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D. Kim

Publications and source records attributed to D. Kim.

At least 145 records · Page 8Linked to original sources
arXiv2004

Steady state solutions of hydrodynamic traffic models

We investigate steady state solutions of hydrodynamic traffic models in the absence of any intrinsic inhomogeneity on roads such as on-ramps. It is shown that typical hydrodynamic models possess seven different types of inhomogeneous steady state solutions. The seven solutions include those that have been reported previously only for microscopic models. The characteristic properties of wide jam such as moving velocity of its spatiotemporal pattern and/or out-flux from wide jam are shown to be uniquely determined and thus independent of initial conditions of dynamic evolution. Topological considerations suggest that all of the solutions should be common to a wide class of traffic models. The results are discussed in connection with the universality conjecture for traffic models. Also the prevalence of the limit-cycle solution in a recent study of a microscopic model is explained in this approach.

cond-mat.stat-mech↗
arXiv2004

Sandpile avalanche dynamics on scale-free networks

Avalanche dynamics is an indispensable feature of complex systems. Here we study the self-organized critical dynamics of avalanches on scale-free networks with degree exponent $γ$ through the Bak-Tang-Wiesenfeld (BTW) sandpile model. The threshold height of a node $i$ is set as $k_i^{1-η}$ with $0\leqη<1$, where $k_i$ is the degree of node $i$. Using the branching process approach, we obtain the avalanche size and the duration distribution of sand toppling, which follow power-laws with exponents $τ$ and $δ$, respectively. They are given as $τ=(γ-2 η)/(γ-1-η)$ and $δ=(γ-1-η)/(γ-2)$ for $γ<3-η$, 3/2 and 2 for $γ>3-η$, respectively. The power-law distributions are modified by a logarithmic correction at $γ=3-η$.

cond-mat.stat-mech↗
arXiv2003

On the evolution of scale-free graphs

We study the evolution of random graphs where edges are added one by one between pairs of weighted vertices so that resulting graphs are scale-free with the degree exponent $γ$. We use the branching process approach to obtain scaling forms for the cluster size distribution and the largest cluster size as functions of the number of edges $L$ and vertices $N$. We find that the process of forming a spanning cluster is qualitatively different between the cases of $γ>3$ and $2<γ<3$. While for the former, a spanning cluster forms abruptly at a critical number of edges $L_c$, generating a single peak in the mean cluster size $ $ as a function of $L$, for the latter, however, the formation of a spanning cluster occurs in a broad range of $L$, generating double peaks in $ $.

cond-mat.stat-mech↗
arXiv2003

Self-organized Model for Modular Complex Networks : Division and Independence

We introduce a minimal network model which generates a modular structure in a self-organized way. To this end, we modify the Barabasi-Albert model into the one evolving under the principle of division and independence as well as growth and preferential attachment (PA). A newly added vertex chooses one of the modules composed of existing vertices, and attaches edges to vertices belonging to that module following the PA rule. When the module size reaches a proper size, the module is divided into two, and a new module is created. The karate club network studied by Zachary is a prototypical example. We find that the model can reproduce successfully the behavior of the hierarchical clustering coefficient of a vertex with degree k, C(k), in good agreement with empirical measurements of real world networks.

cond-mat.stat-mech↗
arXiv2003

Sandpile on Scale-Free Networks

We investigate the avalanche dynamics of the Bak-Tang-Wiesenfeld (BTW) sandpile model on scale-free (SF) networks, where threshold height of each node is distributed heterogeneously, given as its own degree. We find that the avalanche size distribution follows a power law with an exponent $τ$. Applying the theory of multiplicative branching process, we obtain the exponent $τ$ and the dynamic exponent $z$ as a function of the degree exponent $γ$ of SF networks as $τ=γ/(γ-1)$ and $z=(γ-1)/(γ-2)$ in the range $2 < γ< 3$ and the mean field values $τ=1.5$ and $z=2.0$ for $γ>3$, with a logarithmic correction at $γ=3$. The analytic solution supports our numerical simulation results. We also consider the case of uniform threshold, finding that the two exponents reduce to the mean field ones.

cond-mat.stat-mech↗
arXiv2003

Probabilistic prediction in scale-free networks: Diameter changes

In complex systems, responses to small perturbations are too diverse to predict how much they would be definitely, and then such diverse responses can be predicted in a probabilistic way. Here we study such a problem in scale-free networks, for example, the diameter changes by the deletion of each node for various in silico and real world scale-free networks. We find that the diameter changes are indeed diverse and exhibit an algebraic decay with an exponent ζasymptotically. Interestingly, the exponent ζis robust as ζ\simeq 2.2(1) for most scale-free networks, insensitive to the degree exponents γas long as 2 < γ\le 3. However, there is another type with ζ\simeq 1.7(1) and its examples include the Internet and its related in silico model.

