3 papers
physics.soc-ph2026
Analytical Framework for the Approximate Master Equation
Yu Takiguchi, Takehisa Hasegawa
The approximate master equation (AME) provides a highly accurate description of dynamical processes on networks, yet its steady states are generally analytically intractable. In th…
physics.soc-ph2024
Robustness of Random Networks with Selective Reinforcement against Attacks
Tomoyo Kawasumi, Takehisa Hasegawa
We investigate the robustness of random networks reinforced by adding hidden edges against targeted attacks. This study focuses on two types of reinforcement: uniform reinforcement…
physics.soc-ph2024
Influence of initiators on the tipping point in the extended Watts model
Takehisa Hasegawa, Shinji Nishioka
In this paper, we study how the influence of initiators (seeds) affects the tipping point of information cascades in networks. We consider an extended version of the Watts model, i…