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2026
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| Online Access: | https://doi.org/10.5281/zenodo.19133268 |
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| _version_ | 1866901671264649216 |
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| author | Krūger, Marcel |
| author_facet | Krūger, Marcel |
| contents | <p>Operator-based frameworks for biological dynamics have recently introduced reduced state-space representations in which instability can be quantified through a scalar functional ∆Φ(t) relative to a reference stability manifold. While such approaches enable early-warning detection of regime transitions, they do not specify how detected instability can be systematically mapped to controlled perturbations. In this work, we introduce a conservative intervention-mapping framework formulated in a reduced Information–Coherence–Energy (ICE) state space. System dynamics are represented by x(t) = (E,I,C), and instability is defined as a scalar functional ∆Φ(t) measuring deviation from a reference state x∗. We define admissible perturbations u(t) and pose the intervention problem as the identification of inputs that reproducibly reduce ∆Φ(t) under controlled and testable conditions. The framework is formulated in a control-theoretic setting, including Lyapunov-like decrease criteria and explicitly defined intervention classes. It does not assume universal controllability or therapeutic efficacy. Instead, it establishes a falsifiable bridge between instability detection and candidate stabilization mechanisms in biological dynamical systems. The primary contribution is the definition of a minimal, experimentally testable structure for evaluating whether consistent intervention mappings exist across systems.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19133268 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Intervention Mapping in ICE Space: From ∆Φ Detection to Closed-Loop Stabilization Krūger, Marcel <p>Operator-based frameworks for biological dynamics have recently introduced reduced state-space representations in which instability can be quantified through a scalar functional ∆Φ(t) relative to a reference stability manifold. While such approaches enable early-warning detection of regime transitions, they do not specify how detected instability can be systematically mapped to controlled perturbations. In this work, we introduce a conservative intervention-mapping framework formulated in a reduced Information–Coherence–Energy (ICE) state space. System dynamics are represented by x(t) = (E,I,C), and instability is defined as a scalar functional ∆Φ(t) measuring deviation from a reference state x∗. We define admissible perturbations u(t) and pose the intervention problem as the identification of inputs that reproducibly reduce ∆Φ(t) under controlled and testable conditions. The framework is formulated in a control-theoretic setting, including Lyapunov-like decrease criteria and explicitly defined intervention classes. It does not assume universal controllability or therapeutic efficacy. Instead, it establishes a falsifiable bridge between instability detection and candidate stabilization mechanisms in biological dynamical systems. The primary contribution is the definition of a minimal, experimentally testable structure for evaluating whether consistent intervention mappings exist across systems.</p> |
| title | Intervention Mapping in ICE Space: From ∆Φ Detection to Closed-Loop Stabilization |
| url | https://doi.org/10.5281/zenodo.19133268 |