nlin.CD · 2026-06-08 · No. 17

Chaotic Dynamics, 2026-06-08.

1 new papers in nlin.CD. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

1 entries
  1. 01

    Unified Geometry-Guided ML-FTLE for Tracking Transient Chaos from Scalar Time Series

    S. V. Manivelan, Andrei Velichko, I. Manimehan

    nlin.CD · cs.LG · physics.data-an

    Detecting transient chaos from scalar observations without governing equations represents a fundamental challenge in nonlinear dynamics. We propose a geometry-guided machine learning framework that unifies predictive trajectory divergence with macroscopic attractor morphology to track abrupt regime shifts. The methodology extracts a local instability scale via out-of-sample k-nearest neighbor forecast errors to establish the ML-FTLE...

    arxiv.org/abs/2606.07385 · PDF

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