The Persistence Kernel A Minimal Structural Framework for Identity, Constraint, and Collapse

This deposit presents The Persistence Kernel, a foundational structural framework that formalizes the minimal conditions required for a system to remain identifiable under transformation. The work does not assume time, dynamics, computation, probability, agency, optimization, or physical law as primitives. Instead, it begins with identity evaluation as the sole minimal requirement and derives recursion, admissibility, constraint enforcement, irreversibility, and collapse as necessary structural consequences of persistence. Collapse is treated not as failure, erasure, or destruction, but as a constructive reintegration mechanism that preserves global definability when admissible continuation is exhausted. The framework is implementation-agnostic and substrate-independent, applying equally to physical, computational, biological, and institutional systems. All claims are conditional and falsifiable at the level of structural necessity: any system shown to persist under transformation while violating the kernel’s invariants would constitute a counterexample. The Persistence Kernel is not proposed as a physical theory, computational architecture, or metaphysical ontology. It functions as a kernel-level specification that constrains what any survivable system must satisfy in order to remain definable under transformation. By elevating persistence under constraint—rather than correctness, optimization, or goal satisfaction—as the primary invariant, the framework provides a foundation for analyzing noise-robust computation, long-duration autonomy, and alignment without objectives. This release is intended for archival reference, theoretical analysis, and downstream interpretive or empirical work. All mappings to physics, computation, artificial intelligence, ethics, or governance are explicitly external to the kernel itself.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-06
DOI
https://doi.org/10.5281/zenodo.18501559
Primary Topic
Computability, Logic, AI Algorithms
Type
article
Field-Weighted Citation Impact
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The Persistence Kernel A Minimal Structural Framework for Identity, Constraint, and Collapse

James Shipkowski
Zenodo (CERN European Organization for Nuclear Research)
Computability, Logic, AI Algorithms
article

The Persistence Kernel A Minimal Structural Framework for Identity, Constraint, and Collapse

James Shipkowski
article en

Abstract

This deposit presents The Persistence Kernel, a foundational structural framework that formalizes the minimal conditions required for a system to remain identifiable under transformation. The work does not assume time, dynamics, computation, probability, agency, optimization, or physical law as primitives. Instead, it begins with identity evaluation as the sole minimal requirement and derives recursion, admissibility, constraint enforcement, irreversibility, and collapse as necessary structural consequences of persistence. Collapse is treated not as failure, erasure, or destruction, but as a constructive reintegration mechanism that preserves global definability when admissible continuation is exhausted. The framework is implementation-agnostic and substrate-independent, applying equally to physical, computational, biological, and institutional systems. All claims are conditional and falsifiable at the level of structural necessity: any system shown to persist under transformation while violating the kernel’s invariants would constitute a counterexample. The Persistence Kernel is not proposed as a physical theory, computational architecture, or metaphysical ontology. It functions as a kernel-level specification that constrains what any survivable system must satisfy in order to remain definable under transformation. By elevating persistence under constraint—rather than correctness, optimization, or goal satisfaction—as the primary invariant, the framework provides a foundation for analyzing noise-robust computation, long-duration autonomy, and alignment without objectives. This release is intended for archival reference, theoretical analysis, and downstream interpretive or empirical work. All mappings to physics, computation, artificial intelligence, ethics, or governance are explicitly external to the kernel itself.

Zenodo (CERN European Organization for Nuclear Research)
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Openalex Percentile: Top 64%
Computability, Logic, AI Algorithms
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The Persistence Kernel A Minimal Structural Framework for Identity, Constraint, and Collapse — James Shipkowski · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS