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April 17, 20260 citationsOpen Access

Geometric Transfer Entropy: A Grade-Resolved Directional Information Flow for Dynamical Coupling of Time Series

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JBJuan Ignacio Vázquez Broquá

Key Points

  • The aim is to introduce Geometric Transfer Entropy (GTE) as a measure of information flow that accounts for the grade structure of underlying dynamics.
  • Definition of GTE based on geometric and kinematic embedding principles.
  • Assessment of information flow using scalar and bivector channels.
  • Comparative analysis across seven benchmark systems.
  • GTE recovers classical Schreiber transfer entropy in level-coupled systems.
  • Detects velocity-coupled systems four times more effectively than Schreiber TE.
  • Accurately identifies the direction of coupling in stochastic oscillators where classical measures fail.

Abstract

We introduce Geometric Transfer Entropy (GTE), a measure of directionalinformation flow between time series that preserves the grade structure of theClifford-algebraic embedding underlying the Geometric Signal Dynamics (GSD)programme. Building on the kinematic embedding and geometric product of VázquezBroquá (2026a), the spectral bivector identity of Vázquez Broquá (2026b), the jointembedding for cointegration of Vázquez Broquá (2026c), and the antisymmetricentropy HAS of Vázquez Broquá (2026d), we define GTEX→Y (τ ) as the sum oftwo grade-resolved channels: a scalar channel T(0)X→Y that captures transfer of alignment/level information, and a bivector channel T(2)X→Y that captures transfer of rotational information (velocity, curvature, phase). The net flow ΦXY = GTEX→Y −GTEY →X decomposes analogously into a scalar and a rotational flow, ΦXY = Φ(0) XY + Φ(2) XY . Across seven benchmark systems, GTE recovers the classical Schreiber transfer entropy on level-coupled linear systems, detects velocity-coupled systems four times more strongly than Schreiber TE, and correctly identifies the directionof coupling in stochastic oscillators where classical TE reverses sign. The bivariate signature (Φ(0), Φ(2)) produces a taxonomy of dynamical coupling mechanisms and yields geometric diagnostics of cointegration, common confounding, and pure rotational transfer that classical information flow measures cannot provide.

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Cite This Study

Juan Ignacio Vázquez Broquá (2026) studied this question.

synapsesocial.com/papers/69e1cf375cdc762e9d858345https://doi.org/10.5281/zenodo.19600330
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