What is it about?
Extreme events and their evolution and development have become important topics in various fields such as meteorological science, social science, and neuroscience. Statistical modeling methods are commonly used to study the interdependence between these extreme events. In this paper, we propose an optimized event synchronization (OES) method. By proposing minimum delay, this method optimizes the identification criteria of event synchronization. In cases where events are temporally clustered, the OES method enhances the recognition ability of event synchronization features. The OES method is not affected by event aggregation and performs more stably under different parameters. Based on the synchronous relationship and synchronous extent of hightraffic events in a communication system, a functional communication network is constructed. By analyzing the topological characteristics of this functional communication network, we aim to study the synchronous spatiotemporal patterns of high-traffic events, including the synchronous area, the extent of synchronization impact and the spatial continuity.
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Why is it important?
Extreme events can have catastrophic consequences, even though they occur less frequently . In recent years, there has been increased attention from scientists and the public on regular patterns, distribution characteristics, and predictions of extreme events. Examples include identifying earthquake-prone regions, predicting floods, and assessing the impacts of social accidents. Understanding the possible time and location of extreme events can help reduce the impact of their catastrophic consequences. As a method for analyzing complex systems, networks can explore the dynamics and structural characteristics of real-world systems. Some researchers have used network analysis to investigate the synchronization of extreme events and reveal synchronous spatiotemporal patterns.
Perspectives
It is anticipated that the OES method can be utilized in various disciplines, including geology, climatology, and neuroscience, to offer a novel theoretical approach for understanding and addressing scientific issues in those fields.
Li-Na Wang
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This page is a summary of: Optimized event synchronization method: Identifying synchronous spatiotemporal patterns of extreme events, Chaos Solitons & Fractals, September 2025, Elsevier,
DOI: 10.1016/j.chaos.2025.116563.
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