Early warning signals for critical transitions in complex systems

Abstract In this topical review, we present a brief overview of the different methods and measures to detect occurrence critical transitions in complex systems. We start by introducing mechanisms that trigger transitions, how they relate early warning signals (EWS) briefly mention conventional based on slowing down, as computed from data applied real then detail approaches for multivariate data, including those defined networks. More recent techniques like derived recurrence pattern underlying are presented plots This is followed discussion machine learning used most recently, simulated data. Towards end, summarise challenges involved while computing EWS real-world conclude with our outlook perspective future trends area.