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New method predicts and controls extreme events in chaotic systems

Researchers have developed a new technique to identify and predict extreme events in chaotic dynamical systems. This method uses sensitivity-balanced projections, derived through backpropagation in differentiable programming frameworks, to reveal the underlying mechanisms driving these events. The approach has been successfully applied to diverse systems, including fluid dynamics, oscillator networks, and ocean wave formation, demonstrating its ability to forecast events and design controllers to prevent them. AI

IMPACT Introduces a novel method for predicting and controlling complex system behaviors, potentially applicable to real-world phenomena.

RANK_REASON The cluster contains a research paper detailing a new scientific method. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Nicholas Zolman, Sajeda Mokbel, Samuel E. Otto, Steven L. Brunton ·

    Uncovering Extreme Event Mechanisms for Prediction and Control with Sensitivity-Balanced Projections

    arXiv:2606.05618v1 Announce Type: cross Abstract: Extreme events -- such as earthquakes and coronal mass ejections -- are common in many chaotic dynamical systems, yet are difficult to characterize and predict due to the subtle instability mechanisms that drive them. In this work…