of the groups of the introducer. We investigate the emerging community structure analytically and numerically. The group size distribution shows a power law distribution for a variety of growth rules, while the activity distribution follows an exponential or a power law depending on the details of the growth rule. We also present an analysis of empirical data from on the online communities, the ``Groups'' in \url{http://www.yahoo.com} and the ``Cafe'' in \url{http://www.daum.net}, which shows a power law distribution for a wide range of group sizes.

cond-mat.other↗

Random field Ising model and community structure in complex networks

We propose a method to find out the community structure of a complex network. In this method the ground state problem of a ferromagnetic random field Ising model is considered on the network with the magnetic field $B_s = +\infty$, $B_{t} = -\infty$, and $B_{i\neq s,t}=0$ for a node pair $s$ and $t$. The ground state problem is equivalent to the so-called maximum flow problem, which can be solved exactly numerically with the help of a combinatorial optimization algorithm. The community structure is then identified from the ground state Ising spin domains for all pairs of $s$ and $t$. Our method provides a criterion for the existence of the community structure, and is applicable to unweighted and weighted networks equally well. We demonstrate the performance of the method by applying it to the Barabási-Albert network, Zachary karate club network, the scientific collaboration network, and the stock price correlation network.

cond-mat.stat-mech↗

Universality Class of Fiber Bundle Model on Complex Networks

We investigate the failure characteristics of complex networks within the framework of the fiber bundle model subject to the local load sharing rule in which the load of the broken fiber is transferred only to its neighbor fibers. Although the load sharing is strictly local, it is found that the critical behavior belongs to the universality class of the global load sharing where the load is transferred equally to all fibers in the system. From the numerical simulations and the analytical approach applied to the microscopic behavior, it is revealed that the emergence of a single dominant hub cluster of broken fibers causes the global load sharing effect in the failure process.

cond-mat.stat-mech↗

Pattern Formation in a Two-Dimensional Array of Oscillators with Phase-Shifted Coupling

We investigate the dynamics of a two-dimensional array of oscillators with phase-shifted coupling. Each oscillator is allowed to interact with its neighbors within a finite radius. The system exhibits various patterns including squarelike pinwheels, (anti)spirals with phase-randomized cores, and antiferro patterns embedded in (anti)spirals. We consider the symmetry properties of the system to explain the observed behaviors, and estimate the wavelengths of the patterns by linear analysis. Finally, we point out the implications of our work for biological neural networks.

nlin.PS↗

Scale-free trees: the skeletons of complex networks

We investigate the properties of the spanning trees of various real-world and model networks. The spanning tree representing the communication kernel of the original network is determined by maximizing total weight of edges, whose weights are given by the edge betweenness centralities. We find that a scale-free tree and shortcuts organize a complex network. The spanning tree shows robust betweenness centrality distribution that was observed in scale-free tree models. It turns out that the shortcut distribution characterizes the properties of original network, such as the clustering coefficient and the classification of networks by the betweenness centrality distribution.

cond-mat.stat-mech↗

Subnetwork hierarchies of biochemical pathways

We present a method to decompose biochemical networks into subnetworks based on the global geometry of the network. This method enables us to analyse the full hierarchical organisation of biochemical networks and is applied to 43 organisms from the WIT database. Two types of biochemical networks are considered: metabolic networks and whole-cellular networks (also including e.g. information processes). Conceptual and quantitative ways of describing the hierarchical ordering are discussed. The general picture of the metabolic networks arising from our study is that of a few core-clusters centred around the most highly connected substances enclosed by other substances in outer shells, and a few other well-defined subnetworks.

cond-mat.dis-nn↗

Path finding strategies in scale-free networks

We numerically investigate the scale-free network model of Barab{á}si and Albert [A. L. Barab{á}si and R. Albert, Science {\bf 286}, 509 (1999)] through the use of various path finding strategies. In real networks, global network information is not accessible to each vertex, and the actual path connecting two vertices can sometimes be much longer than the shortest one. A generalized diameter depending on the actual path finding strategy is introduced, and a simple strategy, which utilizes only local information on the connectivity, is suggested and shown to yield small-world behavior: the diameter $D$ of the network increases logarithmically with the network size $N$, the same as is found with global strategy. If paths are sought at random, $D \sim N^{0.5}$ is found.

cond-mat.dis-nn↗

Modeling the Internet's Large-Scale Topology

Network generators that capture the Internet's large-scale topology are crucial for the development of efficient routing protocols and modeling Internet traffic. Our ability to design realistic generators is limited by the incomplete understanding of the fundamental driving forces that affect the Internet's evolution. By combining the most extensive data on the time evolution, topology and physical layout of the Internet, we identify the universal mechanisms that shape the Internet's router and autonomous system level topology. We find that the physical layout of nodes form a fractal set, determined by population density patterns around the globe. The placement of links is driven by competition between preferential attachment and linear distance dependence, a marked departure from the currently employed exponential laws. The universal parameters that we extract significantly restrict the class of potentially correct Internet models, and indicate that the networks created by all available topology generators are significantly different from the Internet.

cond-mat.stat-mech↗

Lethality and centrality in protein networks

In this paper we present the first mathematical analysis of the protein interaction network found in the yeast, S. cerevisiae. We show that, (a) the identified protein network display a characteristic scale-free topology that demonstrate striking similarity to the inherent organization of metabolic networks in particular, and to that of robust and error-tolerant networks in general. (b) the likelihood that deletion of an individual gene product will prove lethal for the yeast cell clearly correlates with the number of interactions the protein has, meaning that highly-connected proteins are more likely to prove essential than proteins with low number of links to other proteins. These results suggest that a scale-free architecture is a generic property of cellular networks attributable to universal self-organizing principles of robust and error-tolerant networks and that will likely to represent a generic topology for protein-protein interactions.

cond-mat.stat-mech↗

Error and attack tolerance of complex networks

Many complex systems, such as communication networks, display a surprising degree of robustness: while key components regularly malfunction, local failures rarely lead to the loss of the global information-carrying ability of the network. The stability of these complex systems is often attributed to the redundant wiring of the functional web defined by the systems' components. In this paper we demonstrate that error tolerance is not shared by all redundant systems, but it is displayed only by a class of inhomogeneously wired networks, called scale-free networks. We find that scale-free networks, describing a number of systems, such as the World Wide Web, Internet, social networks or a cell, display an unexpected degree of robustness, the ability of their nodes to communicate being unaffected by even unrealistically high failure rates. However, error tolerance comes at a high price: these networks are extremely vulnerable to attacks, i.e. to the selection and removal of a few nodes that play the most important role in assuring the network's connectivity.

cond-mat.dis-nn↗

The diameter of the world wide web

Despite its increasing role in communication, the world wide web remains the least controlled medium: any individual or institution can create websites with unrestricted number of documents and links. While great efforts are made to map and characterize the Internet's infrastructure, little is known about the topology of the web. Here we take a first step to fill this gap: we use local connectivity measurements to construct a topological model of the world wide web, allowing us to explore and characterize its large scale properties.

cond-mat.dis-nn↗