What question did this study set out to answer?

This research aims to model meaning as a dynamical entity with its own geometry and flow laws in complex systems.

February 13, 2026Open Access

Semantic Gravitation V: Semantic Field Dynamics in Complex Systems — From Neural and Latent States to Semantic State Spaces

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Demonstrates semantic field dynamics impacting neural networks and language models, suggesting new ways to understand meaning in complex systems.

This research aims to model meaning as a dynamical entity with its own geometry and flow laws in complex systems.
Developed operational links between abstract semantic field theory and data-bearing complex systems.
Introduced semantic encoders for mapping states into a semantic Hilbert space.
Formulated a framework for semantic trajectories and gradient flows based on internal dynamics.
Established protocols for inferring semantic geometry and potentials from system behavior.
Identified stability properties of semantic field dynamics relevant to alignment and interpretability.

Gerrit Klawitter (2026) studied this question.

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Demonstrates semantic field dynamics impacting neural networks and language models, suggesting new ways to understand meaning in complex systems.