Transport-First Defect Telemetry on Replay Artifact Graphs: A Minimal Gauge-Covariant Formulation of Closure Inconsistency

This formal technical note provides a minimal mathematical formulation of a transport-first closure-defect readout on replay artifact graphs. It defines projector-first local objects, directed transport, explicit-cycle closure defects, and an equal-rank gauge-invariant closure residual, with a rank-aware partial-isometry appendix. This note is associated with the bounded empirical evidence line documented in Kawasaki (2026), https://doi.org/10.5281/zenodo.19483162. It does not replace or revise that empirical report, and it does not claim universal inconsistency detection, graph-wide operators, or field-level aggregation.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-14
DOI
https://doi.org/10.5281/zenodo.19569051
Primary Topic
Advanced Graph Neural Networks
Type
article
Field-Weighted Citation Impact
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article

Transport-First Defect Telemetry on Replay Artifact Graphs: A Minimal Gauge-Covariant Formulation of Closure Inconsistency

Aoi Kawasaki
Zenodo (CERN European Organization for Nuclear Research)
Advanced Graph Neural Networks
article

Transport-First Defect Telemetry on Replay Artifact Graphs: A Minimal Gauge-Covariant Formulation of Closure Inconsistency

Aoi Kawasaki
article en

Abstract

This formal technical note provides a minimal mathematical formulation of a transport-first closure-defect readout on replay artifact graphs. It defines projector-first local objects, directed transport, explicit-cycle closure defects, and an equal-rank gauge-invariant closure residual, with a rank-aware partial-isometry appendix. This note is associated with the bounded empirical evidence line documented in Kawasaki (2026), https://doi.org/10.5281/zenodo.19483162. It does not replace or revise that empirical report, and it does not claim universal inconsistency detection, graph-wide operators, or field-level aggregation.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 6%
Advanced Graph Neural Networks
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