The paper introduces vertex entanglement (VE), a metric based on quantum information theory that quantifies the perturbations caused by individual vertices on spectral entropy. VE is closely related to network robustness and information transmission ability. The authors demonstrate that VE can be used to address the challenging problem of optimal network dismantling, outperforming state-of-the-art algorithms in empirical experiments. Additionally, VE shows significant differences in hub disruption indices between individuals with autism spectrum disorder (ASD) and typical controls, suggesting its potential as a diagnostic tool for ASD. The study provides a novel approach to identifying key players in complex networks and highlights the importance of considering global network properties in network analysis.The paper introduces vertex entanglement (VE), a metric based on quantum information theory that quantifies the perturbations caused by individual vertices on spectral entropy. VE is closely related to network robustness and information transmission ability. The authors demonstrate that VE can be used to address the challenging problem of optimal network dismantling, outperforming state-of-the-art algorithms in empirical experiments. Additionally, VE shows significant differences in hub disruption indices between individuals with autism spectrum disorder (ASD) and typical controls, suggesting its potential as a diagnostic tool for ASD. The study provides a novel approach to identifying key players in complex networks and highlights the importance of considering global network properties in network analysis.