Title: Controllability of temporal networks: An analysis using higher-order networks,
Abstract: The control of complex networks is a significant challenge, especially when
the network topology of the system to be controlled is dynamic. Addressing this
challenge, here we introduce a novel approach which allows exploring the
controllability of temporal networks. Studying six empirical data sets, we
particularly show that order correlations in the sequence of interactions can
both increase or decrease the time needed to achieve full controllability.
Counter-intuitively, we find that this effect can be opposite than the effect
of order correlations on other dynamical processes. Specifically, we show that
order correlations that speed up a diffusion process in a given system can slow
down the control of the same system, and vice-versa. Building on the
higher-order graphical modeling framework introduced in recent works, we
further demonstrate that spectral properties of higher-order network topologies
can be used to analytically explain this phenomenon.