cond-mat.stat-mech↗
arXiv2003

The q-component static model : modeling social networks

We generalize the static model by assigning a q-component weight on each vertex. We first choose a component $(μ)$ among the q components at random and a pair of vertices is linked with a color $μ$ according to their weights of the component $(μ)$ as in the static model. A (1-f) fraction of the entire edges is connected following this way. The remaining fraction f is added with (q+1)-th color as in the static model but using the maximum weights among the q components each individual has. This model is motivated by social networks. It exhibits similar topological features to real social networks in that: (i) the degree distribution has a highly skewed form, (ii) the diameter is as small as and (iii) the assortativity coefficient r is as positive and large as those in real social networks with r reaching a maximum around $f \approx 0.2$.

cond-mat.stat-mech↗
arXiv2002

Classification of scale-free networks

While the emergence of a power law degree distribution in complex networks is intriguing, the degree exponent is not universal. Here we show that the betweenness centrality displays a power-law distribution with an exponent ηwhich is robust and use it to classify the scale-free networks. We have observed two universality classes with η\approx 2.2(1) and 2.0, respectively. Real world networks for the former are the protein interaction networks, the metabolic networks for eukaryotes and bacteria, and the co-authorship network, and those for the latter one are the Internet, the world-wide web, and the metabolic networks for archaea. Distinct features of the mass-distance relation, generic topology of geodesics and resilience under attack of the two classes are identified. Various model networks also belong to either of the two classes while their degree exponents are tunable.

cond-mat.stat-mech↗
arXiv2002

Betweenness centrality correlation in social networks

Scale-free (SF) networks exhibiting a power-law degree distribution can be grouped into the assortative, dissortative and neutral networks according to the behavior of the degree-degree correlation coefficient. Here we investigate the betweenness centrality (BC) correlation for each type of SF networks. While the BC-BC correlation coefficients behave similarly to the degree-degree correlation coefficients for the dissortative and neutral networks, the BC correlation is nontrivial for the assortative ones found mainly in social networks. The mean BC of neighbors of a vertex with BC $g_i$ is almost independent of $g_i$, implying that each person is surrounded by almost the same influential environments of people no matter how influential the person is.

cond-mat.stat-mech↗
arXiv2002

Tricritical Point and the Doping Dependence of the Order of the Ferromagnetic Phase Transition of La1-xCaxMnO3

We report the doping dependence of the order of the ferromagnetic metal to paramagnetic insulator phase transition in La1-xCaxMnO3. At x = 0.33, magnetization and specific heat data show a first order transition, with an entropy change (2.3 J/molK) accounted for by both volume expansion and the discontinuity of M ~ 1.7 Bohr magnetons via the Clausius-Clapeyron equation. At x = 0.4, the data show a continuous transition with tricritical point exponents alpha = 0.48+/- 0.06, beta = 0.25+/- 0.03, gamma = 1.03+/- 0.05, and delta = 5.0 +/- 0.8. This tricritical point separates first order (x<0.4) from second order (x>0.4) transitions.

cond-mat.str-el↗
arXiv2002

Fluctuation-driven dynamics of the Internet topology

We study the dynamics of the Internet topology based on the empirical data on the level of the autonomous systems. It is found that the fluctuations occurring in the stochastic process of connecting and disconnecting edges are important features of the Internet dynamics. The network's overall growth can be described approximately by a single characteristic degree growth rate $g_{\rm eff} \approx 0.016$ and the fluctuation strength $σ_{\rm eff} \approx 0.14$, together with the vertex growth rate $α\approx 0.029$. A stochastic model which incorporate these values and an adaptation rule newly introduced reproduces several features of the real Internet topology such as the correlations between the degrees of different vertices.

cond-mat.stat-mech↗
arXiv2001

Universal Behavior of Load Distribution in Scale-free Networks

We study a problem of data packet transport in scale-free networks whose degree distribution follows a power-law with the exponent $γ$. We define load at each vertex as the accumulated total number of data packets passing through that vertex when every pair of vertices send and receive a data packet along the shortest path connecting the pair. It is found that the load distribution follows a power-law with the exponent $δ\approx 2.2(1)$, insensitive to different values of $γ$ in the range, $2 < γ\le 3$, and different mean degrees, which is valid for both undirected and directed cases. Thus, we conjecture that the load exponent is a universal quantity to characterize scale-free networks.

