arXiv subjects

Jaeseok Hur

Publications and source records attributed to Jaeseok Hur.

5 recordsLinked to original sources

arXiv2026

Opinion Formation in a Spatially Constrained Coevolving Nonlinear Voter Model

We investigate a spatially constrained coevolving nonlinear voter model. Using a random geometric graph, we constrain the interaction range of voter dynamics. If local rewiring is not possible, the discordant link is deleted. Our results reveal absorbing states that differ not only in magnetization and activity, but also in mean degree and spatial state organization. By exploring dynamical and structural observables, we found that distinct regimes from the existing coevolving nonlinear voter model are characterized by a reduced consensus region, spatially segregated fragmentation, and isolated node formation. Additionally, we develop a phenomenological description of the evolution of the mean degree and terminal non-conserved quantities that is consistent with the numerical results. Our model highlights how local geometric accessibility reshapes the structure of the absorbing states.

cond-mat.stat-mech↗

arXiv2026

Impact of capacity volatility and input substitutability on supply chain resilience

Supply chains are intrinsically vulnerable to stochastic shocks due to their sequential production dependencies. Building on the Feld-Barthelemy framework, we investigate how capacity volatility and input substitutability determine critical demands in stochastic supply chains. By modeling production capacity with a truncated normal distribution, we show that in long supply chains, reducing capacity volatility is often more effective than increasing average capacity, emphasizing the need for firm-level synchronization. Furthermore, introducing a modified Leontief-type production function reveals that input substitutability effectively disperses stochastic shocks. Supplier diversification inherently raises critical demands, even under fixed maximum capacities, by introducing the effect of network topology that independently enhances the resilience of physical stock. Our findings demonstrate that mitigating capacity volatility and structurally diversifying supply routes are just as crucial to supply chain resilience as traditional inventory expansion.

cond-mat.stat-mech↗

arXiv2026

Role of volatility mixing in wealth condensation transition

We study the role of heterogeneous volatility in a networked wealth dynamics model and its impact on the wealth condensation transition. Extending the Bouchaud-M\'ezard framework, we introduce binary volatility in networks and investigate how its configuration affects the effective power-law tail exponent of the wealth distribution. Using a stochastic block model, we control the mixing between volatility groups and show that the effective exponent is governed not only by the global parameter $\Lambda=2J/\beta^2$ but also by the volatility configuration in the network. We find that local interactions between nodes with different volatility induce the neutralization of group-wise exponents, which lowers the aggregate tail exponent and yields a condensation transition across $\gamma_{\rm c}=2$. Our results identify volatility mixing as another control mechanism for wealth condensation and highlight the importance of noise heterogeneity in nonequilibrium systems on networks.

cond-mat.stat-mech↗

arXiv2025

Anomaly, class division, and decoupling in income dynamics

Economic inequality emerges from the interplay between regional growth-rate differences and the interaction network that couples regions. We propose a minimal income-dynamics model, where heterogeneity is governed by growth-rate assortativity $\mathcal{A}$ and regional concentration $\mathcal{R}$, allowing us to quantify the spatiotemporal patterns of empirically observed log-income distributions. To systematically analyze these patterns, we derive closed-form approximations for the Hellinger distance and the Gini index in limiting configurations. Our findings highlight the spatial segregation of growth rates as a key driver of economic class division and demonstrate how small-world shortcuts in the underlying network can disrupt this segregation. Finally, our framework provides a robust explanation for the bimodality and strong regional correlations found in global income distributions.

cond-mat.stat-mech↗

arXiv2024

Interplay of network structure and talent configuration on wealth dynamics

The economic success of individuals is often determined by a combination of talent, luck, and assistance from others. We introduce a new agent-based model that simultaneously considers talent, luck, and social interaction. This model allows us to explore how network structure (how agents interact) and talent distribution among agents affect the dynamics of capital accumulation through analytical and numerical methods. We identify a phenomenon as ``talent configuration effect", which refers to the influence of how talent is allocated to individuals (nodes) in the network. We analyze this effect through two key properties: talent assortativity (TA) and talent-degree correlation (TD). In particular, we focus on three economic indicators: growth rate ($n_{\rm rate}$), Gini coefficient (inequality: $n_{\rm Gini}$), and meritocratic fairness ($n_{LT}$). This investigation helps us understand the interplay between talent configuration and network structure on capital dynamics. We find that, in the short term, positive correlations exist between TA and TD for all three economic indicators. Furthermore, the dominant factor influencing capital dynamics depends on the network topology. In scale-free networks, TD has a stronger influence on the economic indices than TA. Conversely, in lattice-like networks, TA plays a more significant role. Our findings address that high socioeconomic homophily can create a dilemma between growth and equality, and that hub monopolization by few highly talented agents makes economic growth strongly dependent on their performances.

physics.soc-ph↗