746 citations · 2.2k across the 41 of their papers we have counts for
18 papers · 1 filter
Optimal Network Robustness Against Attacks in Varying Degree Distributions
Masaki Chujyo, Yukio Hayashi, Takehisa Hasegawa
In varying degree distributions, we investigate the optimally robust networks against targeted attacks to nodes with higher degrees. In considering that a network tends to have mor…
Revisiting finite size effect of percolation in degree correlated networks
Shogo Mizutaka, Takehisa Hasegawa
In this study, we investigate bond percolation in networks that have the Poisson degree distribution and a nearest-neighbor degree-degree correlation. Previous numerical studies on…
Cascading behavior of an extended Watts model on networks
Shinji Nishioka, Takehisa Hasegawa
In this study, we propose an extended Watts model to examine the effect of initiators on information cascades. The extended Watts model assumes that nodes with connections to initi…
Impact of assortative mixing by mask-wearing on the propagation of epidemics in networks
Hiromu Watanabe, Takehisa Hasegawa
In this study, we discuss the impacts of assortative mixing by mask-wearing on the effectiveness of mask use in suppressing the propagation of epidemics. We employ the mask model,…
Synergistic epidemic spreading in correlated networks
Shogo Mizutaka, Kizashi Mori, Takehisa Hasegawa
We investigate the effect of degree correlation on a susceptible-infected-susceptible (SIS) model with a nonlinear cooperative effect (synergy) in infectious transmissions. In a me…
Emergence of Long-Range Correlations in Random Networks
Shogo Mizutaka, Takehisa Hasegawa
We perform an analytical analysis of the long-range degree correlation of the giant component in an uncorrelated random network by employing generating functions. By introducing a…
Structure of percolating clusters in random clustered networks
Takehisa Hasegawa, Shogo Mizutaka
We examine the structure of the percolating cluster (PC) formed by site percolation on a random clustered network (RCN) model. Using the generating functions, we formulate the clus…
Percolation on a maximally disassortative network
Shogo Mizutaka, Takehisa Hasegawa
We propose a maximally disassortative (MD) network model which realizes a maximally negative degree-degree correlation, and study its percolation transition to discuss the effect o…
Observability transitions in clustered networks
Takehisa Hasegawa, Yuta Iwase
We investigate the effect of clustering on network observability transitions. In the observability model introduced by Yang, Wang, and Motter [Phys. Rev. Lett. 109, 258701 (2012)],…
Disassortativity of percolating clusters in random networks
Shogo Mizutaka, Takehisa Hasegawa
We provide arguments for the property of the degree-degree correlations of giant components formed by the percolation process on uncorrelated random networks. Using the generating…
Efficiency of prompt quarantine measures on a susceptible-infected-removed model in networks
Takehisa Hasegawa, Koji Nemoto
This study focuses on investigating the manner in which a prompt quarantine measure suppresses epidemics in networks. A simple and ideal quarantine measure is considered in which a…
Sudden spreading of infections in an epidemic model with a finite seed fraction
Takehisa Hasegawa, Koji Nemoto
We study a simple case of the susceptible-weakened-infected-removed model in regular random graphs in a situation where an epidemic starts from a finite fraction of initially infec…
Outbreaks in susceptible-infected-removed epidemics with multiple seeds
Takehisa Hasegawa, Koji Nemoto
We study a susceptible-infected-removed (SIR) model with multiple seeds on a regular random graph. Many researchers have studied the epidemic threshold of epidemic models above whi…
Suppressing epidemics on networks by exploiting observer nodes
Taro Takaguchi, Takehisa Hasegawa, Yuichi Yoshida
To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immun…
Observability transitions in correlated networks
Takehisa Hasegawa, Taro Takaguchi, Naoki Masuda
Yang, Wang, and Motter [Phys. Rev. Lett. 109, 258701 (2012)] analyzed a model for network observability transitions in which a sensor placed on a node makes the node and the adjace…
Discontinuous Transition of a Multistage Independent Cascade Model on Networks
Takehisa Hasegawa, Koji Nemoto
We propose a multistage version of the independent cascade model, which we call a multistage independent cascade (MIC) model, on networks. This model is parameterized by two probab…
Robustness of correlated networks against propagating attacks
Takehisa Hasegawa, Keita Konno, Koji Nemoto
We investigate robustness of correlated networks against propagating attacks modeled by a susceptible-infected-removed model. By Monte-Carlo simulations, we numerically determine t…
Robustness of networks against propagating attacks under vaccination strategies
Takehisa Hasegawa, Naoki Masuda
We study the effect of vaccination on robustness of networks against propagating attacks that obey the susceptible-infected-removed model.By extending the generating function forma…