cond-mat.stat-mech↗
arXiv2001

Macroscopic traffic models from microscopic car-following models

We present a method to derive macroscopic fluid-dynamic models from microscopic car-following models via a coarse-graining procedure. The method is first demonstrated for the optimal velocity model. The derived macroscopic model consists of a conservation equation and a momentum equation, and the latter contains a relaxation term, an anticipation term, and a diffusion term. Properties of the resulting macroscopic model are compared with those of the optimal velocity model through numerical simulations, and reasonable agreement is found although there are deviations in the quantitative level. The derivation is also extended to general car-following models.

cond-mat.stat-mech↗
arXiv2001

Spectra and eigenvectors of scale-free networks

We study the spectra and eigenvectors of the adjacency matrices of scale-free networks when bi-directional interaction is allowed, so that the adjacency matrix is real and symmetric. The spectral density shows an exponential decay around the center, followed by power-law long tails at both spectrum edges. The largest eigenvalue λ_1 depends on system size N as λ_1 \sim N^{1/4} for large N, and the corresponding eigenfunction is strongly localized at the hub, the vertex with largest degree. The component of the normalized eigenfunction at the hub is of order unity. We also find that the mass gap scales as N^{-0.68}.

cond-mat.stat-mech↗
arXiv2000

Depinning of an anisotropic interface in random media: The tilt effect

We study the tilt dependence of the pinning-depinning transition for an interface described by the anisotropic quenched Kardar-Parisi-Zhang equation in 2+1 dimensions, where the two signs of the nonlinear terms are different from each other. When the substrate is tilted by m along the positive sign direction, the critical force F_c(m) depends on m as F_c(m)-F_c(0) \sim -|m|^{1.9(1)}. The interface velocity v near the critical force follows the scaling form v \sim |f|^θΨ_{\pm}(m^2 /|f|^{θ+ϕ}) with θ= 0.9(1) and ϕ= 0.2(1), where f \equiv F-F_c(0) and F is the driving force.

cond-mat.stat-mech↗
arXiv2000

Phase diagram of congested traffic flow: an empirical study

We analyze traffic data from a highway section containing one effective on-ramp. Based on two criteria, local velocity variation patterns and expansion (or nonexpansion) of congested regions, three distinct congested traffic states are identified. These states appear at different levels of the upstream flux and the on-ramp flux, thereby generating a phase diagram of the congested traffic flow. Compared to our earliear reports (including cond-mat/9905292) based on 14 day traffic data, the present paper uses a much larger data set (107 days) and the analysis is carried in a more systematic way, which leads to the modification of a part of interpretation in the earlier reports. Observed traffic states are compared with recent theoretical analyses and both agreeing and disagreeing features are found.

cond-mat↗
arXiv2000

Extreme Galactic-Winds and Starburst in IR Mergers and IR QSOs

We report -as a part of a long-term study of mergers and IR QSOs- detailed spectroscopic evidences for outflow (OF) and/or Wolf Rayet features in: (i) low velocity OF in the ongoing mergers NGC 4038/39 and IRAS 23128-5919; (ii) extreme velocity OF (EVOF) in the QSOs IRAS 01003-2238 and IRAS 13218+0552; (iii) OF and EVOF in a complete sample of ultra-luminous IR galaxies/QSOs ("The IRAS 1 Jy MKO-KPNO Survey", of 118 objects). We found EVOF in IRAS 11119+3257, 14394+5332, 15130+1958 and 15462-0450. The OF components detected in these objects were mainly associated to starburst processes: i.e., to galactic-winds generated in multiple type II SN explosions and massive stars. The EVOF were detected in objects with strong starburst plus obscured IR QSOs; which suggest that interaction of both processes could generate EVOF. In addition, we analyze the presence of Wolf Rayet features in the large sample of Bright PG-QSOs (Boroson and Green 1992), and nearby mergers and galactic-wind galaxies. We found clear WR features in the Fe II QSOs (type I): PG 1244+026, 1444+407, 1448+273, 1535+547; and in the IR merger Arp 220. HST archive images of IR+BAL QSOs show in practically all of these objects "arc or shell" features probably associated to galactic-winds (i.e., to multiple type II SN explosions) and/or merger processes. Finally, we discuss the presence of extreme starburst and galactic wind as a possible evolutive link between IR merger and IR QSOs; where the relation between mergers and extreme starburst (with powerful galactic-winds) plays in important role, in the evolution of galaxies.

astro-ph↗