The Koopman Decade: From Silent Foundations to Frontier Geometry and the VORT Framework

This work provides the first unified historical and structural synthesis of Koopman operator theory, tracing its evolution across four periods—Silent, Realization, Challenge, and Frontier—while showing how ideas originating with Koopman (1931) grew into a multi-disciplinary framework spanning dynamical systems, numerical simulation, machine learning, robotics, and autonomous decision-making. By combining a broad literature review with a conceptual analysis of what the community has achieved and where it has struggled, the monograph clarifies the core bottlenecks that persisted for decades: lifting consistency, spectral drift, reconstruction instability, loss of admissibility, and the absence of mechanisms for structural identity and correction. The central contribution is the Vector–Operator Reconstruction Theory (VORT), a six-stage mathematical architecture that unifies all Koopman and Koopman-type operator-learning approaches and explains both their successes and predictable failure modes. Through this lens, the Frontier period becomes coherent: the field now possesses not only powerful computational tools but a complete operator-theoretic structure capable of supporting modern high-dimensional, multi-physics, and safety-critical systems.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-01
DOI
https://doi.org/10.5281/zenodo.18450639
Primary Topic
Model Reduction and Neural Networks
Type
article
Field-Weighted Citation Impact
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article

The Koopman Decade: From Silent Foundations to Frontier Geometry and the VORT Framework

L. D. L. Nguyen
Zenodo (CERN European Organization for Nuclear Research)
Model Reduction and Neural Networks
article

The Koopman Decade: From Silent Foundations to Frontier Geometry and the VORT Framework

L. D. L. Nguyen
article en

Abstract

This work provides the first unified historical and structural synthesis of Koopman operator theory, tracing its evolution across four periods—Silent, Realization, Challenge, and Frontier—while showing how ideas originating with Koopman (1931) grew into a multi-disciplinary framework spanning dynamical systems, numerical simulation, machine learning, robotics, and autonomous decision-making. By combining a broad literature review with a conceptual analysis of what the community has achieved and where it has struggled, the monograph clarifies the core bottlenecks that persisted for decades: lifting consistency, spectral drift, reconstruction instability, loss of admissibility, and the absence of mechanisms for structural identity and correction. The central contribution is the Vector–Operator Reconstruction Theory (VORT), a six-stage mathematical architecture that unifies all Koopman and Koopman-type operator-learning approaches and explains both their successes and predictable failure modes. Through this lens, the Frontier period becomes coherent: the field now possesses not only powerful computational tools but a complete operator-theoretic structure capable of supporting modern high-dimensional, multi-physics, and safety-critical systems.

Zenodo (CERN European Organization for Nuclear Research)
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Openalex Percentile: Top 69%
Model Reduction and Neural Networks
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